Abstract
Recent discoveries have highlighted the significance of inter-organ communication (IOC) in maintaining metabolic homeostasis and counteracting aging. In this review, we delve into IOCs mediated by hormonal signaling, circulating metabolites, cytokines, miRNAs, organelle signaling, and neuronal networks and examine their roles in regulating metabolism and aging. We further discuss recent findings identifying the hypothalamus as a high-order control center for aging and longevity. Dysregulation of distinct IOCs is linked to metabolic derangements and age-related pathologies, implicating IOC as a potential target for therapeutic intervention to promote healthy aging. We particularly emphasize the importance of IOCs between the hypothalamus and peripheral organs and pave the way for a better understanding of this critical machinery in metabolism and aging.
Keywords: Inter-organ communication, metabolism, aging, hypothalamus
Inter-organ communication (IOC) provides new insights into metabolism and aging
A comprehensive understanding of metabolic processes has long been considered foundational in uncovering the mechanisms of aging. Over the past 30 years, several evolutionarily conserved signaling pathways and factors have been identified as key to connecting metabolism to aging and longevity control, including insulin/insulin-like growth factor 1 (IGF-1) signaling [1,2], mechanistic target of rapamycin (mTOR) signaling [3,4], and the sirtuin family of nicotinamide adenine dinucleotide (NAD+)-dependent protein deacetylases/deacylases [5,6]. Whereas we still have not gained a fully articulated picture of how exactly aging and lifespan are regulated, cutting-edge genetic engineering and extensive omics analysis, rather than simply focusing on individual signals or organs, now enable us to examine how organs crosstalk with each other, how age-related changes in one organ affect others, and which organs need to be targeted to counteract aging. Over the past decade, the concept of inter-organ communication (IOC) has been recognized increasingly as a critical component in maintaining robust metabolic networks and healthy lifespan [7,8].
Over time, the delicate balance of IOC is disrupted, leading to the deterioration of physiological homeostasis at both the tissue and organismal levels [9,10]. Indeed, recent studies have revealed that IOC dysfunction underlies age-associated physiological decline, inducing various age-associated metabolic derangements and limiting healthspan and lifespan [11–15]. Therefore, understanding how IOC shifts and collapses over time will shed new light on the mechanisms underlying age-related metabolic changes and organ dysfunction. Interestingly, “Inter-organ Communication in Aging” was highlighted as a new area of research in the September 2022 gathering of the National Advisory Council on Aging (NACA) (https://www.nia.nih.gov/approved-concepts#Interorgan). Furthermore, this concept has received funding since May 2024 through Cooperative Agreement Awards (U01) granted by the National Institute on Aging (NIA). These efforts emphasize the increasingly appreciated significance of IOC in deciphering the mechanisms of aging and longevity control.
In this review article, we discuss how IOC regulates metabolism and aging via hormonal signaling, circulating metabolites, cytokines, miRNA, organelle signaling, and neuronal networks. Additionally, we delve into how the hypothalamus, as a high-order control center of aging, regulates metabolism and aging via IOC. These recent developments have set the stage for a new research direction focusing on these fascinating IOCs.
Circulating hormones from adipose tissue, skeletal muscle, and bone
Over the past few decades, there have been extensive researches on classical hormonal regulation in various endocrine organs, such as the pituitary gland, adrenal glands, pancreas, thyroid gland, testes, and ovaries [16]. Recent studies have suggested that the majority of organs and tissues can be reclassified as endocrine organs, as they communicate with one another through a diverse array of molecular signals [17–20]. A recent review article nicely summarized major circulatory proteins and their axis of secretion [21]. Even organs traditionally categorized as “non-endocrine organs” send humoral signals to others, such as adipose tissue, skeletal muscle, and bone.
Adipose tissue
Since the discovery of leptin and adiponectin as adipokines (see Glossary), many other factors secreted from adipose tissue have been identified and implicated in the control of systemic metabolism [22]. For example, transforming growth factor-β2 (TGF-β2) is secreted from adipose tissue in response to exercise and improves glucose tolerance in mice [23]. Among those newly identified adipokines, the extracellular version of nicotinamide phosphoribosyltransferase (eNAMPT) plays a unique and essential role in the regulation of aging and longevity. The majority of eNAMPT secreted from adipose tissue into plasma is encapsulated into extracellular vesicles (EVs) and remotely enhances NAD+ biosynthesis in the hypothalamus, hippocampus, nucleus accumbens, pancreas, and retina and counteracts aging [24–27]. Recently, it has been demonstrated that stimulation of eNAMPT secretion from white adipose tissue (WAT) by activating a specific neuronal subpopulation in the dorsomedial hypothalamus (DMH) significantly delays aging and extends lifespan in mice [11]. We further discuss the importance of EVs and this newly identified neuronal population in later sections. Brown adipose tissue (BAT) can also secrete numerous humoral factors, called batokines, which exert endocrine actions, in addition to autocrine and paracrine actions. However, to date, no study has identified a batokine specific to BAT. Therefore, batokines are classified as factors that are preferentially secreted by BAT compared to WAT and, in some cases, compared to other tissues or organs [28,29].
Skeletal muscle
In addition to directly consuming excess energy, muscle contraction also influences metabolism. Although the molecular mechanisms underlying the effects of exercise on metabolism remain an area of intensive investigation, muscle-secreted factors, known as myokines, have been identified and studied extensively. Interleukin 6 (IL-6) and myostatin are well-studied myokines that regulate skeletal muscle growth through autocrine and paracrine mechanisms. IL-6 from skeletal muscle regulates glucose disposal, lipolysis, oxidative metabolism, and energy expenditure in multiple tissues. Myostatin is involved in the regulation of insulin sensitivity, glucose utilization, and bone formation [30]. Other myokines, including FGF21 [31] and irisin [32], stimulate white adipocytes to induce uncoupling protein 1 (UCP1) expression, thus contributing to WAT browning and promoting thermogenesis. Moreover, irisin and a newly identified myokine, cathepsin B, have been shown to stimulate neurogenesis and exert neuroprotective effects in the hippocampus via induction of brain-derived neurotrophic factor (BDNF) [33,34]. More myokines that affect vascularization [35], bone formation [36], and cardioprotection [37,38] have been characterized. These beneficial effects of myokines may provide a reasonable explanation for the effects of exercise on the whole-body metabolism.
