The allostatic triage model of psychopathology (ATP Model): How reallocation of brain energetic resources under stress elicits psychiatric symptoms

D Parker Kelley; S Parker Singleton; Katy Venable; Gabriel Sturm; Anna Skovgaard; Joseph Francis; Thomas C Neylan; Ellen R Bradley; Joshua Woolley; Martin Picard; Aoife O’Donovan

doi:10.1016/j.neubiorev.2025.106419

. Author manuscript; available in PMC: 2026 Mar 22.

Published in final edited form as: Neurosci Biobehav Rev. 2025 Oct 13;179:106419. doi: 10.1016/j.neubiorev.2025.106419

The allostatic triage model of psychopathology (ATP Model): How reallocation of brain energetic resources under stress elicits psychiatric symptoms

D Parker Kelley ^a,^b,^*, S Parker Singleton ^c, Katy Venable ^d, Gabriel Sturm ^e, Anna Skovgaard ^a, Joseph Francis ^d, Thomas C Neylan ^a,^b, Ellen R Bradley ^a,^b, Joshua Woolley ^a,^b, Martin Picard ^f, Aoife O’Donovan ^a,^b

PMCID: PMC13005708 NIHMSID: NIHMS2150778 PMID: 41093260

Abstract

Psychiatric, cardiometabolic, and immune disorders are highly comorbid, and are precipitated by psychological stress. To explain why these conditions co-occur and how stress triggers their pathogenesis, we introduce the Allostatic Triage Model of Psychopathology (ATP Model) that explains psychopathogenesis, and these bidirectional associations through a bioenergetic lens. Stress increases the energy demand on biological systems, which operate on a finite energy budget, increasing the risk of energy scarcity, especially in the brain, which faces high energy needs and limited access to energetic resources. Allostatic processes anticipate stress-induced increases in energy demand and regulate systemic and brain energy allocation from mind-to-mitochondria, a process that we call “allostatic triage”. The brain allostatic-interoceptive system generates internal models of systemic and brain metabolism and energy output that are used to produce affective states, which regulate allostasis. In turn, we propose that affect regulates allostatic triage among functional brain networks. Chronic and traumatic stress dysregulates the mitochondrial and brain networks that regulate affect by reducing metabolic efficiency. We propose that stress-induced energy scarcity and affective dysregulation exacerbates allostatic triage to the networks most necessary for short-term survival, at the expense of non-vital processes contributing to long-term optimization and well-being, dysregulating allostasis and driving transdiagnostic disease pathogenesis. Persistent network activation patterns underlying psychiatric symptoms can then become entrenched as psychiatric disorders through activity-dependent neuroplasticity, also known as canalization. Altogether, we propose that stress dysregulates mitochondria, affect, and allostatic triage, impairing allostasis, and driving transdiagnostic pathological states, which are canalized over time into transdiagnostic disease.

Keywords: Allostasis, Mitochondria, Psychopathology, Affect, Allostatic Triage, Allostatic Load, Canalization

1. Introduction

Stress exposure is a risk and precipitating factor for psychiatric (Bourvis et al., 2017; Daviu et al., 2019; Kasai et al., 2008; Kendler et al., 2004, 1999; Lex et al., 2017; van Winkel et al., 2008), cardiometabolic (Backé et al., 2012; Dimsdale, 2008; Gebreab et al., 2018), and immunological (O’Donovan et al., 2015) diseases, which are bidirectionally related to each other. For example, chronic stress increases the odds of developing major depressive disorder (MDD) by > 3.5 fold (Kendler et al., 1999) and more than doubles the odds of developing hypertension (Liu et al., 2017). These psychiatric and medical illnesses are also bidirectionally linked (Chen et al., 2023; Li et al., 2024; Sun et al., 2024; Wang et al., 2025). While autoimmune disorders (O’Donovan et al., 2015), cardiometabolic diseases, and other medical illnesses increase risk for psychiatric disorders (Atlantis and Baker, 2008; Ha et al., 2017; Speed et al., 2019), psychiatric disorders also increase risk for medical diseases (Galts et al., 2019; Miller and Raison, 2016; Miller et al., 2018; Müller, 2018; Penninx and Lange, 2018). For example, hypertension more than doubles the odds of developing MDD (Gan et al., 2023; Turana et al., 2021), and MDD increases the risk of developing hypertension (Meng et al., 2012; Wu et al., 2012; Zhang and Li, 2024). Are there shared psychobiological processes underlying stress effects on psychiatric and medical disorders and the comorbidity of these disorders? Here, we propose a conceptual model to explain bidirectional relationships among stress, chronic medical diseases, and psychopathology by integrating existing and novel concepts into a bioenergetic model of transdiagnostic stress-induced disease pathogenesis.

What is it about stress that drives multisystemic pathology? Hans Seyle defined stress as “the non-specific response of the body to any demand”, but did not clearly define “demand”. An alternative model was proposed by Koolhaas et al. (2011) in which the term “stress” is restricted to stimuli that overwhelm the natural regulatory response of the organism (Koolhaas et al., 2011). Building on these foundations, we define demand bioenergetically: stress is any increase in metabolic demand that overwhelms the capacity of the stress response to increase output of the energy currency, adenine triphosphate (ATP) to meet the increased energy demand. What is known as the stress response, then, is an energetic response that helps the organism survive periods of high energy demands (Armario et al., 1990; Balasanthiran and Shotliff, 2015; Bobba-Alves et al., 2022; Busillo et al., 2011; Du et al., 2009; Eisner et al., 2018; Hunter et al., 2016; Mizuno et al., 2010; Picard et al., 2014; Selye, 1936; Tran and Wang, 2019; Wang et al., 2025; Wende et al., 2017).

Another key role of the stress response is to facilitate adaptations that increase the capacity of organisms to ensure survival and meet the demands of future stressors (Eisner et al., 2018). Although chronic and traumatic stress can trigger adaptive mechanisms that could arguably enhance short-term survival, they also drive maladaptive recalibrations that promote disease in the longer term (Radley and Herman, 2023). Metabolism and energy output, including behavior, are regulated through an anticipatory process called allostasis (Sterling, 1988). Mitochondrial networks within and between cells (Picard and Shirihai, 2022) have been called the mitochondrial information processing system (MIPS), which regulates allostasis at the cellular level, and interacts with the peripheral and central nervous system (CNS) networks that comprise the allostatic-interoceptive system (Kleckner et al., 2017). The MIPS, therefore, plays a key role in regulating systemic allostasis (Kelly et al., 2024). The allostatic-interoceptive system refers to a brain network including insular nuclei that receive and integrate interoceptive and metabolic information from the peripheral nervous system (Craig, 2009; Critchley and Garfinkel, 2017; Tsakiris and Critchley, 2016), and in conjunction with the anterior cingulate cortex, among other regions, generate affective states that fine tune allostasis (Kleckner et al., 2017; Sennesh et al., 2022). However, stress dysregulates the MIPS and the allostatic-interoceptive network, reducing metabolic efficiency, and increasing the risk of energy scarcity when demand is high.

What happens when despite the additional energy made available by the stress response, energy demand exceeds production capacity? A third major function of the stress response is that during energy scarcity, organisms prioritize and (re)direct available energy to the processes necessary for survival (Bobba-Alves et al., 2022). For example, if an organism faces life-threatening danger, the autonomic nervous system shunts blood flow away from digestion towards skeletal muscles to facilitate the fight or flight response (Cannon and de la Paz, 1911). Organisms also shunt energy from systems that produce better long-term outcomes, such as growth, maintenance, and repair process, as explained in the energetic model of allostatic load (EMAL) (Bobba-Alves et al., 2022). Applying EMAL to the CNS, we propose that stress triages energy away from metabolically expensive, but acutely dispensable (for survival) brain functional network activation patterns, to less expensive networks that mediate attentional vigilance and fear-response behaviors. Henceforth, we call this general principle “allostatic triage”, which we propose is a major driver of the bidirectional causation between stress-associated peripheral and psychiatric disease. For brevity, we focus on allostatic triage in the CNS here.

Building on Lisa Feldman Barrett’s embodied predictive interoception coding model (EPIC) of allostatic-interoceptive system function, we propose that affective states, which reflect the brain’s internal model of metabolic efficiency, regulate allostatic triage in the CNS (Barrett et al., 2016; Sennesh et al., 2022). In this model, positive affect represents the organism’s perception of high metabolic efficiency and the ability to handle additional metabolic load. This state of plentiful energy resources drives expensive behaviors, such as goal-oriented decision making and problem solving that optimize long-term outcomes in humans and higher animals. On the other hand, negative affect, as observed in MDD, represents the perception of low metabolic efficiency and the inability to handle additional load. We propose that negative affective states triage energy from costly processes and behaviors until conditions improve, as happens with aging (Shaulson et al., 2024).

Extending these fundamental notions to psychopathology, we propose that the normal process of allostatic triage during stress is exacerbated by stress-induced dysregulation of the MIPS and the allostatic-interoceptive network. We propose that dysregulated mitochondrial and allostatic-interoceptive networks drive unreliable body-to-brain and within-brain cascades that uncouple affective states from metabolic efficiency. When affective states no longer precisely represent metabolic efficiency, allostatic triage is exacerbated, allostasis is impaired (Barrett et al., 2016), and risk for psychiatric and medical diseases increases (Fig. 1).

The ATP model (Fig. 1) integrates existing models of cellular and systemic allostatic regulation into a whole-organism predictive framework. By highlighting the energetic competition that occurs within and between systems during stress, the ATP model aims to explain psychopathogenesis, and the bidirectional association of psychiatric disease with cardiometabolic and immune pathology through a bioenergetic lens. We present the ATP model in seven steps. First, we build on established definitions of stress (Koolhaas et al., 2011; Selye, 1950, 1946, 1936) to define it metabolically, and review its role in driving psychopathogenesis. Second, we review EPIC, which explains how metabolic information processing influences all neural activities through affective states (Barrett et al., 2016; Kleckner et al., 2017; Sennesh et al., 2022). Third, we describe the MIPS, its role in the stress response, and how it regulates cellular, systemic, and CNS allostasis, and behavior (Picard and Shirihai, 2022). Fourth, we outline EMAL, which describes how stress-induced energy scarcity drives energy tradeoffs to ensure short-term survival (Bobba-Alves et al., 2022). Fifth, we explain our novel concepts of affect-driven prioritization and CNS allostatic triage and how they mediate stress-induced CNS functional connectivity changes that we propose underlie psychiatric symptoms. Sixth, we explain how the changes in functional connectivity mediated by allostatic triage become “canalized” into psychopathology (Carhart-Harris et al., 2022). In section eight, we integrate these existing models and our novel concepts into the ATP model, discussing the implications of taking an energetic approach to understand the stress→disease cascade. Finally, we outline remaining gaps in the literature, and propose specific hypothesis that must be addressed to fill these gaps and test the veracity of the ATP model.

2. Section 2: Stress-induced energy scarcity drives psychopathology

Considering established definitions of stress from first principles, we ground our definition of stress metabolically, making stress-induced increases in “demand” quantifiable. It’s helpful to differentiate between stressors, which are internal or external stimuli that increase metabolic demand, and the stress response, an organism’s adaptive response to meet that increased demand. Organisms undergo stress when a stressor overwhelms their capacity to meet the increased metabolic demand, driving adaptations that impair or restrict function (Koolhaas et al., 2011). The stress response has three general roles: 1) increasing the systemic availability of energetic substrates (Armario et al., 1990; Balasanthiran and Shotliff, 2015; Selye, 1936), and energy production in stress-responsive tissues (Bobba-Alves et al., 2022; Busillo et al., 2011; Du et al., 2009; Hunter et al., 2016; Picard and McEwen, 2018; Tran and Wang, 2019; Wang et al., 2025; Wang et al., 2025); 2) activating adaptive processes that help cells and organisms perceive and respond to immediate and future stressors (Cameron and Schoenfeld, 2018; Eisner et al., 2018; McEwen, 1998; McEwen, 1998; Picard and McEwen, 2018; Sorrells and Sapolsky, 2010); and 3) shunting energetic resources to stress-responsive cells and tissues, and away from growth, maintenance, and repair processes (Bobba-Alves et al., 2022), and non-stress responsive cells (Tsigos et al., 2020), a process that we call allostatic triage and extend for the first time to CNS functional connectivity. When the stress response matches stress-induced increases in energy demand, adaptations improve function, but when insufficient energy is available, adaptations impair or restrict function. We define stress intensity as the stress-induced change in metabolic demand between two points in time, minus the stress-response-induced change in energy availability (stress intensity = Δ energy demand_{Time 1-Time 0} − Δ energy availability_{Time 1-Time 0}). Thus, stress occurs when stress intensity is positive, driving allostatic triage and functional impairment. Altogether, we ground established definitions of stressor, stress, stress response, and stress intensity bioenergetically, making each quantifiable from first principles.

We refer to stress as a general construct throughout this work. However, clear distinctions exist among acute, chronic, and traumatic stressors (Abbott et al., 1984; Zucchi et al., 2009), which differ among critical factors that increase stress intensity: 1) large increases in the magnitude or chronicity of increased metabolic demand, requiring greater activation of the stress response to facilitate sufficient energy availability; 2) severe perceived consequences of stress including damage or threat to the self, identity, or others, driving anticipatory stress (Koolhaas et al., 2011; O’Donovan et al., 2012; Selye, 1946, 1936); 3) perceived unpredictability (Anisman and Matheson, 2005; Baker and Stephenson, 2000), preventing anticipatory activation of the stress response to meet the increased demand; and 4) perceived uncontrollability (Baker and Stephenson, 2000), preventing behavioral adaptation to attenuate demand. Acute stressors activate the stress response and change systemic physiology and brain functional connectivity in healthy organisms, but the effects are generally adaptive and resolve quickly (Parihar et al., 2011). In contrast, traumatic stressors involving threat to life or physical integrity more often produce deleterious consequences (Keyes et al., 2013; Willard et al., 2016) Importantly, if unpredictable, even repeated mild stressors can evoke prolonged stress responses (Cameron and Schoenfeld, 2018; Glover et al., 2017; Koolhaas et al., 2011; Onat and Büchel, 2015). Moreover, early-life unpredictability (i.e., unpredictable sensory signals and/or parental behavior) is associated with psychopathology independently of exposure to traumatic stressors (Spadoni et al., 2022), and affects cognitive development and hippocampal signaling in both rats and humans (Davis et al., 2017). Growing evidence also suggests that repeated exposure to unpredictable stressors contributes to systemic metabolic inefficiency, called allostatic load (AL) (Danese and McEwen, 2012). In contrast, predictability and controllability buffer against the deleterious effects of stress (Cohodes et al., 2023). Importantly, other important qualitative and contextual factors are not captured by our definition of stress intensity, and are beyond the current scope to discuss. Altogether, metabolic demand, perceived consequences, predictability, and controllability, determine the adaptations produced by different stressors (Anisman and Matheson, 2005; Baker and Stephenson, 2000; Melo et al., 2020; Zakowski, 1995).

Numerous systems and signaling molecules are part of the stress response, including the sympathetic adrenal medullary axis that is activated within seconds and produces catecholamines (e.g., epinephrine), and the hypothalamic-pituitary adrenal (HPA) axis, which is activated within minutes and produces glucocorticoids (Arango-Lievano et al., 2015; Sapolsky et al., 2000). The stress response also activates the immune system and other diverse cell types, driving the release of immune and metabolic signaling molecules (e.g., cytokines (Garcia-Oscos et al., 2012; Ménard et al., 2017), mitokines, or metabokines (Kang et al., 2021)) to communicate metabolic stress to the CNS and other tissues (Agis-Balboa et al., 2011; Li et al., 2013; Martín-Montañez et al., 2017; Pardo et al., 2018). Within the CNS, stress increases the release of cytokines (Johnson et al., 2004; Wilson et al., 2013), serotonin (Murnane, 2019) and other neurotransmitters (Kelley, 2022; Mateos et al., 2008; Wilson et al., 2014) and neuropeptides (Albrechet-Souza et al., 2021; Itoga et al., 2016; Schreiber et al., 2017), which alter metabolism, plasticity, and the functional connectivity of neural networks. Each of these “stress mediators” modulate metabolism, mitochondrial function, and drive adaptation and allostatic triage (Supplemental Table 1).

Anticipating stress and mounting anticipatory responses enhances survival and attenuates stress intensity, but chronic exposure to unpredictable stressors can drive maladaptive responses and precipitate psychopathology. For example, anticipation of a future threat, real or imagined (i.e., anticipatory stress), activates the stress response and can itself be an endogenously generated stressor. When a threat is imminent, anticipatory activation of the stress response is adaptive, but exposure to real or imagined unpredictable stressors can drive anticipatory activation in the absence of threat (i.e., anxiety), especially in people with preexisting depression and anxiety symptoms (Havranek et al., 2016). Increasing blood glucose and triglycerides in the absence of stress-induced increased demand is metabolically costly because energy is required to both increase and remove them from circulation (Bruce S. McEwen, 1998; M. Picard et al., 2014). Furthermore, persistent stress-induced increases in blood glucose and triglycerides leads to protein and lipid glycation, oxidative and reductive stress, vascular endothelial damage, and insulin resistance, among other deleterious consequences that require additional energy to remediate (Kelley et al., 2022; Vanessa Fiorentino et al., 2013; Wilson et al., 2013). In fact, anticipatory, but not retrospective threat appraisals, mediated the relationship between chronic stress exposure and telomere length in a sample of postmenopausal women, which could occur as a result of repeated and prolonged activation of the biological stress response and increased AL (Kelley, 2022; O’Donovan et al., 2013). Chronic anticipatory activation of the stress response in the absence of a genuine stressor (i.e., false alarms) also dysregulates the MIPS and the allostatic-interoceptive system, perturbing physiology, and we propose, unnecessarily driving allostatic triage (discussed in detail in Sections 3, 4, 5, and 6 below). Altogether, chronic unpredictable stressors can dysregulate systems from mind to mitochondria by driving anticipatory stress that activates the stress response repeatedly and unnecessarily, leading to maladaptations and systemic pathology.

Chronic and traumatic psychological stress are among the strongest known environmental risk factors for psychopathology, including MDD (Kendler et al., 2004), bipolar disorder (Lex et al., 2017), posttraumatic stress disorder (PTSD) (Publishing, 2013; Smoller, 2016), anxiety disorders (Daviu et al., 2019; Kasai et al., 2008), psychotic disorders (van Winkel et al., 2008), and personality disorders (Bourvis et al., 2017). The comorbidity and symptom overlap of many psychiatric disorders may indicate a common etiology and pathophysiology. Indeed, while there are challenges and some debate (Watts et al., 2024), factor analysis of diagnostic and statistical manual of mental disorders-5 symptoms in large data sets yields a general psychopathology factor (p), and two smaller internalizing and externalizing factors, rather than disorder-specific factors (Allegrini et al., 2020; Carhart-Harris et al., 2022; Carver et al., 2017; Caspi et al., 2014; Fissler et al., 2022) and stress exposure is reciprocally linked to p during critical developmental periods (Snyder et al., 2019). While some symptoms are specific to particular psychiatric disorders, the lines between distinct disorders are unclear, and stress is clearly a common driver of psychiatric and transdiagnostic disease and the bidirectional relationships among them.

3. Section 3: CNS allostatic regulation: the EPIC model and affect-driven prioritization

Allostasis was first defined as “maintaining stability through change” (McEwen, 1998; McEwen, 1998; Sterling, 2014, 1988). Energy is the single most important factor for the maintenance of life, and allostasis can also be defined from a metabolic perspective: maintaining bioenergetic stability through stress-induced metabolic perturbations, which has emerged as a major focus of the field (Bobba-Alves et al., 2022; Eisner et al., 2018; Picard et al., 2014). While the concept of allostasis can be accurately applied to numerous biological processes, each of them is fundamentally bioenergetically driven. Therefore, in line with contemporary usage (Bobba-Alves et al., 2022; McEwen and Wingfield, 2010; Picard et al., 2014), we refer to bioenergetic allostasis when using the term “allostasis”. Allostatic systems anticipate metabolic and physiological changes and trigger adaptive processes to ensure equilibrium before setpoints are crossed (McEwen and Wingfield, 2010), as opposed to simpler reactive thermostat-like homeostatic responses (e.g., activate if the temperature exceeds 23°C). Allostatic systems must therefore anticipate the bioenergetic costs of daily activities, and future energy output, likely by maintaining an internal representation (i.e., model) of the important features of the systems they regulate (Barrett et al., 2016).

The brain allostatic-interoceptive system anticipates stress and triggers the energy production necessary to enact the appropriate behavioral responses, and reduce other costly behaviors to balance the energy budget before its overdrawn (Barrett, 2017a). For example, an individual may anticipate a future event that requires additional energy such as public speaking, and trigger the stress response to ensure that energy is available before the energy demand increases. However, chronic and traumatic stress, especially when unpredictable and uncontrollable, can alter important physiological and metabolic setpoints, including reducing or increasing the threshold for activation of the stress response, leading to over or under activation, as is observed in psychopathology (McEwen, 2005; McFarlane et al., 2011; Pariante and Miller, 2001; Yehuda et al., 2015, 2004; Young et al., 1991). In this way, prior stress exposure can impair anticipatory allostatic responses to subsequent stressors, increasing risk of energy scarcity and disease.

3.1. Active inference models of the allostatic-interoceptive system

Active inference posits that organisms interact with sensory information, including signals from the viscera, immune, and cardiovascular systems, to generate internal models of the interactions between the world, themselves, and their internal milieu. Internal models are experience-dependent inferences of the causes of sensory inputs and are refined by predicting the changes in those sensory inputs when the environment changes, or when behaviors are enacted. Active inference models were first developed to explain the function of six-layered neocortex broadly (Friston, 2010), but have now been independently applied to the CNS allostatic-interoceptive system by Lisa Feldman Barrett (Barrett et al., 2016; Kleckner et al., 2017; Sennesh et al., 2022), Anil Seth (Seth and Friston, 2016), and Karl Friston (Pezzulo et al., 2015). Understanding these types of models may be fundamental to understanding diverse anticipatory bioenergetic processes, including stress and affect.

The allostatic-interoceptive system receives sensory information that it uses to generate an internal model (a collection of “priors”) of systemic and cerebral metabolism and its relationship to behaviors, including endogenous functions. Behavior, be it motor, cognitive, or glandular secretions, are enacted as a test of the model’s veracity. If what the model predicts happens, the model is confirmed, and new behaviors are enacted to test the model’s next prediction, and so on. Actions are therefore one side of the two-sided coin of active inference and are inexorably compelled in tandem with the model’s predictions for the purpose of testing them and updating the model. Each time an action or environmental change alters the incoming sensory information unexpectedly, prediction errors are produced that update the model’s priors in real time, leading to a new set of predictions (derived from an updated model), and actions. This describes the basic active inference loop.

Barrett and colleagues proposed the EPIC model (Barrett et al., 2016) based on extensive tract-tracing and functional imaging experiments showing that afferent sensory information from the periphery is received and integrated in the insular cortex, which interacts with visceromotor regions of the anterior cingulate cortex, among other regions, to generate affect, defined as “the expected sensory consequences of allostatic changes within the body’s internal milieu” (Barrett et al., 2016). Visceromotor regions produce actions that regulate systemic allostasis, and efference copies (i.e., predictions) that anticipate the sensory outcomes of those actions, that are compared to incoming sensory information to produce prediction errors, which update the model in real-time. Affect is modeled with two axes, one for valence (i.e., positive vs negative), and one for intensity (Barrett, 2017a; Barrett et al., 2016). Altogether, affect is the continuous subjective experience of the predicted sensory consequences of allostatic active inference, and bioenergetically compels or constrains behavior based on energy availability (i.e., state-dependent behavior).

Barrett also proposed the theory of constructed emotion (Barrett, 2017b), defining emotions as socioculturally-dependent cognitive constructions that explain affective states in context (Barrett, 2017b). Contextual information from the external environment and internal bodily states, and cognitive processes including memory, attention, concepts, and categorization, shape the cognitive categorization and concept formation involved in the construction of emotions. We recognize that Barrett’s contrast between affect and emotions is distinct from common psychological definitions and normative usage, which often use the terms interchangeably. However, there is a critical difference between an organism’s lower-dimensional perception of its allostatic state (i.e., affect) and its interpretation of the causes of that state (i.e., emotion) that is not captured by normative usage. Therefore, we emphasize that affective states regulate systemic allostasis by anticipating and regulating systemic resource allocation as behaviors are enacted and the environment changes, while emotions are constructed through context-dependent, concept-driven predictive coding to explain affective states in context, which guide decision-making and high-order behavior.

3.2. Affective states regulate behavior according to metabolic efficiency: affect-driven prioritization

Metabolic allostasis is the foundation of neural computation. In healthy organisms, affect represents the capacity to handle additional metabolic load. If metabolic efficiency is high, affect is positive, and expensive actions such as challenging, but potentially rewarding activities that support long-term allostatic regulation are facilitated. If metabolic efficiency is low, affect is negative, compelling an organism to conserve energy by delaying costly behaviors and triaging resources away from expensive processing tasks until conditions improve. In this way, organisms regulate metabolic stress by controlling their energy output and resource allocation through affective states, a process that we call ‘affect-driven prioritization’.

Allostatic regulation likely requires an internal representation of metabolic efficiency at the relevant levels of biological organization (Conant and Ross Ashby, 1970; Pezzulo et al., 2015; Sennesh et al., 2022; Seth and Friston, 2016). Biologically, metabolic efficiency is the rate of energy expenditure relative to the minimum metabolic rate required to sustain life (Sturm et al., 2023); henceforth, we call this ‘biological metabolic efficiency’. However, maintaining allostasis itself has a metabolic cost that depends on how precisely internal models of metabolic efficiency fit the incoming sensory data. To account for this additional layer of complexity, we define a new general term: “allostatic metabolic efficiency” as the actual cost of regulating allostasis relative to the cost that would be incurred by a perfectly optimized model. For example, cells must maintain an internal model of cellular metabolic efficiency (Picard and Shirihai, 2022), while the allostatic-interoceptive system must maintain internal models of systemic and/or tissue or region-specific metabolic efficiency. However, metabolic efficiency differs between cells, tissues, networks, and systemically, especially after stress, begging the question: which systems contribute most to affective states? We propose that metabolic efficiency in networks and tissues implicated in expected future behaviors are weighted more heavily and have an outsized impact on affect relative to systemic metabolic efficiency. Altogether, metabolic efficiency, likely in systems implicated in future behavior, drive affective states, which regulate behavior through affect-driven prioritization.

3.3. Stress dysregulates affect by precipitating an inefficient internal model

Chronic and traumatic stress, especially when unpredictable, can reduce allostatic metabolic efficiency and drive psychopathogenesis through multiple mechanisms. Chronic stress increases sympathetic nervous system arborization (Capitanio and Cole, 2015; Sloan et al., 2008, 2007), altering HPA axis¹¹ reactivity (Lowrance et al., 2016), driving “false alarms” and unreliable prediction errors, reducing allostatic metabolic inefficiency (Barrett et al., 2016). Stress also dysregulates mitochondria (Eisner et al., 2018; Picard et al., 2014; Wang et al., 2025; Weger et al., 2020), reducing biological metabolic efficiency, and we propose contributes to the aforementioned (mitochondrially regulated- see Section 3 below) sympathetic nervous system and HPA axis dysfunction (Picard et al., 2014). Altogether, chronic and traumatic stress reduce allostatic metabolic efficiency through the generation of unreliable prediction errors.

Unpredictable stress is a particularly potent generator of unreliable prediction errors. Unpredictable stress leads to a broader distribution of priors for threat detection (i.e., less confidence in the environmental cues and contexts that predict threat or safety) and results in a less confident model of threat avoidance. This, in turn, drives the overgeneralized threat detection, maladaptive attempts at avoidance, and anticipatory stress observed in preclinical stress models (Cameron and Schoenfeld, 2018; Glover et al., 2017), trauma-related disorders (Besnard and Sahay, 2016; Cisler et al., 2024), and anxiety disorders (Fraunfelter et al., 2022). Initially, unpredictable stress drives imprecise internal models, and subsequently, inefficient actions, reducing allostatic metabolic efficiency and impairing allostasis. However, over time, unreliable prediction errors are discounted and internal models can grow overly precise and insensitive to sensory input (Barrett et al., 2016; Kleckner et al., 2017; Sennesh et al., 2022), resulting in inflexible affective states, a “locked in” brain, and the entrenchment of psychopathology, which is sometimes called “canalization” (Carhart-Harris et al., 2022). Altogether, if EPIC or similar models accurately describe CNS allostatic regulation, stress-induced changes in functional network activation and cognition can be understood in metabolic terms. Further, EPIC explains why stress, viewed bioenergetically, leads to unreliable prediction errors and the rigid cognitive landscapes associated with psychopathogenesis.

4. Section 4: The MIPS Bridges cellular and systemic allostasis

Despite their central role in metabolism, the designation of mitochondria as the “powerhouses of the cell” is insufficient to explain their myriad established functions (Belenguer et al., 2019; Picard and Shirihai, 2022). Mitochondria are living, dynamic, intracellular organisms (Picard and Sandi, 2021) and exhibit accepted principles of social behavior: functional specialization (Johri and Beal, 2012), communication, interdependence between individuals, and behavioral synchronization to achieve collective ends (Picard, 2015; Picard and Sandi, 2021; Picard and Shirihai, 2022). Mitochondria also move between cells, including neurons and immune cells (Borcherding and Brestoff, 2023), and high levels of cell-free mitochondria are observed in systemic circulation with unknown origins and destinations (Dache et al., 2020). The MIPS (Picard and Shirihai, 2022) transforms energy, and thus must receive, integrate, and process information about energy demands, communicate, and alter its function, to control energy flow within organisms and regulate local and systemic allostasis in collaboration with the allostatic-interoceptive system.

Mitochondria have evolved as information integration hubs that act as gatekeepers of metabolic information, and output summary signals that regulate allostasis. The MIPS receives signals from steroid (Du et al., 2009; Gak et al., 2015; Hunter et al., 2016; Sapolsky et al., 2000), serotonergic (Fanibunda et al., 2019), catecholaminergic (Lee et al., 2021; Lim et al., 2021; Mishra et al., 2020; Sandroni et al., 2022), insulin and insulin-like peptides (Bhardwaj et al., 2021; Du et al., 2019; Gazit et al., 2016; Gui et al., 2021), immune (Valença-Pereira et al., 2021), and metabolic factors (Sapolsky et al., 2000), and numerous other signaling molecules (Eisner et al., 2018; Picard et al., 2014; Picard et al., 2014; Picard, 2015), integrates that information within and between mitochondrial networks, and outputs summary signals to regulate cellular and systemic allostasis (Table 1). Through these mechanisms, the MIPS orchestrates key aspects of multiple stress-response systems directly (Goglia et al., 2002; Kelley et al., 2025; Midzak and Papadopoulos, 2016; Miller, 2013; Picard et al., 2014; Picard et al., 2018; Picard and Shirihai, 2022; Velarde, 2014), or indirectly (Goffart and Wiesner, 2003; Kim et al., 2018; Lee et al., 2002, 2008; Lombardi et al., 2019; Wiese and Bannister, 2020), allowing it to govern broad cellular and systemic functions. Altogether, the MIPS plays a dual role of energy producer and information processor, keeping the organism alive, and guiding its behaviors according to its allostatic program, forming the central bridge between local and systemic metabolic information processing (Picard, 2015).

Table 1.

Mitochondrial summary signals.

