Hypoxia-Induced Gut-Brain Axis Remodeling and Insomnia: Mechanisms and Microbiota Adaptive Regulation from a Translational Perspective

Abstract

High-altitude hypoxia frequently disrupts sleep–wake cycles, causing insomnia that impairs acclimatization, performance, and health. Emerging evidence implicates the gut–brain axis (GBA) in this disorder. Prolonged or severe hypoxia can disturb intestinal epithelial homeostasis through oxidative, inflammatory, and metabolic changes, increasing barrier permeability and facilitating the translocation of lipopolysaccharide (LPS) and other bacterial products into the circulation. Concurrent gut microbial dysbiosis reduces the production of short-chain fatty acids (SCFAs) and redirects tryptophan metabolism toward the kynurenine pathway, thereby promoting systemic and neuroinflammation. Peripheral inflammatory signals communicate with the central nervous system (CNS) through a compromised blood–brain barrier (BBB), circumventricular organs (CVOs), and vagal afferents, while neuroendocrine stress responses involving the hypothalamic–pituitary–adrenal (HPA) axis and cortisol may further link hypoxia and inflammation to sleep disruption. Together, these pathways activate arousal circuits while inhibiting sleep-promoting gamma-aminobutyric acid (GABA)-ergic neurons, contributing to the characteristic electroencephalographic features of high-altitude insomnia. High-altitude-specific evidence for conventional sleep therapies remains limited, underscoring the need for biologically grounded strategies tailored to hypoxic environments. Preliminary probiotic evidence suggests potential benefits for oxygenation and acclimatization, whereas postbiotics and dietary pre-habilitation represent mechanistically promising approaches. However, the absence of human randomized controlled trials using polysomnography remains a major translational barrier. Future research should prioritize field-deployable diagnostic tools, causal multi-omics studies, and personalized microbiota-targeted interventions for high-altitude insomnia.

Plain Language Summary

Why did we do this study?

People who travel to or live at high altitude often find it difficult to fall asleep or stay asleep because the air contains less oxygen. Poor sleep can affect health, thinking, work, and adjustment to high altitude. Some sleeping medicines may also affect breathing in low-oxygen environments. We therefore examined whether communication between the gut and brain could help explain sleep problems at high altitude and identify new treatment targets.

What did we do and find?

We reviewed studies of how low oxygen affects the gut, brain, and sleep. Low oxygen may change the gut microbiome—the community of microorganisms in the intestine—and weaken the gut lining. Bacterial products and inflammatory signals may then enter the bloodstream more easily. These signals can influence the brain through the circulation, brain regions that monitor the blood, and nerves connecting the gut and brain. Stress-hormone responses may further affect sleep. Together, these changes may increase alertness and reduce restorative deep sleep. Animal studies provide the strongest mechanistic evidence. Human studies show related changes in gut microorganisms and sleep, but they do not yet prove that one causes the other.

What do these results mean?

The gut–brain connection offers potential targets for high-altitude insomnia. Probiotics, postbiotics, and dietary strategies require further study in well-designed human trials using objective sleep measurements. Such trials can determine which approaches are effective and suitable for people living at or traveling to high altitude.

Graphical Abstract

Introduction

High-altitude (HA) environments, typically defined as elevations exceeding 2500 meters, present significant physiological challenges to the human body due to hypobaric hypoxia. As the partial pressure of oxygen (PiO₂) declines, nearly every organ system must undergo acclimatization or maladaptation.¹ Sleep disturbance is highly prevalent during HA exposure, with insomnia symptoms reported in 32–74% of sojourners and residents.^2–4 These symptoms commonly include prolonged sleep latency, frequent nocturnal awakenings, reduced slow-wave sleep (SWS), and daytime fatigue.^5,6 Epidemiological data reveal a strong correlation between elevation and the severity of insomnia;^7,8 individuals ascending rapidly are particularly at risk, although chronic residents also demonstrate altered sleep architecture compared to their sea-level counterparts.^9,10 Although disturbed sleep was included in earlier scoring systems for acute mountain sickness (AMS), it was removed from the 2018 Lake Louise AMS score because it appears to be driven largely by altitude hypoxia itself and does not closely track AMS severity.¹¹ Nevertheless, altitude-related sleep disturbance can impair daytime cognition, psychomotor performance, well-being, and adaptation to hypoxic environments.¹²

Conventional strategies for managing insomnia at sea level typically involve benzodiazepines, non-benzodiazepine hypnotics like zolpidem, and Cognitive Behavioral Therapy for Insomnia (CBT-I).^13,14 However, applying these methods at HA poses challenges. Because nocturnal hypoxemia and periodic breathing are common at altitude,^15,16 benzodiazepines warrant caution in individuals vulnerable to respiratory compromise; however, the available safety evidence is derived mainly from patients with OSA or chronic respiratory disease rather than high-altitude populations.^17,18 Z-drugs have been associated with parasomnias, falls in older adults and adverse cardiovascular outcomes in patients with heart failure.¹⁹ CBT-I is an established treatment for chronic insomnia at sea level; however, its effectiveness for sleep disturbance specifically attributable to acute or sustained HA exposure has not been established. High-altitude-specific evidence for both behavioral and pharmacological treatments therefore remains limited. These limitations underscore the urgent need for biologically grounded strategies tailored to hypoxic environments.

The microbiota–gut–brain axis (GBA) enables bidirectional communication between the gut microbiota and the central nervous system (CNS) through neural, immune, endocrine, and metabolic pathways.²⁰ Neuroendocrine systems provide an important interface through which hypoxic and inflammatory stress may influence the balance between sleep and arousal. Acute hypoxic exposure can activate physiological stress responses; in healthy participants exposed to simulated altitude, an increase in cortisol was accompanied by reductions in deep and rapid eye movement sleep.²¹ Activation of the hypothalamic–pituitary–adrenal (HPA) axis increases corticotropin-releasing hormone and cortisol secretion, and persistent activation of this pathway may impair sleep continuity and SWS.²² In contrast, growth hormone-releasing hormone (GHRH) promotes non-rapid eye movement sleep and is closely associated with slow-wave sleep and nocturnal growth hormone secretion.²³ GHRH also interacts with sleep-regulatory cytokines such as interleukin-1, suggesting that hypoxia-associated inflammation may disturb the balance between stress-related arousal and sleep-promoting neuroendocrine signaling.²⁴ Orexin neurons in the lateral hypothalamus integrate metabolic and stress-related signals and stabilize wakefulness through widespread arousal networks.²⁵ These systems therefore provide a neuroendocrine framework through which hypoxia, inflammation, and microbiota-derived signals may converge to disrupt sleep at HA.

Against this neuroendocrine background, microbiota-derived signals may influence sleep and CNS function through metabolic, immune, and neural mechanisms.^26–28 Human observational studies have reported differences in gut microbial composition, metabolic function, and microbiota-associated inflammatory profiles between individuals with insomnia and healthy controls. However, the direction of diversity changes and taxon-specific signatures has varied across cohorts, and a consistent insomnia-associated microbial profile has not yet been established.^29–31 Animal studies have further supported a causal contribution of the gut microbiota by showing that transplantation of microbiota from patients with insomnia into germ-free mice induced insomnia-like sleep disturbances in recipient animals.³²

Previous research has examined the individual impacts of hypoxia on gut microbiota and the relationship between microbiota and insomnia. However, the precise interconnection among hypoxia, gut dysbiosis, and insomnia remains unclear. A thorough review outlining the sequential mechanisms from hypoxia-induced dysbiosis to insomnia is currently absent. Furthermore, there is a need for a systematic exploration of potential therapeutic approaches that target this pathway. Hence, this review consolidates current evidence on how HA hypoxia remodels the GBA to trigger or worsen insomnia, identifies translational obstacles, evaluates emerging intervention strategies, and outlines a research roadmap for microbiota-focused approaches in low-oxygen populations.