Bone
Bone has traditionally been viewed for its structural role in the human body. Recent research has further shed light on the multifaceted role of bone, including its new, important role as a complex endocrine organ that regulates whole-body metabolism [19]. Osteocalcin is one of the most critical factors produced in bone tissues. Circulating osteocalcin increases insulin secretion and sensitivity [39], lowers blood glucose levels [40], and decreases visceral adipose tissue [41]. While bone marrow mesenchymal stem cells (BMSCs) play a critical role in regulating hematopoiesis within the bone marrow microenvironment, they also have the ability to secrete active molecules that can impact energy metabolism throughout the body [19]. Specifically, a BMSC-derived exosomal microRNA, miR-29b-3p modulates age-related insulin resistance through SIRT1 signaling [42].
Other humoral factors for IOCs
Many studies have highlighted EVs as an essential mediator of intercellular and inter-organ communication that plays a crucial role in various physiological processes, primarily through the encapsulation of proteins, nucleic acids, and other signaling molecules. Recently, the effect of purified plasma EVs on mouse lifespan has been reproduced [12]. Skeletal muscle-secreted EVs, which are induced by exercise, remodel metabolism towards beneficial cardiovascular outcomes [43]. Furthermore, a growing body of evidence suggests that EVs also play a role in mitigating many detrimental consequences associated with aging, including cellular senescence, metabolic dysfunction, cardiovascular disease, cancer, and neurodegeneration [44] (Figure 1). At this moment, it remains unclear what humoral factors, metabolites, miRNAs are encapsulated into EVs and what kinds of EVs contribute to the regulation of metabolism and aging. To understand those details, further investigation will be required. Therefore, in this section, we will discuss metabolites and cytokines that can function without being encapsulated into EVs, and then focus on senescence-associated secretory phenotype (SASP). Additionally, newly identified miRNA-mediated and organelle signaling will be discussed.
Figure 1. Humoral components for inter-organ communication (IOC) in metabolism and aging.

The five humoral components for IOCs in metabolism and aging, discussed in this review, are hormones, cytokines, microRNAs (miRNAs), metabolites, and organelle (mitochondrial) signaling. The extracellular vesicles (EVs) deliver some of those humoral factors to mediate IOCs, as indicated by dotted arrows. Early in life, these factors serve as beneficial signaling molecules and promote organ health. As an organism ages, those beneficial factors decrease, and inflammatory cytokines, such as the ones from the senescence-associated secretory phenotype (SASP), increase throughout the body. The green box indicates changes in those beneficial factors known to counteract aging and extend lifespan in model organisms. The purple box shows genetic manipulations or treatments that accelerate aging and shorten lifespan in model organisms. Abbreviation: MUFAs, mono-unsaturated fatty acids. PF4, platelet factor 4. upd3, cytokine unpaired 3. IL-6, interleukin 6. eNAMPT, extracellular nicotinamide phosphoribosyltransferase. This figure was created using BioRender (www.biorender.com).
Metabolites
Circulating metabolites play a pivotal role in representing the metabolic status of various tissues and organs [45,46]. Dysregulated metabolite profiles have been implicated in age-related metabolic disorders, reflecting metabolic flux and cellular homeostasis perturbations [47–49]. Furthermore, restriction or supplementation of different metabolites can change the activity of these metabolic pathways in ways that improve healthspan and extend lifespan in various organisms [50]. For example, supplementation of alpha-ketoglutarate (α-KG), a key metabolite in the tricarboxylic acid (TCA) cycle, can extend lifespan, compress morbidity, and decrease the levels of systemic inflammatory cytokines in aged mice [51]. In recent years, lipid metabolites, also known as lipokines, have been recognized as crucial signaling molecules that actively contribute to various metabolic processes. By genetic manipulation, the accumulation of mono-unsaturated fatty acids (MUFAs) extends lifespan in worms, and dietary MUFAs are sufficient to extend their lifespan [52]. In contrast, signature metabolic reprogramming that occurs during aging can predict the onset of age-related diseases and lifespan before symptoms become evident. Metabolic reprogramming during aging causes reductions in overall fitness, an increase in susceptibility to age-related dysfunctions, a decrease in stress response capacity, and an increase in frailty. In a recent study, untargeted metabolomic profiling of plasma metabolites from healthy individuals, comprising twin pairs aged 6 months to 82 years, identified 52 metabolites predictive of age [53]. Another interesting study showed that centenarians have a distinct gut microbiome enriched in microorganisms that can synthesize unique secondary bile acids, including various isoforms of lithocholic acid [54]. These emerging data demonstrate that understanding the role of circulating metabolites in mediating IOC provides valuable insights into the pathogenesis of metabolic dysfunction during aging and offers potential targets for therapeutic intervention (Figure 1).
Cytokines
A recent study revealed that, like mammalian interleukins and leptin, Drosophila cytokine unpaired 1 (upd1) regulates intestinal metabolism, spermatogenesis, and food intake through bidirectional testis-midgut interactions under physiological conditions [55]. Another study revealed that systemic administration of exogenous platelet-derived chemokine platelet factor 4 (PF4), also known as CXCL4, attenuates age-related neuroinflammation in the hippocampus, induces molecular changes in synaptic plasticity, and improves cognitive function in aged mice [56]. In contrast, alterations in cytokine levels can also contribute to physiological deterioration or accelerate metabolic dysfunction and aging. For example, acute pancreatitis often leads to multiorgan damage, especially in the lungs and intestines, mainly due to a cytokine-mediated inflammatory response [57]. Additionally, the “cytokine storm” induced by COVID-19 is characterized by excessive production of pro-inflammatory cytokines in the blood, which leads to acute respiratory dysfunction and, eventually, widespread tissue damage, multi-organ failure, and death [58]. A recent study also revealed that the age-dependent induction of cytokine unpaired 3 (upd3), a homolog of mammalian IL-6, in Drosophila oenocytes (hepatocyte-like cells) is the primary mechanism causing cardiac aging [59]. Chronic inflammation mediated by pro-inflammatory cytokines constitutes a critical component of age-associated pathophysiologies called inflammaging, which largely share the same molecular mechanisms with metabolic inflammation [60].