	Function	Summary Signal

1.	Direct: Signaling molecule biosynthesis	Metabolites, DNA & RNA precursors, ROS, cf-mtDNA, ions, bases, ATP, heat, small peptides, steroid hormones, catecholamines, monoamines
2.	Direct: Energy production, distribution, dynamics	ATP production & distribution, mitochondrial dynamics
3.	Indirect: Regulation of nuclear gene expression	Epigenetic regulation by Ca²⁺ signaling, metabolic enzymes, ROS, metabolites

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Table 1: The MIPS receives and integrates diverse inputs, and outputs three types of summary signals to regulate cellular and systemic allostasis: 1) Direct production of outputs: including metabolites, precursors for deoxyribonucleic acid (DNA), ribonucleic acid (RNA), reactive oxygen species (ROS), cell-free mitochondrial DNA, ions, gasses, ATP, heat, small peptides, and steroid hormones (Midzak and Papadopoulos, 2016; Miller, 2013), including sex (Velarde, 2014), metabolic (Goglia et al., 2002), and stress hormones (M. Picard et al., 2014); 2) Direct regulation of host cell activity via ATP production and distribution; 3) Epigenetic regulation of nuclear gene expression: Ca²⁺ signaling, metabolic enzymes, ROS and metabolites (Lombardi et al., 2019; Picard and Shirihai, 2022; Wiese and Bannister, 2020). MIPS: mitochondrial information processing system; DNA: deoxyribonucleic acid; RNA: ribonucleic acid; ROS: reactive oxygen species; ATP: adenine triphosphate.

4.1. The MIPS regulates function and behavior across all levels of biological organization

The MIPS regulates the behavior and function of cells, networks, and whole organisms, including the immune system. For example, mitochondrial respiratory capacity regulates adaptive immunity by regulating CD8 + T cell memory development, and innate immunity by controlling the differentiation and cytokine expression of innate immune cells (Karan et al., 2020; Keeney et al., 2023). Mitochondria also regulate macrophage polarization (Trinchese et al., 2024; Weinberg et al., 2015), inflammasome activation (Weinberg et al., 2015), and various other immune functions through energy sensing pathways (Chen et al., 2023), mitophagy (Angajala et al., 2018), fission and fusion events (Angajala et al., 2018; Trinchese et al., 2024), ROS production (Chen et al., 2023; Weinberg et al., 2015) and metabolic intermediates (S. Chen et al., 2023; Trinchese et al., 2024), each regulating different signal transduction pathways critical to immune function (Iwasaki et al., 2020). Mitochondria also regulate cardiometabolic (Zong et al., 2024), endocrine (Jin and Diano, 2018), and other physiological functions (Harrington et al., 2023). Importantly, psychopathology is associated with chronic inflammation (Mellon et al., 2018; Miller and Raison, 2016; Müller, 2018; O’Donovan et al., 2017), which is metabolically expensive, contributing to systemic metabolic load (Bird, 2019; Ganeshan et al., 2019) during stress.

The MIPS regulates adaptive CNS processes, including gene expression (M. Picard et al., 2014; Yang et al., 2001), the production and metabolism of monoamine and catecholamine neurotransmitters (Graves et al., 2020; Lee et al., 2021; Rasbach et al., 2010), aspects of glutamate (Robinson et al., 2020) and gamma-aminobutyric acid production and metabolism (Besse et al., 2015; Cavalcanti-de-Albuquerque et al., 2021), excitability and neurotransmitter release (Kwon et al., 2018, 2016; Sun et al., 2013; Ugur et al., 2017), neuroplasticity (Cheng et al., 2010; Chihara et al., 2007; Courchet et al., 2013; Fukumitsu et al., 2016; Gebara et al., 2021; Kimura and Murakami, 2014; Mattson, 2007; Mattson et al., 2008) and neurogenesis (Adusumilli et al., 2021; Khacho et al., 2019; Khacho and Slack, 2018), and glial cell function and proliferation (McAvoy and Kawamata, 2019), which scale to whole-organism behaviors. In fact, mitochondrial respiratory chain enzyme activities in one striatal network are associated with anxiety-like and avoidance behavior (Rosenberg et al., 2023), hippocampal mitochondrial gene expression is associated with avoidance, and ROS production is associated with pattern separation in stressed, but not control rats (Kelley et al., 2023). Further, experimental manipulation of mitochondria mediates whole organism behaviors, including anxiety and depressive behaviors (Gebara et al., 2021), social dominance (Ghosal et al., 2023; Hollis et al., 2015), and prosociality (Pozo et al., 2023). In humans, peripheral superoxide-sensitive mitochondrial redox environments bioenergetically mediate motor performance (Spooner et al., 2021). Together, these examples exhibit regulation of broad physiological processes and behaviors across all levels of biological organization by the MIPS.

4.2. The MIPS regulates the allostatic-interoceptive system

The MIPS regulates systemic allostasis directly by managing cellular allostasis and through diverse signaling mechanisms, including stress mediators (Supplemental Table 1), and indirectly by regulating the allostatic-interoceptive system. Interoceptive information about systemic metabolism and metabolic stress is communicated to CNS, linking peripheral and CNS mitochondria into the whole organism MIPS. In the CNS, nodes of the MIPS regulate the allostatic-interoceptive system by receiving, metabolizing, and producing signaling molecules (Supplemental Table 1) and managing allostasis within neurons and glial cells that comprise allostatic-interoceptive networks (Jin and Diano, 2018). Importantly, receptors for many stress mediators are highly expressed in the insular and anterior cingulate regions that comprise the allostatic-interoceptive system (Sjöstedt et al., 2020). Therefore, dysregulation in the MIPS dysregulates the allostatic-interoceptive system, reducing allostatic metabolic efficiency, and dysregulating affect. We discuss the consequences of reduced systemic and CNS metabolic efficiency, and affective dysregulation in Sections 4 and 5 below, respectively.

5. Section 5: EMAL: energetic tradeoffs drive disease

Biological metabolic efficiency is reduced in disease states, primary mitochondrial disorders (Niyazov et al., 2016), and after chronic exposure to stress or stress mediators (Sturm et al., 2023). Biological metabolic efficiency depends on at least three important cellular factors (Table 2), in addition to external factors such as the energetic substrates used as inputs for energy production (i.e., glucose, ketones, etc). Chronic exposure to stress or stress mediators drives hypermetabolism and mitochondrial adaptations (Madrigal et al., 2001; Picard and McEwen, 2018) (Supplemental Table 2) necessary to maintain elevated energy output, but that reduce metabolic efficiency (Sturm et al., 2023). Specifically, stress-induced reductions in the ratio of ATP/adenine diphosphate (ADP) relative to the combined cost of metabolism itself and the increased background costs of hypermetabolic states, characterize mitochondrial allostatic load (MAL) (Picard et al., 2014) (Supplemental Table 3). Stress-induced hypermetabolism is necessary to increase energy production, but is chronically maladaptive because it drives MAL, resulting in genetic and epigenetic dysregulation (Flint et al., 2007), telomere shortening (Kawanishi and Oikawa, 2004), and cellular senescence (Wiley et al., 2016). Chronic MAL reduces the capacity for growth and adaptation, and drives dysregulation at higher levels of biological organization, such as inflammation (Picard et al., 2014; Sturm et al., 2023), metabolic disease (Picard et al., 2014), and psychiatric symptoms. In this way, even if the total amount of ATP and the ATP/ADP ratio is increased, hypermetabolic cells use more energy to produce that ATP and for background costs, which can lead to energy scarcity despite increased metabolism (i.e., metabolic inefficiency). Altogether, when cells are less efficient, they have less energy to repair themselves, grow, and flexibly adapt to their environments.

Table 2.

Factors mediating biological metabolic efficiency.

1. Source of ATP:	ATP production rates by glycolysis or mitochondrial oxidative phosphorylation
2. Stoichiometry:	ATP produced per unit of reductive substrate (NADPH, FADH2) relative to the amount of ADP in the system (ATP/ADP ratio is more important than total ATP levels)
3. Background Costs:	Rate of ATP consumption for allostasis, growth, adaptation, and housekeeping (e.g., transcription, translation, biogenesis, maintenance, and repair)

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Table 2: Three critical factors that contribute to the efficiency of metabolism itself (biological metabolic efficiency). Other factors such as the energetic substrates used as inputs for ATP production also contribute to metabolic efficiency, but are not included here because they are not features of the system itself. ATP: Adenine triphosphate; ADP: Adenine diphosphate; NADPH: Nicotinamide Adenine Dinucleotide Phosphate; FADH2: Reduced form of Flavin Adenine Dinucleotide (FAD)

5.1. MAL drives systemic and CNS metabolic inefficiency

MAL drives dysregulation at higher levels of biological organization because cellular, tissue, organ, and neural network function are regulated by the MIPS. Bruce McEwen described common ways that chronic activation of the stress response alters its dynamics (McEwen, 1998; McEwen, 1998; McEwen and Wingfield, 2010). Chronic or traumatic stress, and MAL (Picard et al., 2014) can reduce or increase thresholds for activation of the stress response, driving repeated activation, a prolonged response, or reduce thresholds, producing an inadequate response (McEwen, 1998). Persistent allostatic states and hypermetabolism results in physiological maladaptations including hypertension, hyperglycemia, hyperlipidemia, and changes to the lipid profile of the brain (Chaichi et al., 2021; Clement et al., 2009; Kelley et al., 2022; Madrigal et al., 2001; Prasad et al., 2019) and other tissues (Miao et al., 2023; Tham et al., 2018), characterizing the shift from allostatic states to AL (Buckwalter et al., 2016; Hilliard et al., 2016; Leslie and Vartak, 2020; McEwen and Wingfield, 2003; Seeman et al., 2001, 1997; Suvarna et al., 2020). Persistent AL drives additional physiological recalibrations, further reducing metabolic efficiency and energy availability for growth, maintenance, and repair, characterizing the shift to allostatic overload (AOL) (Bobba-Alves et al., 2022). AOL is associated with alterations to receptors and chaperones for energetic substrates and stress mediators (Boks et al., 2016; Wang et al., 2018; Xie and Bu, 2019), circadian changes to HPA and sympathoadrenal-medullary axis function (Fava et al., 2019; Sapolsky et al., 2000), increased hemoglobin A1c (Fava et al., 2019; Seeman et al., 1997; Suvarna et al., 2020), chronic inflammation (Buckwalter et al., 2016; Hilliard et al., 2016; Seeman et al., 2001, 1997; Suvarna et al., 2020), arterial stiffening to maintain elevated blood pressure, and the structural remodeling of brain circuits and anatomy (Bobba-Alves et al., 2022), features of cardiometabolic, autoimmune, and psychopathology. MAL characterizes cellular metabolic inefficiency (Picard et al., 2014), and AL and AOL characterize systemic metabolic inefficiency (McEwen, 2015), both forms of biological metabolic efficiency. Importantly, MAL, AL, and AOL contribute to allostatic metabolic inefficiency, dysregulating affect. When affective states become decoupled from biological metabolic efficiency, affective allostatic regulation is impaired, exacerbating biological metabolic inefficiency, a positive feedback loop driving disease.

5.2. Metabolic inefficiency drives disease pathogenesis

Biological metabolic inefficiency drives disease pathogenesis because it reduces the reserve metabolic capacity of cells and organisms, increasing the chances of energetic scarcity and the necessity of deleterious energetic tradeoffs when energy demand is high. Bruce Ames proposed “Triage Theory” which explains that organisms triage micronutrients, including essential vitamins and minerals, to the processes most necessary for survival when resources are scarce (Ames, 2006). EMAL proposes that the same is true for energetic resources; when energy is scarce, or predicted to be scarce by the allostatic-interoceptive system, organisms allocate energetic resources to the processes predicted to be necessary for survival, at the expense of growth, maintenance, repair, and other costly functions in other domains. During scarcity, the finite energy budget of an organism must be distributed competitively among physiological functions according to their metabolic costs and perceived necessity. Reduced energy resource allocation to maintenance and repair leads to the accumulation of damage, further reducing efficiency and impairing function, while reduced allocation of energy to growth impairs flexible adaptation to the environment. Altogether, energy tradeoffs drive and follow from metabolic inefficiency, and reduce phenotypic plasticity, driving transdiagnostic disease pathogenesis.

MAL limits phenotypic flexibility. The integrated stress response (ISR) (Costa-Mattioli and Walter, 2020) is activated by factors of MAL, and globally limits gene transcription and protein translation, apart from a restricted set of genes that are crucial for acute stress adaptation. Furthermore, ISR activation alters systemic allostatic regulation through the mitochondrially-mediated nuclear production of “mitokines” such as fibroblast growth factor 21 (FGF-21) (Flippo and Potthoff, 2021; Restelli et al., 2018) and growth and differentiation factor 15 (GDF-15) (Wang et al., 2021), which are released into systemic circulation and signal metabolic stress to the CNS and other tissues. Both acute (Gouspillou et al., n.d.) and chronic stress can increase mitokine levels, which can activate the HPA axis (Cimino et al., 2021; Ryan et al., 2018) in support of allostasis. Mitokines generally exert protective effects, but we propose that chaotic release of stress mediators, like mitokines, reduces allostatic metabolic efficiency, as discussed above. We hypothesize that the limited breadth of gene expression and phenotypic flexibility that follows from chaotic or chronic ISR activation, entrenches inflexible maladaptive phenotypes at higher levels of biological organization. Indeed, transdiagnostic psychiatric and systemic disorders are associated with AL (Bersani et al., 2020; Kelley, 2022; Lenart-Bugla et al., 2022; McEwen, 2003; Mellon et al., 2018; Miller et al., 2018; Seeman et al., 2001), MAL (Amorim et al., 2025; Becker et al., 2022; Blalock et al., 2024; Hummel et al., 2023; Jiang et al., 2024; Lushchak et al., 2023; Ni et al., 2024; Peoples et al., 2019), and ISR activation (Korneeva, 2022; Zhang et al., 2022). Thus, consistent with EMAL, we propose that AL, MAL and ISR activation drive transdiagnostic disease pathogenesis by inducing metabolic inefficiency, energy scarcity, and subsequently, phenotypic inflexibility.

6. Section 6: CNS allostatic triage: affect-driven prioritization of brain functional connectivity

Applying EMAL to CNS functional networks, we propose a general principle of brain function: allostatic triage regulates brain functional connectivity during energy scarcity according to metabolic cost and survival value. Specifically, allostatic triage leads to the redistribution of brain metabolic resources from metabolically expensive networks optimized for long-term outcomes to the least expensive networks that can ensure short-term survival during energy scarcity. As discussed above in Section 3, affect is generated by the allostatic-interoceptive system from internal models of metabolic efficiency. Integrating EPIC and EMAL, we hypothesize that affect defines the setpoint above which allostatic triage occurs, a process that we call affect-driven prioritization.

Why must the brain triage resources rather than simply increasing energy production? Energy is a finite resource, and the brain is particularly sensitive to metabolic stress. All biological activities are dependent upon energy metabolism, but the human brain is the most expensive organ, using 20 % of oxygen and 25 % of glucose (Erbsloh et al., 1958; Magistretti and Allaman, 2015; Magistretti and Pellerin, 1999; Zhu and Thompson, 2019) despite it being just ~2–3 % of the total body mass (Erbsloh et al., 1958; Magistretti and Pellerin, 1999). While the cardiovascular system is also disproportionally expensive, the brain extracts oxygen (30 %) more slowly compared to the heart (80 %) or muscle (90 %), resulting from its comparatively low capillary density, unique sensitivity to pH changes, hyperglycemia and hyperoxemia, and brain-specific requirements to maintain the entropy change of mitochondrial oxidative metabolism (e.g., the O₂/CO₂ ratio) (Buxton, 2010, 2024, 2021). Due to these limitations, the brain continuously operates at or near its maximal metabolic capacity and can only increase its overall cerebral metabolic rate of oxygen by 10–30 % during intense increases in demand, although some grey matter regions can increase by up to 40 % (compared to a 10 fold increase in muscle) (DiNuzzo et al., 2024). Therefore, brain energy production is restricted by a hard upper limit on its access to energetic resources, making it particularly sensitive to systemic and CNS metabolic inefficiency, which can quickly lead to energy scarcity when demand is high (Buxton, 2021; DiNuzzo et al., 2024).

What is the metabolic value of triaging energetic resources between brain networks? There is a hierarchy of metabolic costs in the brain. Most of the brain’s energy is devoted to intrinsic activity (Zhang and Raichle, 2010), which exerts constant demand, while task-dependent activation is the most variable. The number of neurons in a network increases the metabolic cost of CNS network activation (Arshavsky, 2023), but the preponderance of evidence in humans suggests that synaptic density (Yu et al., 2023) and the number of metabotropic neuromodulator receptors (Castrillon et al., 2023) are the primary determinants of CNS metabolic cost. Indeed, cortical activation typically involves synaptically dense integration hubs (Yu et al., 2023) and is more bioenergetically expensive than subcortical activation, and the most evolutionarily expanded cortical regions are the most costly (Mosharov et al., 2025). Signaling in evolutionarily expanded regions, including the prefrontal cortex (PFC), and networks including the central executive (CEN, also called the frontoparietal network) and default mode networks (DMN), which have the highest number of neuromodulator receptors, have the greatest blood perfusion (Farahani et al., 2025), use up to 67 % more glucose (Castrillon et al., 2023), and show the highest levels of mitochondrial enzyme activity (Mosharov et al., 2025) compared to phylogenetically older and less complex attentional and sensory-motor networks. Several neuromodulator receptors enriched in the most evolutionarily expanded networks (e.g., 5-HT_2A, muscarinic receptors) are activated by stress (Baik, 2020; Glavin, 1985; Murnane, 2019), strongly overlap with mitochondrial enzyme activity (Mosharov et al., 2025) and blood perfusion (Farahani et al., 2025), alter mitochondrial and cellular metabolism (Fanibunda et al., 2019; Graves et al., 2020; Lim et al., 2021; Mishra et al., 2020), and facilitate complex cognition (Castrillon et al., 2023; Grossman and Cohen, 2022). Indeed, experimental evidence from individuals with inherited mitochondrial disorders exposed to stress-induced increases in energy demand, supports the hierarchical triage of metabolic resources from evolutionarily expanded regions mediating complex cognition to older regions mediating sensory, vigilance, and fear-related processes (Bo et al., 2025). Altogether, phylogenetically younger neuromodulator receptor-rich networks that mediate complex executive and self-referential behaviors are more metabolically costly than networks mediating sensory, attention, vigilance, fear, habits, and vital functions (Castrillon et al., 2023; Tomasi et al., 2013), and are more susceptible to allostatic triage during energy scarcity.

According to EPIC, affect predicts the ability of a healthy organism to handle additional stress or metabolic demand without losing function. Activation of the stress response alters affect by changing predictions about energy expenditure and availability. However, chronic and traumatic stress reduces metabolic efficiency and dysregulates affect. We propose that dysregulated affective states still drive allostatic triage such that the negative affect observed in MDD (bottom dark blue dashed line in Fig. 2), will elicit allostatic triage at a lower level of energy demand than if the same individual was in a state of strong positive affect (top light blue line in Fig. 2). We hypothesize that during energy scarcity, the available energy is first triaged between networks within the task-dependent activation category, but as stress grows in intensity and/or chronicity, energy must also be triaged away from growth (i.e., neuroplasticity), maintenance, and repair processes, depending on their predicted survival value in context, further reducing brain metabolic efficiency and phenotypic flexibility over time (Fig. 2). Altogether, we propose that allostatic triage occurs in healthy organisms during high demand but becomes pathological when it’s governed by dysregulated affective states. To illustrate allostatic triage, we discuss examples of stress-induced and psychopathology-associated differences in CNS functional connectivity in relation to their energetic costs below.

Fig. 2. — Hypothetical ATP Model of CNS allostatic triage based on EMAL. Each colored box represents a different category or “bucket” of energy use in the CNS. Increased task-dependent neural activation (red box) is required for cognitive activities that produce the behaviors necessary to respond to stressors, and in the context of increased energy demand (i.e., stress) and insufficient energy production, can necessitate allostatic triage from other networks within that category, or when extreme, from other categories (other colored boxes). Moving from left to right on the figure, the level of bioenergetic demand on the CNS increases, starting with mild stress (− or healthy allostasis) to moderate to intense stress (+, ++ or allostatic load), and extreme stress and energetic demand (+++, ++++ or allostatic overload). The red shaded area indicates which categories are being triaged to support additional resource allocation to task-dependent activation based on the level of demand. Affect, which is derived from the internal model of the predicted bioenergetic state of the organism, is represented by the three different shades of blue dashed lines. We propose that affect determines the setpoint (i.e., the level of energetic demand) at which allostatic triage begins to occur (i.e., affect-driven prioritization) Negative affect, representing the prediction that energy efficiency is low or uncertain (bottom darkest blue dashed line), causes triage at lower levels of stress. Positive affect represents the prediction that energy is abundant and results in reduced triage as stress increases (top lightest blue dashed line). Importantly, allostatic triage need not first triage energy from neuroplasticity followed by maintenance and repair, and so on, in that order. Rather, energetic resources are likely triaged from multiple buckets simultaneously, a limitation of presenting this figure in two dimensions. ATP Model: Allostatic Triage Model of Psychopathology; CNS: Central Nervous System; EMAL: Energetic Model of Allostatic Load. Figure created on Biorender.com.

6.1. Stress and psychopathology alter CNS functional connectivity

Acute stress and stress mediators generally shift CNS activation patterns towards phylogenetically older, less metabolically expensive networks, and alter signaling within and between phylogenetically younger and more expensive networks. For example, norepinephrine and glucocorticoids shift activation from cortico-striatally mediated goal-oriented behavior towards lateral striatally-mediated habits and compulsions (Schwabe and Wolf, 2011), which are less metabolically costly. At the network level, acute stress activates the salience network (SN), which plays a major role in attentional vigilance and threat detection, and the expression of anxiety, fear, and habitual and compulsive behaviors that are associated with psychopathology. Acute stress also activates the DMN, and the CEN, but these effects are complex and differ by the protocol used (van Oort et al., 2017). Some stress paradigms show reduced CEN activation and function, while others show increases or shifts in activation and function within the CEN (van Oort et al., 2017). For example, acute stress-induced cortisol release shifts neural resources within the CEN from circuits underlying cognitive flexibility (Plessow et al., 2011; Shields et al., 2016) to those underlying goal shielding (Plessow et al., 2011), which refers to maintaining one’s focus on a goal by avoiding other goals, a possible bioenergetic tradeoff. Altogether, acute stress and stress mediators alter CNS functional connectivity and function consistently with allostatic triage, though more evidence is needed to fully understand these processes. We hypothesize that allostatic triage is one driver of the effects of acute stress on CNS functional connectivity, especially in the context of metabolic inefficiency.

Pre to post human imaging data in chronic stress paradigms is limited, but the available evidence suggests that chronic stress drives persistent resting state SN activity (McCutcheon et al., 2019), and increased vigilance, habitual, and compulsive behaviors. Chronic stress also modifies CEN functional connectivity (Hermans et al., 2017, 2014; McCutcheon et al., 2019) and impairs broad executive functions (Bloemen et al., 2018). Interestingly, after stress resolves, healthy organisms may show increased rebound activation of the CEN, which may support recovery from stress, but this effect may be impaired after chronic or intense stress (Hermans et al., 2017, 2014). Chronic stress is also associated with impaired DMN network connectivity (Zeev-Wolf et al., 2019). Importantly, brain state transitions are metabolically expensive (Gu et al., 2018), and additional activation energy may be required to transition out of chronic stress-induced functional connectivity patterns, suggesting that stress-induced maladaptive states could become entrenched over time as psychiatric disorders. Altogether, diverse forms of chronic stress increase SN functional connectivity, vigilance, habits, and compulsions, but alter CEN connectivity and reduce executive function (Girotti et al., 2018; Hermans et al., 2017), echoing the transdiagnostic features of psychopathology (Bloemen et al., 2018; Snyder, 2013).

Psychiatric disorders are associated with both transdiagnostic and disorder-specific differences in CNS functional connectivity. The SN is expanded in MDD and connectivity changes in the SN predict affective symptoms (Lynch et al., 2024). There are also differences in SN functional connectivity in schizophrenia (Chen et al., 2016; Pietrzykowski et al., 2022), PTSD (Akiki et al., 2018) and GAD (Xiong et al., 2020), which, like MDD (Li et al., 2021) also exhibit differences in CEN connectivity (Akiki et al., 2018; Coussement et al., 2022), and deficits in executive function. DMN activity is increased in MDD (Scalabrini et al., 2020), though there is ongoing debate, with studies showing both downregulation and upregulation, depending on the analysis techniques used (Scalabrini et al., 2020). Altered DMN functional connectivity has been observed in Schizophrenia (Manoliu et al., 2014), PTSD, and GAD, and GAD is also associated with reduced DMN cortical volume (Bashford-Largo et al., 2022). Activity across all three networks has also been used to predict heterogeneous presentations of PTSD using machine learning approaches (Nicholson et al., 2020). Altogether, while existing data paint a highly nuanced picture of brain connectivity in psychopathology that is beyond the scope of this work to comprehensively review, two networks and their associated behaviors and cognitive functions emerge as transdiagnostic features of chronic stress and psychopathology: 1) increased SN connectivity and vigilance, habitual, and compulsive behaviors, and 2) altered CEN connectivity and impaired cognitive flexibility, goal-oriented cognition, and executive function.

To illustrate the potential role of allostatic triage in driving psychopathogenesis, we highlight 1) and 2) above. We hypothesize that altered CEN functional connectivity and impaired executive function results from allostatic triage within nodes of the CEN, and from the CEN to other networks, including the SN, and from the downregulation of compensatory activation after stress resolves (Fig. 3). Critically, most regions of the SN are less metabolically expensive than those of the CEN (Castrillon et al., 2023; Farahani et al., 2025; Mosharov et al., 2025). Accordingly, Fig. 3 highlights our general principle that in the context of predicted energy scarcity and metabolic inefficiency, negative affective states exacerbate allostatic triage from expensive networks that optimize long-term outcomes, such as the CEN, to less costly networks with high survival value, such as the SN (Fig. 3). Importantly however, the predicted outcomes of circuit and network activation, and the resulting behavioral states are also crucial determinants of brain functional connectivity. Thus, the ATP model does not necessitate that energetic resources are exclusively triaged from more expensive to less expensive networks. Rather, we propose that the allostatic-interoceptive system drives allostatic triage according to the predicted outcomes of network activation (e.g., survival value), and only to the (predicted) extent necessary to maintain allostasis. Altogether, we hypothesize that stress-induced pathological allostatic triage generally impairs CEN function, and leads to SN overactivation, driving general features of psychopathology. However, we hypothesize that stressor and disorder-specific changes in functional connectivity emerge from allostatic triage applied to the specific patterns of network activation predicted to best optimize survival versus long-term outcomes for each individual in context, especially when those predictions are unreliable and the changes are maladaptive.

Fig. 3. — Illustrative example of chronic stress-induced allostatic triage from the central executive network (CEN) and goal-directed and executive functions to the salience network (SN) and vigilance, fear, habitual, compulsive, and stimulus-response behaviors. We propose that this process results from stress-induced reductions in biological metabolic efficiency (i.e., the efficiency of metabolism itself) and allostatic metabolic efficiency (i.e., the efficiency of allostatic regulation), and is regulated by affective states, which represent internal models of metabolic efficiency, a process that we call affective prioritization. Critically, allostatic triage is exacerbated by the affective dysregulation caused by chronic stress. Arrows represent activation and blunted lines indicate inhibition. Black indicates the normal effects of stress and white indicates the effects of allostatic triage. The background color indicates stress intensity with yellow/orange indicating mild or acute stress, light red indicating intense or chronic stress, and dark red indicting stress-induced disease pathogenesis. The shift from light red back to yellow indicates recovery, which may be impaired after chronic stress. The bidirectional white arrows between biological and allostatic metabolic efficiency indicate the mutual dependence of both processes. The white arrow and blunted inhibition symbol from reduced allostatic metabolic efficiency to increased vigilance, fear behaviors, habits, etc, and increased goal directed behaviors and executive control indicate allostatic triage from expensive executive functions that optimize long-term outcomes to less costly behaviors that ensure short-term survival. The white arrows and inhibition symbols from negative affect to vigilance and fear behaviors, and goal-directed behaviors, respectively, during “impaired recovery”, indicates that the process of rebound enhancement of the CEN after stress is impaired after chronic stress-induced allostatic dysregulation, driving psychiatric symptoms. Importantly, the CEN and SN are represented here as illustrative examples, but we propose that allostatic triage occurs among all functional brain networks, depending on their predicted outcomes and metabolic costs. Figure created on BioRender.com.

7. Section 7: Canalization of psychopathology: changes in CNS functional connectivity become entrenched through canonical mechanisms of neuroplasticity

Stress and allostasis alter CNS plasticity (McEwen and Gianaros, 2011), and AL is associated with structural changes in the brain (Lenart-Bugla et al., 2022). Indeed, persistent stress-induced changes in network and circuit activation may be stabilized over time through canonical mechanisms of neuroplasticity, producing psychiatric disease phenotypes. Some anatomical features of psychopathology, like a larger SN, appear stable and “trait-like”, but persistent changes in the patterns of network activation can predict affective symptoms, suggesting that dynamic changes to the SN track with symptoms (Lynch et al., 2024). Further, childhood trauma exposure is associated with a smaller hippocampus and a trend towards larger amygdala volume (Logue et al., 2018) which are risk factors for developing PTSD (Gilbertson et al., 2002), and trauma exposure and PTSD in adulthood may further reduce hippocampal volume (Bremner et al., 2021; Zheng et al., 2021), suggesting that in some cases, even gross anatomical differences can emerge from the neuroplasticity induced by traumatic stress.

Neuroplasticity in some brain networks and contexts may represent a dispensable biological function that is triaged away from some networks and towards others in the context of bioenergetic scarcity according to network activity (Fig. 2, Fig. 3). This is not a new concept; canonical Hebbian neuroplasticity (i.e., long term potentiation (LTP)) applied to consistently expressed brain activation and behavioral patterns may lead to the entrenchment of those patterns and reduced behavioral and phenotypic plasticity (i.e., phenotypic stabilization). This process of phenotypic stabilization has been described as “canalization” by Robin Carhart-Harris, in line with Waddington’s original use of the term (Carhart-Harris et al., 2022; Waddington, 1942). During energy scarcity, we propose that energy is triaged from the expensive CEN to the less costly SN, which drives psychiatric symptoms when overactive. Changes in brain activation patterns are expensive (Gu et al., 2018). Therefore, if there is less post-stress rebound activation of the CEN (Hermans et al., 2017, 2014), we might expect those patterns to become canalized over time into psychopathological phenotypes.

