Glycolytic metabolism: Food for immune cells, fuel for depression?

Abstract

Inflammation is one biological pathway thought to impact the brain to contribute to major depressive disorder (MDD) and is reliably associated with resistance to standard antidepressant treatments. While peripheral immune cells, particularly monocytes, have been associated with aspects of increased inflammation in MDD and symptom severity, significant gaps in knowledge exist regarding the mechanisms by which these cells are activated to contribute to behavioral symptoms in MDD. One concept that has gained recent appreciation is that metabolic rewiring to glycolysis in activated myeloid cells plays a crucial role in facilitating these cells’ pro-inflammatory functions, which may underlie myeloid contribution to systemic inflammation and its effects on the brain. Given emerging evidence from translational studies of depression that peripheral monocytes exhibit signs of glycolytic activation, better understanding the immunometabolic phenotypes of monocytes which are known to be elevated in MDD with high inflammation is a critical step toward comprehending and treating the impact of inflammation on the brain. This narrative review examines the extant literature on glycolytic metabolism of circulating monocytes in depression and discusses the functional implications of immunometabolic shifts at both cellular and systemic levels. Additionally, it proposes potential therapeutic applications of existing immunomodulators that target glycolysis and related metabolic pathways in order to reverse the impact of elevated inflammation on the brain and depressive symptoms.

1. Introduction

Inflammation is one biological pathway thought to impact the brain to contribute to major depressive disorder (MDD) and is reliably associated with resistance to standard antidepressant treatments (Strawbridge et al., 2015; Haroon et al., 2018a; Chamberlain et al., 2018). Indeed, a subgroup of MDD patients display increased inflammatory cytokines and other biomarkers of inflammation (e.g., C-reactive protein [CRP]) in association with risk factors like stress, trauma, metabolic and sleep disturbances, and aging (Osimo et al., 2019; Raison et al., 2013; Michopoulos et al., 2017; Felger, 2018; Passos et al., 2015). A rich literature has ascribed the impact of inflammation on neurotransmitter systems and neurocircuits that regulate behavioral changes in MDD to circulating inflammatory cytokines and the peripheral blood immune cells that produce them (Felger and Treadway, 2017; Felger et al., 2013a, 2013b, 2015; Yohn et al., 2016; Kitagami et al., 2003; Haroon et al., 2014, 2016, 2018b; Walker et al., 2013; Dantzer and Walker, 2014). While circulating immune cells, particularly monocytes, have been associated with varying aspects of increased inflammation in MDD and symptom severity (Lynall et al., 2019; Bekhbat et al., 2022a), significant gaps in knowledge exist regarding the intracellular mechanisms by which these cells are activated and communicate with the brain to drive behavioral symptoms in MDD.

One concept that has recently gained appreciation in psychoneuroimmunology is that during an immune response, cellular metabolic pathways are dynamically rewired to provide the energy and nutrients required by immune cells to transition into their diverse functional states (Bekhbat et al., 2021, 2022a, 2023; Dantzer et al., 2021; Lucido et al., 2021; Gamradt et al., 2021). Immune cells produce energy (adenosine triphosphate [ATP]) to maintain their cellular functions by breaking down glucose among other nutrients. Under homeostatic/quiescent conditions immune cells metabolize glucose through a two-step process involving glycolysis as a first step which converts glucose to pyruvate in the cytosol. In a second step, pyruvate is further oxidized in the mitochondria through the tricarboxylic acid (TCA) cycle to support oxidative phosphorylation (OXPHOS), a slower biochemical process that generates maximal ATP. However, when faced with pathogens or danger signals that provoke inflammation, immune cells rapidly undergo a metabolic reprogramming (Fig. 1). This response is classically thought to involve an upregulation of glycolysis and a concomitant suppression of mitochondrial OXPHOS, culminating in the diversion of pyruvate towards lactate - a phenomenon first described in tumor cells and cells under hypoxia (Viola et al., 2019). Aerobic glycolysis (that which occurs under normal oxygen conditions) is now understood to meet the functional and energetic demands of activated immune cells. Although a shift to glycolysis substantially cuts down the ATP yield per molecule of glucose, it supplies rapid energy that is pivotal for immediate immune cell activation (Ganeshan and Chawla, 2014). Glycolysis, along with adjacent metabolic pathways like glutaminolysis, also supplies necessary components for swift cellular proliferation or growth, including but not limited to amino acids, nucleotides, and lipids in proliferating cells such as activated T cells (Pearce and Pearce, 2013). As will be summarized in this review, the role of glycolysis extends to supporting the synthesis of host defense factors (Xie et al., 2016; Zhang et al., 2019; Dietl et al., 2010), augmenting phagocytic activity (Pavlou et al., 2017; Michl et al., 1976), as well as promoting cellular motility (Hara et al., 2017; Semba et al., 2016; Kaushik et al., 2019; Cramer et al., 2003) – a suite of functions indispensable for an effective immune response.

Fig. 1.