Mechanisms of Gut-Brain Axis Remodeling Under Hypoxia

The GBA functions as a two-way communication system linking the gastrointestinal tract and the central nervous system to uphold physiological balance in normoxic circumstances. In instances of hypoxic stress, whether due to high altitudes or conditions like sleep apnea, this axis experiences organized structural and functional changes leading to sleep disturbances.^33,34

Hypoxia-Induced Intestinal Barrier Disruption

Intestinal barrier integrity is maintained by epithelial tight-junction complexes. In intestinal epithelial cells under normoxic conditions, HIF-1α is rapidly degraded, whereas hypoxia promotes its stabilization. However, the effects of epithelial HIF-1α signaling on barrier integrity are context- and duration-dependent. In a Caco-2 hypoxia/reoxygenation model combined with LPS exposure, barrier dysfunction was accompanied by reduced ZO-1 expression and increased HIF-1α and NF-κB signaling, all of which were attenuated by emodin.³⁵ These findings implicate HIF-1α-related signaling in epithelial injury under these experimental conditions, while its role may vary with the pattern and duration of hypoxic exposure. Hypoxia-associated oxidative stress may further impair epithelial junctions and cytoskeletal organization. However, direct evidence that sustained hypobaric hypoxia activates the TXNIP–NLRP3 inflammasome specifically in intestinal epithelial cells is currently lacking. Evidence implicating this pathway in epithelial pyroptosis and barrier injury is derived primarily from intestinal ischemia–reperfusion and oxygen–glucose deprivation/reoxygenation models; therefore, its contribution to intestinal barrier dysfunction during high-altitude hypoxia remains to be established.³⁶ Concurrently, hypoxia-induced activation of cofilin leads to F-actin depolymerization, disrupting the cytoskeletal framework supporting tight junction proteins and directly compromising paracellular sealing (Figure 1B).³⁷ Apart from its cytoskeletal role, cofilin-1 can also act as a redox-sensitive checkpoint of NLRP3 activation: in macrophage-based experimental systems, ROS-induced cofilin-1 oxidation promoted its dissociation from NLRP3, thereby facilitating inflammasome assembly.³⁸ Ferroptosis is an iron-dependent form of regulated cell death driven by excessive phospholipid peroxidation and can occur in both epithelial and innate immune cells in the intestine, thereby affecting epithelial barrier integrity and mucosal immune homeostasis (Figure 1A).^39–42 In gastric and small-intestinal mucosal models, DHA/EPA supplementation exacerbated hypoxia-induced ferroptosis by further increasing PUFA-containing phospholipid accumulation, which, together with hypoxia-induced ALOX5 and NOX4 expression, promoted excessive lipid peroxidation.⁴³ In an acute hypobaric-hypoxia rat model, intestinal TLR4/NF-κB signaling contributed to mucosal injury and bacterial translocation, while exogenous LPS further amplified this inflammatory response (Figure 1D).⁴⁴ Intestinal mast cells may provide an additional link between hypoxic stress and epithelial barrier dysfunction (Figure 1C). Hypoxia can alter mast-cell function through HIF-1α-dependent induction of histidine decarboxylase and histamine synthesis, while cyclic hypoxia upregulates components of the FcεRI signaling pathway and primes mast cells for enhanced degranulation upon receptor stimulation.^45,46 Mast cells can subsequently impair epithelial barrier integrity through multiple mediators. Mast-cell-derived exosomal miR-223 suppresses claudin-8 expression in intestinal epithelial cells, thereby increasing epithelial permeability.⁴⁷ In addition, mast-cell tryptase increases paracellular permeability through protease-activated receptor 2 (PAR2)/β-arrestin signaling and reduces junctional adhesion molecule-A (JAM-A) expression in intestinal epithelial cells.^48,49 Consistent with these mechanisms, conditioned medium from hypoxia- or hypoxia/reoxygenation-exposed HMC-1 cells aggravated hypoxia/reoxygenation-induced barrier injury in Caco-2 cells, as indicated by increased permeability and reduced ZO-1 and occludin expression.⁵⁰ The intestinal response to hypoxia varies with the duration, severity, and pattern of oxygen deprivation.^51,52 For clarity, in this review, acute exposure refers broadly to the first hours to several days after the onset of hypoxia, whereas chronic exposure refers to sustained or recurrent hypoxia lasting weeks to months. During the early response to moderate hypoxia, HIF-1α can activate epithelial adaptive programs, including intestinal trefoil factor,⁵³ CD73⁵⁴ and claudin-1,⁵⁵ which help preserve barrier integrity and epithelial survival. Hypoxia also induces epithelial metabolic reprogramming, which may occur partly independently of HIF-1-driven glycolytic transcription.⁵⁶ With prolonged, severe, or intermittent hypoxia, however, persistent oxidative stress, inflammasome activation, lipid peroxidation, and immune-cell signaling may overwhelm these adaptive responses and progressively impair the epithelial barrier.^51,57 Thus, the effects of hypoxia should be viewed as a context-dependent continuum rather than a strict switch from protection to injury, providing the basis for the subsequent transmission of systemic inflammatory signals and disruption of sleep-regulatory circuits.

Figure 1.

Proposed pathways linking hypoxic stress to intestinal barrier dysfunction. (A) In a Caco-2 hypoxia/reoxygenation plus LPS model, increased HIF-1α/NF-κB signaling was associated with reduced ZO-1 expression and barrier injury. Hypoxia-associated ALOX5 and NOX4 expression may promote PUFA-containing phospholipid peroxidation and ferroptosis, whereas the SLC7A11/GPX4 system limits phospholipid peroxidation. (B) Hypoxia-associated oxidative stress activates cofilin and promotes F-actin depolymerization, thereby weakening the junctional scaffold. Separate macrophage-based evidence indicates that ROS-induced cofilin-1 oxidation promotes its dissociation from NLRP3 and facilitates inflammasome assembly. (C) Hypoxia or cyclic hypoxia may alter mast-cell activity through HIF-1α/HDC-dependent histamine synthesis and FcεRI priming. Mast-cell-derived exosomal miR-223 suppresses claudin-8, whereas tryptase activates PAR2/β-arrestin signaling and reduces JAM-A expression. (D) Following initial barrier injury, translocated LPS activates TLR4/NF-κB signaling and amplifies pro-inflammatory injury. Solid arrows indicate supported directional relationships, whereas dashed arrows indicate context-specific or model-derived evidence. Together, these pathways may increase epithelial permeability and facilitate the translocation of luminal bacterial products. This figure was created by FigDraw (https://www.figdraw.com) (Copyright Code: OPRYRd9139).