8. Section 8: The allostatic triage model of psychopathology (ATP model)

Each of the prior sections introduced an established principle, or a novel, but well-supported proposal that we integrated into the ATP model Section: 2) Stress-Induced Energy Scarcity: Stress overwhelms the capacity of the stress response to meet stress-induced increases in demand, driving energy scarcity; 3) Affect-Driven Prioritization: affective states represent predicted metabolic efficiency and regulate neural network activation and behavior based on predicted resource availability; 4) MIPS Bridges Cellular and Systemic Allostasis: the MIPS regulates allostasis, function, and behavior across all levels of biological organization, directly, and indirectly by regulating the allostatic-interoceptive system; 5) EMAL: Bioenergetic Tradeoffs: stress induces energy scarcity, requiring the reallocation of resources (i.e., allostatic triage) from metabolically expensive processes that optimize long-term outcomes (i.e., growth, maintenance, and repair) to processes required to maintain short-term survival; 6) Dysregulated CNS Allostatic Triage: stress and metabolic inefficiency drive allostatic triage, and when chronic, impair the affect-driven prioritization of CNS functional network activation, driving persistent allostatic triage from energy-demanding complex cognition, to less expensive networks optimized for survival, driving psychopathogenesis; 7) Canalization: stress-induced network activation patterns and the resulting psychiatric symptoms become entrenched through canonical mechanisms of neuroplasticity. Chronic changes in CNS functional connectivity induced by pathological levels of allostatic triage are essentially maladaptive changes to the functional setpoints of CNS connectivity, echoing established stress-induced shifts in other physiological setpoints (B. S. McEwen, 1998; McEwen, 2005). By fixing the brain into a specific state that is bioenergetically resistant to change, entrenched activity patterns drive psychopathogenesis through canalization.

Each of these principles, other than our novel concept of affect-driven allostatic triage, is well-established in the literature. In Section 6, we provide evidence supporting differences in the metabolic costs of CNS functional network activation, and for the limited access to metabolic resources in the CNS, setting the stage for resource scarcity during stress. Furthermore, recent work on functional network activation in primary mitochondrial disorders (Bo et al., 2025), supports our proposal of an energetic hierarchy in the brain and the prioritization of essential functions including affective responses, while downregulating complex cognition during stress-induced energy scarcity, and especially in the context of pre-existing metabolic inefficiency. The evidence cited in Section 3 supports the idea that affect regulates systemic allostasis (affect-driven prioritization), but the effects of affect on the allostatic triage of CNS functional connectivity have not been directly investigated. Altogether, if our hypotheses are confirmed (Table 3), our novel concept of the affect-driven prioritization of CNS allostatic triage may bridge the gaps between stress, mitochondrial dysfunction, affective dysregulation, energy scarcity, and transdiagnostic disease pathogenesis.

Table 3.

Hypotheses of the allostatic triage model of psychopathology (ATP Model).

H1.	Preexisting peripheral (AL) and/or CNS metabolic inefficiency (MAL), and increases in biological energy demand such as acute inflammation will increase the experience of negative affect during stress
H2.	Affect will closely represent biological metabolic efficiency in healthy organisms, likely within the biological systems and CNS networks implicated in expected future behaviors
H3.	Allostatic Triage: when stress-induced energy demand exceeds the energy production capacity of the CNS, energy will be triaged to the least expensive regions and networks expected to ensure short-term survival, and away from more expensive regions and networks that may produce better long-term outcomes
H4.	Affect-Driven Prioritization: Affective intensity predicts the degree of stress-induced triage of CNS network functional connectivity (e.g., highly negatively valanced states will produce greater triage compared to less negatively valanced states)
H5.	In psychopathology and chronic disease states, affect will become less associated with biological metabolic efficiency (reduced allostatic metabolic inefficiency), but will continue to predict allostatic triage in the CNS
H6.	Triage-Driven Canalization: Persistent allostatic triage from one network or circuit to another will predict the persistent changes in CNS functional connectivity that develop over time in the process of psychopathogenesis (i.e., allostatic triage predicts which networks are canalized)

Open in a new tab

AL: Allostatic Load, CNS: Central Nervous System, MAL: Mitochondrial Allostatic Load.

Importantly, peripheral dysregulation is not necessary for affective dysregulation and allostatic triage, but we propose that it is one pathway that contributes to affective pathology and pathological allostatic triage. Importantly, if psychopathogenesis is first driven by CNS metabolic dysregulation alone, the ATP model predicts that over time, peripheral pathology becomes more likely to develop, driving transdiagnostic disease progression.

8.1. Specific hypotheses, future directions, and remaining questions

The ATP model advances our understanding of psychopathogenesis by integrating the distinct models presented above with our novel concept of affect-driven CNS allostatic triage. The ATP model does not contradict any major model or treatment for psychiatric disease; rather, the ATP model reframes existing evidence and treatments through a bioenergetic lens by integrating established models through our novel concept of affect-driven CNS allostatic triage. Abundant evidence strongly supports each component model, but no existing model spans all levels of biological organization or can fully explain transdiagnostic disease pathogenesis bioenergetically. While the hypotheses in Table 3 are already supported by abundant evidence, we provide testable specific hypotheses of the core ATP model to summarize the investigations necessary to fully confirm its veracity, particularly the core concept of affect-driven allostatic triage.

A deeper investigation of the mechanisms underlying the ATP model will support its further development from a conceptual framework into a genuinely predictive model, and the advancement of the field beyond nonspecific concepts like “mitochondrial dysfunction” and “affective dysregulation”, towards a more nuanced understanding of these processes (Monzel et al., 2023). Further, a deeper understanding of the mechanisms underlying the ATP model may yield novel and improved therapeutic approaches, and lead to new ways to foster preventative approaches to resilience that address transdiagnostic disease before it develops. Specifically, the ATP model suggests that treatment approaches focused on 1) normalizing stress-induced physiological dysregulation; 2) improving metabolic efficiency; 3) reducing the extraneous metabolic cost of dysregulated immune function; 4) updating internal models of metabolic efficiency that drive affective states; and 5) increasing energy availability, may be useful primary or adjunct therapies for psychiatric disorders and their co-morbidities. Such approaches may include psychedelic therapies, which may improve mitochondrial metabolic efficiency (Fanibunda et al., 2019; Fissler et al., 2023; Kelley et al., 2022), reduce inflammation (Flanagan and Nichols, 2022, 2018), and normalize stress-induced alterations to the stress response (Galvão et al., 2018; Jones et al., 2023; Lewis et al., 2023), exercise or movement therapies (Björkman and Ekblom, 2022; Goldstein et al., 2018; Neylan et al., 2025), dietary interventions (Fisk et al., 2020; Murphy et al., 2004; Ricci et al., 2020), novel psychotherapeutic or movement therapies focused on improving the veracity of internal models that drive affective states, pharmacological or dietary supplements that increase energy availability (Bakian et al., 2020; Toniolo et al., 2018), or combinations of each of the aforementioned treatment strategies.

Additional unanswered questions related to the specific mechanisms underlying the ATP model and its component models remain, though the veracity of the core ATP model itself does not depend on specific answers to these inquiries. Among the most important questions is one that remains unanswered in EPIC: what exactly is affect a representation of? Does affect only represent systemic biological metabolic efficiency, or is it weighted more heavily towards the CNS, or the CNS regions and networks needed to respond to current or future stressors (Lockhart et al., 2020; Monzel et al., 2024)? Similarly, what signals or physiological states drive affective states? For example, does the allostatic-interoceptive system model details about systemic or CNS metabolic efficiency by monitoring systemic biomarkers of mitochondrial stress, like lactate or mitokines (Clairis et al., 2024), or is the electrophysiological information carried by vagal afferents described in the EPIC model sufficient? Relatedly, is the affect-driven prioritization of allostatic triage general, as illustrated by the affect-dependent thresholds illustrated in Fig. 2 (blue dashed lines), or do specific affective or emotional states drive allostatic triage towards specific attractor states that are predicted to best optimize outcomes?

Altogether, if our hypotheses are supported, partly or in full, the ATP model will improve our understanding of psychopathogenesis and the relationships between psychiatric and medical diseases. By framing psychopathogenesis and transdiagnostic disease as an energetic, dynamic process, the ATP model may align with the lived experience of patients more closely and suggest novel therapeutics (Monroe and Simons, 1991).

Supplementary Material

Supplement

NIHMS2150778-supplement-Supplement.pdf^{(180KB, pdf)}

Acknowledgements

We would like to acknowledge the support staff at UCSF and SFVAMC who’s tireless work makes this and all of our other work possible. We would also like to thank our lab members at the Translational Psychedelic Research Program (TrPR) and Trauma and Health Research on Immunity, Vitality, and Emotions (THRIVE) Laboratories who have helped us think through many of the ideas and perspectives outlined in this paper and who’s support has been invaluable for this work.

Funding/Support

M.P. gratefully acknowledges support from the Baszucki Brain Research Fund. This work was otherwise not supported by any funding.

Abbreviations:

ADP: Adenine diphosphate
AL: Allostatic load
AOL: Allostatic overload
ATP: Adenine triphosphate
ATP Model: Allostatic Triage Model of Psychopathology
CEN: Central executive network
CNS: Central nervous system
DMN: Default mode network
DNA: Deoxyribonucleic acid
EMAL: Energetic model of allostatic load
EPIC: Embodied prediction interoceptive coding model
FGF-21: Fibroblast growth factor 21
GAD: Generalized anxiety disorder
GDF-15: Growth and differentiation factor 15
HPA: Hypothalamic pituitary adrenal axis
ISR: Integrated stress response
MAL: Mitochondrial allostatic load
MDD: Major Depressive Disorder
MIPS: Mitochondrial information processing system
MFN2: Mitofusion 2
P: General psychopathology factor
PFC: Prefrontal cortex
PTSD: Posttraumatic stress disorder
RNA: Ribonucleic acid
ROS: Reactive oxygen species
SN: Salience Network.

Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.neubiorev.2025.106419.

Footnotes

Declaration of Competing Interest

DPK is supported by a Veterans Administration Mental Illness Research, Education, and Clinical Center (MIRECC) Data Science Fellowship in Trauma and PTSD Research. SPS, GS KV, AL, JF, TCN, ERB, MP, AOD have no disclosures to report.

CRediT authorship contribution statement

Concept and design: DPK conceived of the ATP model with GS, JF, MP, KV, and AOD. Literature review and data collection: DPK performed this task with SPS, GS, MP, AS, and AOD. Drafting the manuscript: DPK drafted the manuscript with SPS, GS, MP and AOD. Critical revisions: DPK, SPS, ASL, MP, JW, GS, AS, KV, TN, ERB, and AOD. Statistical analysis: N/A. Administrative, technical, or material support: N/A. Supervision: AOD, MP, TN, JW.

HPA axis reactivity is increased in MDD and GAD, but may be reduced in PTSD

Data availability

No data was used for the research described in the article.