Senescence-associated secretory phenotype (SASP)
The SASP has been suggested to contribute to inflammaging. Selective elimination of senescent cells (senolytics) or blocking of the SASP (senostatics or senomorphics) have been extensively studied as potential pharmaceutical interventions for age-related diseases [61]. A recent study demonstrated that Luteolin, a polyphenolic extract from Salvia haenkei, shows anti-senescence effects. Daily oral administration of this extract extends the lifespan and healthspan of naturally aged mice [62]. However, studies have also revealed the role of senescent cells in non-harmful physiological processes [63]. Indeed, the elimination of senescent cells that express high levels of p16 disrupts blood-tissue barriers, with subsequent liver and perivascular tissue fibrosis and health deterioration [64], underscoring the critical role of these cells in maintaining homeostasis and physiology. Additionally, the newly developed senescent-cell separation technique demonstrated that senescence is a more complex array of states than previously anticipated [65]. Suppressing the SASP without eliminating senescent cells is a viable therapeutic alternative to address senescence-related metabolic phenotypes and aging. Senostatics or senomorphics can alleviate the SASP of senescent cells directly or indirectly by suppressing multiple pathways, including NF-κB, JAK-STAT signaling, and mTOR, which are involved in the activation and maintenance of SASP [66]. Developing age-related therapies that focus on eliminating senescent cells is a promising approach, although it is expected to be more intricate than initially envisioned.
microRNAs (miRNAs)
Among various components in EVs, miRNAs have been the most extensively studied. miRNAs, classified as noncoding RNAs (ncRNAs), may alter IOC through their critical role in epigenetic reprogramming, a putative hallmark of aging, via post-transcriptional gene silencing [9,67] (Figure 1). Adipose tissue-derived EVs and their cargo miRNAs can be transferred to the brain in a membrane protein-dependent manner, preventing cognitive impairment in obese mice with insulin resistance [68]. Worm miRNAs undergo age-dependent inter-tissue trafficking mediated by EVs, while miRNAs are controlled in a tissue-specific manner to modulate gene expression during aging [69]. A recent study provided a map of the organism-wide expression of ncRNAs with aging in mice. This study identified a set of broadly dysregulated miRNAs that may function as systemic regulators of aging via plasma factors, such as EVs [70]. Interestingly, miRNAs produced and released by hypothalamic stem cells contribute to the speed of aging [71], and miRNAs encapsulated within young EVs ameliorate age-related dysfunction by stimulating PGC-1α expression and enhancing mitochondrial energy metabolism [12]. Given their tightly regulated secretion, signaling properties, and significance in physiological processes and pathological conditions, a novel nomenclature ‘RNAkine’ has been proposed to designate extracellular noncoding RNA, including miRNA, circRNAs, and lncRNAs [72], elegantly conceptualizing the role of extracellular ncRNAs in IOCs.
Organelle signaling
Another exciting and novel biological observation is that cellular organelles send signals between tissues. Recent studies have uncovered mechanisms by which mitochondrial stress in one tissue can affect remote tissues, ultimately promoting organismal health [73,74]. In Caenorhabditis elegans (C. elegans), mitochondria incur age-related damage from reactive oxygen species, harmful metabolic byproducts, and other factors. The mitochondrial stress occurs in neuronal cells, and it triggers the intestinal mitochondrial unfolded protein response (UPRMT), which restores proper protein folding and removes damaged proteins. Interestingly, germline mitochondria integrate inter-tissue mitochondrial stress signaling via neurons and modulate lipid metabolism to activate UPRMT in the periphery, promoting organismal health and lifespan [73]. The specific molecule that may originate in neuronal mitochondria and act as a messenger for non-autonomous UPRMT signaling needs to be identified. However, these data suggest that examining the regulatory mechanisms that underlie lifespan extension in cell-nonautonomous germline-to-intestine processes could provide important insight into how IOC is regulated during aging (Figure 1). Additionally, large EVs, such as microvesicles, apoptotic bodies, migrasomes, and exophers, can be loaded with intact functional or damaged mitochondria, providing a new way of mitochondrial transport for IOCs [75]. In the near future, a newly developed biochemical secretome profiling methodology will enable the direct labeling and identification of secreted proteins in various model organisms at a cell type-specific resolution and provide opportunities to discover novel IOC molecules and associated mechanisms (Box 1).
Box 1: Tools for Dissecting IOC.
A biotin-labeling technique for identifying potential inter-organ signals has been recently developed. Enzyme-catalyzed proximity labeling with BioID and TurboID, which are engineered biotinylation enzymes, is an effective method for investigating IOC. Recent studies have shed light on the molecular identity and cellular source of circulating factors, while elucidating the dynamic regulation of intercellular communication and IOC through TurboID [99–101]. Cell type-specific labeling can be accomplished by restricting the expression of TurboID to specific cells expressing Cre recombinase. Subsequently, biotinylated and secreted plasma proteins can be purified directly from blood plasma using streptavidin beads and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) [102]. The dynamic regulation of intercellular and inter-organ crosstalk by physical activity has also been illuminated by mapping an organism-wide 21-cell-type, 10-tissue secretome in mice using an adeno-associated virus expressing a cre-inducible, endoplasmic reticulum-restricted TurboID [103]. However, viral-mediated approaches for the systemic temporal and spatial analysis of mammalian secretomes in vivo have limitations. The BirA*G3 mouse strain enables Cre-dependent promiscuous biotinylation of protein trafficking through the endoplasmic reticulum [104]. BirA*G3 is a precursor of TurboID generated in the directed evolution of E. coli BirA, which has a higher affinity for biotin and can catalyze biotinylation before adding exogenous biotin [99]. The BirA*G3 mouse model exhibited improved labeling efficiency and tissue-specific expression compared with viral transduction methods. Although not all proteins in the blood are critical for IOC, this method will contribute to a more comprehensive understanding of the interplay between secreted proteins involved in metabolism and aging.
Integration of IOCs through the hypothalamus as a high-order control center for metabolism and aging
Somatosensory input regulates metabolism through the hypothalamus
In addition to humoral factors that control metabolism and aging, neuronal networks are another essential facet of IOCs. Neuronal networks enable bidirectional communication between the peripheral organs and the brain, especially the hypothalamus (Figure 2), which coordinates various neural responses to maintain metabolic homeostasis. It receives and integrates information through hormones and cytokines secreted from peripheral organs and sends neuronal signals back to those organs. Indeed, recent studies have demonstrated that the hypothalamus receives somatosensory input from peripheral organs to fine-tune metabolic homeostasis [76,77]. Somatosensory neurons in the dorsal root ganglia (DRG) and vagal sensory neurons in the jugular and nodose ganglia innervate organs and detect changes in their microenvironments. Information is then relayed to the brain, forming an ascending pathway. Peripheral signals transmitted via vagal afferents regulate behavior and energy homeostasis [78,79]. Interestingly, a specific group of neurons belonging to the DRG, typically associated with transmitting pain, touch, and proprioceptive sensations, has been shown to regulate metabolically active organs, such as bone and WAT. The ablation of somatosensory neurons that project to WAT alters its function, leading to changes in body weight and glucose homeostasis [80].