Abbreviations: ALOX5, arachidonate 5-lipoxygenase; F-actin, filamentous actin; FcεRI, high-affinity immunoglobulin E receptor I; GPX4, glutathione peroxidase 4; H/R, hypoxia/reoxygenation; HDC, histidine decarboxylase; HIF-1α, hypoxia-inducible factor 1 alpha; HMC-1, human mast cell line 1; IL, interleukin; JAM-A, junctional adhesion molecule-A; LPS, lipopolysaccharide; miR-223, microRNA-223; NF-κB, nuclear factor kappa B; NLRP3, NLR family pyrin domain containing 3; NOX4, NADPH oxidase 4; PAR2, protease-activated receptor 2; PUFA-PL, polyunsaturated fatty acid-containing phospholipids; ROS, reactive oxygen species; SLC7A11, solute carrier family 7 member 11; TLR4, Toll-like receptor 4; ZO-1, zonula occludens-1.

Gut Microbiota Dysbiosis and Metabolic Reprogramming

Hypoxic exposure can alter the composition, diversity, and functional output of the gut microbiota, although the magnitude and direction of these changes vary with host species, altitude, exposure duration, diet, and hypoxia pattern.^58,59 Reported changes mainly involve Firmicutes, Bacteroidetes, and Proteobacteria, but no universal phylum-level signature has yet emerged across hypoxic models.^60,61 At lower taxonomic levels, several studies have reported reductions in selected obligate anaerobes and butyrate-producing taxa under hypoxic conditions.⁶² Conversely, the expansion of Blautia A during longitudinal high-altitude exposure suggests that some microbial responses may represent adaptive remodeling rather than dysbiosis alone.⁶³ Meanwhile, facultative anaerobes and potential pathogens, including Enterobacteriaceae, Staphylococcus, Escherichia–Shigella, and Klebsiella, have been enriched in some hypoxic models, potentially contributing to microbial imbalance.^61,64,65 This structural rearrangement coincides with reduced α-diversity and distinct β-diversity partitioning compared to normoxic controls, particularly during acute high-altitude exposure.^66,67 Hypoxia-induced microbial dysbiosis can impair core metabolic functions, particularly microbial SCFA production, including butyrate production.^51,67 Butyrate is a major energy source for colonocytes and promotes tight-junction assembly in intestinal epithelial cells through AMPK-dependent mechanisms.⁶⁸ In parallel, butyrate suppresses NF-κB activation in lamina propria macrophages, thereby limiting mucosal pro-inflammatory signaling.⁶⁹ Hypoxia-associated loss of butyrate-producing bacteria may therefore weaken both epithelial barrier integrity and mucosal immune regulation.^70,71 This depletion compromises the epithelial energy supply, increases mucosal permeability, promotes bacterial translocation, and amplifies systemic low-grade inflammation.⁷² Notably, this reduction stands in contrast to mild normobaric hypoxia, which has been shown to enhance SCFA production as an adaptive metabolic response to support endurance performance.⁷³ Beyond its role in energy metabolism, hypoxia redirects tryptophan metabolism away from the synthesis of serotonin (5-HT) and melatonin,⁷⁴ neurotransmitters that are essential for sleep regulation and circadian rhythm.⁷⁵ Instead, tryptophan is preferentially diverted into the kynurenine pathway due to hypoxia-driven upregulation of indoleamine 2,3-dioxygenase 1 (IDO1).⁷⁶ This metabolic shift diminishes sleep-promoting molecules and leads to the accumulation of neurotoxic kynurenine metabolites, which enhance cortical arousal, suppress slow-wave sleep (SWS), and disrupt overall sleep architecture.^77,78 Collectively, hypoxia exerts stringent selective pressure on the gut microbiota, resulting in the loss of beneficial obligate anaerobes, the proliferation of potentially pathogenic facultative anaerobes, and a coordinated reprogramming of SCFAs and tryptophan metabolism. These interconnected changes establish a mechanistic axis that links hypoxia-induced dysbiosis to impaired intestinal barrier function, heightened systemic inflammation, and disrupted sleep–wake cycles (Figure 2).

Figure 2.

Hypoxia induces gut microbiota dysbiosis and metabolic reprogramming, leading to disrupted sleep architecture through two parallel metabolic shifts. The first track illustrates one maladaptive pattern reported in selected hypoxic models, involving reductions in obligate anaerobes and butyrate-producing taxa, together with enrichment of facultative anaerobes or potential pathogens. The second track involves a tryptophan metabolic shunt, in which hypoxia-induced upregulation of IDO1 redirects tryptophan metabolism away from serotonin and melatonin toward kynurenine metabolites. Together, these pathways contribute to disrupted sleep–wake cycles and suppression of SWS. This figure was created by FigDraw (https://www.figdraw.com) (Copyright Code: TOPUP4fbaf).

Abbreviations: 5-HT, 5-hydroxytryptamine; BBB, blood–brain barrier; IDO1, indoleamine 2,3-dioxygenase 1; LPS, lipopolysaccharide; SCFA, short-chain fatty acid; SWS, slow-wave sleep.

Neuroinflammation and Central Sleep Circuit Dysfunction

The combination of increased systemic exposure to LPS following intestinal barrier injury and reduced availability of anti-inflammatory metabolites such as butyrate may promote persistent low-grade systemic inflammation.^70,79 This state is characterized by increased circulating pro-inflammatory cytokines, including TNF-α, IL-1β, and IL-6. Peripheral inflammatory signals may communicate with the CNS through three principal anatomical routes.

Blood–Brain Barrier Pathway

The first pathway entails the direct diffusion of TNF-α, IL-1β, IL-6, and LPS across a compromised BBB (Figure 3A), which becomes permeable to circulating cytokines and LPS under chronic hypoxic stress, as evidenced by both clinical and experimental models of intermittent hypoxia and chronic mild hypoxia.⁸⁰ This disruption of the barrier is driven by a cascade of interconnected molecular events: the expression of BBB tight junction proteins, particularly claudin-5, occludin, and zonula occludens-1 (ZO-1), is diminished, altered in subcellular localization, or degraded in brain microvascular endothelial cells subjected to hypoxia.^81,82 Multiple regulatory mechanisms underlie this breakdown of tight junctions. The accumulation of HIF-1α in hypoxic endothelial cells transcriptionally downregulates tight junction proteins while upregulating matrix metalloproteinases (MMPs) and VEGF, which actively remodel the basement membrane and junctional complexes.^83–85 Episodes of hypoxia-reoxygenation further enhance BBB permeability through oxidative stress, which triggers direct lipid peroxidation of endothelial membranes, cytoskeletal reorganization, and the opening of intercellular gaps.⁸¹ In addition to active degradation, hypoxia exerts further regulatory effects through epigenetic mechanisms, such as miR-101, which post-transcriptionally suppresses claudin-5 and VE-cadherin expression in brain microvascular endothelium, thereby destabilizing junctional integrity and promoting permeability to immune mediators.⁸⁶ Collectively, these overlapping and temporally distinct mechanisms lower the threshold for peripheral inflammatory mediators to access the CNS parenchyma, establishing the BBB as a permissive gateway for gut-derived signals to initiate neuroinflammation and disrupt central sleep-regulatory circuits.

Figure 3.