References

Abbott BB, Schoen LS, Badia P, 1984. Predictable and unpredictable shock: behavioral measures of aversion and physiological measures of stress. Psychol. Bull. 96, 45–71. 10.1037/0033-2909.96.1.45. [DOI] [PubMed] [Google Scholar]
Adusumilli VS, Walker TL, Overall RW, Klatt GM, Zeidan SA, Zocher S, Kirova DG, Ntitsias K, Fischer TJ, Sykes AM, 2021. ROS dynamics delineate functional states of hippocampal neural stem cells and link to their activity-dependent exit from quiescence. Cell stem Cell 28, 300–314 e6. [DOI] [PMC free article] [PubMed] [Google Scholar]
Agis-Balboa RC, Arcos-Diaz D, Wittnam J, Govindarajan N, Blom K, Burkhardt S, Haladyniak U, Agbemenyah HY, Zovoilis A, Salinas-Riester G, 2011. A hippocampal insulin-growth factor 2 pathway regulates the extinction of fear memories. EMBO J. 30, 4071–4083. 10.1038/emboj.2011.293. [DOI] [PMC free article] [PubMed] [Google Scholar]
Akiki TJ, Averill CL, Wrocklage KM, Scott JC, Averill LA, Schweinsburg B, Alexander-Bloch A, Martini B, Southwick SM, Krystal JH, Abdallah CG, 2018. Default mode network abnormalities in posttraumatic stress disorder: a novel network-restricted topology approach. NeuroImage 176, 489–498. 10.1016/j.neuroimage.2018.05.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
Albrechet-Souza L, Nastase AS, Hill MN, Gilpin NW, 2021. Amygdalar endocannabinoids are affected by predator odor stress in a sex-specific manner and modulate acoustic startle reactivity in female rats. Neurobiol. Stress 15, 100387. 10.1016/j.ynstr.2021.100387. [DOI] [PMC free article] [PubMed] [Google Scholar]
Allegrini AG, Cheesman R, Rimfeld K, Selzam S, Pingault J-B, Eley TC, Plomin R, 2020. The p factor: genetic analyses support a general dimension of psychopathology in childhood and adolescence. J. Child Psychol. Psychiatry 61, 30–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ames BN, 2006. Low micronutrient intake May accelerate the degenerative diseases of aging through allocation of scarce micronutrients by triage. In: Proceedings of the National Academy of Sciences, 103, pp. 17589–17594. [DOI] [PMC free article] [PubMed] [Google Scholar]
Amorim FE, Rye CS, Milton AL, 2025. Mitochondrial dysfunction in PTSD: a mechanism to understand trauma susceptibility? MedRxiv 2025 03 (28), 25324821. [DOI] [PMC free article] [PubMed] [Google Scholar]
Angajala A, Lim S, Phillips JB, Kim J-H, Yates C, You Z, Tan M, 2018. Diverse roles of mitochondria in immune responses: novel insights into Immuno-Metabolism. Front Immunol. 9, 1605. 10.3389/fimmu.2018.01605. [DOI] [PMC free article] [PubMed] [Google Scholar]
Anisman H, Matheson K, 2005. Stress, depression, and anhedonia: caveats concerning animal models. Neurosci. Biobehav. Rev. Anim. Models Depress Antidepressant Act. 29, 525–546. 10.1016/j.neubiorev.2005.03.007. [DOI] [PubMed] [Google Scholar]
Arango-Lievano M, Lambert WM, Bath KG, Garabedian MJ, Chao MV, Jeanneteau F, 2015. Neurotrophic-priming of glucocorticoid receptor signaling is essential for neuronal plasticity to stress and antidepressant treatment. Proc. Natl. Acad. Sci. 112, 15737–15742. [DOI] [PMC free article] [PubMed] [Google Scholar]
Armario A, Marti J, Gil M, 1990. The serum glucose response to acute stress is sensitive to the intensity of the stressor and to habituation. Psychoneuroendocrinology 15, 341–347. [DOI] [PubMed] [Google Scholar]
Arshavsky YI, 2023. Brain energetics and the connectionist concept in cognitive neuroscience. J. Neurophysiol. 130, 61–68. 10.1152/jn.00184.2023. [DOI] [PubMed] [Google Scholar]
Atlantis E, Baker M, 2008. Obesity effects on depression: systematic review of epidemiological studies. Int. J. Obes. 32, 881–891. [DOI] [PubMed] [Google Scholar]
Backé E-M, Seidler A, Latza U, Rossnagel K, Schumann B, 2012. The role of psychosocial stress at work for the development of cardiovascular diseases: a systematic review. Int. Arch. Occup. Environ. Health 85, 67–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
Baik J-H, 2020. Stress and the dopaminergic reward system. Exp. Mol. Med 52, 1879–1890. 10.1038/s12276-020-00532-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
Baker SR, Stephenson D, 2000. Prediction and control as determinants of behavioural uncertainty: effects on task performance and heart rate reactivity. Integr. Physiol. Behav. Sci 35, 235–250. 10.1007/BF02688786. [DOI] [PubMed] [Google Scholar]
Bakian AV, Huber RS, Scholl L, Renshaw PF, Kondo D, 2020. Dietary creatine intake and depression risk among US adults. Transl. Psychiatry 10, 52. [DOI] [PMC free article] [PubMed] [Google Scholar]
Balasanthiran A, Shotliff K, 2015. The history of stress hyperglycaemia. J. R. Coll. Physicians Edinb. 45, 238–247. [DOI] [PubMed] [Google Scholar]
Barrett LF, 2017a. How emotions are made: the secret life of the brain. Houghton Mifflin Harcourt. [Google Scholar]
Barrett LF, 2017b. The theory of constructed emotion: an active inference account of interoception and categorization. Soc. Cogn. Affect. Neurosci. 12, 1–23. 10.1093/scan/nsw154. [DOI] [PMC free article] [PubMed] [Google Scholar]
Barrett LF, Quigley KS, Hamilton P, 2016. An active inference theory of allostasis and interoception in depression. Philos. Trans. R. Soc. B Biol. Sci. 371, 20160011. 10.1098/rstb.2016.0011. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bashford-Largo J, Zhang R, Mathur A, Elowsky J, Schwartz A, Dobbertin M, Blair RJR, Blair KS, Bajaj S, 2022. Reduced cortical volume of the default mode network in adolescents with generalized anxiety disorder. Depress Anxiety 39, 485–495. 10.1002/da.23252. [DOI] [PMC free article] [PubMed] [Google Scholar]
Becker YL, Duvvuri B, Fortin PR, Lood C, Boilard E, 2022. The role of mitochondria in rheumatic diseases. Nat. Rev. Rheumatol. 18, 621–640. [DOI] [PubMed] [Google Scholar]
Belenguer P, Duarte JM, Schuck PF, Ferreira GC, 2019. Mitochondria and the brain: bioenergetics and beyond. Neurotox. Res. 36, 219–238. [DOI] [PubMed] [Google Scholar]
Bersani FS, Mellon SH, Lindqvist D, Kang JI, Rampersaud R, Somvanshi PR, Doyle III FJ, Hammamieh R, Jett M, Yehuda R, 2020. Novel pharmacological targets for combat PTSD—metabolism, inflammation, the gut microbiome, and mitochondrial dysfunction. Mil. Med 185, 311–318. 10.1093/milmed/usz260. [DOI] [PMC free article] [PubMed] [Google Scholar]
Besnard A, Sahay A, 2016. Adult hippocampal neurogenesis, fear generalization, and stress. Neuropsychopharmacol 41, 24–44. 10.1038/npp.2015.167. [DOI] [PMC free article] [PubMed] [Google Scholar]
Besse A, Wu P, Bruni F, Donti T, Graham BH, Craigen WJ, McFarland R, Moretti P, Lalani S, Scott KL, 2015. The GABA transaminase, ABAT, is essential for mitochondrial nucleoside metabolism. Cell Metab. 21, 417–427. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bhardwaj G, Penniman CM, Jena J, Beltran PAS, Foster C, Poro K, Junck TL, Hinton AO, Souvenir R, Fuqua JD, 2021. Insulin and IGF-1 receptors regulate complex I–dependent mitochondrial bioenergetics and supercomplexes via FoxOs in muscle. J. Clin. Investig. 131. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bird L, 2019. Getting enough energy for immunity, 269–269 Nat. Rev. Immunol. 19. 10.1038/s41577-019-0159-y. [DOI] [PubMed] [Google Scholar]
Björkman F, Ekblom Ö, 2022. Physical exercise as treatment for PTSD: a systematic review and meta-analysis. Mil. Med. 187, e1103–e1113. [DOI] [PubMed] [Google Scholar]
Blalock ZN, Wu GWY, Lindqvist D, Trumpff C, Flory JD, Lin J, Reus VI, Rampersaud R, Hammamieh R, Gautam A, Doyle FJ, Marmar CR, Jett M, Yehuda R, Wolkowitz OM, Mellon SH, 2024. Circulating cell-free mitochondrial DNA levels and glucocorticoid sensitivity in a cohort of Male veterans with and without combat-related PTSD. Transl. Psychiatry 14, 1–11. 10.1038/s41398-023-02721-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bloemen AJP, Oldehinkel AJ, Laceulle OM, Ormel J, Rommelse NNJ, Hartman CA, 2018. The association between executive functioning and psychopathology: general or specific? Psychol. Med. 48, 1787–1794. 10.1017/S0033291717003269. [DOI] [PubMed] [Google Scholar]
Bo K, Kelly C, Trumpff C, Hirano M, Picard M, Wager TD, 2025. Mitochondrial energy transformation capacity influences brain activation during sensory, affective, and cognitive tasks. bioRxiv 06 (25), 661482, 2025. [Google Scholar]
Bobba-Alves N, Juster R-P, Picard M, 2022. The energetic cost of allostasis and allostatic load. Psychoneuroendocrinology 146, 105951. [DOI] [PMC free article] [PubMed] [Google Scholar]
Boks MP, Rutten BP, Geuze E, Houtepen LC, Vermetten E, Kaminsky Z, Vinkers CH, 2016. SKA2 methylation is involved in cortisol stress reactivity and predicts the development of post-traumatic stress disorder (PTSD) after military deployment. Neuropsychopharmacology 41, 1350–1356. [DOI] [PMC free article] [PubMed] [Google Scholar]
Borcherding N, Brestoff JR, 2023. The power and potential of mitochondria transfer. Nature 623, 283–291. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bourvis N, Aouidad A, Cabelguen C, Cohen D, Xavier J, 2017. How do stress exposure and stress regulation relate to borderline personality disorder? Front. Psychol. 8, 2054. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bremner JD, Hoffman M, Afzal N, Cheema FA, Novik O, Ashraf A, Brummer M, Nazeer A, Goldberg J, Vaccarino V, 2021. The environment contributes more than genetics to smaller hippocampal volume in posttraumatic stress disorder (PTSD). J. Psychiatr. Res. 137, 579–588. 10.1016/j.jpsychires.2020.10.042. [DOI] [PMC free article] [PubMed] [Google Scholar]
Buckwalter JG, Castellani B, McEwen B, Karlamangla AS, Rizzo AA, John B, O’Donnell K, Seeman T, 2016. Allostatic load as a complex clinical construct: a Case-Based computational modeling approach. Complexity 21, 291–306. 10.1002/cplx.21743. [DOI] [PMC free article] [PubMed] [Google Scholar]
Busillo JM, Azzam KM, Cidlowski JA, 2011. Glucocorticoids sensitize the innate immune system through regulation of the NLRP3 inflammasome. J. Biol. Chem. 286, 38703–38713. [DOI] [PMC free article] [PubMed] [Google Scholar]
Buxton R, 2010. Interpreting oxygenation-based neuroimaging signals: the importance and the challenge of understanding brain oxygen metabolism. Front. Neuroenergetics 2. 10.3389/fnene.2010.00008. [DOI] [PMC free article] [PubMed] [Google Scholar]
Buxton RB, 2021. The thermodynamics of thinking: connections between neural activity, energy metabolism and blood flow. Philos. Trans. R. Soc. B. 10.1098/rstb.2019.0624. [DOI] [PMC free article] [PubMed] [Google Scholar]
Buxton RB, 2024. Thermodynamic limitations on brain oxygen metabolism: physiological implications. J. Physiol. 602, 683–712. [DOI] [PubMed] [Google Scholar]
Cameron HA, Schoenfeld TJ, 2018. Behavioral and structural adaptations to stress. Front. Neuroendocrinol. Stress Brain 49, 106–113. 10.1016/j.yfrne.2018.02.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
Cannon WB, de la Paz D, 1911. Emotional stimulation of adrenal secretion. Am. J. Physiol. Leg. Content 28, 64–70. 10.1152/ajplegacy.1911.28.1.64. [DOI] [Google Scholar]
Capitanio JP, Cole SW, 2015. Social instability and immunity in rhesus monkeys: the role of the sympathetic nervous system. Philos. Trans. R. Soc. B Biol. Sci. 370, 20140104. 10.1098/rstb.2014.0104. [DOI] [PMC free article] [PubMed] [Google Scholar]
Carhart-Harris RL, Chandaria S, Erritzoe DE, Gazzaley A, Girn M, Kettner H, Mediano PAM, Nutt DJ, Rosas FE, Roseman L, 2022. Canalization and plasticity in psychopathology. Neuropharmacology, 109398. [DOI] [PubMed] [Google Scholar]
Carver CS, Johnson SL, Timpano KR, 2017. Toward a functional view of the p factor in psychopathology. Clin. Psychol. Sci. 5, 880–889. [DOI] [PMC free article] [PubMed] [Google Scholar]
Caspi A, Houts RM, Belsky DW, Goldman-Mellor SJ, Harrington H, Israel S, Meier MH, Ramrakha S, Shalev I, Poulton R, 2014. The p factor: one general psychopathology factor in the structure of psychiatric disorders? Clin. Psychol. Sci 2, 119–137. [DOI] [PMC free article] [PubMed] [Google Scholar]
Castrillon G, Epp S, Bose A, Fraticelli L, Hechler A, Belenya R, Ranft A, Yakushev I, Utz L, Sundar L, 2023. An energy costly architecture of neuromodulators for human brain evolution and cognition. Sci. Adv. 9, eadi7632. [DOI] [PMC free article] [PubMed] [Google Scholar]
Cavalcanti-de-Albuquerque JP, de-Souza-Ferreira E, de Carvalho DP, Galina A, 2021. Coupling of GABA metabolism to mitochondrial glucose phosphorylation. Neurochem. Res. 111. [DOI] [PubMed] [Google Scholar]
Chaichi A, Hasan SMA, Mehta N, Donnarumma F, Ebenezer P, Murray KK, Francis J, Gartia MR, 2021. Label-free lipidome study of paraventricular thalamic nucleus (PVT) of rat brain with post-traumatic stress injury by Raman imaging. Analyst 146, 170–183. [DOI] [PubMed] [Google Scholar]
Chen Q, Chen X, He X, Wang L, Wang K, Qiu B, 2016. Aberrant structural and functional connectivity in the salience network and central executive network circuit in schizophrenia. Neurosci. Lett. 627, 178–184. 10.1016/j.neulet.2016.05.035. [DOI] [PubMed] [Google Scholar]
Chen W, Feng J, Jiang S, Guo J, Zhang, XiaoLin, Zhang, Xiaoguan, Wang, C., Ma, Y., Dong, Z., 2023. Mendelian randomization analyses identify bidirectional causal relationships of obesity with psychiatric disorders. J. Affect. Disord. 339, 807–814. [DOI] [PubMed] [Google Scholar]
Chen S, Liao Z, Xu P, 2023. Mitochondrial control of innate immune responses. Front. Immunol. 14. 10.3389/fimmu.2023.1166214. [DOI] [PMC free article] [PubMed] [Google Scholar]
Cheng A, Hou Y, Mattson MP, 2010. Mitochondria and neuroplasticity. ASN neuro 2, AN20100019. [DOI] [PMC free article] [PubMed] [Google Scholar]
Chihara T, Luginbuhl D, Luo L, 2007. Cytoplasmic and mitochondrial protein translation in axonal and dendritic terminal arborization. Nat. Neurosci. 10, 828–837. [DOI] [PubMed] [Google Scholar]
Cimino I, Kim H, Tung YCL, Pedersen K, Rimmington D, Tadross JA, Kohnke SN, Neves-Costa A, Barros A, Joaquim S, Bennett D, Melvin A, Lockhart SM, Rostron AJ, Scott J, Liu H, Burling K, Barker P, Clatworthy MR, Lee E-C, Simpson AJ, Yeo GSH, Moita LF, Bence KK, Jørgensen SB, Coll AP, Breen DM, O’Rahilly S, 2021. Activation of the hypothalamic–pituitary–adrenal axis by exogenous and endogenous GDF15. Proc. Natl. Acad. Sci. 118, e2106868118. 10.1073/pnas.2106868118. [DOI] [PMC free article] [PubMed] [Google Scholar]
Cisler JM, Dunsmoor JE, Fonzo GA, Nemeroff CB, 2024. Latent-state and model-based learning in PTSD. Trends Neurosci. 47, 150–162. 10.1016/j.tins.2023.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
Clairis N, Barakat A, Brochard J, Xin L, Sandi C, 2024. A neurometabolic mechanism involving dmPFC/dACC lactate in physical effort-based decision-making. Mol. Psychiatry. 10.1038/s41380-024-02726-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
Clement AB, Gamerdinger M, Tamboli IY, Lütjohann D, Walter J, Greeve I, Gimpl G, Behl C, 2009. Adaptation of neuronal cells to chronic oxidative stress is associated with altered cholesterol and sphingolipid homeostasis and lysosomal function. J. Neurochem. 111, 669–682. 10.1111/j.1471-4159.2009.06360.x. [DOI] [PubMed] [Google Scholar]
Cohodes EM, Sisk LM, Keding TJ, Mandell JD, Notti ME, Gee DG, 2023. Characterizing experiential elements of early-life stress to inform resilience: buffering effects of controllability and predictability and the importance of their timing. Dev. Psychopathol. 35, 2288–2301. 10.1017/S0954579423000822. [DOI] [PubMed] [Google Scholar]
Conant RC, Ross Ashby W, 1970. Every good regulator of a system must be a model of that system. Int. J. Syst. Sci. 1, 89–97. 10.1080/00207727008920220. [DOI] [Google Scholar]
Costa-Mattioli M, Walter P, 2020. The integrated stress response: from mechanism to disease. Science 368. 10.1126/science.aat5314. [DOI] [PMC free article] [PubMed] [Google Scholar]
Courchet J, Lewis TL, Lee S, Courchet V, Liou D-Y, Aizawa S, Polleux F, 2013. Terminal axon branching is regulated by the LKB1-NUAK1 kinase pathway via presynaptic mitochondrial capture. Cell 153, 1510–1525. [DOI] [PMC free article] [PubMed] [Google Scholar]
Coussement C, De Longueville X, Heeren A, 2022. Attentional networks in co-occurring generalized anxiety disorder and major depression disorder: towards a staging approach to the executive control deficits. Compr. Psychiatry 113, 152294. 10.1016/j.comppsych.2021.152294. [DOI] [PubMed] [Google Scholar]
Craig AD, 2009. How do you feel—now? the anterior insula and human awareness. Nat. Rev. Neurosci. 10, 59–70. [DOI] [PubMed] [Google Scholar]
Critchley HD, Garfinkel SN, 2017. Interoception and emotion. Curr. Opin. Psychol. 17, 7–14. [DOI] [PubMed] [Google Scholar]
Dache ZAA, Otandault A, Tanos R, Pastor B, Meddeb R, Sanchez C, Arena G, Lasorsa L, Bennett EA, Grange T, 2020. Blood contains circulating cell free respiratory competent mitochondria. Faseb J. 34, 3616–3630. [DOI] [PubMed] [Google Scholar]
Danese A, McEwen BS, 2012. Adverse childhood experiences, allostasis, allostatic load, and age-related disease. Physiol. Behav. Allostasis Allostatic Load. 106, 29–39. 10.1016/j.physbeh.2011.08.019. [DOI] [PubMed] [Google Scholar]
Davis EP, Stout SA, Molet J, Vegetabile B, Glynn LM, Sandman CA, Heins K, Stern H, Baram TZ, 2017. Exposure to unpredictable maternal sensory signals influences cognitive development across species. Proc. Natl. Acad. Sci. 114, 10390–10395. 10.1073/pnas.1703444114. [DOI] [PMC free article] [PubMed] [Google Scholar]
Daviu N, Bruchas MR, Moghaddam B, Sandi C, Beyeler A, 2019. Neurobiological links between stress and anxiety. Neurobiol. Stress 11, 100191. [DOI] [PMC free article] [PubMed] [Google Scholar]
Dimsdale JE, 2008. Psychological stress and cardiovascular disease. J. Am. Coll. Cardiol. 51, 1237–1246. [DOI] [PMC free article] [PubMed] [Google Scholar]
DiNuzzo M, Dienel GA, Behar KL, Petroff OA, Benveniste H, Hyder F, Giove F, Michaeli S, Mangia S, Herculano-Houzel S, Rothman DL, 2024. Neurovascular coupling is optimized to compensate for the increase in proton production from nonoxidative glycolysis and glycogenolysis during brain activation and maintain homeostasis of ph, pCO2, and pO2. J. Neurochem. 168, 632–662. 10.1111/jnc.15839. [DOI] [PMC free article] [PubMed] [Google Scholar]
Du L, Lin L, Li Q, Liu K, Huang Y, Wang X, Cao K, Chen X, Cao W, Li F, 2019. IGF-2 preprograms maturing macrophages to acquire oxidative phosphorylation-dependent anti-inflammatory properties. Cell Metab. 29, 1363–1375 e8. [DOI] [PubMed] [Google Scholar]
Du J, Wang Y, Hunter R, Wei Y, Blumenthal R, Falke C, Khairova R, Zhou R, Yuan P, Machado-Vieira R, 2009. Dynamic regulation of mitochondrial function by glucocorticoids. In: Proceedings of the National Academy of Sciences, 106, pp. 3543–3548. [DOI] [PMC free article] [PubMed] [Google Scholar]
Eisner V, Picard M, Hajnóczky G, 2018. Mitochondrial dynamics in adaptive and maladaptive cellular stress responses. Nat. Cell Biol. 20, 755–765. 10.1038/s41556-018-0133-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
Erbsloh F, Bernsmeier A, Hillesheim H, 1958. The glucose consumption of the brain & its dependence on the liver. Archiv fur Psychiatrie und Nervenkrankheiten, vereinigt mit Zeitschrift fur die gesamte Neurologie und Psychiatrie 196, 611–626. [DOI] [PubMed] [Google Scholar]
Fanibunda SE, Deb S, Maniyadath B, Tiwari P, Ghai U, Gupta S, Figueiredo D, Weisstaub N, Gingrich JA, Vaidya AD, 2019. Serotonin regulates mitochondrial biogenesis and function in rodent cortical neurons via the 5-HT2A receptor and SIRT1–PGC-1α axis. In: Proceedings of the National Academy of Sciences, 116, pp. 11028–11037. [DOI] [PMC free article] [PubMed] [Google Scholar]
Farahani A, Liu Z-Q, Ceballos EG, Hansen JY, Wennberg K, Zeighami Y, Dadar M, Gauthier CJ, Dagher A, Misic B, 2025. Cereb. blood Perfus. Across Biol. Syst. Hum. Lifesp. 10.1101/2025.02.05.636674. [DOI] [PMC free article] [PubMed] [Google Scholar]
Fava GA, McEwen BS, Guidi J, Gostoli S, Offidani E, Sonino N, 2019. Clinical characterization of allostatic overload. Psychoneuroendocrinology 108, 94–101. 10.1016/j.psyneuen.2019.05.028. [DOI] [PubMed] [Google Scholar]
Fisk J, Khalid S, Reynolds SA, Williams CM, 2020. Effect of 4 weeks daily wild blueberry supplementation on symptoms of depression in adolescents. Br. J. Nutr. 124, 181–188. [DOI] [PubMed] [Google Scholar]
Fissler P, Mavioglu MSRN, Wenzel MSM, Pruessner JC, Kolassa I-T, Krähenmann PR, 2022. The link between mitochondria, psychopathology, and intelligence: A bioenergetic model of cerebral function. [Google Scholar]
Fissler P, Vandersmissen A, Filippi M, Mavioglu RN, Scholkmann F, Karabatsiakis A, Krähenmann R, 2023. Effects of serotonergic psychedelics on mitochondria: transdiagnostic implications for mitochondria-related pathologies. J. Psychopharmacol., 02698811231164707. [DOI] [PubMed] [Google Scholar]
Flanagan TW, Nichols CD, 2018. Psychedelics as anti-inflammatory agents. Int. Rev. Psychiatry 30, 363–375. [DOI] [PubMed] [Google Scholar]
Flanagan TW, Nichols CD, 2022. Psychedelics and anti-inflammatory activity in animal models. Disruptive Psychopharmacol. 229–245. [DOI] [PubMed] [Google Scholar]
Flint MS, Baum A, Chambers WH, Jenkins FJ, 2007. Induction of DNA damage, alteration of DNA repair and transcriptional activation by stress hormones. Psychoneuroendocrinology 32, 470–479. [DOI] [PubMed] [Google Scholar]
Flippo KH, Potthoff MJ, 2021. Metabolic messengers: FGF21. Nat. Metab. 3, 309–317. 10.1038/s42255-021-00354-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
Fraunfelter L, Gerdes ABM, Alpers GW, 2022. Fear one, fear them all: a systematic review and meta-analysis of fear generalization in pathological anxiety. Neurosci. Biobehav. Rev. 139, 104707. 10.1016/j.neubiorev.2022.104707. [DOI] [PubMed] [Google Scholar]
Friston K, 2010. The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11, 127–138. [DOI] [PubMed] [Google Scholar]
Fukumitsu K, Hatsukano T, Yoshimura A, Heuser J, Fujishima K, Kengaku M, 2016. Mitochondrial fission protein Drp1 regulates mitochondrial transport and dendritic arborization in cerebellar purkinje cells. Mol. Cell. Neurosci. 71, 56–65. [DOI] [PubMed] [Google Scholar]
Gak IA, Radovic SM, Dukic AR, Janjic MM, Stojkov-Mimic NJ, Kostic TS, Andric SA, 2015. Stress triggers mitochondrial biogenesis to preserve steroidogenesis in leydig cells. Biochim Biophys. Acta 1853, 2217–2227. 10.1016/j.bbamcr.2015.05.030. [DOI] [PubMed] [Google Scholar]
Galts CP, Bettio LE, Jewett DC, Yang CC, Brocardo PS, Rodrigues ALS, Thacker JS, Gil-Mohapel J, 2019. Depression in neurodegenerative diseases: common mechanisms and current treatment options. Neurosci. Biobehav. Rev. 102, 56–84. [DOI] [PubMed] [Google Scholar]
Galvão AC de M, de Almeida R.N., Silva EADS, Freire FAM, Palhano-Fontes F, Onias H, Arcoverde E, Maia-de-Oliveira JP, de Araújo DB, Lobão-Soares B, Galvão-Coelho NL, 2018. Cortisol modulation by ayahuasca in patients with treatment resistant depression and healthy controls. Front Psychiatry 9, 185. 10.3389/fpsyt.2018.00185. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gan Q, Yu R, Lian Z, Yuan Y, Li Y, Zheng L, 2023. Unraveling the link between hypertension and depression in older adults: a meta-analysis. Front. Public Health 11, 1302341. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ganeshan K, Nikkanen J, Man K, Leong YA, Sogawa Y, Maschek JA, Ry TV, Chagwedera DN, Cox JE, Chawla A, 2019. Energetic Trade-Offs and hypometabolic states promote disease tolerance. Cell 177, 399–413.e12. 10.1016/j.cell.2019.01.050. [DOI] [PMC free article] [PubMed] [Google Scholar]
Garcia-Oscos F, Salgado H, Hall S, Thomas F, Farmer GE, Bermeo J, Galindo LC, Ramirez RD, D’Mello S, Rose-John S, 2012. The stress-induced cytokine interleukin-6 decreases the inhibition/excitation ratio in the rat temporal cortex via trans-signaling. Biol. Psychiatry 71, 574–582. 10.1016/j.biopsych.2011.11.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gazit N, Vertkin I, Shapira I, Helm M, Slomowitz E, Sheiba M, Mor Y, Rizzoli S, Slutsky I, 2016. IGF-1 receptor differentially regulates spontaneous and evoked transmission via mitochondria at hippocampal synapses. Neuron 89, 583–597. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gebara E, Zanoletti O, Ghosal S, Grosse J, Schneider BL, Knott G, Astori S, Sandi C, 2021. Mitofusin-2 in the nucleus accumbens regulates anxiety and depression-like behaviors through mitochondrial and neuronal actions. Biol. Psychiatry 89, 1033–1044. [DOI] [PubMed] [Google Scholar]
Gebreab SZ, Vandeleur CL, Rudaz D, Strippoli M-PF, Gholam-Rezaee M, Castelao E, Lasserre AM, Glaus J, Pistis G, Kuehner C, 2018. Psychosocial stress over the lifespan, psychological factors, and cardiometabolic risk in the community. Psychosom. Med. 80, 628–639. [DOI] [PubMed] [Google Scholar]
Ghosal S, Gebara E, Ramos-Fernández E, Chioino A, Grosse J, de Suduiraut IG, Zanoletti O, Schneider B, Zorzano A, Astori S, 2023. Mitofusin-2 in nucleus accumbens D2-MSNs regulates social dominance and neuronal function. Cell Rep. 42. [DOI] [PubMed] [Google Scholar]
Gilbertson MW, Shenton ME, Ciszewski A, Kasai K, Lasko NB, Orr SP, Pitman RK, 2002. Smaller hippocampal volume predicts pathologic vulnerability to psychological trauma. Nat. Neurosci. 5, 1242–1247. 10.1038/nn958. [DOI] [PMC free article] [PubMed] [Google Scholar]
Girotti M, Adler SM, Bulin SE, Fucich EA, Paredes D, Morilak DA, 2018. Prefrontal cortex executive processes affected by stress in health and disease. Prog. NeuroPsychopharmacol. Biol. Psychiatry 85, 161–179. 10.1016/j.pnpbp.2017.07.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
Glavin GB, 1985. Stress and brain noradrenaline: a review. Neurosci. Biobehav Rev. 9, 233–243. 10.1016/0149-7634(85)90048-x. [DOI] [PubMed] [Google Scholar]
Glover LR, Schoenfeld TJ, Karlsson R-M, Bannerman DM, Cameron HA, 2017. Ongoing neurogenesis in the adult dentate gyrus mediates behavioral responses to ambiguous threat cues. PLOS Biol. 15, e2001154. 10.1371/journal.pbio.2001154. [DOI] [PMC free article] [PubMed] [Google Scholar]
Goffart S, Wiesner RJ, 2003. Regulation and co-ordination of nuclear gene expression during mitochondrial biogenesis. Exp. Physiol. 88, 33–40. [DOI] [PubMed] [Google Scholar]
Goglia F, Silvestri E, Lanni A, 2002. Thyroid hormones and mitochondria. Biosci. rep. 22, 17–32. [DOI] [PubMed] [Google Scholar]
Goldstein LA, Mehling WE, Metzler TJ, Cohen BE, Barnes DE, Choucroun GJ, Silver A, Talbot LS, Maguen S, Hlavin JA, 2018. Veterans group exercise: a randomized pilot trial of an integrative exercise program for veterans with posttraumatic stress. J. Affect. Disord. 227, 345–352. [DOI] [PubMed] [Google Scholar]
Gouspillou G, Hirano M, Picard M, Trumpff C, n.d. The Energetic Stress Marker GDF15 is Induced by Acute Psychosocial Stress. [Google Scholar]
Graves SM, Xie Z, Stout KA, Zampese E, Burbulla LF, Shih JC, Kondapalli J, Patriarchi T, Tian L, Brichta L, 2020. Dopamine metabolism by a monoamine oxidase mitochondrial shuttle activates the electron transport chain. Nat. Neurosci. 23, 15–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
Grossman CD, Cohen JY, 2022. Neuromodulation and neurophysiology on the timescale of learning and Decision-Making. Annu. Rev. Neurosci. 45, 317–337. 10.1146/annurev-neuro-092021-125059. [DOI] [PubMed] [Google Scholar]
Gu S, Cieslak M, Baird B, Muldoon SF, Grafton ST, Pasqualetti F, Bassett DS, 2018. The energy landscape of neurophysiological activity implicit in brain network structure. Sci. Rep. 8, 2507. 10.1038/s41598-018-20123-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gui W, Zhu Y, Sun S, Zhu W, Tan B, Zhao H, Shang C, Zheng F, Lin X, Li H, 2021. Knockdown of insulin-like growth factor 2 gene disrupts mitochondrial functions in the liver. J. Mol. Cell Biol. 13 543555. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ha H, Han C, Kim B, 2017. Can obesity cause depression? A pseudo-panel analysis. J. Prev. Med. Public Health 50, 262. [DOI] [PMC free article] [PubMed] [Google Scholar]
Harrington JS, Ryter SW, Plataki M, Price DR, Choi AMK, 2023. Mitochondria in health, disease, and aging. Physiol. Rev. 103, 2349–2422. 10.1152/physrev.00058.2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
Havranek MM, Bolliger B, Roos S, Pryce CR, Quednow BB, Seifritz E, 2016. Uncontrollable and unpredictable stress interacts with subclinical depression and anxiety scores in determining anxiety response. Stress 19, 53–62. 10.3109/10253890.2015.1117449. [DOI] [PubMed] [Google Scholar]
Hermans EJ, Henckens MJ, Joëls M, Fernández G, 2014. Dynamic adaptation of large-scale brain networks in response to acute stressors. Trends Neurosci. 37, 304–314. [DOI] [PubMed] [Google Scholar]
Hermans EJ, Henckens MJAG, Joëls M, Fernández G, 2017. Chapter 30 - Time-Dependent shifts in neural systems supporting Decision-Making under stress. In: Dreher J-C, Tremblay L (Eds.), Decision Neuroscience. Academic Press, San Diego, pp. 371–385. 10.1016/B978-0-12-805308-9.00030-0. [DOI] [Google Scholar]
Hilliard ME, Yi-Frazier JP, Hessler D, Butler AM, Anderson BJ, Jaser S, 2016. Stress and A1c among people with diabetes across the lifespan. Curr. Diabetes Rep. 16, 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
Hollis F, van der Kooij MA, Zanoletti O, Lozano L, Cantó C, Sandi C, 2015. Mitochondrial function in the brain links anxiety with social subordination. In: Proceedings of the National Academy of Sciences, 112, pp. 15486–15491. [DOI] [PMC free article] [PubMed] [Google Scholar]
Hummel EM, Piovesan K, Berg F, Herpertz S, Kessler H, Kumsta R, Moser DA, 2023. Mitochondrial DNA as a marker for treatment-response in post-traumatic stress disorder. Psychoneuroendocrinology 148, 105993. 10.1016/j.psyneuen.2022.105993. [DOI] [PubMed] [Google Scholar]
Hunter RG, Seligsohn M, Rubin TG, Griffiths BB, Ozdemir Y, Pfaff DW, Datson NA, McEwen BS, 2016. Stress and corticosteroids regulate rat hippocampal mitochondrial DNA gene expression via the glucocorticoid receptor. Proc. Natl. Acad. Sci. USA 113, 9099–9104. 10.1073/pnas.1602185113. [DOI] [PMC free article] [PubMed] [Google Scholar]
Itoga CA, Hellard EAR, Whitaker AM, Lu Y-L, Schreiber AL, Baynes BB, Baiamonte BA, Richardson HN, Gilpin NW %J.N., 2016. Traumatic stress promotes hyperalgesia via corticotropin-releasing factor-1 receptor (CRFR1) signaling in central amygdala. Neuropsychopharmacology 41, 2463. 10.1038/npp.2016.44. [DOI] [PMC free article] [PubMed] [Google Scholar]
Iwasaki Y, Takeshima Yusuke, Fujio K, 2020. Basic mechanism of immune system activation by mitochondria. Immunol. Med. 43, 142–147. 10.1080/25785826.2020.1756609. [DOI] [PubMed] [Google Scholar]
Jiang M, Wang L, Sheng H, 2024. Mitochondria in depression: the dysfunction of mitochondrial energy metabolism and quality control systems. CNS Neurosci. Ther. 30, e14576. [DOI] [PMC free article] [PubMed] [Google Scholar]
Jin S, Diano S, 2018. Mitochondrial dynamics and hypothalamic regulation of metabolism. Endocrinology 159, 3596–3604. [DOI] [PMC free article] [PubMed] [Google Scholar]
Johnson JD, O’Connor KA, Watkins LR, Maier SF, 2004. The role of IL-1β in stress-induced sensitization of proinflammatory cytokine and corticosterone responses. Neuroscience 127, 569–577. 10.1016/j.neuroscience.2004.05.046. [DOI] [PubMed] [Google Scholar]
Johri A, Beal MF, 2012. Mitochondrial dysfunction in neurodegenerative diseases. J. Pharm. Exp. Ther. 342, 619–630. 10.1124/jpet.112.192138. [DOI] [PMC free article] [PubMed] [Google Scholar]
Jones NT, Zahid Z, Grady SM, Sultan ZW, Zheng Z, Razidlo J, Banks MI, Wenthur CJ, 2023. Transient elevation of plasma glucocorticoids supports psilocybin-induced anxiolysis in mice. ACS Pharmacol. Transl. Sci. 6, 1221–1231. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kang SG, Choi MJ, Jung S-B, Chung HK, Chang JY, Kim JT, Kang YE, Lee JH, Hong HJ, Jun SM, 2021. Differential roles of GDF15 and FGF21 in systemic metabolic adaptation to the mitochondrial integrated stress response. IScience 24. [DOI] [PMC free article] [PubMed] [Google Scholar]
Karan KR, Trumpff C, McGill MA, Thomas JE, Sturm G, Lauriola V, Sloan RP, Rohleder N, Kaufman BA, Marsland AL, 2020. Mitochondrial respiratory capacity modulates LPS-induced inflammatory signatures in human blood. Brain Behav. Immun. Health 5, 100080. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kasai K, Yamasue H, Gilbertson MW, Shenton ME, Rauch SL, Pitman RK, 2008. Evidence for acquired pregenual anterior cingulate gray matter loss from a twin study of combat-related posttraumatic stress disorder. Biol. Psychiatry 63, 550–556. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kawanishi S, Oikawa S, 2004. Mechanism of telomere shortening by oxidative stress. Ann. N. Y. Acad. Sci. 1019, 278–284. [DOI] [PubMed] [Google Scholar]
Keeney JN, Winters AD, Sitcheran R, West AP, 2023. NF-κB–Inducing kinase governs the mitochondrial respiratory capacity, differentiation, and inflammatory status of innate immune cells. J. Immunol. 210, 1123–1133. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kelley DP, 2022. Evaluation of hippocampal allostatic Load-Associated factors in animal models of Post-Traumatic stress disorder: relevance to human PTSD. Louisiana State University and Agricultural & Mechanical College. [Google Scholar]
Kelley DP, Albrechet-Souza L, Cruise S, Maiya R, Destouni A, Sakamuri SS, Duplooy A, Hibicke M, Nichols C, Katakam PV, 2023. Conditioned place avoidance is associated with a distinct hippocampal phenotype, partly preserved pattern separation, and reduced reactive oxygen species production after stress. Genes Brain Behav, e12840. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kelley DParker, Chaichi, A., Duplooy, A., Singh, D., Gartia, M.R., Francis, J., 2022. Labelfree mapping and profiling of altered lipid homeostasis in the rat hippocampus after traumatic stress: role of oxidative homeostasis. Neurobiol. Stress 20, 100476. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kelley DP, Venable K, Destouni A, Billac G, Ebenezer P, Stadler K, Nichols C, Barker S, Francis J, 2022. Pharmahuasca and DMT rescue ROS production and differentially expressed genes observed after predator and psychosocial stress: relevance to human PTSD. ACS Chem. Neurosci. 10.1021/acschemneuro.1c00660. [DOI] [PubMed] [Google Scholar]
Kelley D, Venable K, Sturm G, Skovgaard A, Francis J, Neylan T, Bradley E, Picard M, O’Donovan A, Singleton S, 2025. A llostatic Triage Model of Psychopathology (ATP Model): How Reallocation of Brain Energetic Resources Under Stress Elicits Psychiatric Symptoms. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kelly C, Trumpff C, Acosta C, Assuras S, Baker J, Basarrate S, Behnke A, Bo K, Bobba-Alves N, Champagne FA, Conklin Q, Cross M, De Jager P, Engelstad K, Epel E, Franklin SG, Hirano M, Huang Q, Junker A, Juster R-P, Kapri D, Kirschbaum C, Kurade M, Lauriola V, Li S, Liu CC, Liu G, McEwen B, McGill MA, McIntyre K, Monzel AS, Michelson J, Prather AA, Puterman E, Rosales XQ, Shapiro PA, Shire D, Slavich GM, Sloan RP, Smith JLM, Spann M, Spicer J, Sturm G, Tepler S, de Schotten MT, Wager TD, Picard M, 2024. A platform to map the mind–mitochondria connection and the hallmarks of psychobiology: the MiSBIE study. Trends Endocrinol. Metab. 35, 884–901. 10.1016/j.tem.2024.08.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kendler KS, Karkowski LM, Prescott CA, 1999. Causal relationship between stressful life events and the onset of major depression. AJP 156, 837–841. 10.1176/ajp.156.6.837. [DOI] [PubMed] [Google Scholar]
Kendler KS, Kuhn J, Prescott CA, 2004. The interrelationship of neuroticism, sex, and stressful life events in the prediction of episodes of major depression. Am. J. Psychiatry 161, 631–636. [DOI] [PubMed] [Google Scholar]
Keyes KM, McLaughlin KA, Demmer RT, Cerdá M, Koenen KC, Uddin M, Galea S, 2013. Potentially traumatic events and the risk of six physical health conditions in a population-based sample. Depress Anxiety 30, 451–460. [DOI] [PMC free article] [PubMed] [Google Scholar]
Khacho M, Harris R, Slack RS, 2019. Mitochondria as central regulators of neural stem cell fate and cognitive function. Nat. Rev. Neurosci. 20, 34–48. [DOI] [PubMed] [Google Scholar]
Khacho M, Slack RS, 2018. Mitochondrial dynamics in the regulation of neurogenesis: from development to the adult brain. Dev. Dyn. 247, 47–53. [DOI] [PubMed] [Google Scholar]
Kim KH, Son JM, Benayoun BA, Lee C, 2018. The mitochondrial-encoded peptide MOTS-c translocates to the nucleus to regulate nuclear gene expression in response to metabolic stress. Cell Metab. 28, 516–524 e7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kimura T, Murakami F, 2014. Evidence that dendritic mitochondria negatively regulate dendritic branching in pyramidal neurons in the neocortex. J. Neurosci. 34, 6938–6951. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kleckner IR, Zhang J, Touroutoglou A, Chanes L, Xia C, Simmons WK, Quigley KS, Dickerson BC, Barrett LF, 2017. Evidence for a large-scale brain system supporting allostasis and interoception in humans. Nat. Hum. Behav. 1. 10.1038/s41562-017-0069. [DOI] [PMC free article] [PubMed] [Google Scholar]
Koolhaas JM, Bartolomucci A, Buwalda B, de Boer SF, Flügge G, Korte SM, Meerlo P, Murison R, Olivier B, Palanza P, Richter-Levin G, Sgoifo A, Steimer T, Stiedl O, van Dijk G, Wöhr M, Fuchs E, 2011. Stress revisited: a critical evaluation of the stress concept. Neurosci. Biobehav. Rev. 35, 1291–1301. 10.1016/j.neubiorev.2011.02.003. [DOI] [PubMed] [Google Scholar]
Korneeva NL, 2022. Integrated stress response in neuronal pathology and in health. Biochemistry (Moscow) 87, S111–S127. [DOI] [PubMed] [Google Scholar]
Kwon S-K, Sando III R, Lewis TL, Hirabayashi Y, Maximov A, Polleux F, 2016. LKB1 regulates mitochondria-dependent presynaptic calcium clearance and neurotransmitter release properties at excitatory synapses along cortical axons. PLoS Biol. 14, e1002516. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kwon S-K, Sando III R, Lewis TL, Hirabayashi Y, Maximov A, Polleux F, 2018. Correction: LKB1 regulates mitochondria-dependent presynaptic calcium clearance and neurotransmitter release properties at excitatory synapses along cortical axons. PLoS Biol. 16, e3000040. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lee H, Jiang X, Perwaiz I, Yu P, Wang J, Wang Y, Hüttemann M, Felder RA, Sibley DR, Polster BM, 2021. Dopamine D5 receptor-mediated decreases in mitochondrial reactive oxygen species production are cAMP and autophagy dependent. Hypertens. Res. 44, 628–641. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lee B, Lee H, Xiong L, Zhu J-K, 2002. A mitochondrial complex I defect impairs cold-regulated nuclear gene expression. Plant Cell 14, 1235–1251. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lee J, Sharma S, Kim J, Ferrante RJ, Ryu H, 2008. Mitochondrial nuclear receptors and transcription factors: who’s minding the cell? J. Neurosci. Res. 86, 961–971. 10.1002/jnr.21564. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lenart-Bugla M, Szcześniak D, Bugla B, Kowalski K, Niwa S, Rymaszewska J, Misiak B, 2022. The association between allostatic load and brain: a systematic review. Psychoneuroendocrinology 145, 105917. 10.1016/j.psyneuen.2022.105917. [DOI] [PubMed] [Google Scholar]