Figure 2. Neuronal and humoral integration of inter-organ communications (IOCs) in metabolism and aging.

Both secreted humoral factors and the nerve signals passing through the spinal cord convey the metabolic status from peripheral organs to the brain, especially to the hypothalamus, which integrates IOCs to regulate whole-body metabolic homeostasis through the descending sympathetic nerves. Sensory nerve fibers from dorsal root ganglia (DRG) innervate skeletal muscle, adipose tissue, and bone. Distinct afferent sensory neurons have been identified to control appetite and metabolism through different IOCs. Peripheral organs also communicate with each other through a variety of humoral factors. These multi-layered feedback loops maintain healthy metabolism and regulate the aging process in mammals. This figure was created using BioRender (www.biorender.com).
Additionally, the nervous system tightly regulates bone metabolism through the hypothalamus-derived descending interoceptive pathway [77]. Prostaglandin E2, secreted by osteoblasts, activates EP4 in sensory nerves in the ascending pathway that project to the ventromedial hypothalamic nucleus (VMH). This stimulation then downregulates descending sympathetic tone from the VMH, promoting the differentiation of BMSCs into osteoblasts and inducing bone formation, thereby maintaining skeletal homeostasis [81,82]. Moreover, hypothalamus-derived autonomic nervous stimulation is regulated by humoral factors such as leptin [83]. The mechanism by which these endocrine and sensory feedback signals are integrated into the brain, as well as the potential interplay between these signals, remains poorly understood. However, these findings suggest that this integration is likely critical for generating appropriate behavioral responses and hormonal regulation via hypothalamus-derived autonomic nervous signaling to maintain metabolic homeostasis, potentially regulating aging (Figure 2).
The hypothalamus functions as a high-order control center of aging and longevity
Decline in metabolic homeostasis and plasticity is a common characteristic of aging. In 2013, two independent groups reached the same conclusion regarding the importance of the hypothalamus in mammalian aging and longevity. The mammalian NAD+-dependent protein deacetylase SIRT1 in the hypothalamus, particularly in the DMH and lateral hypothalamic nuclei (LH), plays a critical role in delaying aging and extending the lifespan of mice [84]. Another group demonstrated that inhibiting nuclear factor-κB (NF-κB) in neurons of the mediobasal hypothalamus (MBH) extends the lifespan of mice, whereas activating NF-κB in MBH neurons shortens their lifespan [85]. Since these groundbreaking findings, hypothalamic dysfunction has been increasingly acknowledged as a significant cause of aging phenotypes at the systemic level [86,87]. For example, mice lacking hypothalamic mTORC2 signaling display reduced activity levels, an elevated set point for adiposity, increased susceptibility to diet-induced obesity, heightened frailty with age, and shorter overall survival [86]. Prdm13, a downstream target of SIRT1 signaling in the dorsomedial hypothalamus (DMH), regulates lipolysis in WAT and sleep-wake patterns, both of which are dysregulated during aging, and mediates the effect of caloric restriction in improving sleep in aged mice [88,89]. DMH-specific Prdm13-knockout mice recapitulate age-associated sleep alterations such as sleep fragmentation with increased adiposity and decreased physical activity, resulting in a shortened lifespan. In contrast, overexpression of Prdm13 in the DMH can ameliorate increased sleep attempts during sleep deprivation in old mice [89].
The hypothalamus is also essential for the regulation of hormone production. For example, hypothalamic secretion of gonadotropin-releasing hormone (GnRH) is impaired during aging, resulting in decreased pituitary secretion of luteinizing hormone [90] and loss of hypothalamic neural stem/progenitor cells (hNSCs) [71]. While the exact mechanism by which GnRH neurons and hNSCs in the MBH regulates aging and lifespan remains unknown, several supportive studies have demonstrated the importance of specific hypothalamic regions in aging and longevity control [71,85,91,92]. Inflammation in the MBH has been causally linked to the pathogenesis of aging phenotypes and metabolic dysfunction [93]. Menin signaling in the ventromedial hypothalamus has recently been shown to reduce inflammatory conditions and counteract systemic aging and cognitive deficits [87]. Additionally, whole hypothalamic single-cell RNA sequencing analysis revealed a clear age-associated induction of inflammatory signaling in microglia and macrophages [94], suggesting that chronic inflammation within the hypothalamus causes detrimental effects on metabolism and induces aging.
Over the past decade, increasing lines of evidence have demonstrated that maintaining a youthful sympathetic nervous system (SNS) plays an essential role in counteracting aging through the IOCs between the hypothalamus and peripheral tissues (Figure 2). Brain-specific SIRT1-overexpressing (BRASTO) mice significantly delay aging and lifespan extension. BRASTO mice also maintain the youthful structure and function of the mitochondria in skeletal muscle during aging due to enhanced SNS [84]. Indeed, hypothalamic SIRT1 induces activation of the sympathetic nervous system, protecting the structure of neuromuscular junctions in skeletal muscles from age-related deterioration [95]. A subset of neurons in the LH expressing solute carrier family 12 member 8 (Slc12a8), which encodes a specific transporter for nicotinamide mononucleotide, also maintains the structure and function of fast-twitching skeletal muscles during aging through β2 adrenergic receptor-mediated sympathetic nervous stimulation. Restoring Slc12a8 expression in the LH can ameliorate age-associated sarcopenia and frailty-like symptoms in aged mice [96].