Schematic illustration of three CNS pathways mediating hypoxia-induced neuroinflammation and sleep disruption. (A) The blood–brain barrier (BBB) pathway involves hypoxia-associated changes in brain microvascular endothelial cells, including HIF-1α-related signaling, increased MMP and VEGF expression, tight-junction disruption, and increased BBB permeability, which may facilitate the entry of circulating inflammatory mediators into the brain. (B) The circumventricular organ (CVO) pathway involves direct sensing of circulating pro-inflammatory cytokines and lipopolysaccharide (LPS) by structures lacking a conventional BBB, including the subfornical organ (SFO) and area postrema (AP), thereby promoting microglial priming and neuroinflammatory signaling. (C) The vagal afferent pathway involves hypoxia-associated reactive oxygen species generation and increased NMDAR1 expression, which may alter vagal sensory responsiveness and signaling through the nucleus tractus solitarius (NTS) to central sleep-regulatory nuclei. Together, these pathways may reduce slow-wave sleep, increase wakefulness, and promote sleep fragmentation during high-altitude hypoxia. This figure was created by FigDraw (https://www.figdraw.com) (Copyright Code: PURPI07779).

Abbreviations: AP, area postrema; BBB, blood–brain barrier; CNS, central nervous system; CR3, complement receptor 3; CVOs, circumventricular organs; GABA, gamma-aminobutyric acid; HIF-1α, hypoxia-inducible factor-1α; HT, hypothalamus; LC, locus coeruleus; LPS, lipopolysaccharide; MHC II, major histocompatibility complex class II; MMPs, matrix metalloproteinases; NMDAR1, N-methyl-D-aspartate receptor subunit 1; NTS, nucleus tractus solitarius; ROS, reactive oxygen species; SFO, subfornical organ; SWS, slow-wave sleep; TJ, tight junction; VEGF, vascular endothelial growth factor.

Circumventricular Organs as Sensory Gateways

The circumventricular organs (CVOs; Figure 3B) are specialized midline structures situated around the third and fourth ventricles. While the BBB typically limits the entry of blood-derived substances, the CVOs are devoid of these endothelial barriers and possess fenestrated capillaries. This anatomical characteristic enables them to directly transduce information between the blood circulation and the brain.⁸⁷ Such unique anatomy allows circulating molecules—including LPS, TNF-α, IL-1β, and IL-6—to diffuse from the bloodstream into the CVO parenchyma, facilitating direct contact with neurons, microglia, and astrocytes.⁸⁸ Among the sensory CVOs, the area postrema (AP) and the subfornical organ (SFO) have been the focus of extensive research concerning immune-to-brain communication. In the AP, this direct interaction elicits a robust response. Following exposure to systemic LPS, microglial cells in the AP become activated, displaying rapid intracellular calcium transients and releasing proinflammatory cytokines such as TNF-α and IL-6. This evidence indicates that the CVOs function not merely as passive windows but as active sensors and transducers of peripheral inflammation.⁸⁹ Under normoxic conditions, the LPS-sensing mechanism is calibrated to detect high levels of circulating endotoxin. Prolonged hypobaric hypoxia alters the immune profile of the AP directly. When exposed to hypoxic conditions, activated microglia/macrophages exhibit increased expression of CR3, a co-receptor for TLR4, and major histocompatibility complex class II (MHC II), indicating enhanced cellular activation and antigen presentation capacity. CR3 is recognized for enhancing TLR4-triggered cytokine production. Consequently, in the presence of chronic low-grade inflammation induced by gut-derived LPS, the same LPS concentration in the bloodstream may provoke an exaggerated pro-inflammatory response from sensitized AP microglia, a phenomenon known as “microglial priming.” This heightened reactivity likely contributes to the continuous activation of downstream sleep-wake regulatory centers.⁹⁰

In the subfornical organ (SFO), peripheral administration of LPS induces proinflammatory cytokines rapidly, including interleukin-1β (IL-1β).⁹¹ Activated CVO cells then transmit signals to neighboring brain nuclei through established neural pathways. Specifically, the AP projects efferent signals to the nucleus tractus solitarius (NTS) and the parabrachial nucleus,⁹² while the SFO connects to the hypothalamic paraventricular nucleus (PVN) and supraoptic nucleus.⁹³ These brain regions play crucial roles in coordinating autonomic, neuroendocrine, and behavioral responses to systemic inflammation. Notably, the CVO pathway functions as a blood-borne, non-neural alternative system even in the absence of other pathways like the vagus nerve.⁹⁴ In conditions of prolonged hypoxia-induced chronic low-grade inflammation, the CVOs may become sensitized, displaying heightened cytokine responses that sustain the activation of downstream sleep-wake regulatory centers. Ultimately, the integration of CVO-mediated signals with inputs from the vagal and BBB pathways in the hypothalamus and brainstem establishes a redundant, resilient, and adaptable relay system. This mechanism effectively translates peripheral inflammation originating from the gut into central neuroinflammation, leading to the characteristic sleep disturbances observed in high-altitude insomnia.

Vagal Afferent Pathway

The vagus nerve provides a neural communication route between the gut and the central nervous system (Figure 3C). Vagal afferent fibers end in the intestinal lamina propria, expressing TLR4 for LPS, free fatty acid receptor 3 (FFAR3) for SCFAs, and 5-HT receptors.^95,96 When exposed to normoxic conditions, the activation of these receptors triggers action potentials that travel through the nodose ganglion to the nucleus tractus solitarius (NTS), then to the parabrachial nucleus, and finally to the hypothalamus and locus coeruleus.⁹⁷ This signaling pathway operates independently of the bloodstream and functions on a rapid timescale.

Hypoxia induces significant alterations in this pathway at various levels. Chronic intermittent hypoxia (CIH) enhances reactive oxygen species (ROS) production through NADPH oxidase activity in vagal afferents, sensitizing TLR4-mediated signaling.⁹⁸ Consequently, even minimal levels of luminal LPS, typically subthreshold under normoxic conditions, may elicit heightened responses in vagal afferents during hypoxic stress, potentially amplifying the transmission of inflammatory signals from the gut to the brain. Acute severe hypobaric hypoxia increased N-methyl-D-aspartate receptor subunit 1 (NMDAR1) immunoreactivity in rat nodose ganglion neurons.⁹⁹ Separately, 24-h sustained hypoxia increased TRPM3 mRNA expression and enhanced TRPM3-mediated Ca²⁺ influx in rat nodose ganglion neurons.¹⁰⁰ While NMDAR and TRPM3 minimally affect baseline vagal firing under normoxic conditions, their upregulation due to hypoxia suggests that the vagal gateway becomes hyper-responsive to incoming signals, further facilitating the relay of gut-derived inflammatory signals to the brain. Exposure to high altitudes diminishes systemic vagal tone, as evidenced by reduced heart rate variability.¹⁰¹ Under normoxic conditions, efferent vagal activity supports an anti-inflammatory cholinergic reflex that limits peripheral cytokine release. The decrease in vagal tone at high altitudes may weaken this regulatory mechanism, potentially allowing unchecked escalation of gut-derived inflammation. In essence, although the vagus nerve maintains its rapid conduction under hypoxia anatomically, its functionality is dynamic. Hypoxia is likely to heighten afferent sensing, boost ganglionic excitability, and diminish efferent anti-inflammatory capability. The overall impact, whether facilitating or reducing gut-to-brain inflammatory signaling, is yet to be established, but current evidence suggests a pro-inflammatory gain-of-function that could hasten the shift from intestinal dysbiosis to central neuroinflammation and disrupted sleep.