Leslie RD, Vartak T, 2020. Allostasis and the origins of adult-onset diabetes. Diabetologia 63, 261–265. 10.1007/s00125-019-05048-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lewis CR, Tafur J, Spencer S, Green JM, Harrison C, Kelmendi B, Rabin DM, Yehuda R, Yazar-Klosinski B, Cahn BR, 2023. Pilot study suggests DNA methylation of the glucocorticoid receptor gene (NR3C1) is associated with MDMA-assisted therapy treatment response for severe PTSD. Front. Psychiatry 14, 959590. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lex C, Baezner E, Meyer TD, 2017. Does stress play a significant role in bipolar disorder? A meta-analysis. J. Affect. Disord. 208, 298–308. [DOI] [PubMed] [Google Scholar]
Li L, Li X, Zhou W, Messina JL, 2013. Acute psychological stress results in the rapid development of insulin resistance. J. Endocrinol. 217, 175. [DOI] [PMC free article] [PubMed] [Google Scholar]
Li J, Liu J, Zhong Y, Wang H, Yan B, Zheng K, Wei L, Lu H, Li B, 2021. Causal interactions between the default mode network and central executive network in patients with major depression. Neuroscience 475, 93–102. 10.1016/j.neuroscience.2021.08.033. [DOI] [PubMed] [Google Scholar]
Li Y, Zhao C, Sun S, Mi G, Liu C, Ding G, Wang C, Tang F, 2024. Elucidating the bidirectional association between autoimmune diseases and depression: a systematic review and meta-analysis. BMJ Ment. Health 27. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lim Y, Cho I-T, Rennke HG, Cho G, 2021. β2-adrenergic receptor regulates ER-mitochondria contacts. Sci. Rep. 11, 21477. [DOI] [PMC free article] [PubMed] [Google Scholar]
Liu M-Y, Li N, Li WA, Khan H, 2017. Association between psychosocial stress and hypertension: a systematic review and meta-analysis. Neurol. Res. [DOI] [PubMed] [Google Scholar]
Lockhart SM, Saudek V, O’Rahilly S, 2020. GDF15: a hormone conveying somatic distress to the brain. Endocr. Rev. 41, bnaa007. 10.1210/endrev/bnaa007. [DOI] [PMC free article] [PubMed] [Google Scholar]
Logue MW, van Rooij SJH, Dennis EL, Davis SL, Hayes JP, Stevens JS, Densmore M, Haswell CC, Ipser J, Koch SBJ, Korgaonkar M, Lebois LAM, Peverill M, Baker JT, Boedhoe PSW, Frijling JL, Gruber SA, Harpaz-Rotem I, Jahanshad N, Koopowitz S, Levy I, Nawijn L, O’Connor L, Olff M, Salat DH, Sheridan MA, Spielberg JM, van Zuiden M, Winternitz SR, Wolff JD, Wolf EJ, Wang X, Wrocklage K, Abdallah CG, Bryant RA, Geuze E, Jovanovic T, Kaufman ML, King AP, Krystal JH, Lagopoulos J, Bennett M, Lanius R, Liberzon I, McGlinchey RE, McLaughlin KA, Milberg WP, Miller MW, Ressler KJ, Veltman DJ, Stein DJ, Thomaes K, Thompson PM, Morey RA, 2018. Smaller hippocampal volume in posttraumatic stress disorder: a multisite ENIGMA-PGC study: subcortical volumetry results from posttraumatic stress disorder consortia. Biol. Psychiatry 83, 244–253. 10.1016/j.biopsych.2017.09.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lombardi AA, Gibb AA, Arif E, Kolmetzky DW, Tomar D, Luongo TS, Jadiya P, Murray EK, Lorkiewicz PK, Hajnóczky G, 2019. Mitochondrial calcium exchange links metabolism with the epigenome to control cellular differentiation. Nat. commun. 10, 4509. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lowrance SA, Ionadi A, McKay E, Douglas X, Johnson JD, 2016. Sympathetic nervous system contributes to enhanced corticosterone levels following chronic stress. Psychoneuroendocrinology 68, 163–170. 10.1016/j.psyneuen.2016.02.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lushchak O, Strilbytska O, Koliada A, Storey KB, 2023. An orchestrating role of mitochondria in the origin and development of post-traumatic stress disorder. Front. Physiol. 13, 1094076. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lynch CJ, Elbau IG, Ng T, Ayaz A, Zhu S, Wolk D, Manfredi N, Johnson M, Chang M, Chou J, Summerville I, Ho C, Lueckel M, Bukhari H, Buchanan D, Victoria LW, Solomonov N, Goldwaser E, Moia S, Caballero-Gaudes C, Downar J, Vila-Rodriguez F, Daskalakis ZJ, Blumberger DM, Kay K, Aloysi A, Gordon EM, Bhati MT, Williams N, Power JD, Zebley B, Grosenick L, Gunning FM, Liston C, 2024. Frontostriatal salience network expansion in individuals in depression. Nature 110. 10.1038/s41586-024-07805-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
Madrigal JL, Olivenza R, Moro MA, Lizasoain I, Lorenzo P, Rodrigo J, Leza JC, 2001. Glutathione depletion, lipid peroxidation and mitochondrial dysfunction are induced by chronic stress in rat brain. Neuropsychopharmacology 24, 420–429. [DOI] [PubMed] [Google Scholar]
Magistretti PJ, Allaman I, 2015. A cellular perspective on brain energy metabolism and functional imaging. Neuron 86, 883–901. 10.1016/j.neuron.2015.03.035. [DOI] [PubMed] [Google Scholar]
Magistretti PJ, Pellerin L, 1999. Cellular mechanisms of brain energy metabolism and their relevance to functional brain imaging. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci 354, 1155–1163. [DOI] [PMC free article] [PubMed] [Google Scholar]
Manoliu A, Riedl V, Zherdin A, Mühlau M, Schwerthöffer D, Scherr M, Peters H, Zimmer C, Förstl H, Bäuml J, Wohlschläger AM, Sorg C, 2014. Aberrant dependence of default Mode/Central executive network interactions on anterior insular salience network activity in schizophrenia. Schizophr. Bull. 40, 428–437. 10.1093/schbul/sbt037. [DOI] [PMC free article] [PubMed] [Google Scholar]
Martín-Montañez E, Millon C, Boraldi F, Garcia-Guirado F, Pedraza C, Lara E, Santin LJ, Pavia J, Garcia-Fernandez M, 2017. IGF-II promotes neuroprotection and neuroplasticity recovery in a long-lasting model of oxidative damage induced by glucocorticoids. Redox Biol. 13, 69–81. 10.1016/j.redox.2017.05.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
Mateos MV, Uranga RM, Salvador GA, Giusto NM, 2008. Activation of phosphatidylcholine signalling during oxidative stress in synaptic endings. Neurochem. Int. 53, 199–206. [DOI] [PubMed] [Google Scholar]
Mattson MP, 2007. Mitochondrial regulation of neuronal plasticity. Neurochem. Res. 32, 707–715. [DOI] [PubMed] [Google Scholar]
Mattson MP, Gleichmann M, Cheng A, 2008. Mitochondria in neuroplasticity and neurological disorders. Neuron 60, 748–766. 10.1016/j.neuron.2008.10.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
McAvoy K, Kawamata H, 2019. Glial mitochondrial function and dysfunction in health and neurodegeneration. Mol. Cell. Neurosci. 101, 103417. [DOI] [PubMed] [Google Scholar]
McCutcheon RA, Bloomfield MAP, Dahoun T, Mehta M, Howes OD, 2019. Chronic psychosocial stressors are associated with alterations in salience processing and corticostriatal connectivity. Schizophr. Res. Stress Schizophr. 213, 56–64. 10.1016/j.schres.2018.12.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
McEwen BS, 1998. Stress, adaptation, and disease. Allostasis and allostatic load. Ann. N. Y Acad. Sci. 840, 33–44. 10.1111/j.1749-6632.1998.tb09546.x. [DOI] [PubMed] [Google Scholar]
McEwen Bruce S., 1998. Protective and damaging effects of stress mediators. N. Engl. J. Med. 338, 171–179. [DOI] [PubMed] [Google Scholar]
McEwen BS, 2003. Mood disorders and allostatic load. Biol. Psychiatry 54, 200–207. [DOI] [PubMed] [Google Scholar]
McEwen BS, 2005. Glucocorticoids, depression, and mood disorders: structural remodeling in the brain. Metabolism 54, 20–23. [DOI] [PubMed] [Google Scholar]
McEwen BS, 2015. Biomarkers for assessing population and individual health and disease related to stress and adaptation. Metabolism 64, S2–s10. 10.1016/j.metabol.2014.10.029. [DOI] [PubMed] [Google Scholar]
McEwen BS, Gianaros PJ, 2011. Stress- and Allostasis-Induced brain plasticity. Annu. Rev. Med. 62, 431–445. 10.1146/annurev-med-052209-100430. [DOI] [PMC free article] [PubMed] [Google Scholar]
McEwen BS, Wingfield JC, 2003. The concept of allostasis in biology and biomedicine. Horm. Behav. 43, 2–15. [DOI] [PubMed] [Google Scholar]
McEwen BS, Wingfield JC, 2010. What is in a name? Integrating homeostasis, allostasis and stress. Horm. Behav. 57, 105–111. 10.1016/j.yhbeh.2009.09.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
McFarlane AC, Barton CA, Yehuda R, Wittert G, 2011. Cortisol response to acute trauma and risk of posttraumatic stress disorder. Psychoneuroendocrinology 36, 720–727. 10.1016/j.psyneuen.2010.10.007. [DOI] [PubMed] [Google Scholar]
Mellon SH, Gautam A, Hammamieh R, Jett M, Wolkowitz OM, 2018. Metabolism, metabolomics, and inflammation in posttraumatic stress disorder. Biol. Psychiatry 83, 866–875. 10.1016/j.biopsych.2018.02.007. [DOI] [PubMed] [Google Scholar]
Melo SR, de Antoniazzi C.T., de D, Hossain S, Kolb B, 2020. Short predictable stress promotes resistance to anxiety behavior and increases dendritic spines in prefrontal cortex and hippocampus. Brain Res. 1746, 147020. 10.1016/j.brainres.2020.147020. [DOI] [PubMed] [Google Scholar]
Ménard C, Pfau ML, Hodes GE, Russo SJ, 2017. Immune and neuroendocrine mechanisms of stress vulnerability and resilience. Neuropsychopharmacology 42, 62–80. 10.1038/npp.2016.90. [DOI] [PMC free article] [PubMed] [Google Scholar]
Meng L, Chen D, Yang Y, Zheng Y, Hui R, 2012. Depression increases the risk of hypertension incidence: a meta-analysis of prospective cohort studies. J. Hypertens. 30, 842–851. 10.1097/HJH.0b013e32835080b7. [DOI] [PubMed] [Google Scholar]
Miao G, Deen J, Struzeski JB, Chen M, Zhang Y, Cole SA, Fretts AM, Lee ET, Howard BV, Fiehn O, 2023. Plasma lipidomic profile of depressive symptoms: a longitudinal study in a large sample of community-dwelling American Indians in the strong heart study. Mol. Psychiatry 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
Midzak A, Papadopoulos V, 2016. Adrenal mitochondria and steroidogenesis: From individual proteins to functional protein assemblies. Front Endocrinol (Lausanne) 7, 106. 10.3389/fendo.2016.00106. [DOI] [PMC free article] [PubMed] [Google Scholar]
Miller WL, 2013. Steroid hormone synthesis in mitochondria. Mol. cell. endocrinol. 379, 62–73. [DOI] [PubMed] [Google Scholar]
Miller MW, Lin AP, Wolf EJ, Miller DR, 2018. Oxidative stress, inflammation, and neuroprogression in chronic PTSD. Harv. Rev. Psychiatry 26, 57–69. 10.1097/hrp.0000000000000167. [DOI] [PMC free article] [PubMed] [Google Scholar]
Miller AH, Raison CL, 2016. The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nat. Rev. Immunol. 16, 22–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
Mishra A, Singh S, Tiwari V, Bano S, Shukla S, 2020. Dopamine D1 receptor agonism induces dynamin related protein-1 inhibition to improve mitochondrial biogenesis and dopaminergic neurogenesis in rat model of Parkinson’s disease. Behav. Brain Res. 378, 112304. [DOI] [PubMed] [Google Scholar]
Mizuno M, Takeba Y, Matsumoto N, Tsuzuki Y, Asoh K, Takagi M, Kobayashi S, Yamamoto H, 2010. Antenatal glucocorticoid therapy accelerates ATP production with creatine kinase increase in the growth-enhanced fetal rat heart. Circ. J. 74, 171–180. [DOI] [PubMed] [Google Scholar]
Monroe SM, Simons AD, 1991. Diathesis-stress theories in the context of life stress research: implications for the depressive disorders. Psychol. Bull. 110, 406. [DOI] [PubMed] [Google Scholar]
Monzel AS, Enríquez JA, Picard M, 2023. Multifaceted mitochondria: moving mitochondrial science beyond function and dysfunction. Nat. Metab. 5, 546–562. [DOI] [PMC free article] [PubMed] [Google Scholar]
Monzel AS, Levin M, Picard M, 2024. The energetics of cellular life transitions. Life Metab 3, load051. 10.1093/lifemeta/load051. [DOI] [PMC free article] [PubMed] [Google Scholar]
Mosharov EV, Rosenberg AM, Monzel AS, Osto CA, Stiles L, Rosoklija GB, Dwork AJ, Bindra S, Junker A, Zhang Y, Fujita M, Mariani MB, Bakalian M, Sulzer D, De Jager PL, Menon V, Shirihai OS, Mann JJ, Underwood MD, Boldrini M, Thiebaut de Schotten M, Picard M, 2025. A human brain map of mitochondrial respiratory capacity and diversity. Nature 1–10. 10.1038/s41586-025-08740-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
Müller N, 2018. Inflammation in schizophrenia: pathogenetic aspects and therapeutic considerations. Schizophr. Bull. 44, 973–982. [DOI] [PMC free article] [PubMed] [Google Scholar]
Murnane KS, 2019. Serotonin 2A receptors are a stress response system: implications for post-traumatic stress disorder. Behav. Pharmacol. 30, 151. [DOI] [PMC free article] [PubMed] [Google Scholar]
Murphy P, Likhodii S, Nylen K, Burnham WM, 2004. The antidepressant properties of the ketogenic diet. Biol. Psychiatry 56, 981–983. [DOI] [PubMed] [Google Scholar]
Neylan TC, Muratore LA, Williams CL, Schmitz M, Valdez CV, Maguen S, O’Donovan A, Kelley DP, Metzler TJ, Cohen BE, West AC, Phan JDV, Antonetti V, Mayzel O, Hlavin JA, Chesney MA, Mehling WE, 2025. Group integrated exercise versus recovery class for veterans with posttraumatic stress disorder: a randomized clinical trial. BMC Psychiatry 25, 185. 10.1186/s12888-025-06638-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ni P, Ma Y, Chung S, 2024. Mitochondrial dysfunction in psychiatric disorders. Schizophr. Res. 273, 62–77. [DOI] [PMC free article] [PubMed] [Google Scholar]
Nicholson AA, Harricharan S, Densmore M, Neufeld RWJ, Ros T, McKinnon MC, Frewen PA, Théberge J, Jetly R, Pedlar D, Lanius RA, 2020. Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning. NeuroImage Clin. 27, 102262. 10.1016/j.nicl.2020.102262. [DOI] [PMC free article] [PubMed] [Google Scholar]
Niyazov DM, Kahler SG, Frye RE, 2016. Primary mitochondrial disease and secondary mitochondrial dysfunction: importance of distinction for diagnosis and treatment. Mol. Syndromol. 7, 122–137. [DOI] [PMC free article] [PubMed] [Google Scholar]
O’Donovan A, Ahmadian AJ, Neylan TC, Pacult MA, Edmondson D, Cohen BE, 2017. Current posttraumatic stress disorder and exaggerated threat sensitivity associated with elevated inflammation in the mind your heart study. Brain Behav. Immun. 60, 198–205. [DOI] [PMC free article] [PubMed] [Google Scholar]
O’Donovan A, Cohen BE, Seal KH, Bertenthal D, Margaretten M, Nishimi K, Neylan TC, 2015. Elevated risk for autoimmune disorders in Iraq and Afghanistan veterans with posttraumatic stress disorder. Biol. Psychiatry 77, 365–374. [DOI] [PMC free article] [PubMed] [Google Scholar]
O’Donovan A, Rush G, Hoatam G, Hughes BM, McCrohan A, Kelleher C, O’Farrelly C, Malone KM, 2013. Suicidal ideation is associated with elevated inflammation in patients with major depressive disorder. Depress Anxiety 30, 307–314. 10.1002/da.22087. [DOI] [PubMed] [Google Scholar]
O’Donovan A, Tomiyama AJ, Lin J, Puterman E, Adler NE, Kemeny M, Wolkowitz OM, Blackburn EH, Epel ES, 2012. Stress appraisals and cellular aging: a key role for anticipatory threat in the relationship between psychological stress and telomere length. Brain Behav. Immun. 26, 573–579. 10.1016/j.bbi.2012.01.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
Onat S, Büchel C, 2015. The neuronal basis of fear generalization in humans. Nat. Neurosci. 18, 1811–1818. 10.1038/nn.4166. [DOI] [PubMed] [Google Scholar]
Pardo M, Cheng Y, Sitbon Y, Lowell J, Grieco S, Worthen R, Desse S, Barreda-Diaz A, 2018. Insulin growth factor 2 (IGF2) as an emergent target in psychiatric and neurological disorders. Review. Neurosci. Res. [DOI] [PubMed] [Google Scholar]
Pariante CM, Miller AH, 2001. Glucocorticoid receptors in major depression: relevance to pathophysiology and treatment. Biol. Psychiatry 49, 391–404. [DOI] [PubMed] [Google Scholar]
Parihar VK, Hattiangady B, Kuruba R, Shuai B, Shetty AK, 2011. Predictable chronic mild stress improves mood, hippocampal neurogenesis and memory. Mol. Psychiatry 16, 171–183. 10.1038/mp.2009.130. [DOI] [PMC free article] [PubMed] [Google Scholar]
Penninx BW, Lange SM, 2018. Metabolic syndrome in psychiatric patients: overview, mechanisms, and implications. Dialog. Clin. Neurosci. 20, 63–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
Peoples JN, Saraf A, Ghazal N, Pham TT, Kwong JQ, 2019. Mitochondrial dysfunction and oxidative stress in heart disease. Exp. Mol. Med. 51, 1–13. 10.1038/s12276-019-0355-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Pezzulo G, Rigoli F, Friston K, 2015. Active inference, homeostatic regulation and adaptive behavioural control. Prog. Neurobiol. 134, 17–35. 10.1016/j.pneurobio.2015.09.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
Picard M, 2015. Mitochondrial synapses: intracellular communication and signal integration. Trends Neurosci. 38, 468–474. 10.1016/j.tins.2015.06.001. [DOI] [PubMed] [Google Scholar]
Picard M, Juster RP, McEwen BS, 2014. Mitochondrial allostatic load puts the “gluc” back in glucocorticoids. Nat. Rev. Endocrinol. 10, 303–310. 10.1038/nrendo.2014.22. [DOI] [PubMed] [Google Scholar]
Picard M, McEwen BS, 2018. Psychological stress and mitochondria: a systematic review. Psychosom. Med. 80, 141–153. 10.1097/psy.0000000000000545. [DOI] [PMC free article] [PubMed] [Google Scholar]
Picard M, McEwen BS, Epel ES, Sandi C, 2018. An energetic view of stress: focus on mitochondria. Front. Neuroendocrinol. 49, 72–85. 10.1016/j.yfrne.2018.01.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
Picard M, Sandi C, 2021. The social nature of mitochondria: implications for human health. Neurosci. Biobehav. Rev. 120, 595–610. [DOI] [PMC free article] [PubMed] [Google Scholar]
Picard M, Shirihai OS, 2022. Mitochondrial signal transduction. Cell Metab. 34, 1620–1653. [DOI] [PMC free article] [PubMed] [Google Scholar]
Picard Martin, Zhang, J., Hancock, S., Derbeneva, O., Golhar, R., Golik, P., O’Hearn, S., Levy, S., Potluri, P., Lvova, M., 2014. Progressive increase in mtDNA 3243A> g heteroplasmy causes abrupt transcriptional reprogramming. Proc. Natl. Acad. Sci. 111, E4033–E4042. [DOI] [PMC free article] [PubMed] [Google Scholar]
Pietrzykowski MO, Daigle KM, Waters AB, Swenson LP, Gansler DA, 2022. The central executive network and executive function in healthy and persons with schizophrenia groups: a meta-analysis of structural and functional MRI. Brain Imaging Behav. 16, 1451–1464. 10.1007/s11682-021-00589-3. [DOI] [PubMed] [Google Scholar]
Plessow F, Fischer R, Kirschbaum C, Goschke T, 2011. Inflexibly focused under stress: acute psychosocial stress increases shielding of action goals at the expense of reduced cognitive flexibility with increasing time lag to the stressor. J. Cogn. Neurosci. 23, 3218–3227. [DOI] [PubMed] [Google Scholar]
Pozo M, Milà-Guasch M, Haddad-Tóvolli R, Boudjadja MB, Chivite I, Toledo M, Gómez-Valadés AG, Eyre E, Ramírez S, Obri A, 2023. Negative energy balance hinders prosocial helping behavior. Proc. Natl. Acad. Sci. 120, e2218142120. [DOI] [PMC free article] [PubMed] [Google Scholar]
Prasad A, Chaichi A, Kelley DP, Francis J, Gartia MR, 2019. Current and future functional imaging techniques for post-traumatic stress disorder. RSC Adv. 9, 24568–24594. 10.1039/C9RA03562A. [DOI] [PMC free article] [PubMed] [Google Scholar]
Publishing D−5 A.P.A. %J.A.A.P., 2013. Diagnostic and statistical manual of mental disorders. 10.1176/appi.books.9780890425596. [DOI] [Google Scholar]
Radley JJ, Herman JP, 2023. Preclinical models of chronic stress: adaptation or pathology? Biol. Psychiatry 94, 194–202. [DOI] [PMC free article] [PubMed] [Google Scholar]
Rasbach KA, Funk JA, Jayavelu T, Green PT, Schnellmann RG, 2010. 5-hydroxytryptamine receptor stimulation of mitochondrial biogenesis. J. Pharmacol. Exp. Ther. 332, 632–639. [DOI] [PMC free article] [PubMed] [Google Scholar]
Restelli LM, Oettinghaus B, Halliday M, Agca C, Licci M, Sironi L, Savoia C, Hench J, Tolnay M, Neutzner A, Schmidt A, Eckert A, Mallucci G, Scorrano L, Frank S, 2018. Neuronal mitochondrial dysfunction activates the integrated stress response to induce fibroblast growth factor 21. Cell Rep. 24, 1407–1414. 10.1016/j.celrep.2018.07.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ricci A, Idzikowski MA, Soares CN, Brietzke E, 2020. Exploring the mechanisms of action of the antidepressant effect of the ketogenic diet. Rev. Neurosci. 31, 637–648. [DOI] [PubMed] [Google Scholar]
Robinson MB, Lee ML, DaSilva S, 2020. Glutamate transporters and mitochondria: signaling, Co-compartmentalization, functional coupling, and future directions. Neurochem. Res 45, 526–540. 10.1007/s11064-020-02974-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Rosenberg AM, Saggar M, Monzel AS, Devine J, Rogu P, Limoges A, Junker A, Sandi C, Mosharov EV, Dumitriu D, 2023. Brain mitochondrial diversity and network organization predict anxiety-like behavior in male mice. Nat. Commun. 14, 4726. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ryan KK, Packard AE, Larson KR, Stout J, Fourman SM, Thompson AM, Ludwick K, Habegger KM, Stemmer K, Itoh N, 2018. Dietary manipulations that induce ketosis activate the HPA axis in male rats and mice: a potential role for fibroblast growth factor-21. Endocrinology 159, 400–413. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sandroni PB, Fisher-Wellman KH, Jensen BC, 2022. Adrenergic receptor regulation of mitochondrial function in cardiomyocytes. J. Cardiovasc. Pharmacol. 80, 364–377. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sapolsky RM, Romero LM, Munck AU, 2000. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr. Rev. 21, 55–89. 10.1210/edrv.21.1.0389. [DOI] [PubMed] [Google Scholar]
Scalabrini A, Vai B, Poletti S, Damiani S, Mucci C, Colombo C, Zanardi R, Benedetti F, Northoff G, 2020. All roads lead to the default-mode network—global source of DMN abnormalities in major depressive disorder. Neuropsychopharmacol 45, 2058–2069. 10.1038/s41386-020-0785-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
Schreiber AL, Lu Y-L, Baynes BB, Richardson HN, Gilpin NW %J.N., 2017. Corticotropin-releasing factor in ventromedial prefrontal cortex mediates avoidance of a traumatic stress-paired context. Neuropharmacology 113, 323–330. 10.1016/j.neuropharm.2016.05.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
Schwabe L, Wolf OT, 2011. Stress-induced modulation of instrumental behavior: from goal-directed to habitual control of action. Behav. Brain Res. 219, 321–328. [DOI] [PubMed] [Google Scholar]
Seeman TE, McEwen BS, Rowe JW, Singer BH, 2001. Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proc. Natl. Acad. Sci. USA 98, 4770–4775. 10.1073/pnas.081072698. [DOI] [PMC free article] [PubMed] [Google Scholar]
Seeman TE, Singer BH, Rowe JW, Horwitz RI, McEwen BS, 1997. Price of adaptation—allostatic load and its health consequences: MacArthur studies of successful aging. Arch. Intern. Med. 157, 2259–2268. [PubMed] [Google Scholar]
Selye H, 1936. A syndrome produced by diverse nocuous agents. Nature 138. 10.1038/138032a0, 32–32. [DOI] [PubMed] [Google Scholar]
Selye H, 1946. The general adaptation syndrome and the diseases of adaptation. J. Clin. Endocrinol. 6, 117–230. [DOI] [PubMed] [Google Scholar]
Selye H, 1950. Stress and the general adaptation syndrome. Br. Med. J. 1, 1383–1392. 10.1136/bmj.1.4667.1383. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sennesh E, Theriault J, Brooks D, van de Meent J-W, Barrett LF, Quigley KS, 2022. Interoception as modeling, allostasis as control. Biol. Psychol. 167, 108242. [DOI] [PMC free article] [PubMed] [Google Scholar]
Seth AK, Friston KJ, 2016. Active interoceptive inference and the emotional brain. Philos. Trans. R. Soc. Lond. B Biol. Sci. 371. 10.1098/rstb.2016.0007. [DOI] [PMC free article] [PubMed] [Google Scholar]
Shaulson ED, Cohen AA, Picard M, 2024. The brain–body energy conservation model of aging. Nat. Aging 4, 1354–1371. 10.1038/s43587-024-00716-x. [DOI] [PubMed] [Google Scholar]
Shields GS, Sazma MA, Yonelinas AP, 2016. The effects of acute stress on core executive functions: a meta-analysis and comparison with cortisol. Neurosci. Biobehav. Rev. 68, 651–668. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sjöstedt E, Zhong W, Fagerberg L, Karlsson M, Mitsios N, Adori C, Oksvold P, Edfors F, Limiszewska A, Hikmet F, Huang J, Du Y, Lin L, Dong Z, Yang L, Liu X, Jiang H, Xu X, Wang J, Yang H, Bolund L, Mardinoglu A, Zhang C, von Feilitzen K, Lindskog C, Pontén F, Luo Y, Hökfelt T, Uhlén M, Mulder J, 2020. An Atlas of the protein-coding genes in the human, pig, and mouse brain. Science 367, eaay5947. 10.1126/science.aay5947. [DOI] [PubMed] [Google Scholar]
Sloan EK, Capitanio JP, Cole SW, 2008. Stress-induced remodeling of lymphoid innervation. Brain Behav. Immun. 22, 15–21. 10.1016/j.bbi.2007.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sloan EK, Capitanio JP, Tarara RP, Mendoza SP, Mason WA, Cole SW, 2007. Social stress enhances sympathetic innervation of primate lymph nodes: mechanisms and implications for viral pathogenesis. J. Neurosci. 27, 8857–8865. 10.1523/JNEUROSCI.1247-07.2007. [DOI] [PMC free article] [PubMed] [Google Scholar]
Smoller JW, 2016. The genetics of stress-related disorders: PTSD, depression, and anxiety disorders. Neuropsychopharmacology 41, 297–319. [DOI] [PMC free article] [PubMed] [Google Scholar]
Snyder HR, 2013. Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: a meta-analysis and review. Psychol. Bull. 139, 81–132. 10.1037/a0028727. [DOI] [PMC free article] [PubMed] [Google Scholar]
Snyder HR, Young JF, Hankin BL, 2019. Chronic stress exposure and generation are related to the p-factor and externalizing specific psychopathology in youth. J. Clin. Child Adolesc. Psychol. 48, 306–315. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sorrells SF, Sapolsky RM, 2010. Glucocorticoids can arm macrophages for innate immune battle. Brain Behav. Immun. 24, 17–18. 10.1016/j.bbi.2009.10.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
Spadoni AD, Vinograd M, Cuccurazzu B, Torres K, Glynn LM, Davis EP, Baram TZ, Baker DG, Nievergelt CM, Risbrough VB, 2022. Contribution of early-life unpredictability to neuropsychiatric symptom patterns in adulthood. Depress Anxiety 39, 706–717. 10.1002/da.23277. [DOI] [PMC free article] [PubMed] [Google Scholar]
Speed MS, Jefsen OH, Børglum AD, Speed D, Østergaard SD, 2019. Investigating the association between body fat and depression via mendelian randomization. Transl. Psychiatry 9, 184. [DOI] [PMC free article] [PubMed] [Google Scholar]
Spooner RK, Taylor BK, Ahmad IM, Dyball KN, Emanuel K, Fox HS, Stauch KL, Zimmerman MC, Wilson TW, 2021. Neural oscillatory activity serving sensorimotor control is predicted by superoxide-sensitive mitochondrial redox environments. Proc. Natl. Acad. Sci. 118, e2104569118. 10.1073/pnas.2104569118. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sterling P, 1988. Allostasis: a new paradigm to explain arousal pathology. Handbook of life stress, cognition and health. [Google Scholar]
Sterling P, 2014. Homeostasis vs allostasis: implications for brain function and mental disorders. JAMA Psychiatry 71, 1192–1193. [DOI] [PubMed] [Google Scholar]
Sturm G, Karan KR, Monzel AS, Santhanam B, Taivassalo T, Bris C, Ware SA, Cross M, Towheed A, Higgins-Chen A, 2023. OxPhos defects cause hypermetabolism and reduce lifespan in cells and in patients with mitochondrial diseases. Commun. Biol. 6, 22. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sun W, Baranova A, Liu D, Cao H, Zhang X, Zhang F, 2024. Phenome-wide investigation of bidirectional causal relationships between major depressive disorder and common human diseases. Transl. Psychiatry 14, 506. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sun T, Qiao H, Pan P-Y, Chen Y, Sheng Z-H, 2013. Motile axonal mitochondria contribute to the variability of presynaptic strength. Cell Rep. 4, 413–419. [DOI] [PMC free article] [PubMed] [Google Scholar]
Suvarna B, Suvarna A, Phillips R, Juster R-P, McDermott B, Sarnyai Z, 2020. Health risk behaviours and allostatic load: a systematic review. Neurosci. Biobehav. Rev. 108, 694–711. [DOI] [PubMed] [Google Scholar]
Tham YK, Bernardo BC, Huynh K, Ooi JY, Gao XM, Kiriazis H, Giles C, Meikle PJ, McMullen JR, 2018. Lipidomic profiles of the heart and circulation in response to exercise versus cardiac pathology: a resource of potential biomarkers and drug targets. Cell Rep. 24, 2757–2772. [DOI] [PubMed] [Google Scholar]
Tomasi D, Wang G-J, Volkow ND, 2013. Energetic cost of brain functional connectivity. Proc. Natl. Acad. Sci. 110, 13642–13647. [DOI] [PMC free article] [PubMed] [Google Scholar]
Toniolo RA, Silva M, Fernandes F, de BF, Amaral JA, de MS, Dias R, da S, Lafer B, 2018. A randomized, double-blind, placebo-controlled, proof-of-concept trial of creatine monohydrate as adjunctive treatment for bipolar depression. J. Neural Transm. 125, 247–257. [DOI] [PMC free article] [PubMed] [Google Scholar]
Tran DH, Wang ZV, 2019. Glucose metabolism in cardiac hypertrophy and heart failure. J. Am. Heart Assoc. 8, e012673. [DOI] [PMC free article] [PubMed] [Google Scholar]
Trinchese G, Cimmino F, Catapano A, Cavaliere G, Mollica MP, 2024. Mitochondria: the gatekeepers between metabolism and immunity. Front. Immunol. 15. 10.3389/fimmu.2024.1334006. [DOI] [PMC free article] [PubMed] [Google Scholar]
Tsakiris M, Critchley H, 2016. Interoception beyond homeostasis: affect, cognition and mental health. Philosophical Transactions of the Royal Society B: Biological Sciences. The Royal Society. [DOI] [PMC free article] [PubMed] [Google Scholar]
Tsigos C, Kyrou I, Kassi E, Chrousos GP, 2020. tress: endocrine physiology and pathophysiology. Endotext [Internet]. [Google Scholar]
Turana Y, Tengkawan J, Chia YC, Shin J, Chen C-H, Park S, Tsoi K, Buranakitjaroen P, Soenarta AA, Siddique S, Cheng H-M, Tay JC, Teo BW, Wang T-D, Kario K, 2021. Mental health problems and hypertension in the elderly: review from the HOPE Asia network. J. Clin. Hypertens. 23, 504–512. 10.1111/jch.14121. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ugur B, Bao H, Stawarski M, Duraine LR, Zuo Z, Lin YQ, Neely GG, Macleod GT, Chapman ER, Bellen HJ, 2017. The krebs cycle enzyme isocitrate dehydrogenase 3A couples mitochondrial metabolism to synaptic transmission. Cell Rep 21, 3794–3806. [DOI] [PMC free article] [PubMed] [Google Scholar]
Valença-Pereira F, Fang Q, Marié IJ, Giddings EL, Fortner KA, Yang R, Villarino AV, Huang YH, Frank DA, Wen H, 2021. IL-6 enhances CD4 cell motility by sustaining mitochondrial Ca2+ through the noncanonical STAT3 pathway. Proc. Natl. Acad. Sci. 118, e2103444118. [DOI] [PMC free article] [PubMed] [Google Scholar]
van Oort J, Tendolkar I, Hermans EJ, Mulders PC, Beckmann CF, Schene AH, Fernández G, van Eijndhoven PF, 2017. How the brain connects in response to acute stress: a review at the human brain systems level. Neurosci. Biobehav. Rev. 83, 281–297. 10.1016/j.neubiorev.2017.10.015. [DOI] [PubMed] [Google Scholar]
van Winkel R, Stefanis NC, Myin-Germeys I, 2008. Psychosocial stress and psychosis. A review of the neurobiological mechanisms and the evidence for gene-stress interaction. Schizophr. Bull. 34, 1095–1105. [DOI] [PMC free article] [PubMed] [Google Scholar]
Vanessa Fiorentino T, Prioletta A, Zuo P, Folli F, 2013. Hyperglycemia-induced oxidative stress and its role in diabetes mellitus related cardiovascular diseases. Curr. Pharm. Des. 19, 5695–5703. [DOI] [PubMed] [Google Scholar]
Velarde MC, 2014. Mitochondrial and sex steroid hormone crosstalk during aging. Longev. heal. 3, 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
Waddington CH, 1942. Canalization of development and the inheritance of acquired characters. Nature 150, 563–565. [DOI] [PubMed] [Google Scholar]
Wang H, Cheng Z, Xu Z, Wang M, Sun X, Liu W, Wang J, Yang Q, Zhang T, Song J, 2025. Systemic inflammatory factors and neuropsychiatric disorders: a bidirectional mendelian randomization study. Brain Behav. 15, e70478. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wang D, Day EA, Townsend LK, Djordjevic D, Jørgensen SB, Steinberg GR, 2021. GDF15: emerging biology and therapeutic applications for obesity and cardiometabolic disease. Nat. Rev. Endocrinol. 17, 592–607. 10.1038/s41574-021-00529-7. [DOI] [PubMed] [Google Scholar]
Wang M, Jin B, Jo J, 2025. Acute restraint stress induces Long-Lasting synaptic enhancement by inhibiting AMPK activation in AD model mice. CNS Neurosci. Ther. 31, e70335. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wang Q, Shelton RC, Dwivedi Y, 2018. Interaction between early-life stress and FKBP5 gene variants in major depressive disorder and post-traumatic stress disorder: a systematic review and meta-analysis. J. Affect Disord. 225, 422–428. 10.1016/j.jad.2017.08.066. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wang L, Xu Y, Jiang M, Wang M, Ji M, Xie X, Sheng H, 2025. Chronic stress induces depression-like behavior in rats through affecting brain mitochondrial function and inflammation. Psychoneuroendocrinology 172, 107261. [DOI] [PubMed] [Google Scholar]
Watts AL, Greene AL, Bonifay W, Fried EI, 2024. A critical evaluation of the p-factor literature. Nat. Rev. Psychol. 3, 108–122. [Google Scholar]
Weger M, Alpern D, Cherix A, Ghosal S, Grosse J, Russeil J, Gruetter R, de Kloet ER, Deplancke B, Sandi C, 2020. Mitochondrial gene signature in the prefrontal cortex for differential susceptibility to chronic stress. Sci. Rep. 10, 18308. [DOI] [PMC free article] [PubMed] [Google Scholar]
Weinberg SE, Sena LA, Chandel NS, 2015. Mitochondria in the regulation of innate and adaptive immunity. Immunity 42, 406–417. 10.1016/j.immuni.2015.02.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wende AR, Brahma MK, McGinnis GR, Young ME, 2017. Metabolic origins of heart failure. Basic Transl. Sci. 2, 297–310. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wiese M, Bannister AJ, 2020. Two genomes, one cell: Mitochondrial-nuclear coordination via epigenetic pathways. Mol. metab. 38, 100942. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wiley CD, Velarde MC, Lecot P, Liu SU, Sarnoski EA, Freund A, Shirakawa K, Lim HW, Davis SS, Ramanathan A, 2016. Mitochondrial dysfunction induces senescence with a distinct secretory phenotype. Cell Metab. 23, 303–314. [DOI] [PMC free article] [PubMed] [Google Scholar]
Willard VW, Long A, Phipps S, 2016. Life stress versus traumatic stress: the impact of life events on psychological functioning in children with and without serious illness. Psychol. Trauma. Theory Res. Pract. Policy 8, 63. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wilson CB, Ebenezer PJ, McLaughlin LD, Francis J, 2014. Predator exposure/psychosocial stress animal model of post-traumatic stress disorder modulates neurotransmitters in the rat hippocampus and prefrontal cortex. PLoS One 9, e89104. 10.1371/journal.pone.0089104. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wilson CB, McLaughlin LD, Nair A, Ebenezer PJ, Dange R, Francis J, 2013. Inflammation and oxidative stress are elevated in the brain, blood, and adrenal glands during the progression of post-traumatic stress disorder in a predator exposure animal model. PLoS One 8, e76146. 10.1371/journal.pone.0076146. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wu E-L, Chien I-C, Lin C-H, Chou Y-J, Chou P, 2012. Increased risk of hypertension in patients with major depressive disorder: a population-based study. J. Psychosom. Res. 73, 169–174. [DOI] [PubMed] [Google Scholar]
Xie M, Bu Y, 2019. SKA2/FAM33A: a novel gene implicated in cell cycle, tumorigenesis, and psychiatric disorders. Genes Dis. 6, 25–30. 10.1016/j.gendis.2018.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
Xiong H, Guo R-J, Shi H-W, 2020. Altered default mode network and salience network functional connectivity in patients with generalized anxiety disorders: an ICA-based resting-state fMRI study. Evid. Based Complement. Altern. Med. 2020, 4048916. 10.1155/2020/4048916. [DOI] [PMC free article] [PubMed] [Google Scholar]
Yang C, Silver B, Ellis SR, Mower GD, 2001. Bidirectional regulation of mitochondrial gene expression during developmental neuroplasticity of visual cortex. Biochem. Biophys. Res. Commun. 287, 1070–1074. [DOI] [PubMed] [Google Scholar]
Yehuda R, Flory JD, Bierer LM, Henn-Haase C, Lehrner A, Desarnaud F, Makotkine I, Daskalakis NP, Marmar CR, Meaney MJ, 2015. Lower methylation of glucocorticoid receptor gene promoter 1F in peripheral blood of veterans with posttraumatic stress disorder. Biol. Psychiatry 77, 356–364. 10.1016/j.biopsych.2014.02.006. [DOI] [PubMed] [Google Scholar]
Yehuda R, Golier JA, Halligan SL, Meaney M, Bierer LM, 2004. The ACTH response to dexamethasone in PTSD. Am. J. Psychiatry 161, 1397–1403. 10.1176/appi.ajp.161.8.1397. [DOI] [PubMed] [Google Scholar]
Young EA, Haskett RF, Murphy-Weinberg V, Watson SJ, Akil H, 1991. Loss of glucocorticoid fast feedback in depression. Arch. Gen. Psychiatry 48, 693–699. [DOI] [PubMed] [Google Scholar]
Yu Y, Akif A, Herman P, Cao M, Rothman DL, Carson RE, Agarwal D, Evans AC, Hyder F, 2023. A 3D Atlas of functional human brain energetic connectome based on neuropil distribution. Cereb. Cortex 33, 3996–4012. 10.1093/cercor/bhac322. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zakowski SG, 1995. The effects of stressor predictability on lymphocyte proliferation in humans. Psychol. Health 10, 409–425. 10.1080/08870449508401960. [DOI] [Google Scholar]
Zeev-Wolf M, Levy J, Goldstein A, Zagoory-Sharon O, Feldman R, 2019. Chronic early stress impairs default mode network connectivity in preadolescents and their mothers. Biol. Psychiatry Cognit. Neurosci. Neuroimaging 4, 72–80. 10.1016/j.bpsc.2018.09.009. [DOI] [PubMed] [Google Scholar]
Zhang X, Li C, 2024. Major depressive disorder increased the risk of hypertension: a mendelian randomization study. J. Affect. Disord. 355, 184–189. [DOI] [PubMed] [Google Scholar]
Zhang D, Raichle ME, 2010. Disease and the brain’s dark energy. Nat. Rev. Neurol. 6, 15–28. 10.1038/nrneurol.2009.198. [DOI] [PubMed] [Google Scholar]
Zhang G, Wang X, Rothermel BA, Lavandero S, Wang ZV, 2022. The integrated stress response in ischemic diseases. Cell Death Differ. 29, 750–757. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zheng Y, Garrett ME, Sun D, Clarke-Rubright EK, Haswell CC, Maihofer AX, Elman JA, Franz CE, Lyons MJ, Kremen WS, Peverill M, Sambrook K, McLaughlin KA, Davenport ND, Disner S, Sponheim SR, Andrew E, Korgaonkar M, Bryant R, Varkevisser T, Geuze E, Coleman J, Beckham JC, Kimbrel NA, Sullivan D, Miller M, Hayes J, Verfaellie M, Wolf E, Salat D, Spielberg JM, Milberg W, McGlinchey R, Dennis EL, Thompson PM, Medland S, Jahanshad N, Nievergelt CM, Ashley-Koch AE, Logue MW, Morey RA, 2021. Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume. Transl. Psychiatry 11, 1–10. 10.1038/s41398-021-01707-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhu J, Thompson CB, 2019. Metabolic regulation of cell growth and proliferation. Nat. Rev. Mol. Cell Biol. 20, 436–450. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zong Y, Li H, Liao P, Chen L, Pan Y, Zheng Y, Zhang C, Liu D, Zheng M, Gao J, 2024. Mitochondrial dysfunction: mechanisms and advances in therapy. Sig. Transduct. Target Ther. 9, 1–29. 10.1038/s41392-024-01839-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zucchi FCR, Kirkland SW, Jadavji NM, van Waes LT, Klein A, Supina RD, Metz GA, 2009. Predictable stress versus unpredictable stress: a comparison in a rodent model of stroke. Behav. Brain Res. 205, 67–75. 10.1016/j.bbr.2009.06.030. [DOI] [PubMed] [Google Scholar]