Monocyte activation is coupled to metabolic reprograming toward glycolysis which may promote pro-inflammatory functions to contribute to systemic inflammation. Monocytes rely on glucose for energy but metabolize it differently based on their activation status. Naïve monocytes primarily undergo oxidative phosphorylation (OXPHOS) to produce energy, whereas activated monocytes downregulate OXPHOS and shift to glycolysis for faster energy and metabolic intermediates necessary for pro-inflammatory functions such as cytokine production, proliferation, and adherence/migration. Glycolytically activated monocytes may therefore a be contributor to systemic inflammation and immune-to-brain communication, as well as a novel target for immunomodulation approaches in depression.

It is amply clear that the circulating inflammatory and metabolic disturbances commonly seen in MDD (Chae et al., 2023; Watson et al., 2021; Milaneschi et al., 2020) – in the form of both pathogen- and danger-associated molecular patterns (PAMPs and DAMPs) – can shift immune cells toward glycolytic metabolism, with the clearest evidence in peripheral myeloid cells. In addition to pro-inflammatory stimuli, certain metabolic stress markers, including ATP, insulin, oxidized lipoproteins, and cholesterol crystals, have been shown to induce glycolytic reprogramming in myeloid cells in association with pro-inflammatory processes (O'Rourke et al., 2022; Hu et al., 2020; Ratter et al., 2021; Di Gioia et al., 2020). This is not surprising given that the most important regulators of glycolysis, the phosphoinositide 3-kinase/protein kinase B (PI3K/Akt) signaling pathway and its downstream effector mechanistic target of rapamycin (mTOR), are sensitive to diverse stimuli including growth factors, insulin, glucose, and cytokines (Szwed et al., 2021). One mechanism through which the PI3K/Akt/mTOR axis promotes a feed-forward cycle of glycolysis and inflammation is the transcription factor hypoxia-inducible factor-1α (HIF-1α), which engages in extensive crosstalk with nuclear factor kappa (NFκB) (D'Ignazio et al., 2016) particularly in conditions of immune challenge or inflammatory stimulation, whereas additional pro-glycolytic factors may be involved in conditions of low-grade inflammation.

More than a mere consequence of immune activation, the shift towards myeloid glycolysis and related metabolic changes may in turn actively perpetuate systemic inflammation through increased cytokine and reactive oxygen species production, cell proliferation, and migration, thus contributing to the underlying mechanisms of depression. A better understanding of these intracellular mechanisms is required to develop more nuanced and specific immune-based strategies to reverse the impact of inflammation on the brain and behavior. Here I provide a narrative review of the available studies evaluating glycolytic metabolism of circulating immune cells in MDD with an emphasis on monocytes and discuss the functional role of immunometabolic shifts at cellular and systemic levels. Next, I present possible therapeutic applications of immunometabolic modulators in MDD and suggest future directions in cellular immunometabolic investigations in MDD.

2. Evidence of altered cellular immunometabolism in depression

2.1. Increased glycolysis as a biomarker of depression with high inflammation

A number of gene expression studies in whole blood and peripheral blood mononuclear cells (PBMCs) of depressed patients have highlighted increased glycolysis as a disease biomarker particularly in patients who have elevated inflammation (see Table 1). Blocking inflammation with infliximab has been shown to reduce depressive symptoms in patients with treatment resistant depression and high inflammation, with greatest improvements observed in anhedonia and psychomotor slowing (Raison et al., 2013). Interestingly, those who showed antidepressant response to infliximab had altered baseline expression of glycolysis-related genes, many of which were significantly regulated by infliximab over time compared to non-responders (Mehta et al., 2013). Glycolytic gene expression has also been associated with depressive symptoms that are reliably associated with and known to be induced by circulating inflammation. For example, the severity of psychomotor slowing in medically stable MDD outpatients was associated with gene clusters that were enriched for glycolysis along with inflammatory signaling pathways (e.g., interferon, interleukin [IL]-6) (Bekhbat et al., 2021). Moreover, our previous work has identified links between anhedonia severity in MDD and gene expression patterns related to altered glucose metabolism, such as insulin signaling and the pro-glycolytic HIF-1 pathway, but only among patients with high inflammation (CRP >3 mg/L per CDC/AHA definition of high risk (Pearson et al., 2003)) (Bekhbat et al., 2020). These results suggest that inflammation and altered glucose metabolism synergize at the level of circulating immune cells, thus creating a distinct ‘immunometabolic’ phenotype that promotes depressive symptoms. Interestingly, glycolytic gene expression in PBMCs was increased in MDD and bipolar depression patients during the depressive, but not remissive, state compared to healthy controls (Shibata et al., 2013). This suggests that increased glycolysis in circulating immune cells reflects and/or contributes to (see 3.2 below) fluctuations in systemic inflammation that have been shown to track with remission of depression (Hannestad et al., 2011; Liu et al., 2020).

Table 1.

List of glycolytic genes and proteins associated with depressive phenotypes in humans or chronic stress in rodents.