Most recently, it has been demonstrated that the IOC between the hypothalamus and WAT plays a crucial role in mammalian aging and longevity control. A newly identified neuronal subpopulation in the DMH, marked by protein phosphatase 1 regulatory subunit 17 (Ppp1r17) expression (DMHPpp1r17 neurons), counteracts aging and determines lifespan through the IOC between the hypothalamus and WAT via SNS. An age-associated decline in DMHPpp1r17 neuronal activity leads to physiological functional decline, including a significant reduction in physical activity, lipolysis, and eNAMPT secretion from WAT. Importantly, activation of DMHPpp1r17 neurons by genetic and chemogenetic manipulations in aged mice ameliorates age-associated physiological decline, delaying aging and extending lifespan [11]. Given that eNAMPT-containing EVs promote NAD+ biosynthesis specifically in the DMH [97], it is conceivable that DMHPpp1r17 neurons and WAT comprise a key feedback loop for aging and longevity control through the combination of neuronal and humoral IOCs. These findings provide critical insights into the importance of IOC in mammalian aging and longevity control. It will be of great importance to understand how the function of this key IOC is disrupted during aging. In addition to the IOC between the hypothalamus and WAT, it is likely that IOCs between the hypothalamus and other peripheral tissues, including skeletal muscle, also cooperate to maintain metabolic resilience and regulate aging and longevity in mammals. These recent discoveries have opened a new avenue to explore the precise mechanisms by which IOCs regulate metabolism and aging, and further investigations are required to elucidate such underlying mechanisms.
Concluding remarks and future perspectives
IOCs represent dynamic and multifaceted physiological processes that are now clearly gaining more attention in metabolic and aging research. As enthusiasm for the mechanistic details of IOC grows, there is an urgent need to develop novel biological tools to identify systems that deliver effector molecules and analyze the interactions between different effector molecules. By unraveling the intricate signaling mechanisms that govern tissue crosstalk, we will gain new insights into the pathophysiology of age-related metabolic derangements and identify novel therapeutic targets to promote healthy aging and longevity. For instance, newly identified signaling molecules mediating IOCs between the hypothalamus and peripheral organs could be used to maintain the strength of targeted IOCs and treat or prevent age-related dysfunctions. We are only beginning to understand how distinct IOCs regulate diverse physiological processes that maintain metabolic resilience and thereby counteract aging. Several outstanding questions remain to be answered to better understand the mechanisms by which IOCs regulate metabolism and aging (see Outstanding Questions).
Outstanding Questions.
Is the IOC a critical determinant for lifespan? If so, is there any specific subset of hypothalamic neurons that controls aging and determines lifespan?
What triggers the deterioration of IOCs in the regulation of metabolism and aging? Where and how does the decline in IOCs start?
How do each IOC, such as the hypothalamus-WAT and the hypothalamus-skeletal muscle, interact with each other in mammalian aging and longevity control?
How do sex differences in IOCs impact the regulation of metabolism and aging?
The hypothalamus functions as a key central hub for IOCs. Additionally, numerous approaches for extending lifespan in animal models, such as specific dietary regimens and metabolic and genetic manipulations, involve the hypothalamus. Despite extensive research in this area over several decades, the complexity of each individual hypothalamic nucleus and the lack of good molecular markers for each neuronal subpopulation still create serious technical challenges in analyzing and manipulating hypothalamic neuronal functions [98]. Our challenge to understand the exact mechanisms by which IOCs between the hypothalamus and peripheral organs regulate metabolism and aging has just begun.
Supplementary Material
Highlights.
Adipose tissues, skeletal muscle, and bone, traditionally categorized as non-endocrine organs, send humoral signals to others to maintain metabolic homeostasis.
Humoral factors, such as hormones, cytokines, microRNAs, metabolites, and mitochondrial signaling, contribute to metabolic health and aging regulation through inter-organ communication (IOC).
Neuronal integration of IOC by the hypothalamus is a critical contributor to metabolism and aging.
Acknowledgments
We particularly thank Brian Lananna for his critical comments and suggestions on this article. The authors apologize to those whose work has not been cited because of space limitations. This work was supported by grants to S.I. from the National Institute on Aging (AG037457, AG047902, and U01AG086196).
Declaration of interests
S.I. declares no Competing Non-Financial Interests but the following Competing Financial Interests: S.I. receives a part of patent-licensing fees from MetroBiotech (USA) and the Institute for Research on Productive Aging (Japan) through Washington University. S.I. also serves as the President of the Institute for Research on Productive Aging (Japan) and a co-CEO of LongGen Bioscience (Japan). S.I.’s External Professional Activities (EPAs) have already been reported to, and a potential conflict of interest has been appropriately resolved through the Washington University Conflict of Interest Committee.
Reference
- 1.Kenyon CJ (2010) The genetics of ageing. Nature 464, 504–512. 10.1038/nature08980 [DOI] [PubMed] [Google Scholar]
- 2.Vitale G et al. (2019) ROLE of IGF-1 System in the Modulation of Longevity: Controversies and New Insights From a Centenarians’ Perspective. Front Endocrinol (Lausanne) 10, 27. 10.3389/fendo.2019.00027 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Zoncu R et al. (2011) mTOR: from growth signal integration to cancer, diabetes and ageing. Nat Rev Mol Cell Biol 12, 21–35. 10.1038/nrm3025 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Papadopoli D et al. (2019) mTOR as a central regulator of lifespan and aging. F1000Res 8. 10.12688/f1000research.17196.1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Imai S and Guarente L (2014) NAD+ and sirtuins in aging and disease. Trends Cell Biol 24, 464–471. 10.1016/j.tcb.2014.04.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Lee SH et al. (2019) Sirtuin signaling in cellular senescence and aging. BMB Rep 52, 24–34. 10.5483/BMBRep.2019.52.1.290 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Priest C and Tontonoz P (2019) Inter-organ cross-talk in metabolic syndrome. Nat Metab 1, 1177–1188. 10.1038/s42255-019-0145-5 [DOI] [PubMed] [Google Scholar]