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[R1] Abbott BB, Schoen LS, Badia P, 1984. Predictable and unpredictable shock: behavioral measures of aversion and physiological measures of stress. Psychol. Bull. 96, 45–71. 10.1037/0033-2909.96.1.45. [DOI] [PubMed] [Google Scholar]

[R2] Adusumilli VS, Walker TL, Overall RW, Klatt GM, Zeidan SA, Zocher S, Kirova DG, Ntitsias K, Fischer TJ, Sykes AM, 2021. ROS dynamics delineate functional states of hippocampal neural stem cells and link to their activity-dependent exit from quiescence. Cell stem Cell 28, 300–314 e6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R3] Agis-Balboa RC, Arcos-Diaz D, Wittnam J, Govindarajan N, Blom K, Burkhardt S, Haladyniak U, Agbemenyah HY, Zovoilis A, Salinas-Riester G, 2011. A hippocampal insulin-growth factor 2 pathway regulates the extinction of fear memories. EMBO J. 30, 4071–4083. 10.1038/emboj.2011.293. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R4] Akiki TJ, Averill CL, Wrocklage KM, Scott JC, Averill LA, Schweinsburg B, Alexander-Bloch A, Martini B, Southwick SM, Krystal JH, Abdallah CG, 2018. Default mode network abnormalities in posttraumatic stress disorder: a novel network-restricted topology approach. NeuroImage 176, 489–498. 10.1016/j.neuroimage.2018.05.005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R5] Albrechet-Souza L, Nastase AS, Hill MN, Gilpin NW, 2021. Amygdalar endocannabinoids are affected by predator odor stress in a sex-specific manner and modulate acoustic startle reactivity in female rats. Neurobiol. Stress 15, 100387. 10.1016/j.ynstr.2021.100387. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R6] Allegrini AG, Cheesman R, Rimfeld K, Selzam S, Pingault J-B, Eley TC, Plomin R, 2020. The p factor: genetic analyses support a general dimension of psychopathology in childhood and adolescence. J. Child Psychol. Psychiatry 61, 30–39. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R7] Ames BN, 2006. Low micronutrient intake May accelerate the degenerative diseases of aging through allocation of scarce micronutrients by triage. In: Proceedings of the National Academy of Sciences, 103, pp. 17589–17594. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R8] Amorim FE, Rye CS, Milton AL, 2025. Mitochondrial dysfunction in PTSD: a mechanism to understand trauma susceptibility? MedRxiv 2025 03 (28), 25324821. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R9] Angajala A, Lim S, Phillips JB, Kim J-H, Yates C, You Z, Tan M, 2018. Diverse roles of mitochondria in immune responses: novel insights into Immuno-Metabolism. Front Immunol. 9, 1605. 10.3389/fimmu.2018.01605. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R10] Anisman H, Matheson K, 2005. Stress, depression, and anhedonia: caveats concerning animal models. Neurosci. Biobehav. Rev. Anim. Models Depress Antidepressant Act. 29, 525–546. 10.1016/j.neubiorev.2005.03.007. [DOI] [PubMed] [Google Scholar]

[R11] Arango-Lievano M, Lambert WM, Bath KG, Garabedian MJ, Chao MV, Jeanneteau F, 2015. Neurotrophic-priming of glucocorticoid receptor signaling is essential for neuronal plasticity to stress and antidepressant treatment. Proc. Natl. Acad. Sci. 112, 15737–15742. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] Armario A, Marti J, Gil M, 1990. The serum glucose response to acute stress is sensitive to the intensity of the stressor and to habituation. Psychoneuroendocrinology 15, 341–347. [DOI] [PubMed] [Google Scholar]

[R13] Arshavsky YI, 2023. Brain energetics and the connectionist concept in cognitive neuroscience. J. Neurophysiol. 130, 61–68. 10.1152/jn.00184.2023. [DOI] [PubMed] [Google Scholar]

[R14] Atlantis E, Baker M, 2008. Obesity effects on depression: systematic review of epidemiological studies. Int. J. Obes. 32, 881–891. [DOI] [PubMed] [Google Scholar]

[R15] Backé E-M, Seidler A, Latza U, Rossnagel K, Schumann B, 2012. The role of psychosocial stress at work for the development of cardiovascular diseases: a systematic review. Int. Arch. Occup. Environ. Health 85, 67–79. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R16] Baik J-H, 2020. Stress and the dopaminergic reward system. Exp. Mol. Med 52, 1879–1890. 10.1038/s12276-020-00532-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] Baker SR, Stephenson D, 2000. Prediction and control as determinants of behavioural uncertainty: effects on task performance and heart rate reactivity. Integr. Physiol. Behav. Sci 35, 235–250. 10.1007/BF02688786. [DOI] [PubMed] [Google Scholar]

[R18] Bakian AV, Huber RS, Scholl L, Renshaw PF, Kondo D, 2020. Dietary creatine intake and depression risk among US adults. Transl. Psychiatry 10, 52. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R19] Balasanthiran A, Shotliff K, 2015. The history of stress hyperglycaemia. J. R. Coll. Physicians Edinb. 45, 238–247. [DOI] [PubMed] [Google Scholar]

[R20] Barrett LF, 2017a. How emotions are made: the secret life of the brain. Houghton Mifflin Harcourt. [Google Scholar]

[R21] Barrett LF, 2017b. The theory of constructed emotion: an active inference account of interoception and categorization. Soc. Cogn. Affect. Neurosci. 12, 1–23. 10.1093/scan/nsw154. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R22] Barrett LF, Quigley KS, Hamilton P, 2016. An active inference theory of allostasis and interoception in depression. Philos. Trans. R. Soc. B Biol. Sci. 371, 20160011. 10.1098/rstb.2016.0011. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R23] Bashford-Largo J, Zhang R, Mathur A, Elowsky J, Schwartz A, Dobbertin M, Blair RJR, Blair KS, Bajaj S, 2022. Reduced cortical volume of the default mode network in adolescents with generalized anxiety disorder. Depress Anxiety 39, 485–495. 10.1002/da.23252. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R24] Becker YL, Duvvuri B, Fortin PR, Lood C, Boilard E, 2022. The role of mitochondria in rheumatic diseases. Nat. Rev. Rheumatol. 18, 621–640. [DOI] [PubMed] [Google Scholar]

[R25] Belenguer P, Duarte JM, Schuck PF, Ferreira GC, 2019. Mitochondria and the brain: bioenergetics and beyond. Neurotox. Res. 36, 219–238. [DOI] [PubMed] [Google Scholar]

[R26] Bersani FS, Mellon SH, Lindqvist D, Kang JI, Rampersaud R, Somvanshi PR, Doyle III FJ, Hammamieh R, Jett M, Yehuda R, 2020. Novel pharmacological targets for combat PTSD—metabolism, inflammation, the gut microbiome, and mitochondrial dysfunction. Mil. Med 185, 311–318. 10.1093/milmed/usz260. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R27] Besnard A, Sahay A, 2016. Adult hippocampal neurogenesis, fear generalization, and stress. Neuropsychopharmacol 41, 24–44. 10.1038/npp.2015.167. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R28] Besse A, Wu P, Bruni F, Donti T, Graham BH, Craigen WJ, McFarland R, Moretti P, Lalani S, Scott KL, 2015. The GABA transaminase, ABAT, is essential for mitochondrial nucleoside metabolism. Cell Metab. 21, 417–427. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R29] Bhardwaj G, Penniman CM, Jena J, Beltran PAS, Foster C, Poro K, Junck TL, Hinton AO, Souvenir R, Fuqua JD, 2021. Insulin and IGF-1 receptors regulate complex I–dependent mitochondrial bioenergetics and supercomplexes via FoxOs in muscle. J. Clin. Investig. 131. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R30] Bird L, 2019. Getting enough energy for immunity, 269–269 Nat. Rev. Immunol. 19. 10.1038/s41577-019-0159-y. [DOI] [PubMed] [Google Scholar]

[R31] Björkman F, Ekblom Ö, 2022. Physical exercise as treatment for PTSD: a systematic review and meta-analysis. Mil. Med. 187, e1103–e1113. [DOI] [PubMed] [Google Scholar]

[R32] Blalock ZN, Wu GWY, Lindqvist D, Trumpff C, Flory JD, Lin J, Reus VI, Rampersaud R, Hammamieh R, Gautam A, Doyle FJ, Marmar CR, Jett M, Yehuda R, Wolkowitz OM, Mellon SH, 2024. Circulating cell-free mitochondrial DNA levels and glucocorticoid sensitivity in a cohort of Male veterans with and without combat-related PTSD. Transl. Psychiatry 14, 1–11. 10.1038/s41398-023-02721-x. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R33] Bloemen AJP, Oldehinkel AJ, Laceulle OM, Ormel J, Rommelse NNJ, Hartman CA, 2018. The association between executive functioning and psychopathology: general or specific? Psychol. Med. 48, 1787–1794. 10.1017/S0033291717003269. [DOI] [PubMed] [Google Scholar]

[R34] Bo K, Kelly C, Trumpff C, Hirano M, Picard M, Wager TD, 2025. Mitochondrial energy transformation capacity influences brain activation during sensory, affective, and cognitive tasks. bioRxiv 06 (25), 661482, 2025. [Google Scholar]

[R35] Bobba-Alves N, Juster R-P, Picard M, 2022. The energetic cost of allostasis and allostatic load. Psychoneuroendocrinology 146, 105951. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R36] Boks MP, Rutten BP, Geuze E, Houtepen LC, Vermetten E, Kaminsky Z, Vinkers CH, 2016. SKA2 methylation is involved in cortisol stress reactivity and predicts the development of post-traumatic stress disorder (PTSD) after military deployment. Neuropsychopharmacology 41, 1350–1356. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R37] Borcherding N, Brestoff JR, 2023. The power and potential of mitochondria transfer. Nature 623, 283–291. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R38] Bourvis N, Aouidad A, Cabelguen C, Cohen D, Xavier J, 2017. How do stress exposure and stress regulation relate to borderline personality disorder? Front. Psychol. 8, 2054. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R39] Bremner JD, Hoffman M, Afzal N, Cheema FA, Novik O, Ashraf A, Brummer M, Nazeer A, Goldberg J, Vaccarino V, 2021. The environment contributes more than genetics to smaller hippocampal volume in posttraumatic stress disorder (PTSD). J. Psychiatr. Res. 137, 579–588. 10.1016/j.jpsychires.2020.10.042. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R40] Buckwalter JG, Castellani B, McEwen B, Karlamangla AS, Rizzo AA, John B, O’Donnell K, Seeman T, 2016. Allostatic load as a complex clinical construct: a Case-Based computational modeling approach. Complexity 21, 291–306. 10.1002/cplx.21743. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R41] Busillo JM, Azzam KM, Cidlowski JA, 2011. Glucocorticoids sensitize the innate immune system through regulation of the NLRP3 inflammasome. J. Biol. Chem. 286, 38703–38713. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R42] Buxton R, 2010. Interpreting oxygenation-based neuroimaging signals: the importance and the challenge of understanding brain oxygen metabolism. Front. Neuroenergetics 2. 10.3389/fnene.2010.00008. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R43] Buxton RB, 2021. The thermodynamics of thinking: connections between neural activity, energy metabolism and blood flow. Philos. Trans. R. Soc. B. 10.1098/rstb.2019.0624. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R44] Buxton RB, 2024. Thermodynamic limitations on brain oxygen metabolism: physiological implications. J. Physiol. 602, 683–712. [DOI] [PubMed] [Google Scholar]

[R45] Cameron HA, Schoenfeld TJ, 2018. Behavioral and structural adaptations to stress. Front. Neuroendocrinol. Stress Brain 49, 106–113. 10.1016/j.yfrne.2018.02.002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R46] Cannon WB, de la Paz D, 1911. Emotional stimulation of adrenal secretion. Am. J. Physiol. Leg. Content 28, 64–70. 10.1152/ajplegacy.1911.28.1.64. [DOI] [Google Scholar]

[R47] Capitanio JP, Cole SW, 2015. Social instability and immunity in rhesus monkeys: the role of the sympathetic nervous system. Philos. Trans. R. Soc. B Biol. Sci. 370, 20140104. 10.1098/rstb.2014.0104. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R48] Carhart-Harris RL, Chandaria S, Erritzoe DE, Gazzaley A, Girn M, Kettner H, Mediano PAM, Nutt DJ, Rosas FE, Roseman L, 2022. Canalization and plasticity in psychopathology. Neuropharmacology, 109398. [DOI] [PubMed] [Google Scholar]

[R49] Carver CS, Johnson SL, Timpano KR, 2017. Toward a functional view of the p factor in psychopathology. Clin. Psychol. Sci. 5, 880–889. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R50] Caspi A, Houts RM, Belsky DW, Goldman-Mellor SJ, Harrington H, Israel S, Meier MH, Ramrakha S, Shalev I, Poulton R, 2014. The p factor: one general psychopathology factor in the structure of psychiatric disorders? Clin. Psychol. Sci 2, 119–137. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R51] Castrillon G, Epp S, Bose A, Fraticelli L, Hechler A, Belenya R, Ranft A, Yakushev I, Utz L, Sundar L, 2023. An energy costly architecture of neuromodulators for human brain evolution and cognition. Sci. Adv. 9, eadi7632. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R52] Cavalcanti-de-Albuquerque JP, de-Souza-Ferreira E, de Carvalho DP, Galina A, 2021. Coupling of GABA metabolism to mitochondrial glucose phosphorylation. Neurochem. Res. 111. [DOI] [PubMed] [Google Scholar]

[R53] Chaichi A, Hasan SMA, Mehta N, Donnarumma F, Ebenezer P, Murray KK, Francis J, Gartia MR, 2021. Label-free lipidome study of paraventricular thalamic nucleus (PVT) of rat brain with post-traumatic stress injury by Raman imaging. Analyst 146, 170–183. [DOI] [PubMed] [Google Scholar]

[R54] Chen Q, Chen X, He X, Wang L, Wang K, Qiu B, 2016. Aberrant structural and functional connectivity in the salience network and central executive network circuit in schizophrenia. Neurosci. Lett. 627, 178–184. 10.1016/j.neulet.2016.05.035. [DOI] [PubMed] [Google Scholar]

[R55] Chen W, Feng J, Jiang S, Guo J, Zhang, XiaoLin, Zhang, Xiaoguan, Wang, C., Ma, Y., Dong, Z., 2023. Mendelian randomization analyses identify bidirectional causal relationships of obesity with psychiatric disorders. J. Affect. Disord. 339, 807–814. [DOI] [PubMed] [Google Scholar]

[R56] Chen S, Liao Z, Xu P, 2023. Mitochondrial control of innate immune responses. Front. Immunol. 14. 10.3389/fimmu.2023.1166214. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R57] Cheng A, Hou Y, Mattson MP, 2010. Mitochondria and neuroplasticity. ASN neuro 2, AN20100019. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R58] Chihara T, Luginbuhl D, Luo L, 2007. Cytoplasmic and mitochondrial protein translation in axonal and dendritic terminal arborization. Nat. Neurosci. 10, 828–837. [DOI] [PubMed] [Google Scholar]

[R59] Cimino I, Kim H, Tung YCL, Pedersen K, Rimmington D, Tadross JA, Kohnke SN, Neves-Costa A, Barros A, Joaquim S, Bennett D, Melvin A, Lockhart SM, Rostron AJ, Scott J, Liu H, Burling K, Barker P, Clatworthy MR, Lee E-C, Simpson AJ, Yeo GSH, Moita LF, Bence KK, Jørgensen SB, Coll AP, Breen DM, O’Rahilly S, 2021. Activation of the hypothalamic–pituitary–adrenal axis by exogenous and endogenous GDF15. Proc. Natl. Acad. Sci. 118, e2106868118. 10.1073/pnas.2106868118. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R60] Cisler JM, Dunsmoor JE, Fonzo GA, Nemeroff CB, 2024. Latent-state and model-based learning in PTSD. Trends Neurosci. 47, 150–162. 10.1016/j.tins.2023.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R61] Clairis N, Barakat A, Brochard J, Xin L, Sandi C, 2024. A neurometabolic mechanism involving dmPFC/dACC lactate in physical effort-based decision-making. Mol. Psychiatry. 10.1038/s41380-024-02726-y. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R62] Clement AB, Gamerdinger M, Tamboli IY, Lütjohann D, Walter J, Greeve I, Gimpl G, Behl C, 2009. Adaptation of neuronal cells to chronic oxidative stress is associated with altered cholesterol and sphingolipid homeostasis and lysosomal function. J. Neurochem. 111, 669–682. 10.1111/j.1471-4159.2009.06360.x. [DOI] [PubMed] [Google Scholar]

[R63] Cohodes EM, Sisk LM, Keding TJ, Mandell JD, Notti ME, Gee DG, 2023. Characterizing experiential elements of early-life stress to inform resilience: buffering effects of controllability and predictability and the importance of their timing. Dev. Psychopathol. 35, 2288–2301. 10.1017/S0954579423000822. [DOI] [PubMed] [Google Scholar]

[R64] Conant RC, Ross Ashby W, 1970. Every good regulator of a system must be a model of that system. Int. J. Syst. Sci. 1, 89–97. 10.1080/00207727008920220. [DOI] [Google Scholar]

[R65] Costa-Mattioli M, Walter P, 2020. The integrated stress response: from mechanism to disease. Science 368. 10.1126/science.aat5314. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R66] Courchet J, Lewis TL, Lee S, Courchet V, Liou D-Y, Aizawa S, Polleux F, 2013. Terminal axon branching is regulated by the LKB1-NUAK1 kinase pathway via presynaptic mitochondrial capture. Cell 153, 1510–1525. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R67] Coussement C, De Longueville X, Heeren A, 2022. Attentional networks in co-occurring generalized anxiety disorder and major depression disorder: towards a staging approach to the executive control deficits. Compr. Psychiatry 113, 152294. 10.1016/j.comppsych.2021.152294. [DOI] [PubMed] [Google Scholar]

[R68] Craig AD, 2009. How do you feel—now? the anterior insula and human awareness. Nat. Rev. Neurosci. 10, 59–70. [DOI] [PubMed] [Google Scholar]

[R69] Critchley HD, Garfinkel SN, 2017. Interoception and emotion. Curr. Opin. Psychol. 17, 7–14. [DOI] [PubMed] [Google Scholar]

[R70] Dache ZAA, Otandault A, Tanos R, Pastor B, Meddeb R, Sanchez C, Arena G, Lasorsa L, Bennett EA, Grange T, 2020. Blood contains circulating cell free respiratory competent mitochondria. Faseb J. 34, 3616–3630. [DOI] [PubMed] [Google Scholar]

[R71] Danese A, McEwen BS, 2012. Adverse childhood experiences, allostasis, allostatic load, and age-related disease. Physiol. Behav. Allostasis Allostatic Load. 106, 29–39. 10.1016/j.physbeh.2011.08.019. [DOI] [PubMed] [Google Scholar]

[R72] Davis EP, Stout SA, Molet J, Vegetabile B, Glynn LM, Sandman CA, Heins K, Stern H, Baram TZ, 2017. Exposure to unpredictable maternal sensory signals influences cognitive development across species. Proc. Natl. Acad. Sci. 114, 10390–10395. 10.1073/pnas.1703444114. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R73] Daviu N, Bruchas MR, Moghaddam B, Sandi C, Beyeler A, 2019. Neurobiological links between stress and anxiety. Neurobiol. Stress 11, 100191. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R74] Dimsdale JE, 2008. Psychological stress and cardiovascular disease. J. Am. Coll. Cardiol. 51, 1237–1246. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R75] DiNuzzo M, Dienel GA, Behar KL, Petroff OA, Benveniste H, Hyder F, Giove F, Michaeli S, Mangia S, Herculano-Houzel S, Rothman DL, 2024. Neurovascular coupling is optimized to compensate for the increase in proton production from nonoxidative glycolysis and glycogenolysis during brain activation and maintain homeostasis of ph, pCO2, and pO2. J. Neurochem. 168, 632–662. 10.1111/jnc.15839. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R76] Du L, Lin L, Li Q, Liu K, Huang Y, Wang X, Cao K, Chen X, Cao W, Li F, 2019. IGF-2 preprograms maturing macrophages to acquire oxidative phosphorylation-dependent anti-inflammatory properties. Cell Metab. 29, 1363–1375 e8. [DOI] [PubMed] [Google Scholar]

[R77] Du J, Wang Y, Hunter R, Wei Y, Blumenthal R, Falke C, Khairova R, Zhou R, Yuan P, Machado-Vieira R, 2009. Dynamic regulation of mitochondrial function by glucocorticoids. In: Proceedings of the National Academy of Sciences, 106, pp. 3543–3548. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R78] Eisner V, Picard M, Hajnóczky G, 2018. Mitochondrial dynamics in adaptive and maladaptive cellular stress responses. Nat. Cell Biol. 20, 755–765. 10.1038/s41556-018-0133-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R79] Erbsloh F, Bernsmeier A, Hillesheim H, 1958. The glucose consumption of the brain & its dependence on the liver. Archiv fur Psychiatrie und Nervenkrankheiten, vereinigt mit Zeitschrift fur die gesamte Neurologie und Psychiatrie 196, 611–626. [DOI] [PubMed] [Google Scholar]

[R80] Fanibunda SE, Deb S, Maniyadath B, Tiwari P, Ghai U, Gupta S, Figueiredo D, Weisstaub N, Gingrich JA, Vaidya AD, 2019. Serotonin regulates mitochondrial biogenesis and function in rodent cortical neurons via the 5-HT2A receptor and SIRT1–PGC-1α axis. In: Proceedings of the National Academy of Sciences, 116, pp. 11028–11037. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R81] Farahani A, Liu Z-Q, Ceballos EG, Hansen JY, Wennberg K, Zeighami Y, Dadar M, Gauthier CJ, Dagher A, Misic B, 2025. Cereb. blood Perfus. Across Biol. Syst. Hum. Lifesp. 10.1101/2025.02.05.636674. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R82] Fava GA, McEwen BS, Guidi J, Gostoli S, Offidani E, Sonino N, 2019. Clinical characterization of allostatic overload. Psychoneuroendocrinology 108, 94–101. 10.1016/j.psyneuen.2019.05.028. [DOI] [PubMed] [Google Scholar]

[R83] Fisk J, Khalid S, Reynolds SA, Williams CM, 2020. Effect of 4 weeks daily wild blueberry supplementation on symptoms of depression in adolescents. Br. J. Nutr. 124, 181–188. [DOI] [PubMed] [Google Scholar]

[R84] Fissler P, Mavioglu MSRN, Wenzel MSM, Pruessner JC, Kolassa I-T, Krähenmann PR, 2022. The link between mitochondria, psychopathology, and intelligence: A bioenergetic model of cerebral function. [Google Scholar]

[R85] Fissler P, Vandersmissen A, Filippi M, Mavioglu RN, Scholkmann F, Karabatsiakis A, Krähenmann R, 2023. Effects of serotonergic psychedelics on mitochondria: transdiagnostic implications for mitochondria-related pathologies. J. Psychopharmacol., 02698811231164707. [DOI] [PubMed] [Google Scholar]

[R86] Flanagan TW, Nichols CD, 2018. Psychedelics as anti-inflammatory agents. Int. Rev. Psychiatry 30, 363–375. [DOI] [PubMed] [Google Scholar]

[R87] Flanagan TW, Nichols CD, 2022. Psychedelics and anti-inflammatory activity in animal models. Disruptive Psychopharmacol. 229–245. [DOI] [PubMed] [Google Scholar]

[R88] Flint MS, Baum A, Chambers WH, Jenkins FJ, 2007. Induction of DNA damage, alteration of DNA repair and transcriptional activation by stress hormones. Psychoneuroendocrinology 32, 470–479. [DOI] [PubMed] [Google Scholar]

[R89] Flippo KH, Potthoff MJ, 2021. Metabolic messengers: FGF21. Nat. Metab. 3, 309–317. 10.1038/s42255-021-00354-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R90] Fraunfelter L, Gerdes ABM, Alpers GW, 2022. Fear one, fear them all: a systematic review and meta-analysis of fear generalization in pathological anxiety. Neurosci. Biobehav. Rev. 139, 104707. 10.1016/j.neubiorev.2022.104707. [DOI] [PubMed] [Google Scholar]

[R91] Friston K, 2010. The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11, 127–138. [DOI] [PubMed] [Google Scholar]

[R92] Fukumitsu K, Hatsukano T, Yoshimura A, Heuser J, Fujishima K, Kengaku M, 2016. Mitochondrial fission protein Drp1 regulates mitochondrial transport and dendritic arborization in cerebellar purkinje cells. Mol. Cell. Neurosci. 71, 56–65. [DOI] [PubMed] [Google Scholar]

[R93] Gak IA, Radovic SM, Dukic AR, Janjic MM, Stojkov-Mimic NJ, Kostic TS, Andric SA, 2015. Stress triggers mitochondrial biogenesis to preserve steroidogenesis in leydig cells. Biochim Biophys. Acta 1853, 2217–2227. 10.1016/j.bbamcr.2015.05.030. [DOI] [PubMed] [Google Scholar]

[R94] Galts CP, Bettio LE, Jewett DC, Yang CC, Brocardo PS, Rodrigues ALS, Thacker JS, Gil-Mohapel J, 2019. Depression in neurodegenerative diseases: common mechanisms and current treatment options. Neurosci. Biobehav. Rev. 102, 56–84. [DOI] [PubMed] [Google Scholar]