Publication	Associated phenotype	Immune cell type	Measured by:	Pathway ID (if applicable)	Pathway name (if applicable)	Glycolysis-related genes
Shibata et al., 2013	Upregulated in MDD vs control during depressive state	Whole blood	qPCR			HIF1A, HIF-1beta (ARNT), VEGF, GLUT1, PGK1, PFKFB3, LDHA
	Remained upregulated in MDD vs control during remissive state	Whole blood	qPCR			HIF1A, LDHA
	Upregulated in BPD vs control during depressive state	Whole blood	qPCR			HIF1A, HIF-1beta (ARNT), VEGF, PFKFB3
Mehta et al., 2013	Baseline predictors of antidepressant response to infliximab among treatment resistant MD patients	Whole blood	Microarray	MetaCore 930, WikiPathways WP534	Glycolysis and Gluconeogenesis	PGAM4, ENO2, ALDOA
Bekhbat et al., 2020	High vs low anhedonia among MD patients with high inflammation	Whole blood	Microarray	KEGG hsa04066	HIF-1 signaling	PFKFB3, EGLN1, STAT3, ENO2, MKNK1, PIK3CA, TLR4, PIK3CD, INS, IGF1R, ENO3, IFNGR2, EP300, AKT3, PDK1, MAPK1, ALDOB, HK3, HIF1A, MAP2K2, MKNK2, CAMK2G, CREBBP
Bekhbat et al., 2021	Psychomotor slowing among MD patients	Whole blood	Microarray	WikiPathways WP4629	Computational Model of Aerobic Glycolysis	PGK1, GAPDH, TPI1, ALDOA
				KEGG hsa00010	Glycolysis/Gluconeogenesis	PGK1, GAPDH, PGAM1, TPI1, ALDOA, PGAM4, DLD, PGM1, ALDH2
Bekhbat et al., 2022a	Upregulated in MD patients with high vs. low inflammation	CD14+ monocytes	scRNA-Seq	WikiPathways WP4629	Aerobic glycolysis	GAPDH, PKM
				WikiPathways WP3614	Photodynamic therapy-induced HIF-1 survival signaling	SLC2A3, PKM, BNIP3L
				KEGG hsa00010	Glycolysis/Gluconeogenesis	GAPDH, ALDH2, PKM
				KEGG hsa00030	Pentose phosphate pathway	TALDO1, TKT
Li et al., 2017	Upregulated in susceptible vs. resilient rats subjected to chronic unpredictable mild stress	PBMCs	Metabolomics	IPA	HIF-1 signaling	Pyruvic acid, Lactic acid
Barrett et al., 2021	Upregulated in chronic variable stress vs. non-stressed mice	Bone marrow monocytes	RNA-Seq			Hif1a, Hmox1, Fau, Pik3c2a, Pik3r5, Prkce, Eif3e, Eif3f
Lee et al., 2022	Upregulated in subordinate vs. dominant mice in social hierarchies	Spleen cells	RNA-Seq			Pcx, Fkbp4, Cxcr4, Pygb and 18 more genes
Bekhbat et al., 2023	Upregulated in repeated social defeat vs. non-stressed mice	Spleen macrophages	scRNA-Seq	WikiPathways WP157	Glycolysis and gluconeogenesis	Gapdh, Got1, Eno1, Hk3, Pgam1
				KEGG mmu00010	Glycolysis/Gluconeogenesis	Gapdh, Eno1, Eno1b, Akr1a1, Hk3, Aldh7a1, Pgam1
				KEGG mmu04066	HIF-1 signaling pathway	Gapdh, Rps6, Eno1, Eno1b, Elob, Rbx1, Hk3
		Spleen granulocytes	scRNA-Seq	WikiPathways WP157	Glycolysis and gluconeogenesis	Mpc2, Ldha, Gapdh, Mdh2, Pgk1, Mpc1
				KEGG mmu00010	Glycolysis/Gluconeogenesis	Adpgk, Ldha, Gapdh, Aldh3b1, Pgk1, Aldh2

Abbreviations: MDD, major depressive disorder; BPD, bipolar depression; MD, major depression (includes bipolar current episode depressed); qPCR, quantitative polymerase chain reaction; scRNA-Seq, single-cell RNA-Seq; KEGG, Kyoto Encyclopedia of Genes and Genomes; IPA, Ingenuity Pathway Analysis; CD14, cluster of differentiation 14; HIF-1, Hypoxia-Inducible Factor-1.

2.2. Monocytes are a main source of glycolysis in depression with high inflammation

Immune cells vary on the spectrum of glycolytic to mitochondrial metabolism, with neutrophils and monocytes displaying the highest level of glycolysis (Kramer et al., 2014). Even within T lymphocytes, which rely mainly on mitochondrial metabolism, immunometabolic programs differ in opposing directions between effector and memory subsets (Bantug et al., 2018). Therefore, variability in the composition of immune cell subsets within whole blood or PBMC admixtures could influence the overall immunometabolic profiles of these bulk samples (Brasanac et al., 2022). For example, lactate production (a byproduct and index of glycolysis) in PBMCs was associated with monocyte percentage within the sample, particularly after stimulation of the cells with various pathogens (Vrieling et al., 2022), suggesting that glycolysis production by PBMCs is either driven in large part by monocytes or reflects inflammation that causes monocytosis.