Temporal integration across the entire GBA provides a comprehensive perspective. Initially, chronic hypoxia compromises the intestinal barrier, resulting in systemic exposure to LPS. This exposure triggers microbial dysbiosis, characterized by decreased butyrate production and altered tryptophan metabolism. Consequently, systemic low-grade inflammation develops, impacting the BBB, CVO, and vagal pathways that relay signals to the CNS. Acute and chronic inflammation have contrasting impacts on sleep regulation. IL-1β and TNF-α are well-established somnogenic agents that enhance non-rapid eye movement (NREM) sleep during acute immune responses.¹⁰² In contrast, persistent low-grade neuroinflammation, such as that associated with sustained gut-derived LPS translocation under hypoxic conditions, may disrupt sleep–wake continuity rather than promote restorative sleep. Persistent inflammatory signaling may also engage the hypothalamic–pituitary–adrenal axis, increasing corticotropin-releasing hormone and cortisol signaling, which favors arousal, whereas growth hormone-releasing hormone promotes non-rapid eye movement and slow-wave sleep. A shift from GHRH-mediated sleep promotion toward CRH/cortisol-mediated arousal may therefore contribute to reduced slow-wave sleep and sleep fragmentation under sustained hypoxic stress. Prolonged TNF-α signaling in the preoptic area can impair the function of the ventrolateral preoptic nucleus, a key sleep-promoting center.¹⁰³ In parallel, stress-related CRH signaling may recruit orexin neurons and downstream arousal networks; however, inflammatory effects on the orexin system appear to be context-dependent, because experimental TNF-α exposure can also suppress hypothalamic orexin expression.^104,105 Persistent neuroinflammatory and neuroendocrine signaling may activate microglia and destabilize the balance between the orexin/locus coeruleus (LC) arousal system and gamma-aminobutyric acid (GABA)-ergic sleep-promoting mechanisms.^106,107 The resulting electroencephalogram (EEG) pattern, marked by reduced delta power, decreased spindle density, increased beta/gamma activity, and heightened fragmentation, manifests as the clinical phenotype of high-altitude insomnia.¹⁰⁸ This intricate cascade illustrates that hypoxia-induced sleep disruption is not a solitary central event but rather the integrative outcome of a multifaceted failure within the GBA (Figure 3).

Evidence Chain Linking Gut Microbiota to High-Altitude Insomnia

Current evidence relevant to the relationships among hypoxia, gut microbial alterations, and sleep–wake disturbances comprises experimental animal studies, observational human studies, and proof-of-concept microbiota-targeted interventions (Table 1). Experimental evidence suggests that hypoxia-induced alterations in the gut microbiota can modify sleep–wake regulation. Badran et al demonstrated that fecal microbiota transplantation from mice exposed to chronic intermittent hypoxia increased sleep duration and the frequency of longer sleep bouts during the dark phase in naïve recipients, indicating that the resulting microbial alterations can transmit an increased sleep propensity even in the absence of concurrent hypoxic exposure.¹⁰⁹ More directly relevant to insomnia, transplantation of gut microbiota from patients with insomnia to germ-free mice induced insomnia-like sleep disturbances and reduced circulating butyrate levels, whereas butyrate supplementation reversed these abnormalities by modulating orexin neuronal activity in the lateral hypothalamus.³² Together, these findings suggest that hypoxia-responsive dysbiosis and microbiota-derived metabolites may provide complementary pathways through which the gut microbiota contributes to abnormal sleep regulation. Additional animal studies provide mechanistic support for this association. In mice, CIH altered gut microbial composition and was accompanied by systemic inflammation and metabolic dysfunction.¹¹⁰ Intermittent hypoxia and hypercapnia also reshaped the gut microbiome and metabolome, including bile acid and fatty-acid profiles.¹¹¹ In guinea pigs, CIH-induced microbial alterations coincided with reduced brainstem noradrenaline levels and impaired cardiorespiratory regulation.¹¹² However, these models primarily mimic CIH associated with OSA rather than prolonged high-altitude hypoxia, thus limiting the direct applicability of these results.

Table 1.

Evidence Linking the Gut–Brain Axis to Sleep-Related and Systemic Outcomes Under Different Hypoxic Conditions