- 8.Castillo-Armengol J et al. (2019) Inter-organ communication: a gatekeeper for metabolic health. EMBO Rep 20, e47903. 10.15252/embr.201947903 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.López-Otín C et al. (2023) Hallmarks of aging: An expanding universe. Cell 186, 243–278. 10.1016/j.cell.2022.11.001 [DOI] [PubMed] [Google Scholar]
- 10.Petr MA et al. (2021) A cross-sectional study of functional and metabolic changes during aging through the lifespan in male mice. Elife 10. 10.7554/eLife.62952 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Tokizane K et al. (2024) DMH(Ppp1r17) neurons regulate aging and lifespan in mice through hypothalamic-adipose inter-tissue communication. Cell Metab. 10.1016/j.cmet.2023.12.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Chen X et al. (2024) Small extracellular vesicles from young plasma reverse age-related functional declines by improving mitochondrial energy metabolism. Nat Aging 4, 814–838. 10.1038/s43587-024-00612-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Tian YE et al. (2023) Heterogeneous aging across multiple organ systems and prediction of chronic disease and mortality. Nat Med 29, 1221–1231. 10.1038/s41591-023-02296-6 [DOI] [PubMed] [Google Scholar]
- 14.Savini M et al. (2022) Lysosome lipid signalling from the periphery to neurons regulates longevity. Nat Cell Biol 24, 906–916. 10.1038/s41556-022-00926-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Rai M et al. (2021) Proteasome stress in skeletal muscle mounts a long-range protective response that delays retinal and brain aging. Cell Metab 33, 1137–1154.e1139. 10.1016/j.cmet.2021.03.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Campbell M and Jialal I (2024) Physiology, Endocrine Hormones. In StatPearls, StatPearls Publishing Copyright © 2024, StatPearls Publishing LLC. [PubMed] [Google Scholar]
- 17.Bany Bakar R et al. (2023) The intestine as an endocrine organ and the role of gut hormones in metabolic regulation. Nat Rev Gastroenterol Hepatol 20, 784–796. 10.1038/s41575-023-00830-y [DOI] [PubMed] [Google Scholar]
- 18.Scheja L and Heeren J (2019) The endocrine function of adipose tissues in health and cardiometabolic disease. Nat Rev Endocrinol 15, 507–524. 10.1038/s41574-019-0230-6 [DOI] [PubMed] [Google Scholar]
- 19.Zhou R et al. (2021) Endocrine role of bone in the regulation of energy metabolism. Bone Res 9, 25. 10.1038/s41413-021-00142-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Pedersen BK and Febbraio MA (2012) Muscles, exercise and obesity: skeletal muscle as a secretory organ. Nat Rev Endocrinol 8, 457–465. 10.1038/nrendo.2012.49 [DOI] [PubMed] [Google Scholar]
- 21.Kreissl FK et al. (2023) Molecular methods to study protein trafficking between organs. Proteomics 23, e2100331. 10.1002/pmic.202100331 [DOI] [PubMed] [Google Scholar]
- 22.Stern JH et al. (2016) Adiponectin, Leptin, and Fatty Acids in the Maintenance of Metabolic Homeostasis through Adipose Tissue Crosstalk. Cell Metab 23, 770–784. 10.1016/j.cmet.2016.04.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Takahashi H et al. (2019) TGF-β2 is an exercise-induced adipokine that regulates glucose and fatty acid metabolism. Nat Metab 1, 291–303. 10.1038/s42255-018-0030-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Yoon MJ et al. (2015) SIRT1-Mediated eNAMPT Secretion from Adipose Tissue Regulates Hypothalamic NAD+ and Function in Mice. Cell Metab 21, 706–717. 10.1016/j.cmet.2015.04.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Yoshida M et al. (2019) Extracellular Vesicle-Contained eNAMPT Delays Aging and Extends Lifespan in Mice. Cell Metab 30, 329–342.e325. 10.1016/j.cmet.2019.05.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Morato L et al. (2022) eNAMPT actions through nucleus accumbens NAD(+)/SIRT1 link increased adiposity with sociability deficits programmed by peripuberty stress. Sci Adv 8, eabj9109. 10.1126/sciadv.abj9109 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Park JW et al. (2023) Circulating blood eNAMPT drives the circadian rhythms in locomotor activity and energy expenditure. Nat Commun 14, 1994. 10.1038/s41467-023-37517-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Gavaldà-Navarro A et al. (2022) The endocrine role of brown adipose tissue: An update on actors and actions. Rev Endocr Metab Disord 23, 31–41. 10.1007/s11154-021-09640-6 [DOI] [PubMed] [Google Scholar]
- 29.Ziqubu K et al. (2024) Brown adipose tissue-derived metabolites and their role in regulating metabolism. Metabolism 150, 155709. 10.1016/j.metabol.2023.155709 [DOI] [PubMed] [Google Scholar]
- 30.Severinsen MCK and Pedersen BK (2020) Muscle-Organ Crosstalk: The Emerging Roles of Myokines. Endocr Rev 41, 594–609. 10.1210/endrev/bnaa016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Lee P et al. (2014) Irisin and FGF21 are cold-induced endocrine activators of brown fat function in humans. Cell Metab 19, 302–309. 10.1016/j.cmet.2013.12.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Boström P et al. (2012) A PGC1-α-dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature 481, 463–468. 10.1038/nature10777 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Wrann CD et al. (2013) Exercise induces hippocampal BDNF through a PGC-1α/FNDC5 pathway. Cell Metab 18, 649–659. 10.1016/j.cmet.2013.09.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Moon HY et al. (2016) Running-Induced Systemic Cathepsin B Secretion Is Associated with Memory Function. Cell Metab 24, 332–340. 10.1016/j.cmet.2016.05.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Qi C et al. (2022) The role of exercise-induced myokines in promoting angiogenesis. Front Physiol 13, 981577. 10.3389/fphys.2022.981577 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Kim BJ (2022) Effects of Muscles on Bone Metabolism-with a Focus on Myokines. Ann Geriatr Med Res 26, 63–71. 10.4235/agmr.22.0054 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Otaka N et al. (2018) Myonectin Is an Exercise-Induced Myokine That Protects the Heart From Ischemia-Reperfusion Injury. Circ Res 123, 1326–1338. 10.1161/circresaha.118.313777 [DOI] [PubMed] [Google Scholar]