This is consistent with our earlier finding that immunometabolic whole blood gene pathways associated with anhedonia in MDD with high inflammation were driven by genes estimated to derive from circulating monocytes (Bekhbat et al., 2020). While much of the evidence pointing to monocytes as the source of increased glycolysis in bulk samples is computationally derived, using single-cell RNA-Seq we have reported direct evidence of increased glycolytic gene expression specifically in monocytes (but not other cell types) of MDD patients with higher inflammation (Bekhbat et al., 2022a). In this study, MDD patients with high plasma CRP (>3 mg/L) exhibited a profound enrichment of monocytes expressing CD14 and CD16 compared to patients with low CRP. Genes upregulated in monocytes of high CRP patients enriched inflammatory (phagocytosis, complement, chemotaxis) and immunometabolic pathways (aerobic glycolysis, HIF-1) (Bekhbat et al., 2022a). Moreover, in MDD patients with high inflammation who were administered an anti-inflammatory challenge with infliximab, changes in the number of CD14-expressing monocytes predicted improvements in anhedonia severity. Another study that examined bioenergetics of purified monocytes from MDD patients (without stratification by inflammation) reported trends toward reduced mitochondrial respiration metrics (including significantly lower coupling efficiency) compared to monocytes from non-depressed controls (Gamradt et al., 2021), suggesting that increased glycolysis in MDD monocyte samples may be accompanied by unchanged or lower mitochondrial metabolism. Taken together, these data implicate monocyte glycolytic metabolism as a biomarker of symptom severity in MDD, especially in patients with high inflammation.

It should be noted that while this review focuses on immunometabolism of monocytes as they are a key leukocyte source of systemic inflammation (Vanderbeke et al., 2021; Arango and Descoteaux, 2014) which may in turn impact the brain and behavior in MDD, studies using flow cytometry and scRNA-Seq have identified associations between both myeloid and lymphoid cells and varying aspects of increased inflammation in MDD (Lynall et al., 2019; Bekhbat et al., 2022a). Bioenergetic and gene expression assessments in T cells of MDD patients versus healthy controls have revealed prominent reductions in mitochondrial respiration as well as genes related to mitochondrial fatty acid oxidation (Gamradt et al., 2021). These findings are consistent with results from our MDD scRNA-Seq study, where CD4⁺ central memory T cells of patients with high inflammation exhibited downregulated genes of the OXPHOS pathway, a primary energy source in this cell type (Bekhbat et al., 2022a). Together, these results affirm a role for CD4⁺ T cell mitochondrial dysfunction in depression.

2.3. Myeloid cell glycolysis as a biomarker for susceptibility to stress

Chronic stress is a major risk factor for MDD and is linked to systemic inflammation and metabolic alterations like insulin resistance (Black, 2006). At the cellular level, glucocorticoids are recognized for their immediate anti-inflammatory actions (Bekhbat et al., 2017). However, chronic glucocorticoid exposure, typical of sustained stress, has been shown to prime peripheral myeloid cells toward a pro-inflammatory state that drives depressive- and anxiety-like behavior in animal models (Avitsur et al., 2001; Stark et al., 2001).

Recent investigations have uncovered that acute glucocorticoid administration in myeloid cells attenuates glycolysis while enhancing the TCA cycle's activity (Stifel et al., 2022). This mechanism contrasts with the chronic stress response, where prolonged psychosocial stress has been linked to increased glycolysis and changes in several of its upstream pathways, including HIF-1α and its regulators mTOR and PI3K. Specifically, monocytes from mice exposed to continuous variable stress exhibited upregulated gene expression within the PI3K-Akt, mTOR, and HIF-1α pathways, concomitant with a decline in OXPHOS and reduced chromatin accessibility at genomic sites associated with mitochondrial respiration (Barrett et al., 2021). Moreover, behavioral susceptibility to stress has been shown to be associated with increased glycolysis in peripheral immune cells (Lee et al., 2022; Li et al., 2017). Monocytes from chronic stress-exposed mice become primed, and reside in higher numbers in the spleen as an immunologic reservoir (McKim et al., 2018a). Interestingly, some chronic stress studies reported that myeloid cells in the spleen of chronic stress-exposed mice show increased expression of both glycolytic and OXPHOS pathway genes (Bekhbat et al., 2023; Lee et al., 2022), suggesting a hypermetabolic phenotype that may enable cellular proliferation of these cells (see 4.2 below).

Together, these findings indicate that immunometabolic changes within peripheral immune cells involving increased glycolysis may serve as both a biomarker and an underlying mechanism in depression, particularly depression involving high inflammation. Causal relationships between immune cell metabolism and behavioral outcomes, as well as the roles of specific immune cell subsets can be powerfully queried using mouse genetic models. Experiments involving depletion or adoptive transfer of peripheral immune cells have shown that monocytes (Wohleb et al., 2013) and T cells (Fan et al., 2019) play causal roles in the behavioral consequences of chronic stress. Fan et al. (2019) reported that chronic stress reduced OXPHOS and mitochondrial fusion in CD4⁺ T cells. By transferring CD4⁺ T cells lacking mitochondrial fusion proteins into lymphocyte-deficient mice, the authors were able to causally link CD4⁺ T cell mitochondrial metabolism to anxiety-like behavior. Myeloid-specific deletions of glycolytic enzymes such as Pkm2 and Ldha, have been shown to reduce inflammation in diverse settings (Xie et al., 2016; Dhanesha et al., 2022; Flick, 2022; Seth et al., 2017). Therefore, inducible genetic modifications that delete or overexpress glycolytic enzymes, combined with chronic stress models of depression such as the social defeat paradigm, can help elucidate the specific role of monocyte glycolysis in behavioral changes.