Stratum	Study Design	Model/Population	Hypoxic Exposure/Clinical Definition	Sample Size	Gut-Related Findings	Relevant Findings (Sleep/CNS or Systemic Outcomes)	Proposed Pathway or Interpretation	Ref.
I. Interventional evidence (FMT or germ-free models)
	Interventional (FMT)	Male C57BL/6J donor and naïve recipient mice	Donor CIH: 21↔6.1% O2, 20 cycles/h, 12 h/d × 6 wk; FMT under normoxia	7–8 recipient mice/group	FMT-IH recipients developed a microbial community distinct from FMT-room-air recipients	Dark-phase wake time decreased (45.2 ± 1.6% vs 58.3 ± 1.6%; p<0.0001), with longer dark-phase sleep bouts (672.1 ± 87.9 vs 427.4 ± 58.3 s; p<0.05)	Transfer of CIH-associated microbiota reproduced sleep-pattern alterations in naïve recipient mice	[109]
	Interventional (germ-free model)	ApoE−/− mice (GF vs SPF)	IHC: O2 21↔8%/CO2 0.5↔8%, 10 h/d × 10 wk; HFHC	N/A	Atherosclerosis markedly reduced in GF mice; ↑ Akkermansiaceae, ↓ Muribaculaceae	↓ Aortic lesions; no change in pulmonary artery	Microbial colonization modulated atherosclerosis in a vascular-bed-dependent manner	[121]
II. Preclinical mechanistic evidence
	Controlled animal experiment	Adult male Wistar rats	Simulated OSA-IH; sampling at wk 2 and 4; FiO2/cycle NR	12/group; 24 rats in total	Intestinal mucosal injury, bacterial translocation to MLNs, and increased ROS/MDA	MLN structural damage; ↑ serum DAO	Intermittent hypoxia-associated barrier injury and bacterial translocation were accompanied by oxidative injury in MLNs	[122]
	Controlled animal experiment	C57BL/6J mice	CIH × 6 wk; FiO2, cycle frequency and daily duration NR	10/10	↑Bacteroides and Desulfovibrionaceae; ↓ Bifidobacterium	Systemic inflammation (↑ IL-6, ↑ TNF-α)	CIH-induced dysbiosis was associated with systemic inflammation and predicted metabolic dysfunction	[110]
	Controlled animal experiment	Ldlr−/− mice	IHH: O2 21↔8%/CO2 0.5↔8%, 10 h/d × 6 wk; HFD	8/group	↑ Clostridia; altered bile acids, enterolignans, fatty acids	No direct sleep outcome assessed; study modeled an OSA-associated cardiometabolic environment	IHH and high-fat diet jointly altered the microbiome–metabolome profile	[111]
	Controlled animal experiment	Guinea pigs	FiO2 21↔6.5%, 10-min cycles, 8 h/d × 12 d	10/group	↑ Bacteroidetes, ↓ Firmicutes; reduced richness	↓ Brainstem noradrenaline; abnormal heart rate control; ↓ respiratory variability	Microbiota–gut–brainstem axis independent of chemoreflex	[112]
	Controlled animal experiment	C57BL/6J mice	O2 21↔5%, 60 cycles/h, 6 h/d × 6 wk	10/group	↑ Firmicutes, ↓ Bacteroidetes, ↓ Proteobacteria	No sleep, cardiac-function, or CNS outcome assessed	Intermittent hypoxia alone altered gut microbial ecology in mice	[123]
III. Observational evidence in OSA
	Cross-sectional	Adults with OSAHS (n = 93)	PSG-defined OSAHS: AHI 5–15, 15–30, or ≥30 events/h; controls AHI≤5	93/20	Reduced SCFA-producing taxa and enrichment of potential pathogens	↑ IL-6, ↑ homocysteine (correlated with Lactobacillus)	OSAHS severity was associated with dysbiosis and inflammatory/metabolic abnormalities	[113]
	Cross-sectional	Adults with severe OSA + hypertension (n = 60)	Severe OSA: AHI≥30 events/h; 27 without hypertension and 33 with hypertension; controls AHI≤5	60/12	↓ SCFA producers; ↓ arginine/proline metabolism	↑ N1, ↓ N2/N3; altered mTOR signaling	Gut microbial, sleep-architecture, and PBMC mTOR alterations co-occurred in severe OSA-associated hypertension	[124]
	Cross-sectional	Adults with OSA (n = 113)	PSG-defined OSA; hypoxic burden assessed by T90	97/16	Reduced diversity and SCFA-producing taxa; ↓ Gemmiger, Faecalibacterium, and Gemmiger formicilis	T90 (nocturnal hypoxia time) strongly associated with microbiota shifts	Duration of nocturnal hypoxaemia was associated with the degree of gut dysbiosis	[115]
	Cross-sectional	Japanese adults with OSA (n = 74)	OSA severity assessed by 3% ODI; mean 39.9 ± 20.0 events/h	74 (no control)	↑ Actinobacteria (Bifidobacteriaceae), ↓ Firmicutes	ODI positively correlated with Actinobacteria	OSA severity measured by 3% ODI was associated with phylum-level microbial composition	[116]
IV. Observational evidence in high-altitude populations
	Longitudinal cohort with supporting animal experiments	Healthy Han adults traveling from lowland (243 m) to high-altitude (3,658 m) and back (n = 45)	243→3,658 m; >2-mo exposure within a 108-d longitudinal study	45	↓ species/functional diversity, ↑ functional redundancy; overgrowth of Blautia A	Human cohort: species diversity↓, functional diversity↓, functional redundancy↑; Animal experiment: Blautia A-fed mice: ↑ intestinal health, ↑ acclimatization phenotype, ↑ blood oxygen saturation, ↓ pulmonary arterial pressure, ↓ lung injury	Longitudinal human findings identified Blautia A as a reproducible responder; animal supplementation supported a role in hypoxic acclimatization	[63]
	Cross-sectional	Indigenous high-altitude residents (n = 211)	Lifelong residence at 2,000, 3,000 or 4,000 m	211	At 4,000 m: ↑ SCFA producers (Roseburia, Blautia, Coprococcus)	↑ Resting delta power; ↑ P3 amplitude	Altitude-associated microbial and neurophysiological patterns were correlated but do not establish causality	[118]
	Cross-sectional, multi-group comparison	Plain: 1,200 m; high altitude: 4,300 m for 4 or 6 d, >3 mo, or lifelong residence; additional group assessed 3 mo after return to the plain	1,200 vs 4,300 m: 4 d, 6 d or >3 mo; plus 3 mo post-return	393	High-altitude residence rapidly and persistently altered α/β diversity, taxonomic composition, and predicted microbial functions	Alterations in multiple blood clinical indices; sleep outcomes were not measured	Altitude exposure duration was associated with progressive and persistent microbiota remodeling	[58]
V. Pediatric observational evidence
	Case–control	Children with OSAS (n = 16)	PSG-defined pediatric OSAS versus healthy controls	8/8	↓ Microbial diversity; ↑ Proteobacteria, Clostridiaceae, Klebsiella	Sleep parameters correlated with diversity	Pediatric OSAS was associated with altered gut microbial composition; the pilot sample precludes causal inference	[117]

Abbreviations: AHI, apnea–hypopnea index; ApoE, apolipoprotein E; BP, blood pressure; CIH, chronic intermittent hypoxia; CNS, central nervous system; DAO, diamine oxidase; FiO₂, fraction of inspired oxygen; FMT, fecal microbiota transplantation; GF, germ-free; HFHC, high-fat, high-cholesterol; HFD, high-fat diet; IHC, intermittent hypoxia/hypercapnia; IH, intermittent hypoxia; IHH, intermittent hypoxia and hypercapnia; IL, interleukin; Ldlr, low-density lipoprotein receptor; MDA, malondialdehyde; MLN, mesenteric lymph node; mTOR, mechanistic target of rapamycin; N/A, not applicable; NR, not reported; ODI, oxygen desaturation index; OSA, obstructive sleep apnea; OSAHS, obstructive sleep apnea–hypopnea syndrome; PBMC, peripheral blood mononuclear cell; PSG, polysomnography; RA, room air; ROS, reactive oxygen species; SCFA, short-chain fatty acid; SpO₂, peripheral oxygen saturation; SPF, specific pathogen-free; T90, percentage of sleep time with oxygen saturation below 90%; TMAO, trimethylamine N-oxide; TNF-α, tumor necrosis factor-alpha.

Human observational data primarily derive from patients with OSA. In a cross-sectional study, patients with OSA exhibited gut microbial dysbiosis characterized by reductions in several short-chain fatty acid-producing taxa, enrichment of potential pathogens, and elevated circulating IL-6 levels.¹¹³ A separate study integrating gut microbiota profiling with polysomnography found that patients with a Prevotella-dominant enterotype and an apnea–hypopnea index of ≥15 events/h exhibited more stage N1 sleep, less stage N3 sleep, and greater sleep fragmentation than those with milder disease.¹¹⁴ Additional cross-sectional studies associated indices of nocturnal hypoxemia with specific microbial features: the proportion of sleep time spent below 90% oxygen saturation was associated with reduced microbial diversity and depletion of taxa such as Faecalibacterium and Gemmiger,¹¹⁵ whereas the 3% oxygen desaturation index was associated with Actinobacteria, Firmicutes, and Bifidobacteriaceae abundance in a Japanese OSA cohort.¹¹⁶ A small pediatric case–control study likewise identified reduced microbial diversity and associations between specific microbial features and polysomnographic parameters in children with OSA.¹¹⁷ However, OSA cohorts differ substantially from otherwise healthy individuals exposed to high altitude because obesity, metabolic abnormalities, upper-airway obstruction, and recurrent sleep fragmentation may independently influence the gut microbiota. Accordingly, these studies support the biological plausibility of interactions among intermittent hypoxia, gut dysbiosis, and altered sleep architecture but do not provide direct evidence for high-altitude insomnia.