- 38.Parikh VN et al. (2018) Apelin and APJ orchestrate complex tissue-specific control of cardiomyocyte hypertrophy and contractility in the hypertrophy-heart failure transition. Am J Physiol Heart Circ Physiol 315, H348–h356. 10.1152/ajpheart.00693.2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Lee NK et al. (2007) Endocrine regulation of energy metabolism by the skeleton. Cell 130, 456–469. 10.1016/j.cell.2007.05.047 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Yoshikawa Y et al. (2011) Genetic evidence points to an osteocalcin-independent influence of osteoblasts on energy metabolism. J Bone Miner Res 26, 2012–2025. 10.1002/jbmr.417 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Ferron M et al. (2008) Osteocalcin differentially regulates beta cell and adipocyte gene expression and affects the development of metabolic diseases in wild-type mice. Proc Natl Acad Sci U S A 105, 5266–5270. 10.1073/pnas.0711119105 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Su T et al. (2019) Bone Marrow Mesenchymal Stem Cells-Derived Exosomal MiR-29b-3p Regulates Aging-Associated Insulin Resistance. ACS Nano 13, 2450–2462. 10.1021/acsnano.8b09375 [DOI] [PubMed] [Google Scholar]
- 43.Wang Y et al. (2023) Exercise Improves Metabolism and Alleviates Atherosclerosis via Muscle-Derived Extracellular Vesicles. Aging Dis 14, 952–965. 10.14336/ad.2022.1131 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Lananna BV and Imai SI (2021) Friends and foes: Extracellular vesicles in aging and rejuvenation. FASEB Bioadv 3, 787–801. 10.1096/fba.2021-00077 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Yang Q et al. (2018) Metabolites as regulators of insulin sensitivity and metabolism. Nat Rev Mol Cell Biol 19, 654–672. 10.1038/s41580-018-0044-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Baker SA and Rutter J (2023) Metabolites as signalling molecules. Nat Rev Mol Cell Biol 24, 355–374. 10.1038/s41580-022-00572-w [DOI] [PubMed] [Google Scholar]
- 47.Zhou Y et al. (2021) Host and microbiota metabolic signals in aging and longevity. Nat Chem Biol 17, 1027–1036. 10.1038/s41589-021-00837-z [DOI] [PubMed] [Google Scholar]
- 48.Panyard DJ et al. (2022) The metabolomics of human aging: Advances, challenges, and opportunities. Sci Adv 8, eadd6155. 10.1126/sciadv.add6155 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Fang W et al. (2023) Metabolomics in aging research: aging markers from organs. Front Cell Dev Biol 11, 1198794. 10.3389/fcell.2023.1198794 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Parkhitko AA et al. (2020) Targeting metabolic pathways for extension of lifespan and healthspan across multiple species. Ageing Res Rev 64, 101188. 10.1016/j.arr.2020.101188 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Asadi Shahmirzadi A et al. (2020) Alpha-Ketoglutarate, an Endogenous Metabolite, Extends Lifespan and Compresses Morbidity in Aging Mice. Cell Metab 32, 447–456.e446. 10.1016/j.cmet.2020.08.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Han S et al. (2017) Mono-unsaturated fatty acids link H3K4me3 modifiers to C. elegans lifespan. Nature 544, 185–190. 10.1038/nature21686 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Bunning BJ et al. (2020) Global metabolic profiling to model biological processes of aging in twins. Aging Cell 19, e13073. 10.1111/acel.13073 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Sato Y et al. (2021) Novel bile acid biosynthetic pathways are enriched in the microbiome of centenarians. Nature 599, 458–464. 10.1038/s41586-021-03832-5 [DOI] [PubMed] [Google Scholar]
- 55.Hudry B et al. (2019) Sex Differences in Intestinal Carbohydrate Metabolism Promote Food Intake and Sperm Maturation. Cell 178, 901–918.e916. 10.1016/j.cell.2019.07.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Schroer AB et al. (2023) Platelet factors attenuate inflammation and rescue cognition in ageing. Nature 620, 1071–1079. 10.1038/s41586-023-06436-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Liu D et al. (2022) The Mechanism of Lung and Intestinal Injury in Acute Pancreatitis: A Review. Front Med (Lausanne) 9, 904078. 10.3389/fmed.2022.904078 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Ragab D et al. (2020) The COVID-19 Cytokine Storm; What We Know So Far. Front Immunol 11, 1446. 10.3389/fimmu.2020.01446 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Huang K et al. (2020) Impaired peroxisomal import in Drosophila oenocytes causes cardiac dysfunction by inducing upd3 as a peroxikine. Nat Commun 11, 2943. 10.1038/s41467-020-16781-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Franceschi C et al. (2018) Inflammaging: a new immune-metabolic viewpoint for age-related diseases. Nat Rev Endocrinol 14, 576–590. 10.1038/s41574-018-0059-4 [DOI] [PubMed] [Google Scholar]
- 61.Khosla S et al. (2020) The role of cellular senescence in ageing and endocrine disease. Nat Rev Endocrinol 16, 263–275. 10.1038/s41574-020-0335-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Zumerle S et al. (2024) Targeting senescence induced by age or chemotherapy with a polyphenol-rich natural extract improves longevity and healthspan in mice. Nat Aging. 10.1038/s43587-024-00663-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.de Magalhães JP (2024) Cellular senescence in normal physiology. Science 384, 1300–1301. 10.1126/science.adj7050 [DOI] [PubMed] [Google Scholar]
- 64.Grosse L et al. (2020) Defined p16(High) Senescent Cell Types Are Indispensable for Mouse Healthspan. Cell Metab 32, 87–99.e86. 10.1016/j.cmet.2020.05.002 [DOI] [PubMed] [Google Scholar]
- 65.Moiseeva V et al. (2023) Senescence atlas reveals an aged-like inflamed niche that blunts muscle regeneration. Nature 613, 169–178. 10.1038/s41586-022-05535-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Chaib S et al. (2022) Cellular senescence and senolytics: the path to the clinic. Nat Med 28, 1556–1568. 10.1038/s41591-022-01923-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Bartel DP (2018) Metazoan MicroRNAs. Cell 173, 20–51. 10.1016/j.cell.2018.03.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Wang J et al. (2022) Extracellular vesicles mediate the communication of adipose tissue with brain and promote cognitive impairment associated with insulin resistance. Cell Metab 34, 1264–1279.e1268. 10.1016/j.cmet.2022.08.004 [DOI] [PubMed] [Google Scholar]
- 69.Wang X et al. (2024) Tissue-specific profiling of age-dependent miRNAomic changes in Caenorhabditis elegans. Nat Commun 15, 955. 10.1038/s41467-024-45249-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Wagner V et al. (2024) Characterizing expression changes in noncoding RNAs during aging and heterochronic parabiosis across mouse tissues. Nat Biotechnol 42, 109–118. 10.1038/s41587-023-01751-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Zhang Y et al. (2017) Hypothalamic stem cells control ageing speed partly through exosomal miRNAs. Nature 548, 52–57. 10.1038/nature23282 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Li J et al. (2024) RNAkines are secreted messengers shaping health and disease. Trends Endocrinol Metab 35, 201–218. 10.1016/j.tem.2023.12.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73.Shen K et al. (2023) The germline coordinates mitokine signaling. bioRxiv. 10.1101/2023.08.21.554217 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Charmpilas N et al. (2024) Reproductive regulation of the mitochondrial stress response in Caenorhabditis elegans. Cell Rep 43, 114336. 10.1016/j.celrep.2024.114336 [DOI] [PubMed] [Google Scholar]