3. Glycolytic rewiring enhances inflammatory responses: relevance to MDD

3.1. Role of glycolysis in monocyte subsets and macrophage/microglia polarization

There is evidence that the three main subpopulations of human monocytes are characterized by divergent metabolic gene expression. Classical monocytes (CD14⁺⁺CD16⁻) were reported to have the highest expression of glycolytic genes, whereas nonclassical monocytes (CD14^dimCD16⁺) had highest OXPHOS gene expression, with the intermediate subset (CD14⁺CD16⁺) falling between these two phenotypes (Schmidl et al., 2014). Within classical or overall monocytes, factors such as aging (Saare et al., 2020; Wang et al., 2023) and elevated circulating inflammation and other soluble factors (Bekhbat et al., 2022a; Giacomello et al., 2023; Wolfe et al., 2019) may be further associated with greater glycolysis. While anti-inflammatory agents have been shown to reduce monocyte numbers, activation, and glycolysis (Cordes et al., 2020; Tucci et al., 2022; Lee et al., 2019), whether metabolic approaches can influence monocyte subsets and phenotypes is not as clear.

Macrophages, which differentiate from circulating monocytes upon their tissue entry, also exhibit distinct immunometabolic programs that not only vary between macrophage subtypes but in part determine their polarization into these subtypes (Wculek et al., 2022). Classically activated macrophages (induced by stimulation with interferon-gamma [INF-γ] and/or lipopolysaccharide [LPS], also referred to as M1-like) display increased glycolysis. Simultaneously, these macrophages display a “broken TCA cycle” where the TCA intermediates succinate and citrate build up and promote HIF-1α stabilization and the generation of cytokines, nitric oxide, and prostaglandins, thus perpetuating glycolysis and inflammatory responses further (Infantino et al., 2011; Tannahill et al., 2013). In contrast, alternatively activated macrophages (induced by IL-4, also known as M2-like) have an intact TCA cycle along with increased fatty acid oxidation (Mills and O'Neill, 2016). Similar immunometabolic programs govern the phenotype of other myeloid cells of interest in MDD, including adipose tissue macrophages (Kohlgruber et al., 2016) and microglia (Song et al., 2022). However, the impact of metabolism on the differentiation and function of perivascular macrophages has not been studied and would be of interest in depression (see 3.4 below).

3.2. Activation of the inflammasome and cytokine release

Glycolysis supports the activation of inflammasomes and the production of cytokines, key outcomes of myeloid cell stimulation through various mechanisms (Hughes and O'Neill, 2018). For example, in LPS-treated macrophages the rate-limiting glycolytic enzyme PKM2 forms a complex with Hif-1α, binding directly to the IL-1β promoter and enhancing its expression (Palsson-McDermott et al., 2015). Moreover, in a mouse model of sepsis, PKM2 has been shown to activate the NLRP3 (NOD-, LRR- and pyrin domain-containing protein 3) and AIM2 (absent in melanoma 2) inflammasomes, leading to caspase 1-dependent processing and release of IL-1β, IL-18, and high mobility group box 1 (HMGB1) (Xie et al., 2016). Pharmacologic or genetic inhibition of glycolytic enzymes, as well as the commonly used glycolysis inhibitor 2-deoxy-D-glucose (2-DG), a glucose analog that cannot be further metabolized, abrogate LPS-induced cytokine production (Xie et al., 2016; Zhang et al., 2019; Dietl et al., 2010). In addition, signals derived from glycolytic rewiring (such as the broken TCA intermediate succinate) support the production of cytokines, most notably IL-1β (Tannahill et al., 2013). Interestingly, in autoimmune conditions such as type 1 diabetes mellitus, monocyte glycolysis and cytokine production may become uncoupled (Vrieling et al., 2022; Thiem et al., 2020). Other examples of glycolysis enhancement of inflammation gone awry in disease include the role of glycolysis in enabling SARS-CoV-2 infection of monocytes and the subsequent cytokine storm (Codo et al., 2020) as well as promoting and sustaining HIV-1 viral persistence and reactivation of myeloid viral reservoirs (Real et al., 2022; Shytaj et al., 2021). Pilot data from MDD patients suggests that monocyte glycolytic state associates with circulating inflammation levels (measured by CRP) as well as anhedonia severity (Bekhbat et al., 2022b). Further investigation of the role of glycolysis in promoting systemic inflammation in MDD is currently underway.