[R95] Galvão AC de M, de Almeida R.N., Silva EADS, Freire FAM, Palhano-Fontes F, Onias H, Arcoverde E, Maia-de-Oliveira JP, de Araújo DB, Lobão-Soares B, Galvão-Coelho NL, 2018. Cortisol modulation by ayahuasca in patients with treatment resistant depression and healthy controls. Front Psychiatry 9, 185. 10.3389/fpsyt.2018.00185. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R96] Gan Q, Yu R, Lian Z, Yuan Y, Li Y, Zheng L, 2023. Unraveling the link between hypertension and depression in older adults: a meta-analysis. Front. Public Health 11, 1302341. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R97] Ganeshan K, Nikkanen J, Man K, Leong YA, Sogawa Y, Maschek JA, Ry TV, Chagwedera DN, Cox JE, Chawla A, 2019. Energetic Trade-Offs and hypometabolic states promote disease tolerance. Cell 177, 399–413.e12. 10.1016/j.cell.2019.01.050. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R98] Garcia-Oscos F, Salgado H, Hall S, Thomas F, Farmer GE, Bermeo J, Galindo LC, Ramirez RD, D’Mello S, Rose-John S, 2012. The stress-induced cytokine interleukin-6 decreases the inhibition/excitation ratio in the rat temporal cortex via trans-signaling. Biol. Psychiatry 71, 574–582. 10.1016/j.biopsych.2011.11.018. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R99] Gazit N, Vertkin I, Shapira I, Helm M, Slomowitz E, Sheiba M, Mor Y, Rizzoli S, Slutsky I, 2016. IGF-1 receptor differentially regulates spontaneous and evoked transmission via mitochondria at hippocampal synapses. Neuron 89, 583–597. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R100] Gebara E, Zanoletti O, Ghosal S, Grosse J, Schneider BL, Knott G, Astori S, Sandi C, 2021. Mitofusin-2 in the nucleus accumbens regulates anxiety and depression-like behaviors through mitochondrial and neuronal actions. Biol. Psychiatry 89, 1033–1044. [DOI] [PubMed] [Google Scholar]

[R101] Gebreab SZ, Vandeleur CL, Rudaz D, Strippoli M-PF, Gholam-Rezaee M, Castelao E, Lasserre AM, Glaus J, Pistis G, Kuehner C, 2018. Psychosocial stress over the lifespan, psychological factors, and cardiometabolic risk in the community. Psychosom. Med. 80, 628–639. [DOI] [PubMed] [Google Scholar]

[R102] Ghosal S, Gebara E, Ramos-Fernández E, Chioino A, Grosse J, de Suduiraut IG, Zanoletti O, Schneider B, Zorzano A, Astori S, 2023. Mitofusin-2 in nucleus accumbens D2-MSNs regulates social dominance and neuronal function. Cell Rep. 42. [DOI] [PubMed] [Google Scholar]

[R103] Gilbertson MW, Shenton ME, Ciszewski A, Kasai K, Lasko NB, Orr SP, Pitman RK, 2002. Smaller hippocampal volume predicts pathologic vulnerability to psychological trauma. Nat. Neurosci. 5, 1242–1247. 10.1038/nn958. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R104] Girotti M, Adler SM, Bulin SE, Fucich EA, Paredes D, Morilak DA, 2018. Prefrontal cortex executive processes affected by stress in health and disease. Prog. NeuroPsychopharmacol. Biol. Psychiatry 85, 161–179. 10.1016/j.pnpbp.2017.07.004. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R105] Glavin GB, 1985. Stress and brain noradrenaline: a review. Neurosci. Biobehav Rev. 9, 233–243. 10.1016/0149-7634(85)90048-x. [DOI] [PubMed] [Google Scholar]

[R106] Glover LR, Schoenfeld TJ, Karlsson R-M, Bannerman DM, Cameron HA, 2017. Ongoing neurogenesis in the adult dentate gyrus mediates behavioral responses to ambiguous threat cues. PLOS Biol. 15, e2001154. 10.1371/journal.pbio.2001154. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R107] Goffart S, Wiesner RJ, 2003. Regulation and co-ordination of nuclear gene expression during mitochondrial biogenesis. Exp. Physiol. 88, 33–40. [DOI] [PubMed] [Google Scholar]

[R108] Goglia F, Silvestri E, Lanni A, 2002. Thyroid hormones and mitochondria. Biosci. rep. 22, 17–32. [DOI] [PubMed] [Google Scholar]

[R109] Goldstein LA, Mehling WE, Metzler TJ, Cohen BE, Barnes DE, Choucroun GJ, Silver A, Talbot LS, Maguen S, Hlavin JA, 2018. Veterans group exercise: a randomized pilot trial of an integrative exercise program for veterans with posttraumatic stress. J. Affect. Disord. 227, 345–352. [DOI] [PubMed] [Google Scholar]

[R110] Gouspillou G, Hirano M, Picard M, Trumpff C, n.d. The Energetic Stress Marker GDF15 is Induced by Acute Psychosocial Stress. [Google Scholar]

[R111] Graves SM, Xie Z, Stout KA, Zampese E, Burbulla LF, Shih JC, Kondapalli J, Patriarchi T, Tian L, Brichta L, 2020. Dopamine metabolism by a monoamine oxidase mitochondrial shuttle activates the electron transport chain. Nat. Neurosci. 23, 15–20. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R112] Grossman CD, Cohen JY, 2022. Neuromodulation and neurophysiology on the timescale of learning and Decision-Making. Annu. Rev. Neurosci. 45, 317–337. 10.1146/annurev-neuro-092021-125059. [DOI] [PubMed] [Google Scholar]

[R113] Gu S, Cieslak M, Baird B, Muldoon SF, Grafton ST, Pasqualetti F, Bassett DS, 2018. The energy landscape of neurophysiological activity implicit in brain network structure. Sci. Rep. 8, 2507. 10.1038/s41598-018-20123-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R114] Gui W, Zhu Y, Sun S, Zhu W, Tan B, Zhao H, Shang C, Zheng F, Lin X, Li H, 2021. Knockdown of insulin-like growth factor 2 gene disrupts mitochondrial functions in the liver. J. Mol. Cell Biol. 13 543555. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R115] Ha H, Han C, Kim B, 2017. Can obesity cause depression? A pseudo-panel analysis. J. Prev. Med. Public Health 50, 262. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R116] Harrington JS, Ryter SW, Plataki M, Price DR, Choi AMK, 2023. Mitochondria in health, disease, and aging. Physiol. Rev. 103, 2349–2422. 10.1152/physrev.00058.2021. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R117] Havranek MM, Bolliger B, Roos S, Pryce CR, Quednow BB, Seifritz E, 2016. Uncontrollable and unpredictable stress interacts with subclinical depression and anxiety scores in determining anxiety response. Stress 19, 53–62. 10.3109/10253890.2015.1117449. [DOI] [PubMed] [Google Scholar]

[R118] Hermans EJ, Henckens MJ, Joëls M, Fernández G, 2014. Dynamic adaptation of large-scale brain networks in response to acute stressors. Trends Neurosci. 37, 304–314. [DOI] [PubMed] [Google Scholar]

[R119] Hermans EJ, Henckens MJAG, Joëls M, Fernández G, 2017. Chapter 30 - Time-Dependent shifts in neural systems supporting Decision-Making under stress. In: Dreher J-C, Tremblay L (Eds.), Decision Neuroscience. Academic Press, San Diego, pp. 371–385. 10.1016/B978-0-12-805308-9.00030-0. [DOI] [Google Scholar]

[R120] Hilliard ME, Yi-Frazier JP, Hessler D, Butler AM, Anderson BJ, Jaser S, 2016. Stress and A1c among people with diabetes across the lifespan. Curr. Diabetes Rep. 16, 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R121] Hollis F, van der Kooij MA, Zanoletti O, Lozano L, Cantó C, Sandi C, 2015. Mitochondrial function in the brain links anxiety with social subordination. In: Proceedings of the National Academy of Sciences, 112, pp. 15486–15491. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R122] Hummel EM, Piovesan K, Berg F, Herpertz S, Kessler H, Kumsta R, Moser DA, 2023. Mitochondrial DNA as a marker for treatment-response in post-traumatic stress disorder. Psychoneuroendocrinology 148, 105993. 10.1016/j.psyneuen.2022.105993. [DOI] [PubMed] [Google Scholar]

[R123] Hunter RG, Seligsohn M, Rubin TG, Griffiths BB, Ozdemir Y, Pfaff DW, Datson NA, McEwen BS, 2016. Stress and corticosteroids regulate rat hippocampal mitochondrial DNA gene expression via the glucocorticoid receptor. Proc. Natl. Acad. Sci. USA 113, 9099–9104. 10.1073/pnas.1602185113. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R124] Itoga CA, Hellard EAR, Whitaker AM, Lu Y-L, Schreiber AL, Baynes BB, Baiamonte BA, Richardson HN, Gilpin NW %J.N., 2016. Traumatic stress promotes hyperalgesia via corticotropin-releasing factor-1 receptor (CRFR1) signaling in central amygdala. Neuropsychopharmacology 41, 2463. 10.1038/npp.2016.44. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R125] Iwasaki Y, Takeshima Yusuke, Fujio K, 2020. Basic mechanism of immune system activation by mitochondria. Immunol. Med. 43, 142–147. 10.1080/25785826.2020.1756609. [DOI] [PubMed] [Google Scholar]

[R126] Jiang M, Wang L, Sheng H, 2024. Mitochondria in depression: the dysfunction of mitochondrial energy metabolism and quality control systems. CNS Neurosci. Ther. 30, e14576. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R127] Jin S, Diano S, 2018. Mitochondrial dynamics and hypothalamic regulation of metabolism. Endocrinology 159, 3596–3604. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R128] Johnson JD, O’Connor KA, Watkins LR, Maier SF, 2004. The role of IL-1β in stress-induced sensitization of proinflammatory cytokine and corticosterone responses. Neuroscience 127, 569–577. 10.1016/j.neuroscience.2004.05.046. [DOI] [PubMed] [Google Scholar]

[R129] Johri A, Beal MF, 2012. Mitochondrial dysfunction in neurodegenerative diseases. J. Pharm. Exp. Ther. 342, 619–630. 10.1124/jpet.112.192138. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R130] Jones NT, Zahid Z, Grady SM, Sultan ZW, Zheng Z, Razidlo J, Banks MI, Wenthur CJ, 2023. Transient elevation of plasma glucocorticoids supports psilocybin-induced anxiolysis in mice. ACS Pharmacol. Transl. Sci. 6, 1221–1231. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R131] Kang SG, Choi MJ, Jung S-B, Chung HK, Chang JY, Kim JT, Kang YE, Lee JH, Hong HJ, Jun SM, 2021. Differential roles of GDF15 and FGF21 in systemic metabolic adaptation to the mitochondrial integrated stress response. IScience 24. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R132] Karan KR, Trumpff C, McGill MA, Thomas JE, Sturm G, Lauriola V, Sloan RP, Rohleder N, Kaufman BA, Marsland AL, 2020. Mitochondrial respiratory capacity modulates LPS-induced inflammatory signatures in human blood. Brain Behav. Immun. Health 5, 100080. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R133] Kasai K, Yamasue H, Gilbertson MW, Shenton ME, Rauch SL, Pitman RK, 2008. Evidence for acquired pregenual anterior cingulate gray matter loss from a twin study of combat-related posttraumatic stress disorder. Biol. Psychiatry 63, 550–556. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R134] Kawanishi S, Oikawa S, 2004. Mechanism of telomere shortening by oxidative stress. Ann. N. Y. Acad. Sci. 1019, 278–284. [DOI] [PubMed] [Google Scholar]

[R135] Keeney JN, Winters AD, Sitcheran R, West AP, 2023. NF-κB–Inducing kinase governs the mitochondrial respiratory capacity, differentiation, and inflammatory status of innate immune cells. J. Immunol. 210, 1123–1133. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R136] Kelley DP, 2022. Evaluation of hippocampal allostatic Load-Associated factors in animal models of Post-Traumatic stress disorder: relevance to human PTSD. Louisiana State University and Agricultural & Mechanical College. [Google Scholar]

[R137] Kelley DP, Albrechet-Souza L, Cruise S, Maiya R, Destouni A, Sakamuri SS, Duplooy A, Hibicke M, Nichols C, Katakam PV, 2023. Conditioned place avoidance is associated with a distinct hippocampal phenotype, partly preserved pattern separation, and reduced reactive oxygen species production after stress. Genes Brain Behav, e12840. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R138] Kelley DParker, Chaichi, A., Duplooy, A., Singh, D., Gartia, M.R., Francis, J., 2022. Labelfree mapping and profiling of altered lipid homeostasis in the rat hippocampus after traumatic stress: role of oxidative homeostasis. Neurobiol. Stress 20, 100476. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R139] Kelley DP, Venable K, Destouni A, Billac G, Ebenezer P, Stadler K, Nichols C, Barker S, Francis J, 2022. Pharmahuasca and DMT rescue ROS production and differentially expressed genes observed after predator and psychosocial stress: relevance to human PTSD. ACS Chem. Neurosci. 10.1021/acschemneuro.1c00660. [DOI] [PubMed] [Google Scholar]

[R140] Kelley D, Venable K, Sturm G, Skovgaard A, Francis J, Neylan T, Bradley E, Picard M, O’Donovan A, Singleton S, 2025. A llostatic Triage Model of Psychopathology (ATP Model): How Reallocation of Brain Energetic Resources Under Stress Elicits Psychiatric Symptoms. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R141] Kelly C, Trumpff C, Acosta C, Assuras S, Baker J, Basarrate S, Behnke A, Bo K, Bobba-Alves N, Champagne FA, Conklin Q, Cross M, De Jager P, Engelstad K, Epel E, Franklin SG, Hirano M, Huang Q, Junker A, Juster R-P, Kapri D, Kirschbaum C, Kurade M, Lauriola V, Li S, Liu CC, Liu G, McEwen B, McGill MA, McIntyre K, Monzel AS, Michelson J, Prather AA, Puterman E, Rosales XQ, Shapiro PA, Shire D, Slavich GM, Sloan RP, Smith JLM, Spann M, Spicer J, Sturm G, Tepler S, de Schotten MT, Wager TD, Picard M, 2024. A platform to map the mind–mitochondria connection and the hallmarks of psychobiology: the MiSBIE study. Trends Endocrinol. Metab. 35, 884–901. 10.1016/j.tem.2024.08.006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R142] Kendler KS, Karkowski LM, Prescott CA, 1999. Causal relationship between stressful life events and the onset of major depression. AJP 156, 837–841. 10.1176/ajp.156.6.837. [DOI] [PubMed] [Google Scholar]

[R143] Kendler KS, Kuhn J, Prescott CA, 2004. The interrelationship of neuroticism, sex, and stressful life events in the prediction of episodes of major depression. Am. J. Psychiatry 161, 631–636. [DOI] [PubMed] [Google Scholar]

[R144] Keyes KM, McLaughlin KA, Demmer RT, Cerdá M, Koenen KC, Uddin M, Galea S, 2013. Potentially traumatic events and the risk of six physical health conditions in a population-based sample. Depress Anxiety 30, 451–460. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R145] Khacho M, Harris R, Slack RS, 2019. Mitochondria as central regulators of neural stem cell fate and cognitive function. Nat. Rev. Neurosci. 20, 34–48. [DOI] [PubMed] [Google Scholar]

[R146] Khacho M, Slack RS, 2018. Mitochondrial dynamics in the regulation of neurogenesis: from development to the adult brain. Dev. Dyn. 247, 47–53. [DOI] [PubMed] [Google Scholar]

[R147] Kim KH, Son JM, Benayoun BA, Lee C, 2018. The mitochondrial-encoded peptide MOTS-c translocates to the nucleus to regulate nuclear gene expression in response to metabolic stress. Cell Metab. 28, 516–524 e7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R148] Kimura T, Murakami F, 2014. Evidence that dendritic mitochondria negatively regulate dendritic branching in pyramidal neurons in the neocortex. J. Neurosci. 34, 6938–6951. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R149] Kleckner IR, Zhang J, Touroutoglou A, Chanes L, Xia C, Simmons WK, Quigley KS, Dickerson BC, Barrett LF, 2017. Evidence for a large-scale brain system supporting allostasis and interoception in humans. Nat. Hum. Behav. 1. 10.1038/s41562-017-0069. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R150] Koolhaas JM, Bartolomucci A, Buwalda B, de Boer SF, Flügge G, Korte SM, Meerlo P, Murison R, Olivier B, Palanza P, Richter-Levin G, Sgoifo A, Steimer T, Stiedl O, van Dijk G, Wöhr M, Fuchs E, 2011. Stress revisited: a critical evaluation of the stress concept. Neurosci. Biobehav. Rev. 35, 1291–1301. 10.1016/j.neubiorev.2011.02.003. [DOI] [PubMed] [Google Scholar]

[R151] Korneeva NL, 2022. Integrated stress response in neuronal pathology and in health. Biochemistry (Moscow) 87, S111–S127. [DOI] [PubMed] [Google Scholar]

[R152] Kwon S-K, Sando III R, Lewis TL, Hirabayashi Y, Maximov A, Polleux F, 2016. LKB1 regulates mitochondria-dependent presynaptic calcium clearance and neurotransmitter release properties at excitatory synapses along cortical axons. PLoS Biol. 14, e1002516. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R153] Kwon S-K, Sando III R, Lewis TL, Hirabayashi Y, Maximov A, Polleux F, 2018. Correction: LKB1 regulates mitochondria-dependent presynaptic calcium clearance and neurotransmitter release properties at excitatory synapses along cortical axons. PLoS Biol. 16, e3000040. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R154] Lee H, Jiang X, Perwaiz I, Yu P, Wang J, Wang Y, Hüttemann M, Felder RA, Sibley DR, Polster BM, 2021. Dopamine D5 receptor-mediated decreases in mitochondrial reactive oxygen species production are cAMP and autophagy dependent. Hypertens. Res. 44, 628–641. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R155] Lee B, Lee H, Xiong L, Zhu J-K, 2002. A mitochondrial complex I defect impairs cold-regulated nuclear gene expression. Plant Cell 14, 1235–1251. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R156] Lee J, Sharma S, Kim J, Ferrante RJ, Ryu H, 2008. Mitochondrial nuclear receptors and transcription factors: who’s minding the cell? J. Neurosci. Res. 86, 961–971. 10.1002/jnr.21564. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R157] Lenart-Bugla M, Szcześniak D, Bugla B, Kowalski K, Niwa S, Rymaszewska J, Misiak B, 2022. The association between allostatic load and brain: a systematic review. Psychoneuroendocrinology 145, 105917. 10.1016/j.psyneuen.2022.105917. [DOI] [PubMed] [Google Scholar]

[R158] Leslie RD, Vartak T, 2020. Allostasis and the origins of adult-onset diabetes. Diabetologia 63, 261–265. 10.1007/s00125-019-05048-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R159] Lewis CR, Tafur J, Spencer S, Green JM, Harrison C, Kelmendi B, Rabin DM, Yehuda R, Yazar-Klosinski B, Cahn BR, 2023. Pilot study suggests DNA methylation of the glucocorticoid receptor gene (NR3C1) is associated with MDMA-assisted therapy treatment response for severe PTSD. Front. Psychiatry 14, 959590. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R160] Lex C, Baezner E, Meyer TD, 2017. Does stress play a significant role in bipolar disorder? A meta-analysis. J. Affect. Disord. 208, 298–308. [DOI] [PubMed] [Google Scholar]

[R161] Li L, Li X, Zhou W, Messina JL, 2013. Acute psychological stress results in the rapid development of insulin resistance. J. Endocrinol. 217, 175. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R162] Li J, Liu J, Zhong Y, Wang H, Yan B, Zheng K, Wei L, Lu H, Li B, 2021. Causal interactions between the default mode network and central executive network in patients with major depression. Neuroscience 475, 93–102. 10.1016/j.neuroscience.2021.08.033. [DOI] [PubMed] [Google Scholar]

[R163] Li Y, Zhao C, Sun S, Mi G, Liu C, Ding G, Wang C, Tang F, 2024. Elucidating the bidirectional association between autoimmune diseases and depression: a systematic review and meta-analysis. BMJ Ment. Health 27. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R164] Lim Y, Cho I-T, Rennke HG, Cho G, 2021. β2-adrenergic receptor regulates ER-mitochondria contacts. Sci. Rep. 11, 21477. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R165] Liu M-Y, Li N, Li WA, Khan H, 2017. Association between psychosocial stress and hypertension: a systematic review and meta-analysis. Neurol. Res. [DOI] [PubMed] [Google Scholar]

[R166] Lockhart SM, Saudek V, O’Rahilly S, 2020. GDF15: a hormone conveying somatic distress to the brain. Endocr. Rev. 41, bnaa007. 10.1210/endrev/bnaa007. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R167] Logue MW, van Rooij SJH, Dennis EL, Davis SL, Hayes JP, Stevens JS, Densmore M, Haswell CC, Ipser J, Koch SBJ, Korgaonkar M, Lebois LAM, Peverill M, Baker JT, Boedhoe PSW, Frijling JL, Gruber SA, Harpaz-Rotem I, Jahanshad N, Koopowitz S, Levy I, Nawijn L, O’Connor L, Olff M, Salat DH, Sheridan MA, Spielberg JM, van Zuiden M, Winternitz SR, Wolff JD, Wolf EJ, Wang X, Wrocklage K, Abdallah CG, Bryant RA, Geuze E, Jovanovic T, Kaufman ML, King AP, Krystal JH, Lagopoulos J, Bennett M, Lanius R, Liberzon I, McGlinchey RE, McLaughlin KA, Milberg WP, Miller MW, Ressler KJ, Veltman DJ, Stein DJ, Thomaes K, Thompson PM, Morey RA, 2018. Smaller hippocampal volume in posttraumatic stress disorder: a multisite ENIGMA-PGC study: subcortical volumetry results from posttraumatic stress disorder consortia. Biol. Psychiatry 83, 244–253. 10.1016/j.biopsych.2017.09.006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R168] Lombardi AA, Gibb AA, Arif E, Kolmetzky DW, Tomar D, Luongo TS, Jadiya P, Murray EK, Lorkiewicz PK, Hajnóczky G, 2019. Mitochondrial calcium exchange links metabolism with the epigenome to control cellular differentiation. Nat. commun. 10, 4509. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R169] Lowrance SA, Ionadi A, McKay E, Douglas X, Johnson JD, 2016. Sympathetic nervous system contributes to enhanced corticosterone levels following chronic stress. Psychoneuroendocrinology 68, 163–170. 10.1016/j.psyneuen.2016.02.027. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R170] Lushchak O, Strilbytska O, Koliada A, Storey KB, 2023. An orchestrating role of mitochondria in the origin and development of post-traumatic stress disorder. Front. Physiol. 13, 1094076. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R171] Lynch CJ, Elbau IG, Ng T, Ayaz A, Zhu S, Wolk D, Manfredi N, Johnson M, Chang M, Chou J, Summerville I, Ho C, Lueckel M, Bukhari H, Buchanan D, Victoria LW, Solomonov N, Goldwaser E, Moia S, Caballero-Gaudes C, Downar J, Vila-Rodriguez F, Daskalakis ZJ, Blumberger DM, Kay K, Aloysi A, Gordon EM, Bhati MT, Williams N, Power JD, Zebley B, Grosenick L, Gunning FM, Liston C, 2024. Frontostriatal salience network expansion in individuals in depression. Nature 110. 10.1038/s41586-024-07805-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R172] Madrigal JL, Olivenza R, Moro MA, Lizasoain I, Lorenzo P, Rodrigo J, Leza JC, 2001. Glutathione depletion, lipid peroxidation and mitochondrial dysfunction are induced by chronic stress in rat brain. Neuropsychopharmacology 24, 420–429. [DOI] [PubMed] [Google Scholar]

[R173] Magistretti PJ, Allaman I, 2015. A cellular perspective on brain energy metabolism and functional imaging. Neuron 86, 883–901. 10.1016/j.neuron.2015.03.035. [DOI] [PubMed] [Google Scholar]

[R174] Magistretti PJ, Pellerin L, 1999. Cellular mechanisms of brain energy metabolism and their relevance to functional brain imaging. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci 354, 1155–1163. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R175] Manoliu A, Riedl V, Zherdin A, Mühlau M, Schwerthöffer D, Scherr M, Peters H, Zimmer C, Förstl H, Bäuml J, Wohlschläger AM, Sorg C, 2014. Aberrant dependence of default Mode/Central executive network interactions on anterior insular salience network activity in schizophrenia. Schizophr. Bull. 40, 428–437. 10.1093/schbul/sbt037. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R176] Martín-Montañez E, Millon C, Boraldi F, Garcia-Guirado F, Pedraza C, Lara E, Santin LJ, Pavia J, Garcia-Fernandez M, 2017. IGF-II promotes neuroprotection and neuroplasticity recovery in a long-lasting model of oxidative damage induced by glucocorticoids. Redox Biol. 13, 69–81. 10.1016/j.redox.2017.05.012. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R177] Mateos MV, Uranga RM, Salvador GA, Giusto NM, 2008. Activation of phosphatidylcholine signalling during oxidative stress in synaptic endings. Neurochem. Int. 53, 199–206. [DOI] [PubMed] [Google Scholar]

[R178] Mattson MP, 2007. Mitochondrial regulation of neuronal plasticity. Neurochem. Res. 32, 707–715. [DOI] [PubMed] [Google Scholar]

[R179] Mattson MP, Gleichmann M, Cheng A, 2008. Mitochondria in neuroplasticity and neurological disorders. Neuron 60, 748–766. 10.1016/j.neuron.2008.10.010. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R180] McAvoy K, Kawamata H, 2019. Glial mitochondrial function and dysfunction in health and neurodegeneration. Mol. Cell. Neurosci. 101, 103417. [DOI] [PubMed] [Google Scholar]

[R181] McCutcheon RA, Bloomfield MAP, Dahoun T, Mehta M, Howes OD, 2019. Chronic psychosocial stressors are associated with alterations in salience processing and corticostriatal connectivity. Schizophr. Res. Stress Schizophr. 213, 56–64. 10.1016/j.schres.2018.12.011. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R182] McEwen BS, 1998. Stress, adaptation, and disease. Allostasis and allostatic load. Ann. N. Y Acad. Sci. 840, 33–44. 10.1111/j.1749-6632.1998.tb09546.x. [DOI] [PubMed] [Google Scholar]

[R183] McEwen Bruce S., 1998. Protective and damaging effects of stress mediators. N. Engl. J. Med. 338, 171–179. [DOI] [PubMed] [Google Scholar]

[R184] McEwen BS, 2003. Mood disorders and allostatic load. Biol. Psychiatry 54, 200–207. [DOI] [PubMed] [Google Scholar]

[R185] McEwen BS, 2005. Glucocorticoids, depression, and mood disorders: structural remodeling in the brain. Metabolism 54, 20–23. [DOI] [PubMed] [Google Scholar]

[R186] McEwen BS, 2015. Biomarkers for assessing population and individual health and disease related to stress and adaptation. Metabolism 64, S2–s10. 10.1016/j.metabol.2014.10.029. [DOI] [PubMed] [Google Scholar]

[R187] McEwen BS, Gianaros PJ, 2011. Stress- and Allostasis-Induced brain plasticity. Annu. Rev. Med. 62, 431–445. 10.1146/annurev-med-052209-100430. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R188] McEwen BS, Wingfield JC, 2003. The concept of allostasis in biology and biomedicine. Horm. Behav. 43, 2–15. [DOI] [PubMed] [Google Scholar]

[R189] McEwen BS, Wingfield JC, 2010. What is in a name? Integrating homeostasis, allostasis and stress. Horm. Behav. 57, 105–111. 10.1016/j.yhbeh.2009.09.011. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R190] McFarlane AC, Barton CA, Yehuda R, Wittert G, 2011. Cortisol response to acute trauma and risk of posttraumatic stress disorder. Psychoneuroendocrinology 36, 720–727. 10.1016/j.psyneuen.2010.10.007. [DOI] [PubMed] [Google Scholar]

[R191] Mellon SH, Gautam A, Hammamieh R, Jett M, Wolkowitz OM, 2018. Metabolism, metabolomics, and inflammation in posttraumatic stress disorder. Biol. Psychiatry 83, 866–875. 10.1016/j.biopsych.2018.02.007. [DOI] [PubMed] [Google Scholar]

[R192] Melo SR, de Antoniazzi C.T., de D, Hossain S, Kolb B, 2020. Short predictable stress promotes resistance to anxiety behavior and increases dendritic spines in prefrontal cortex and hippocampus. Brain Res. 1746, 147020. 10.1016/j.brainres.2020.147020. [DOI] [PubMed] [Google Scholar]

[R193] Ménard C, Pfau ML, Hodes GE, Russo SJ, 2017. Immune and neuroendocrine mechanisms of stress vulnerability and resilience. Neuropsychopharmacology 42, 62–80. 10.1038/npp.2016.90. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R194] Meng L, Chen D, Yang Y, Zheng Y, Hui R, 2012. Depression increases the risk of hypertension incidence: a meta-analysis of prospective cohort studies. J. Hypertens. 30, 842–851. 10.1097/HJH.0b013e32835080b7. [DOI] [PubMed] [Google Scholar]

[R195] Miao G, Deen J, Struzeski JB, Chen M, Zhang Y, Cole SA, Fretts AM, Lee ET, Howard BV, Fiehn O, 2023. Plasma lipidomic profile of depressive symptoms: a longitudinal study in a large sample of community-dwelling American Indians in the strong heart study. Mol. Psychiatry 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R196] Midzak A, Papadopoulos V, 2016. Adrenal mitochondria and steroidogenesis: From individual proteins to functional protein assemblies. Front Endocrinol (Lausanne) 7, 106. 10.3389/fendo.2016.00106. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R197] Miller WL, 2013. Steroid hormone synthesis in mitochondria. Mol. cell. endocrinol. 379, 62–73. [DOI] [PubMed] [Google Scholar]

[R198] Miller MW, Lin AP, Wolf EJ, Miller DR, 2018. Oxidative stress, inflammation, and neuroprogression in chronic PTSD. Harv. Rev. Psychiatry 26, 57–69. 10.1097/hrp.0000000000000167. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R199] Miller AH, Raison CL, 2016. The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nat. Rev. Immunol. 16, 22–34. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R200] Mishra A, Singh S, Tiwari V, Bano S, Shukla S, 2020. Dopamine D1 receptor agonism induces dynamin related protein-1 inhibition to improve mitochondrial biogenesis and dopaminergic neurogenesis in rat model of Parkinson’s disease. Behav. Brain Res. 378, 112304. [DOI] [PubMed] [Google Scholar]

[R201] Mizuno M, Takeba Y, Matsumoto N, Tsuzuki Y, Asoh K, Takagi M, Kobayashi S, Yamamoto H, 2010. Antenatal glucocorticoid therapy accelerates ATP production with creatine kinase increase in the growth-enhanced fetal rat heart. Circ. J. 74, 171–180. [DOI] [PubMed] [Google Scholar]

[R202] Monroe SM, Simons AD, 1991. Diathesis-stress theories in the context of life stress research: implications for the depressive disorders. Psychol. Bull. 110, 406. [DOI] [PubMed] [Google Scholar]

[R203] Monzel AS, Enríquez JA, Picard M, 2023. Multifaceted mitochondria: moving mitochondrial science beyond function and dysfunction. Nat. Metab. 5, 546–562. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R204] Monzel AS, Levin M, Picard M, 2024. The energetics of cellular life transitions. Life Metab 3, load051. 10.1093/lifemeta/load051. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R205] Mosharov EV, Rosenberg AM, Monzel AS, Osto CA, Stiles L, Rosoklija GB, Dwork AJ, Bindra S, Junker A, Zhang Y, Fujita M, Mariani MB, Bakalian M, Sulzer D, De Jager PL, Menon V, Shirihai OS, Mann JJ, Underwood MD, Boldrini M, Thiebaut de Schotten M, Picard M, 2025. A human brain map of mitochondrial respiratory capacity and diversity. Nature 1–10. 10.1038/s41586-025-08740-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R206] Müller N, 2018. Inflammation in schizophrenia: pathogenetic aspects and therapeutic considerations. Schizophr. Bull. 44, 973–982. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R207] Murnane KS, 2019. Serotonin 2A receptors are a stress response system: implications for post-traumatic stress disorder. Behav. Pharmacol. 30, 151. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R208] Murphy P, Likhodii S, Nylen K, Burnham WM, 2004. The antidepressant properties of the ketogenic diet. Biol. Psychiatry 56, 981–983. [DOI] [PubMed] [Google Scholar]