Observational evidence from high-altitude populations further supports associations among hypobaric hypoxia, gut microbial composition, and sleep-related outcomes. In a cross-sectional study of 211 indigenous residents living at altitudes of 2,000, 3,000, and 4,000 m, participants at 4,000 m exhibited poorer self-reported sleep quality, enhanced resting-state EEG delta power and frontal–occipital functional connectivity, and enrichment of short-chain fatty acid-producing genera, including Roseburia, Blautia, and Coprococcus. The abundances of Blautia and Dorea were positively associated with delta-band functional connectivity, which was in turn associated with higher Pittsburgh Sleep Quality Index scores.¹¹⁸ These findings indicate coordinated changes in microbial composition, resting brain activity, and sleep-related outcomes, although they do not establish a direct microbiota–sleep relationship. In a cross-sectional comparison of 393 Han and Tibetan individuals with different durations of plateau residence, microbial composition changed within 4–6 days of high-altitude exposure, and individuals who had returned to the lowlands after prolonged plateau residence retained an altitude-associated microbial profile for at least three months.⁵⁸ A separate 108-day longitudinal study of 45 healthy adults exposed to elevations above 3,600 m demonstrated reduced microbial species and functional diversity together with an expansion of Blautia A during high-altitude exposure.⁶³ Complementary mouse experiments in the same study showed that Blautia A supplementation improved oxygen saturation and reduced pulmonary arterial pressure and lung injury, potentially through anti-inflammatory and intestinal barrier-protective effects.⁶³ However, the latter two studies did not assess sleep outcomes, and the study by Bai et al used resting-state EEG rather than polysomnographic sleep recordings. Thus, current human evidence demonstrates concurrent altitude-associated changes in gut microbial composition and sleep-related measures but does not establish that microbial alterations cause high-altitude insomnia.

Microbiota-targeted interventions provide additional proof-of-concept evidence. In a mouse model of high-altitude sleep disturbance, oral quercetin nanoparticles incorporated into hydrogel microspheres prolonged sleep duration, increased the abundance of Lactobacillus and Lachnospira, and reduced intestinal and systemic inflammatory responses. These benefits were abolished following antibiotic-mediated depletion of the gut microbiota, supporting a microbiota-dependent effect.¹¹⁹ In a CIH mouse model, melatonin partially normalized the altered gut microbial composition, preserved goblet cells and intestinal tight-junction proteins, and reduced intestinal permeability. Mechanistically, these effects were accompanied by inhibition of JAK2/STAT3 signaling, reduced pathological Th17 differentiation, and attenuation of systemic low-grade inflammation.¹²⁰ However, this study did not assess sleep outcomes. No human randomized controlled trial has yet evaluated a microbiota-targeted intervention for high-altitude insomnia using polysomnography as the primary outcome.

Diagnostic Approaches for Hypoxia-Induced Insomnia

Microbial Compositional Biomarkers

Identifying non-invasive biomarkers is crucial for diagnosing hypoxia-induced insomnia associated with gut microbiota. Several studies have developed diagnostic models that utilize gut microbial composition to identify sleep disorders. In cases of general insomnia, a random forest classifier achieved an area under the curve (AUC) of 0.87, with Bacteroides and Clostridiales identified as the most discriminative features.²⁹ For hypoxia-related sleep conditions, including obstructive sleep apnea-hypopnea syndrome (OSAHS), a microbial dysbiosis index distinguished patients from controls with an AUC of 0.789; notably, reduced levels of short-chain fatty acid (SCFA)-producing bacteria, such as Lactobacillus and Ruminococcus, correlated with disease severity.¹¹³ Similarly, severe OSA was characterized by diminished levels of Gemmiger and Faecalibacterium, which were associated with the hypoxia burden (T90).¹¹⁵ Additionally, post-stroke sleep disorders could be predicted by the presence of Blautia and Streptococcus, yielding an AUC of 0.768.¹²⁵ Together, these models show that gut microbial signatures can distinguish sleep disorders from healthy conditions effectively. Nevertheless, these models were developed in heterogeneous non-altitude cohorts, including individuals with insomnia, OSAHS, or post-stroke sleep disorders; therefore, their performance cannot be extrapolated directly to high-altitude insomnia.

Metabolite Biomarkers

Metabolic profiling has identified potential biomarkers for insomnia, including reduced fecal SCFAs like acetate, propionate, and butyrate in insomnia patients, with a possible age dependency.^126,127 Additionally, the tryptophan-kynurenine pathway is noteworthy, as tryptophan is a serotonin precursor while kynurenines impact sleep behavior; elevated plasma kynurenine has been associated with delayed circadian timing.^128,129 Integration of multi-omics data has highlighted changes in glycerophospholipid and glutathione metabolism, emphasizing Prevotella abundance as a significant factor.³⁰

Intestinal Barrier Injury Markers

Hypoxia elevates circulating I-FABP (indicative of enterocyte damage) and LPS in healthy volunteers subjected to simulated altitude¹³⁰ and in rat models.⁷⁹ In patients with OSA, serum levels of D-lactate and I-FABP are increased and correlate with the apnea-hypopnea index (AHI) and the lowest oxygen saturation (SpO₂).¹³¹ I-FABP, zonulin, and LPS may function as blood-based markers of gut barrier integrity during hypoxic stress; however, their specificity for insomnia remains uncertain.

High-Altitude Specific Biomarkers

Indigenous populations residing at an altitude of 4,000 meters demonstrate an increased prevalence of short-chain fatty acid (SCFA)-producing bacteria, including Roseburia, Blautia, and Coprococcus. Importantly, the abundance of Blautia is inversely correlated with sleep disturbances. Acute hypoxia exposure leads to a reduction in α-diversity and Bifidobacterium levels, while an overgrowth of Blautia A appears to facilitate host acclimatization.¹¹⁸ A meta-analysis of 668 16S rRNA samples from populations on the Qinghai-Tibet Plateau has identified robust gut microbial signatures—particularly within the Ruminococcaceae and Lachnospiraceae families—that are associated with high-altitude adaptation.⁷⁰ These taxa are recognized as SCFA producers and have been linked to metabolic and immune modulation, positioning them as plausible candidate biomarkers for hypoxia-related sleep disturbances. However, their diagnostic performance for insomnia has not been directly assessed, and it remains uncertain whether they can differentiate adaptive from maladaptive responses to hypoxia.

Integrated Diagnostic Framework and Future Directions

Diagnostic models utilizing gut microbial composition have demonstrated promising accuracy in identifying sleep disorders. An AUC of 0.87 for diagnosing insomnia was achieved by a random forest classifier, with Bacteroides and Clostridiales identified as key discriminators.²⁹ In the case of OSAHS, a microbial dysbiosis index was able to differentiate patients from controls with an AUC of 0.789.¹¹³ Furthermore, a predictive model designed for post-stroke sleep disorders yielded an AUC of 0.768.¹²⁵ It is important to note that these models were developed in heterogeneous non-altitude cohorts, including patients with insomnia, OSAHS, and post-stroke sleep disorders, and their performance therefore cannot be extrapolated directly to high-altitude insomnia.