3.3. Reactive oxygen species generation and cellular proliferation

Upon myeloid cell activation, along with a shift to glycolysis, concurrent changes occur to related metabolic pathways such as an upregulation of the pentose phosphate pathway, which supplies the reducing agent NADPH necessary for reactive oxygen species generation (O'Neill et al., 2016). In addition, other products resulting from glycolysis, glutaminolysis, and pentose phosphate pathway including amino acids, fatty acids, and nucleotides also provide biosynthetic material needed for rapid cellular proliferation (Ganeshan and Chawla, 2014).

3.4. Migration

Emerging studies have suggested a critical role for cellular metabolism in regulating immune cell motility and migration. By definition, monocytes are highly motile immune cells that traffic to regions of inflammation and damage. Migrating cells have glycolytic metabolism (Kathagen-Buhmann et al., 2016), which in turn increases monocytic markers that are associated with trafficking, including chemokine receptors and adhesion molecules (Schioppa et al., 2003). Glycolysis is also required for the cytoskeleton remodeling that enables migration (Guak and Krawczyk, 2020; Marelli-Berg and Jangani, 2018). Inhibition of glycolysis via blocking glycolytic enzymes or deficiency of HIF-1α reduces monocyte transmigration (Hara et al., 2017; Semba et al., 2016; Kaushik et al., 2019; Cramer et al., 2003). These studies suggest that glycolysis is necessary for migration.

The relevance of peripheral monocyte trafficking to the brain in depression and other behavioral changes associated with inflammation is supported by a wealth of pre-clinical and translational, as well as limited clinical data. Mechanistic studies in rodent models of social defeat stress demonstrate that Ly6C^hi monocytes expressing CCR2 (C-C chemokine receptor type 2) traffic to the parenchyma and perivascular spaces in the brain and lead to the production of inflammatory cytokines that are essential for the development of stress-induced behavioral changes (Wohleb et al., 2013, 2014; Sawicki et al., 2015; McKim et al., 2016, 2018b; Menard et al., 2017; Dudek et al., 2020; Dion-Albert et al., 2022). Increased number and in vitro blood-brain barrier (BBB) transmigration of monocytes, particularly those that express trafficking markers like CCR2, are associated with neurocognitive impairments in people with HIV (Veenhuis et al., 2021; Williams et al., 2014). Finally, increased perivascular monocytes/macrophages have been identified in postmortem brains of depressed patients who committed suicide (Torres-Platas et al., 2014). In light of these findings, whether monocyte glycolytic reprograming promotes immune-to-brain communication in association with behavioral symptoms is a topic that is being actively investigated (e.g., Bekhbat et al. (2023) and the ongoing NIMH-funded project 1K01MH136861-01 examining the role of monocyte metabolism and BBB transmigration in symptoms of anhedonia in people with HIV).

In addition to the above-mentioned investigations of the mechanistic role of myeloid glycolysis in MDD pathophysiology, several other questions warrant further examination as follows.

4. Outstanding questions and future directions

4.1. Relevance of glycolytic shift to energy availability and expenditure in the context of MDD

Inflammation is reliably associated with depressive symptoms characterized by reduced energy expenditure such as anhedonia, which involves decreases in effort-based motivation for reward (Treadway and Zald, 2011; Treadway et al., 2012), and psychomotor slowing (Carvalho et al., 2014; Goldsmith et al., 2016). Both symptoms (Bekhbat et al., 2020, 2021, 2022a, 2022b) and changes to relevant neural circuitry (Goldsmith et al., 2020) have been associated with markers of glycolysis, which generates a fraction of energy that can be produced from OXPHOS. Additionally, inflammation is also linked to fatigue, which involves a perceived lack of energy (Lacourt et al., 2018). Whether lower ATP production through glycolysis is a cause of low energy availability is currently unclear.

A more likely scenario is that increased glycolysis is an indicator and driver of inflammatory states associated with increased energy consumption and anabolic metabolism (Wang et al., 2019). For instance, during infection the innate immune response, which relies more heavily on increased glycolysis, drives most of the systemic metabolic demand, with the maximal adaptive immune response occurring once metabolic homeostasis has been re-established (Johnson et al., 2020). Additionally, patients with mitochondrial disorders who have OXPHOS defects and compensatory increases in glycolysis also display increased resting energy expenditure and fatigue (Sturm et al., 2023). At a systemic level, increased energy demand in the immune system, which is a compartment that is in large parts physically separated from the brain, is thought to be communicated to the brain through hypothalamic axes coordinating metabolic resources toward growth, reproduction, and maintenance programs (Wang et al., 2019). The resulting behavioral adaptations (i.e., sickness behaviors such as decreased nutrient uptake and hypersomnia) aim to increase energy-saving, catabolic metabolism (Wang et al., 2019) that then may serve to move cellular immunometabolism from immune resistance/defense (glycolysis) to tolerance/dormancy (e.g., OXPHOS) states. Whether myeloid glycolysis inhibition presents a viable target to reduce resting energy expenditure in MDD and mitigate symptoms of anhedonia and psychomotor slowing is an important question that should be addressed. Moreover, the extent to which increased energy consumption through peripheral immunometabolic shifts compromises the brain's energy demands needs further investigation. Similar to immune defense programs, energy-requiring CNS processes like synaptic growth, plasticity, and learning are supported in part by aerobic glycolysis (Diaz-Garcia et al., 2017; Shannon et al., 2016; Li et al., 2023). Emerging research from neurodegenerative diseases evaluating aerobic glycolysis in neurons as well as central and peripheral immune cells may shed more light on this topic (de Geus et al., 2023; Goyal et al., 2023; Schmidt et al., 2023).