[R209] Neylan TC, Muratore LA, Williams CL, Schmitz M, Valdez CV, Maguen S, O’Donovan A, Kelley DP, Metzler TJ, Cohen BE, West AC, Phan JDV, Antonetti V, Mayzel O, Hlavin JA, Chesney MA, Mehling WE, 2025. Group integrated exercise versus recovery class for veterans with posttraumatic stress disorder: a randomized clinical trial. BMC Psychiatry 25, 185. 10.1186/s12888-025-06638-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R210] Ni P, Ma Y, Chung S, 2024. Mitochondrial dysfunction in psychiatric disorders. Schizophr. Res. 273, 62–77. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R211] Nicholson AA, Harricharan S, Densmore M, Neufeld RWJ, Ros T, McKinnon MC, Frewen PA, Théberge J, Jetly R, Pedlar D, Lanius RA, 2020. Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning. NeuroImage Clin. 27, 102262. 10.1016/j.nicl.2020.102262. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R212] Niyazov DM, Kahler SG, Frye RE, 2016. Primary mitochondrial disease and secondary mitochondrial dysfunction: importance of distinction for diagnosis and treatment. Mol. Syndromol. 7, 122–137. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R213] O’Donovan A, Ahmadian AJ, Neylan TC, Pacult MA, Edmondson D, Cohen BE, 2017. Current posttraumatic stress disorder and exaggerated threat sensitivity associated with elevated inflammation in the mind your heart study. Brain Behav. Immun. 60, 198–205. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R214] O’Donovan A, Cohen BE, Seal KH, Bertenthal D, Margaretten M, Nishimi K, Neylan TC, 2015. Elevated risk for autoimmune disorders in Iraq and Afghanistan veterans with posttraumatic stress disorder. Biol. Psychiatry 77, 365–374. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R215] O’Donovan A, Rush G, Hoatam G, Hughes BM, McCrohan A, Kelleher C, O’Farrelly C, Malone KM, 2013. Suicidal ideation is associated with elevated inflammation in patients with major depressive disorder. Depress Anxiety 30, 307–314. 10.1002/da.22087. [DOI] [PubMed] [Google Scholar]

[R216] O’Donovan A, Tomiyama AJ, Lin J, Puterman E, Adler NE, Kemeny M, Wolkowitz OM, Blackburn EH, Epel ES, 2012. Stress appraisals and cellular aging: a key role for anticipatory threat in the relationship between psychological stress and telomere length. Brain Behav. Immun. 26, 573–579. 10.1016/j.bbi.2012.01.007. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R217] Onat S, Büchel C, 2015. The neuronal basis of fear generalization in humans. Nat. Neurosci. 18, 1811–1818. 10.1038/nn.4166. [DOI] [PubMed] [Google Scholar]

[R218] Pardo M, Cheng Y, Sitbon Y, Lowell J, Grieco S, Worthen R, Desse S, Barreda-Diaz A, 2018. Insulin growth factor 2 (IGF2) as an emergent target in psychiatric and neurological disorders. Review. Neurosci. Res. [DOI] [PubMed] [Google Scholar]

[R219] Pariante CM, Miller AH, 2001. Glucocorticoid receptors in major depression: relevance to pathophysiology and treatment. Biol. Psychiatry 49, 391–404. [DOI] [PubMed] [Google Scholar]

[R220] Parihar VK, Hattiangady B, Kuruba R, Shuai B, Shetty AK, 2011. Predictable chronic mild stress improves mood, hippocampal neurogenesis and memory. Mol. Psychiatry 16, 171–183. 10.1038/mp.2009.130. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R221] Penninx BW, Lange SM, 2018. Metabolic syndrome in psychiatric patients: overview, mechanisms, and implications. Dialog. Clin. Neurosci. 20, 63–73. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R222] Peoples JN, Saraf A, Ghazal N, Pham TT, Kwong JQ, 2019. Mitochondrial dysfunction and oxidative stress in heart disease. Exp. Mol. Med. 51, 1–13. 10.1038/s12276-019-0355-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R223] Pezzulo G, Rigoli F, Friston K, 2015. Active inference, homeostatic regulation and adaptive behavioural control. Prog. Neurobiol. 134, 17–35. 10.1016/j.pneurobio.2015.09.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R224] Picard M, 2015. Mitochondrial synapses: intracellular communication and signal integration. Trends Neurosci. 38, 468–474. 10.1016/j.tins.2015.06.001. [DOI] [PubMed] [Google Scholar]

[R225] Picard M, Juster RP, McEwen BS, 2014. Mitochondrial allostatic load puts the “gluc” back in glucocorticoids. Nat. Rev. Endocrinol. 10, 303–310. 10.1038/nrendo.2014.22. [DOI] [PubMed] [Google Scholar]

[R226] Picard M, McEwen BS, 2018. Psychological stress and mitochondria: a systematic review. Psychosom. Med. 80, 141–153. 10.1097/psy.0000000000000545. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R227] Picard M, McEwen BS, Epel ES, Sandi C, 2018. An energetic view of stress: focus on mitochondria. Front. Neuroendocrinol. 49, 72–85. 10.1016/j.yfrne.2018.01.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R228] Picard M, Sandi C, 2021. The social nature of mitochondria: implications for human health. Neurosci. Biobehav. Rev. 120, 595–610. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R229] Picard M, Shirihai OS, 2022. Mitochondrial signal transduction. Cell Metab. 34, 1620–1653. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R230] Picard Martin, Zhang, J., Hancock, S., Derbeneva, O., Golhar, R., Golik, P., O’Hearn, S., Levy, S., Potluri, P., Lvova, M., 2014. Progressive increase in mtDNA 3243A> g heteroplasmy causes abrupt transcriptional reprogramming. Proc. Natl. Acad. Sci. 111, E4033–E4042. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R231] Pietrzykowski MO, Daigle KM, Waters AB, Swenson LP, Gansler DA, 2022. The central executive network and executive function in healthy and persons with schizophrenia groups: a meta-analysis of structural and functional MRI. Brain Imaging Behav. 16, 1451–1464. 10.1007/s11682-021-00589-3. [DOI] [PubMed] [Google Scholar]

[R232] Plessow F, Fischer R, Kirschbaum C, Goschke T, 2011. Inflexibly focused under stress: acute psychosocial stress increases shielding of action goals at the expense of reduced cognitive flexibility with increasing time lag to the stressor. J. Cogn. Neurosci. 23, 3218–3227. [DOI] [PubMed] [Google Scholar]

[R233] Pozo M, Milà-Guasch M, Haddad-Tóvolli R, Boudjadja MB, Chivite I, Toledo M, Gómez-Valadés AG, Eyre E, Ramírez S, Obri A, 2023. Negative energy balance hinders prosocial helping behavior. Proc. Natl. Acad. Sci. 120, e2218142120. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R234] Prasad A, Chaichi A, Kelley DP, Francis J, Gartia MR, 2019. Current and future functional imaging techniques for post-traumatic stress disorder. RSC Adv. 9, 24568–24594. 10.1039/C9RA03562A. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R235] Publishing D−5 A.P.A. %J.A.A.P., 2013. Diagnostic and statistical manual of mental disorders. 10.1176/appi.books.9780890425596. [DOI] [Google Scholar]

[R236] Radley JJ, Herman JP, 2023. Preclinical models of chronic stress: adaptation or pathology? Biol. Psychiatry 94, 194–202. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R237] Rasbach KA, Funk JA, Jayavelu T, Green PT, Schnellmann RG, 2010. 5-hydroxytryptamine receptor stimulation of mitochondrial biogenesis. J. Pharmacol. Exp. Ther. 332, 632–639. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R238] Restelli LM, Oettinghaus B, Halliday M, Agca C, Licci M, Sironi L, Savoia C, Hench J, Tolnay M, Neutzner A, Schmidt A, Eckert A, Mallucci G, Scorrano L, Frank S, 2018. Neuronal mitochondrial dysfunction activates the integrated stress response to induce fibroblast growth factor 21. Cell Rep. 24, 1407–1414. 10.1016/j.celrep.2018.07.023. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R239] Ricci A, Idzikowski MA, Soares CN, Brietzke E, 2020. Exploring the mechanisms of action of the antidepressant effect of the ketogenic diet. Rev. Neurosci. 31, 637–648. [DOI] [PubMed] [Google Scholar]

[R240] Robinson MB, Lee ML, DaSilva S, 2020. Glutamate transporters and mitochondria: signaling, Co-compartmentalization, functional coupling, and future directions. Neurochem. Res 45, 526–540. 10.1007/s11064-020-02974-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R241] Rosenberg AM, Saggar M, Monzel AS, Devine J, Rogu P, Limoges A, Junker A, Sandi C, Mosharov EV, Dumitriu D, 2023. Brain mitochondrial diversity and network organization predict anxiety-like behavior in male mice. Nat. Commun. 14, 4726. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R242] Ryan KK, Packard AE, Larson KR, Stout J, Fourman SM, Thompson AM, Ludwick K, Habegger KM, Stemmer K, Itoh N, 2018. Dietary manipulations that induce ketosis activate the HPA axis in male rats and mice: a potential role for fibroblast growth factor-21. Endocrinology 159, 400–413. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R243] Sandroni PB, Fisher-Wellman KH, Jensen BC, 2022. Adrenergic receptor regulation of mitochondrial function in cardiomyocytes. J. Cardiovasc. Pharmacol. 80, 364–377. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R244] Sapolsky RM, Romero LM, Munck AU, 2000. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr. Rev. 21, 55–89. 10.1210/edrv.21.1.0389. [DOI] [PubMed] [Google Scholar]

[R245] Scalabrini A, Vai B, Poletti S, Damiani S, Mucci C, Colombo C, Zanardi R, Benedetti F, Northoff G, 2020. All roads lead to the default-mode network—global source of DMN abnormalities in major depressive disorder. Neuropsychopharmacol 45, 2058–2069. 10.1038/s41386-020-0785-x. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R246] Schreiber AL, Lu Y-L, Baynes BB, Richardson HN, Gilpin NW %J.N., 2017. Corticotropin-releasing factor in ventromedial prefrontal cortex mediates avoidance of a traumatic stress-paired context. Neuropharmacology 113, 323–330. 10.1016/j.neuropharm.2016.05.008. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R247] Schwabe L, Wolf OT, 2011. Stress-induced modulation of instrumental behavior: from goal-directed to habitual control of action. Behav. Brain Res. 219, 321–328. [DOI] [PubMed] [Google Scholar]

[R248] Seeman TE, McEwen BS, Rowe JW, Singer BH, 2001. Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proc. Natl. Acad. Sci. USA 98, 4770–4775. 10.1073/pnas.081072698. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R249] Seeman TE, Singer BH, Rowe JW, Horwitz RI, McEwen BS, 1997. Price of adaptation—allostatic load and its health consequences: MacArthur studies of successful aging. Arch. Intern. Med. 157, 2259–2268. [PubMed] [Google Scholar]

[R250] Selye H, 1936. A syndrome produced by diverse nocuous agents. Nature 138. 10.1038/138032a0, 32–32. [DOI] [PubMed] [Google Scholar]

[R251] Selye H, 1946. The general adaptation syndrome and the diseases of adaptation. J. Clin. Endocrinol. 6, 117–230. [DOI] [PubMed] [Google Scholar]

[R252] Selye H, 1950. Stress and the general adaptation syndrome. Br. Med. J. 1, 1383–1392. 10.1136/bmj.1.4667.1383. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R253] Sennesh E, Theriault J, Brooks D, van de Meent J-W, Barrett LF, Quigley KS, 2022. Interoception as modeling, allostasis as control. Biol. Psychol. 167, 108242. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R254] Seth AK, Friston KJ, 2016. Active interoceptive inference and the emotional brain. Philos. Trans. R. Soc. Lond. B Biol. Sci. 371. 10.1098/rstb.2016.0007. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R255] Shaulson ED, Cohen AA, Picard M, 2024. The brain–body energy conservation model of aging. Nat. Aging 4, 1354–1371. 10.1038/s43587-024-00716-x. [DOI] [PubMed] [Google Scholar]

[R256] Shields GS, Sazma MA, Yonelinas AP, 2016. The effects of acute stress on core executive functions: a meta-analysis and comparison with cortisol. Neurosci. Biobehav. Rev. 68, 651–668. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R257] Sjöstedt E, Zhong W, Fagerberg L, Karlsson M, Mitsios N, Adori C, Oksvold P, Edfors F, Limiszewska A, Hikmet F, Huang J, Du Y, Lin L, Dong Z, Yang L, Liu X, Jiang H, Xu X, Wang J, Yang H, Bolund L, Mardinoglu A, Zhang C, von Feilitzen K, Lindskog C, Pontén F, Luo Y, Hökfelt T, Uhlén M, Mulder J, 2020. An Atlas of the protein-coding genes in the human, pig, and mouse brain. Science 367, eaay5947. 10.1126/science.aay5947. [DOI] [PubMed] [Google Scholar]

[R258] Sloan EK, Capitanio JP, Cole SW, 2008. Stress-induced remodeling of lymphoid innervation. Brain Behav. Immun. 22, 15–21. 10.1016/j.bbi.2007.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R259] Sloan EK, Capitanio JP, Tarara RP, Mendoza SP, Mason WA, Cole SW, 2007. Social stress enhances sympathetic innervation of primate lymph nodes: mechanisms and implications for viral pathogenesis. J. Neurosci. 27, 8857–8865. 10.1523/JNEUROSCI.1247-07.2007. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R260] Smoller JW, 2016. The genetics of stress-related disorders: PTSD, depression, and anxiety disorders. Neuropsychopharmacology 41, 297–319. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R261] Snyder HR, 2013. Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: a meta-analysis and review. Psychol. Bull. 139, 81–132. 10.1037/a0028727. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R262] Snyder HR, Young JF, Hankin BL, 2019. Chronic stress exposure and generation are related to the p-factor and externalizing specific psychopathology in youth. J. Clin. Child Adolesc. Psychol. 48, 306–315. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R263] Sorrells SF, Sapolsky RM, 2010. Glucocorticoids can arm macrophages for innate immune battle. Brain Behav. Immun. 24, 17–18. 10.1016/j.bbi.2009.10.004. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R264] Spadoni AD, Vinograd M, Cuccurazzu B, Torres K, Glynn LM, Davis EP, Baram TZ, Baker DG, Nievergelt CM, Risbrough VB, 2022. Contribution of early-life unpredictability to neuropsychiatric symptom patterns in adulthood. Depress Anxiety 39, 706–717. 10.1002/da.23277. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R265] Speed MS, Jefsen OH, Børglum AD, Speed D, Østergaard SD, 2019. Investigating the association between body fat and depression via mendelian randomization. Transl. Psychiatry 9, 184. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R266] Spooner RK, Taylor BK, Ahmad IM, Dyball KN, Emanuel K, Fox HS, Stauch KL, Zimmerman MC, Wilson TW, 2021. Neural oscillatory activity serving sensorimotor control is predicted by superoxide-sensitive mitochondrial redox environments. Proc. Natl. Acad. Sci. 118, e2104569118. 10.1073/pnas.2104569118. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R267] Sterling P, 1988. Allostasis: a new paradigm to explain arousal pathology. Handbook of life stress, cognition and health. [Google Scholar]

[R268] Sterling P, 2014. Homeostasis vs allostasis: implications for brain function and mental disorders. JAMA Psychiatry 71, 1192–1193. [DOI] [PubMed] [Google Scholar]

[R269] Sturm G, Karan KR, Monzel AS, Santhanam B, Taivassalo T, Bris C, Ware SA, Cross M, Towheed A, Higgins-Chen A, 2023. OxPhos defects cause hypermetabolism and reduce lifespan in cells and in patients with mitochondrial diseases. Commun. Biol. 6, 22. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R270] Sun W, Baranova A, Liu D, Cao H, Zhang X, Zhang F, 2024. Phenome-wide investigation of bidirectional causal relationships between major depressive disorder and common human diseases. Transl. Psychiatry 14, 506. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R271] Sun T, Qiao H, Pan P-Y, Chen Y, Sheng Z-H, 2013. Motile axonal mitochondria contribute to the variability of presynaptic strength. Cell Rep. 4, 413–419. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R272] Suvarna B, Suvarna A, Phillips R, Juster R-P, McDermott B, Sarnyai Z, 2020. Health risk behaviours and allostatic load: a systematic review. Neurosci. Biobehav. Rev. 108, 694–711. [DOI] [PubMed] [Google Scholar]

[R273] Tham YK, Bernardo BC, Huynh K, Ooi JY, Gao XM, Kiriazis H, Giles C, Meikle PJ, McMullen JR, 2018. Lipidomic profiles of the heart and circulation in response to exercise versus cardiac pathology: a resource of potential biomarkers and drug targets. Cell Rep. 24, 2757–2772. [DOI] [PubMed] [Google Scholar]

[R274] Tomasi D, Wang G-J, Volkow ND, 2013. Energetic cost of brain functional connectivity. Proc. Natl. Acad. Sci. 110, 13642–13647. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R275] Toniolo RA, Silva M, Fernandes F, de BF, Amaral JA, de MS, Dias R, da S, Lafer B, 2018. A randomized, double-blind, placebo-controlled, proof-of-concept trial of creatine monohydrate as adjunctive treatment for bipolar depression. J. Neural Transm. 125, 247–257. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R276] Tran DH, Wang ZV, 2019. Glucose metabolism in cardiac hypertrophy and heart failure. J. Am. Heart Assoc. 8, e012673. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R277] Trinchese G, Cimmino F, Catapano A, Cavaliere G, Mollica MP, 2024. Mitochondria: the gatekeepers between metabolism and immunity. Front. Immunol. 15. 10.3389/fimmu.2024.1334006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R278] Tsakiris M, Critchley H, 2016. Interoception beyond homeostasis: affect, cognition and mental health. Philosophical Transactions of the Royal Society B: Biological Sciences. The Royal Society. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R279] Tsigos C, Kyrou I, Kassi E, Chrousos GP, 2020. tress: endocrine physiology and pathophysiology. Endotext [Internet]. [Google Scholar]

[R280] Turana Y, Tengkawan J, Chia YC, Shin J, Chen C-H, Park S, Tsoi K, Buranakitjaroen P, Soenarta AA, Siddique S, Cheng H-M, Tay JC, Teo BW, Wang T-D, Kario K, 2021. Mental health problems and hypertension in the elderly: review from the HOPE Asia network. J. Clin. Hypertens. 23, 504–512. 10.1111/jch.14121. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R281] Ugur B, Bao H, Stawarski M, Duraine LR, Zuo Z, Lin YQ, Neely GG, Macleod GT, Chapman ER, Bellen HJ, 2017. The krebs cycle enzyme isocitrate dehydrogenase 3A couples mitochondrial metabolism to synaptic transmission. Cell Rep 21, 3794–3806. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R282] Valença-Pereira F, Fang Q, Marié IJ, Giddings EL, Fortner KA, Yang R, Villarino AV, Huang YH, Frank DA, Wen H, 2021. IL-6 enhances CD4 cell motility by sustaining mitochondrial Ca2+ through the noncanonical STAT3 pathway. Proc. Natl. Acad. Sci. 118, e2103444118. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R283] van Oort J, Tendolkar I, Hermans EJ, Mulders PC, Beckmann CF, Schene AH, Fernández G, van Eijndhoven PF, 2017. How the brain connects in response to acute stress: a review at the human brain systems level. Neurosci. Biobehav. Rev. 83, 281–297. 10.1016/j.neubiorev.2017.10.015. [DOI] [PubMed] [Google Scholar]

[R284] van Winkel R, Stefanis NC, Myin-Germeys I, 2008. Psychosocial stress and psychosis. A review of the neurobiological mechanisms and the evidence for gene-stress interaction. Schizophr. Bull. 34, 1095–1105. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R285] Vanessa Fiorentino T, Prioletta A, Zuo P, Folli F, 2013. Hyperglycemia-induced oxidative stress and its role in diabetes mellitus related cardiovascular diseases. Curr. Pharm. Des. 19, 5695–5703. [DOI] [PubMed] [Google Scholar]

[R286] Velarde MC, 2014. Mitochondrial and sex steroid hormone crosstalk during aging. Longev. heal. 3, 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R287] Waddington CH, 1942. Canalization of development and the inheritance of acquired characters. Nature 150, 563–565. [DOI] [PubMed] [Google Scholar]

[R288] Wang H, Cheng Z, Xu Z, Wang M, Sun X, Liu W, Wang J, Yang Q, Zhang T, Song J, 2025. Systemic inflammatory factors and neuropsychiatric disorders: a bidirectional mendelian randomization study. Brain Behav. 15, e70478. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R289] Wang D, Day EA, Townsend LK, Djordjevic D, Jørgensen SB, Steinberg GR, 2021. GDF15: emerging biology and therapeutic applications for obesity and cardiometabolic disease. Nat. Rev. Endocrinol. 17, 592–607. 10.1038/s41574-021-00529-7. [DOI] [PubMed] [Google Scholar]

[R290] Wang M, Jin B, Jo J, 2025. Acute restraint stress induces Long-Lasting synaptic enhancement by inhibiting AMPK activation in AD model mice. CNS Neurosci. Ther. 31, e70335. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R291] Wang Q, Shelton RC, Dwivedi Y, 2018. Interaction between early-life stress and FKBP5 gene variants in major depressive disorder and post-traumatic stress disorder: a systematic review and meta-analysis. J. Affect Disord. 225, 422–428. 10.1016/j.jad.2017.08.066. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R292] Wang L, Xu Y, Jiang M, Wang M, Ji M, Xie X, Sheng H, 2025. Chronic stress induces depression-like behavior in rats through affecting brain mitochondrial function and inflammation. Psychoneuroendocrinology 172, 107261. [DOI] [PubMed] [Google Scholar]

[R293] Watts AL, Greene AL, Bonifay W, Fried EI, 2024. A critical evaluation of the p-factor literature. Nat. Rev. Psychol. 3, 108–122. [Google Scholar]

[R294] Weger M, Alpern D, Cherix A, Ghosal S, Grosse J, Russeil J, Gruetter R, de Kloet ER, Deplancke B, Sandi C, 2020. Mitochondrial gene signature in the prefrontal cortex for differential susceptibility to chronic stress. Sci. Rep. 10, 18308. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R295] Weinberg SE, Sena LA, Chandel NS, 2015. Mitochondria in the regulation of innate and adaptive immunity. Immunity 42, 406–417. 10.1016/j.immuni.2015.02.002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R296] Wende AR, Brahma MK, McGinnis GR, Young ME, 2017. Metabolic origins of heart failure. Basic Transl. Sci. 2, 297–310. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R297] Wiese M, Bannister AJ, 2020. Two genomes, one cell: Mitochondrial-nuclear coordination via epigenetic pathways. Mol. metab. 38, 100942. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R298] Wiley CD, Velarde MC, Lecot P, Liu SU, Sarnoski EA, Freund A, Shirakawa K, Lim HW, Davis SS, Ramanathan A, 2016. Mitochondrial dysfunction induces senescence with a distinct secretory phenotype. Cell Metab. 23, 303–314. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R299] Willard VW, Long A, Phipps S, 2016. Life stress versus traumatic stress: the impact of life events on psychological functioning in children with and without serious illness. Psychol. Trauma. Theory Res. Pract. Policy 8, 63. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R300] Wilson CB, Ebenezer PJ, McLaughlin LD, Francis J, 2014. Predator exposure/psychosocial stress animal model of post-traumatic stress disorder modulates neurotransmitters in the rat hippocampus and prefrontal cortex. PLoS One 9, e89104. 10.1371/journal.pone.0089104. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R301] Wilson CB, McLaughlin LD, Nair A, Ebenezer PJ, Dange R, Francis J, 2013. Inflammation and oxidative stress are elevated in the brain, blood, and adrenal glands during the progression of post-traumatic stress disorder in a predator exposure animal model. PLoS One 8, e76146. 10.1371/journal.pone.0076146. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R302] Wu E-L, Chien I-C, Lin C-H, Chou Y-J, Chou P, 2012. Increased risk of hypertension in patients with major depressive disorder: a population-based study. J. Psychosom. Res. 73, 169–174. [DOI] [PubMed] [Google Scholar]

[R303] Xie M, Bu Y, 2019. SKA2/FAM33A: a novel gene implicated in cell cycle, tumorigenesis, and psychiatric disorders. Genes Dis. 6, 25–30. 10.1016/j.gendis.2018.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R304] Xiong H, Guo R-J, Shi H-W, 2020. Altered default mode network and salience network functional connectivity in patients with generalized anxiety disorders: an ICA-based resting-state fMRI study. Evid. Based Complement. Altern. Med. 2020, 4048916. 10.1155/2020/4048916. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R305] Yang C, Silver B, Ellis SR, Mower GD, 2001. Bidirectional regulation of mitochondrial gene expression during developmental neuroplasticity of visual cortex. Biochem. Biophys. Res. Commun. 287, 1070–1074. [DOI] [PubMed] [Google Scholar]

[R306] Yehuda R, Flory JD, Bierer LM, Henn-Haase C, Lehrner A, Desarnaud F, Makotkine I, Daskalakis NP, Marmar CR, Meaney MJ, 2015. Lower methylation of glucocorticoid receptor gene promoter 1F in peripheral blood of veterans with posttraumatic stress disorder. Biol. Psychiatry 77, 356–364. 10.1016/j.biopsych.2014.02.006. [DOI] [PubMed] [Google Scholar]

[R307] Yehuda R, Golier JA, Halligan SL, Meaney M, Bierer LM, 2004. The ACTH response to dexamethasone in PTSD. Am. J. Psychiatry 161, 1397–1403. 10.1176/appi.ajp.161.8.1397. [DOI] [PubMed] [Google Scholar]

[R308] Young EA, Haskett RF, Murphy-Weinberg V, Watson SJ, Akil H, 1991. Loss of glucocorticoid fast feedback in depression. Arch. Gen. Psychiatry 48, 693–699. [DOI] [PubMed] [Google Scholar]

[R309] Yu Y, Akif A, Herman P, Cao M, Rothman DL, Carson RE, Agarwal D, Evans AC, Hyder F, 2023. A 3D Atlas of functional human brain energetic connectome based on neuropil distribution. Cereb. Cortex 33, 3996–4012. 10.1093/cercor/bhac322. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R310] Zakowski SG, 1995. The effects of stressor predictability on lymphocyte proliferation in humans. Psychol. Health 10, 409–425. 10.1080/08870449508401960. [DOI] [Google Scholar]

[R311] Zeev-Wolf M, Levy J, Goldstein A, Zagoory-Sharon O, Feldman R, 2019. Chronic early stress impairs default mode network connectivity in preadolescents and their mothers. Biol. Psychiatry Cognit. Neurosci. Neuroimaging 4, 72–80. 10.1016/j.bpsc.2018.09.009. [DOI] [PubMed] [Google Scholar]

[R312] Zhang X, Li C, 2024. Major depressive disorder increased the risk of hypertension: a mendelian randomization study. J. Affect. Disord. 355, 184–189. [DOI] [PubMed] [Google Scholar]

[R313] Zhang D, Raichle ME, 2010. Disease and the brain’s dark energy. Nat. Rev. Neurol. 6, 15–28. 10.1038/nrneurol.2009.198. [DOI] [PubMed] [Google Scholar]

[R314] Zhang G, Wang X, Rothermel BA, Lavandero S, Wang ZV, 2022. The integrated stress response in ischemic diseases. Cell Death Differ. 29, 750–757. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R315] Zheng Y, Garrett ME, Sun D, Clarke-Rubright EK, Haswell CC, Maihofer AX, Elman JA, Franz CE, Lyons MJ, Kremen WS, Peverill M, Sambrook K, McLaughlin KA, Davenport ND, Disner S, Sponheim SR, Andrew E, Korgaonkar M, Bryant R, Varkevisser T, Geuze E, Coleman J, Beckham JC, Kimbrel NA, Sullivan D, Miller M, Hayes J, Verfaellie M, Wolf E, Salat D, Spielberg JM, Milberg W, McGlinchey R, Dennis EL, Thompson PM, Medland S, Jahanshad N, Nievergelt CM, Ashley-Koch AE, Logue MW, Morey RA, 2021. Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume. Transl. Psychiatry 11, 1–10. 10.1038/s41398-021-01707-x. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R316] Zhu J, Thompson CB, 2019. Metabolic regulation of cell growth and proliferation. Nat. Rev. Mol. Cell Biol. 20, 436–450. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R317] Zong Y, Li H, Liao P, Chen L, Pan Y, Zheng Y, Zhang C, Liu D, Zheng M, Gao J, 2024. Mitochondrial dysfunction: mechanisms and advances in therapy. Sig. Transduct. Target Ther. 9, 1–29. 10.1038/s41392-024-01839-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R318] Zucchi FCR, Kirkland SW, Jadavji NM, van Waes LT, Klein A, Supina RD, Metz GA, 2009. Predictable stress versus unpredictable stress: a comparison in a rodent model of stroke. Behav. Brain Res. 205, 67–75. 10.1016/j.bbr.2009.06.030. [DOI] [PubMed] [Google Scholar]

PERMALINK

The allostatic triage model of psychopathology (ATP Model): How reallocation of brain energetic resources under stress elicits psychiatric symptoms

D Parker Kelley

S Parker Singleton

Katy Venable

Gabriel Sturm

Anna Skovgaard

Joseph Francis

Thomas C Neylan

Ellen R Bradley

Joshua Woolley

Martin Picard

Aoife O’Donovan

Abstract

1. Introduction

Fig. 1.

2. Section 2: Stress-induced energy scarcity drives psychopathology

3. Section 3: CNS allostatic regulation: the EPIC model and affect-driven prioritization

3.1. Active inference models of the allostatic-interoceptive system

3.2. Affective states regulate behavior according to metabolic efficiency: affect-driven prioritization

3.3. Stress dysregulates affect by precipitating an inefficient internal model

4. Section 4: The MIPS Bridges cellular and systemic allostasis

Table 1.

4.1. The MIPS regulates function and behavior across all levels of biological organization

4.2. The MIPS regulates the allostatic-interoceptive system

5. Section 5: EMAL: energetic tradeoffs drive disease

Table 2.

5.1. MAL drives systemic and CNS metabolic inefficiency

5.2. Metabolic inefficiency drives disease pathogenesis

6. Section 6: CNS allostatic triage: affect-driven prioritization of brain functional connectivity

Fig. 2.

6.1. Stress and psychopathology alter CNS functional connectivity

Fig. 3.

7. Section 7: Canalization of psychopathology: changes in CNS functional connectivity become entrenched through canonical mechanisms of neuroplasticity

8. Section 8: The allostatic triage model of psychopathology (ATP model)

Table 3.

8.1. Specific hypotheses, future directions, and remaining questions

Supplementary Material

Acknowledgements

Funding/Support

Abbreviations:

Appendix A. Supporting information

Footnotes

Data availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

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