- 75.Wu S et al. (2024) Extracellular vesicles meet mitochondria: Potential roles in regenerative medicine. Pharmacol Res 206, 107307. 10.1016/j.phrs.2024.107307 [DOI] [PubMed] [Google Scholar]
- 76.Mishra G and Townsend KL (2023) The metabolic and functional roles of sensory nerves in adipose tissues. Nat Metab 5, 1461–1474. 10.1038/s42255-023-00868-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.Lv X et al. (2022) Skeletal interoception in bone homeostasis and pain. Cell Metab 34, 1914–1931. 10.1016/j.cmet.2022.09.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78.Payne SC et al. (2022) Blood glucose modulation and safety of efferent vagus nerve stimulation in a type 2 diabetic rat model. Physiol Rep 10, e15257. 10.14814/phy2.15257 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79.Yao G et al. (2018) Effective weight control via an implanted self-powered vagus nerve stimulation device. Nat Commun 9, 5349. 10.1038/s41467-018-07764-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 80.Wang Y et al. (2022) The role of somatosensory innervation of adipose tissues. Nature 609, 569–574. 10.1038/s41586-022-05137-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Hu B et al. (2020) Sensory nerves regulate mesenchymal stromal cell lineage commitment by tuning sympathetic tones. J Clin Invest 130, 3483–3498. 10.1172/jci131554 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Chen H et al. (2019) Prostaglandin E2 mediates sensory nerve regulation of bone homeostasis. Nat Commun 10, 181. 10.1038/s41467-018-08097-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Wang P et al. (2020) A leptin-BDNF pathway regulating sympathetic innervation of adipose tissue. Nature 583, 839–844. 10.1038/s41586-020-2527-y [DOI] [PubMed] [Google Scholar]
- 84.Satoh A et al. (2013) Sirt1 extends life span and delays aging in mice through the regulation of Nk2 homeobox 1 in the DMH and LH. Cell Metab 18, 416–430. 10.1016/j.cmet.2013.07.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Zhang G et al. (2013) Hypothalamic programming of systemic ageing involving IKK-β, NF-κB and GnRH. Nature 497, 211–216. 10.1038/nature12143 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Chellappa K et al. (2019) Hypothalamic mTORC2 is essential for metabolic health and longevity. Aging Cell 18, e13014. 10.1111/acel.13014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 87.Leng L et al. (2023) Hypothalamic Menin regulates systemic aging and cognitive decline. PLoS Biol 21, e3002033. 10.1371/journal.pbio.3002033 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Satoh A et al. (2015) Deficiency of Prdm13, a dorsomedial hypothalamus-enriched gene, mimics age-associated changes in sleep quality and adiposity. Aging Cell 14, 209–218. 10.1111/acel.12299 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Tsuji S et al. (2023) Sleep-wake patterns are altered with age, Prdm13 signaling in the DMH, and diet restriction in mice. Life Sci Alliance 6. 10.26508/lsa.202301992 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Anawalt BD and Matsumoto AM (2022) Aging and androgens: Physiology and clinical implications. Rev Endocr Metab Disord 23, 1123–1137. 10.1007/s11154-022-09765-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.Wang Z et al. (2021) GnRH pulse frequency and irregularity play a role in male aging. Nature Aging 1, 904–918. 10.1038/s43587-021-00116-5 [DOI] [PubMed] [Google Scholar]
- 92.Xiao YZ et al. (2020) Reducing Hypothalamic Stem Cell Senescence Protects against Aging-Associated Physiological Decline. Cell Metab 31, 534–548.e535. 10.1016/j.cmet.2020.01.002 [DOI] [PubMed] [Google Scholar]
- 93.Cai D and Khor S (2021) Hypothalamic microinflammation. Handb Clin Neurol 181, 311–322. 10.1016/b978-0-12-820683-6.00023-3 [DOI] [PubMed] [Google Scholar]
- 94.Hajdarovic KH et al. (2022) Single-cell analysis of the aging female mouse hypothalamus. Nat Aging 2, 662–678. 10.1038/s43587-022-00246-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95.Snyder-Warwick AK et al. (2018) Hypothalamic Sirt1 protects terminal Schwann cells and neuromuscular junctions from age-related morphological changes. Aging Cell 17, e12776. 10.1111/acel.12776 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96.Ito N et al. (2022) Slc12a8 in the lateral hypothalamus maintains energy metabolism and skeletal muscle functions during aging. Cell Rep 40, 111131. 10.1016/j.celrep.2022.111131 [DOI] [PubMed] [Google Scholar]
- 97.Johnson S et al. (2023) Quantification of localized NAD(+) changes reveals unique specificity of NAD(+) regulation in the hypothalamus. NPJ Aging 9, 1. 10.1038/s41514-023-00098-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.Hajdarovic KH et al. (2022) Understanding the aging hypothalamus, one cell at a time. Trends Neurosci 45, 942–954. 10.1016/j.tins.2022.10.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Branon TC et al. (2018) Efficient proximity labeling in living cells and organisms with TurboID. Nat Biotechnol 36, 880–887. 10.1038/nbt.4201 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Droujinine IA et al. (2021) Proteomics of protein trafficking by in vivo tissue-specific labeling. Nat Commun 12, 2382. 10.1038/s41467-021-22599-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 101.Kim KE et al. (2021) Dynamic tracking and identification of tissue-specific secretory proteins in the circulation of live mice. Nat Commun 12, 5204. 10.1038/s41467-021-25546-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 102.Wei W et al. (2021) Cell type-selective secretome profiling in vivo. Nat Chem Biol 17, 326–334. 10.1038/s41589-020-00698-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 103.Wei W et al. (2023) Organism-wide, cell-type-specific secretome mapping of exercise training in mice. Cell Metab 35, 1261–1279.e1211. 10.1016/j.cmet.2023.04.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 104.Yang R et al. (2022) A genetic model for in vivo proximity labelling of the mammalian secretome. Open Biol 12, 220149. 10.1098/rsob.220149 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