4.2. Concurrent change to OXPHOS during glycolytic rewiring

Much of the existing literature on immunometabolic regulation of immune cell function has utilized LPS, which signals through a toll-like receptor 4 (TLR4) cascade. It is well known that LPS-activated myeloid cells undergo increased glycolysis along with reduced OXPHOS, similar to the classic Warburg effect. However, emerging reports suggest that non-LPS pathogens (particularly those not signaling through TLR4) increase both glycolysis and OXPHOS (Lachmandas et al., 2016; Keating et al., 2016; Kumar et al., 2019; Janzic et al., 2023; Boutens et al., 2018; Hong et al., 2022). This concurrent upregulation of OXPHOS is thought to facilitate the survival, proliferation, and effector functions of immune cells such as cytokine production and phagocytosis. Interestingly, metabolic DAMPs appear to simultaneously augment glycolysis and OXPHOS (Hu et al., 2020; Ratter et al., 2021; Di Gioia et al., 2020), resembling the hypermetabolic and hyper-inflammatory phenotype induced by non-LPS pathogens. In contrast, a metabolic deficit induced by fasting can shift bone marrow myeloid cells from a hypermetabolic state to a more quiescent metabolic profile characterized by decreased glycolysis and OXPHOS, leading to a reduction in their release from the bone marrow into the bloodstream (Jordan et al., 2019).

In the case of proliferating cells, which are known to exhibit a hypermetabolic phenotype, concurrent increase in aerobic glycolysis has been shown to result from glycolysis outpacing mitochondrial NADH shuttles (Wang et al., 2022) whereas increase in mitochondrial OXPHOS was shown to be mediated by mitochondrial fusion (Yao et al., 2019). It has been suggested that psychosocial stress-induced proliferation and differentiation of myeloid reservoirs within the spleen may rely on increased glycolysis, along with increased OXPHOS (Bekhbat et al., 2023; Lee et al., 2022). Future studies on the role of OXPHOS in myeloid cell activation and function will contribute to identification of more specific immunomodulatory approaches in MDD.

5. Repurposing immunometabolic modulators as therapies for MDD

Given that elevated inflammation promotes resistance to standard antidepressant therapies, interest in immunomodulatory treatment of psychiatric illnesses with increased inflammation is high. Unlike non-specific anti-inflammatory agents (Eyre et al., 2015; Rosenblat and McIntyre, 2018; Husain et al., 2020), anti-cytokine therapies have shown efficacy for specific depressive symptoms (notably anhedonia) when targeted to patients with increased inflammation (Raison et al., 2013; Salvadore et al., 2018; Lee et al., 2020). However, anti-cytokine therapies have substantial safety risks and limited use as antidepressants (Dreyer et al., 2016; Miller et al., 2017). Monocyte glycolysis and related immunometabolic reprograming needed to sustain cellular activation may serve as alternative targets for reducing inflammation and its effects on the brain and behavior.

Glycolysis and related pathways such as mTOR and nuclear factor-erythroid factor 2-related factor 2 (Nrf2) can be uniquely targeted by FDA-approved therapies for autoimmune, inflammatory, and metabolic disorders as well as experimental drugs in development (see Table 2) (Palsson-McDermott and O'Neill, 2020). Dimethyl Fumarate (DMF), a treatment for relapsing remitting multiple sclerosis, inhibits pro-glycolytic shifts and inflammatory cytokine production in humans and mice, both in vivo and in vitro (Kornberg et al., 2018). Crucially, DMF only targets immune cells relying on aerobic glycolysis (e.g., activated macrophages, Th1 and Th17 cells), while sparing resting macrophages or regulatory T cells. Rapamycin, an inhibitor of mTORC1 signaling and glycolysis (Lee et al., 2019), has been shown to enhance the antidepressant effect of ketamine, the response to which has been predicted by increased inflammatory markers (Abdallah et al., 2020; Yang et al., 2015). Itaconate is a promising approach to target metabolic pathways specifically in activated myeloid cells (O'Neill and Artyomov, 2019; Peace and O'Neill, 2022). An endogenous anti-inflammatory molecule derived from the TCA cycle, itaconate has been shown to reverse glycolysis-related oxidative stress, and prevent LPS-induced depressive-like behavior in mice (Dantzer, 2021). Finally, 2-DG, a potent glycolysis inhibitor, is well tolerated at low doses in phase I trials, with some showing favorable early clinical outcomes in cancer (Raez et al., 2013; Stein et al., 2010). To take advantage of these therapeutic opportunities in psychiatry, a more nuanced understanding of the cellular metabolic processes that enable immune cell/monocyte activation is required.

Table 2.

Immunometabolic modulators with potential applicability to MDD.

Drug	Molecular target	Clinical indication	Effect on cellular metabolism & function, or behavior; Advantages	Brain penetrance
Dimethyl Fumarate	Nrf2	Multiple sclerosis, psoriasis	•Specifically targets glycolytically active immune cells •Limits leukocyte entry to the brain	Derivative (MMF)-yes
Rapamycin	Inhibition of mTORC1	Prevention of organ rejection, cancer	•Reduces monocyte glycolysis and adhesion •Prolongs ketamine's antidepressant effects	Low
2-DG	Hexokinase	N/A. Pre-clinical applications	•Potent inhibitor of glycolysis •Reduces monocyte transmigration, adhesion •Some clinical evidence of safety & efficacy	Yes
Itaconate	Succinate dehydrogenase, Nrf2	N/A. Pre-clinical applications	•Specifically targets activated macrophages/monocytes •Endogenous, low toxicity	Derivatives-likely

Abbreviations: Nrf2, Nuclear factor erythroid 2-related factor 2; mTORC1, mechanistic target of rapamycin complex 1; 2-DG, 2-deoxy-D-glucose; MMF, monomethyl fumarate (active metabolite of dimethyl fumarate).

It's currently unclear whether immunometabolic therapies need to target the brain, the immune system, or both to improve behavior. Most drugs in Table 2 or their derivates cross the BBB, albeit to varying degrees. For instance, 2-DG, a glucose analog, readily crosses the BBB (Hasselbalch et al., 1996). DMF quickly metabolizes into its active ingredient monomethyl fumarate (MMF), which crosses the BBB to provide neuroprotection (Edwards et al., 2021). Although itaconate itself likely doesn't penetrate the brain, its derivatives, such as dimethyl itaconate and 4-octyl itaconate, reduce neuroinflammation and improve outcomes in various CNS disease models (Liu et al., 2023). Rapamycin, thought to have low brain penetrance (Brandt et al., 2018), was nevertheless detectable in the brain tumor tissue of patients on oral rapamycin (Cloughesy et al., 2008). As CNS diseases often involve extensive BBB breaches, it's unclear if these molecules can cross the BBB in non-pathological conditions.

On the other hand, all molecules in Table 2 have been shown to alter peripheral inflammation by modulating glycolytic or related metabolic processes in immune cells, as described above. Importantly, inhibition of peripheral blood cytokines using anti-cytokine treatments that do not cross the BBB nonetheless blocks depressive-like behavior in rodents (Bayramgurler et al., 2013; O'Connor et al., 2009), while also reducing depressive symptoms in patients with autoimmune and inflammatory disorders as well as otherwise medically-healthy MD patients with increased inflammation (Raison et al., 2013; Salvadore et al., 2018; Kappelmann et al., 2018; McIntyre et al., 2019). Therefore, it is possible that immunometabolic therapies need only target the immune system to revert inflammation-related changes to the brain and behavior.

6. Conclusions

Given that peripheral monocytes show evidence of glycolytic activation in depression and relevant pre-clinical models, determining the immunometabolic phenotypes of monocytes known to be elevated in MDD with high inflammation is a critical next step to better understanding and treating the effects of inflammation on the brain. These investigations will be greatly aided by the novel application of existing immunomodulatory approaches to depression, which in turn can serve as a foundation for developing new therapies that target the immune system to treat depressive symptoms such as anhedonia and psychomotor slowing.

CRediT authorship contribution statement

Mandakh Bekhbat: Writing – review & editing, Writing – original draft, Visualization, Conceptualization.

Declaration of competing interest

None.

Biography

Dr. Mandakh Bekhbat is an Assistant Professor in the Department of Psychiatry and Behavioral Sciences at Emory School of Medicine. Her research combines translational and clinical approaches to understand the neuroimmune and endocrine basis of psychiatric illnesses and identify mechanisms for developing novel treatments. Dr. Bekhbat's work in depressed patients examines metabolic shifts within circulating immune cells that influence their inflammatory phenotypes. These cellular immunometabolic shifts are hypothesized to contribute to systemic inflammation and its effects on the brain and behavior, particularly symptoms of anhedonia. Most recently, she has extended this work to examine immune cell metabolic pathways that contribute to the impact of inflammation on the brain and depressive symptoms in patients with HIV, work that was supported by a KL2 award from the Georgia Clinical and Translational Science Alliance and expanded under a K01 award from the National Institute of Mental Health. Mandy obtained her undergraduate education at Vassar College in 2013, and began her career in psychoneuroimmunology research through her PhD training in the laboratory of Dr. Gretchen Neigh at Emory University and Virginia Commonwealth University as well as postdoctoral training under the mentorship of Dr. Jennifer Felger at Emory University. She was recently appointed to faculty in the Department of Psychiatry and Behavioral Sciences at Emory and the Emory Behavioral Immunology Program led by Dr. Andrew Miller. Mandy is looking forward to establishing a research program spanning basic, translational, and clinical settings that is focused on designing novel immunometabolic treatment strategies for depression and other psychiatric disorders associated with increased inflammation.

Data availability

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