An integrated diagnostic framework could enhance the existing International Classification of Sleep Disorders, 3rd edition (ICSD-3) criteria by incorporating three key elements: objective measures of hypoxia exposure, such as T90; characteristic dysbiosis, which includes a reduction in SCFA producers and an increase in pro-inflammatory taxa; and biomarker evidence, exemplified by low butyrate levels alongside elevated I-FABP or LPS.^122,132,133 Validation of this framework in large prospective cohorts at high altitude is essential. A significant translational obstacle remains: many potential markers depend on time-consuming, lab-based techniques like 16S sequencing and mass spectrometry, which are not suitable for field use. While point-of-care technologies are available for various biomarkers, such as an electrochemical biosensor for I-FABP^134,135 and wearable devices for salivary melatonin and cortisol,¹³⁶ none have been tailored for high-altitude applications. Closing this gap in implementation is crucial for translating microbiome findings into actionable diagnostic tools for high-altitude insomnia. However, before these tools can be deployed, their performance must be validated in prospective high-altitude cohorts, and their integration into clinical decision-making requires evidence that microbiome-based stratification improves outcomes—a question that ultimately depends on successful GBA-targeted RCTs.

From Bench to Bedside: Intervention Evidence and Translational Priorities

Existing Intervention Strategies: Evidence Assessment

Intervention studies directly examining the GBA under hypoxic conditions with sleep as the primary endpoint are scarce. Specifically, there is a lack of substantial evidence, and notably, no human trial conducted at high altitudes has utilized polysomnography as a primary measure (Table 2).

Table 2.

Interventional Studies Targeting the Gut–Brain Axis to Improve Sleep or Cognitive Function Under Hypoxic versus Normoxic Conditions

Condition	Intervention Category	Study	Model/Population	Intervention (Dose, Route, Duration)	Comparator	Sleep/Cognitive Outcome (Key Quantitative Results)	Gut Microbiota Outcome (Key Quantitative Results)	Ref.
Hypoxia	Probiotic (human)	Yu et al, 2025	Healthy adults ascending to 3,800 m (n=17)	Oxxyslab/SLAB51 (eight-strain probiotic mixture; 8 × 1011 live bacteria/dose; oral; up to eight post-meal doses over 4 days at 3,800 m)	Matched placebo	Higher nocturnal SpO2 (81.9 ± 4.1% vs 76.9 ± 6.6%; p = 0.011); no between-group differences in AHI or ODI; sleep quality and cognitive outcomes not assessed	Not reported	[137]
Hypoxia	Probiotic (animal)	Liu J et al, 2019	Sprague-Dawley rats, CIH + high-salt diet	LGG-fermented milk (2 mL/day, 1 × 109 CFU/mL; intragastric; 4 weeks after 6-week CIH plus high-salt-diet modelling)	Post-model normal-diet and high-salt-diet groups without LGG	↓ BP, ↓ TMAO, restored Th1/Th2 balance	Restored depleted Lactobacillus	[144]
Hypoxia	Nanoparticle (animal)	Wu et al, 2024	C57BL/6J mice, hypobaric hypoxia (5,500 m, 72 h) (n=12/group)	Quercetin nanoparticles (QNP@HMs, 50 mg/kg, oral gavage, 7 d pre‑treatment)	Hypobaric hypoxia model receiving vehicle; additional antibiotic-depleted groups with or without QNP@HMs	Sleep duration: 448 vs 285 min (p<0.001); recognition index: 0.72 vs 0.49 (p<0.01); TNF‑α: 145 vs 312 pg/mL; effect abolished by antibiotics	↑ Lactobacillus, ↑ Lachnospira (effect abolished by antibiotics)	[119]
Hypoxia	Probiotic (animal, FMT)	Badran M et al, 2023	C57BL/6J mice	IH- or room-air-donor fecal slurry (100 μL, oral gavage, three times weekly for 6 weeks) with or without VSL#3 (4 × 109 CFU)	RA-FMT, IH-FMT, RA-FMT + VSL#3, and IH-FMT + VSL#3 groups	↑ BP and coronary dysfunction partially reversed	IH-FMT dysbiosis partially reversed by VSL#3	[145]
Hypoxia	Melatonin (animal)	Li X et al, 2023	C57BL/6J mice, CIH	Melatonin (30 mg/kg, oral; 5 weeks during a 10-week CIH exposure)	Normoxic control and untreated CIH groups	↓ Th17 differentiation; ↓ STAT3 phosphorylation; intestinal barrier repair	Restored Clostridium, Akkermansia, Bacteroides; ↓ Desulfovibrio	[120]
Hypoxia	TCM formula (animal)	Zhou et al, 2025	Adult male Drosophila, acute hypobaric hypoxia (4,000 m, 4 h) (n=50/group)	Danggui Buxue Decoction (0.5–2.0% w/v in medium, 7 d)	Normoxia; hypoxia+vehicle	Sleep/24h: 980 vs 615 min (p<0.001); sleep bouts: 34 vs 61 (p<0.01); 5‑HT1A/1B mRNA ↑2.1‑fold	Not reported	[141]
Hypoxia (FMT)	FMT intervention (animal)	Badran et al, 2020	Naïve C57BL/6J mice (n=7‑8/group)	Fecal slurry from CIH‑exposed donors (6 wk IH; oral gavage, 2×/wk, 3 wk)	FMT from room air donors	Dark‑phase wake: 45.2% vs 58.3% (p<0.0001); sleep bout length (dark): 672.1 vs 427.4 s (p<0.05); short bouts (30 s): 57.7 vs 93.7 (p<0.001)	Taxonomic profile recapitulating donor IH: ↑ Lachnospiraceae, ↑ Prevotella, ↓ Alistipes	[109]
Hypoxia (FMT)	FMT intervention (animal)	Li W et al, 2025	Naïve C57BL/6J mice (n=6/group)	Fecal slurry from sustained hypoxia donors (4,000 m, 28 d; oral gavage, 2 wk)	FMT from control donors; FMT‑Con	2‑h recognition index ↓ (p<0.05); freezing % ↓ (p<0.01)	↓ Ligilactobacillus, ↓ Muribaculum	[146]
Normoxia	FMT-based protocol (human)	Gao et al, 2026	Adults with chronic insomnia disorder, n=80	Short-course antibiotic pretreatment followed by oral donor-microbiota capsules	Placebo capsules without antibiotic pretreatment	PSG sleep efficiency improved by 13.9 percentage points versus placebo; 95% CI, 7.29–20.41; p=0.003	Increased microbial richness and diversity; altered community structure	[143]
Normoxia	Postbiotic (animal)	Szentirmai et al, 2019	Adult male Wistar rats (n=8/group)	Sodium butyrate (1 µmol, portal vein injection, single dose)	Saline	NREM sleep ↑70% (from 48% to 81% of total sleep time) within 6 h (p<0.001)	Not reported	[26]
Normoxia	TCM formula (background)	Zhang et al, 2024	PCPA‑induced insomnia rats	Suanzaoren Decoction (3.6 or 36 g/kg/day; route not reported; 4 weeks)	Model control	Improved sleep (behavioral)	Restored fecal SCFAs (acetate, propionate, butyrate); regulated GABA/glutamate metabolism	[138]
Normoxia	TCM formula (background)	Chu et al, 2025	PCPA‑induced insomnia mice	Baihe Dihuang Tang (9.315, 18.63, or 37.26 g/kg; intragastric once daily; 21 days)	Model control	Reduced sleep latency and improved behavioral and pentobarbital-assisted sleep measures; no EEG- or PSG-based sleep outcome assessed	↑ Fusobacteria, ↑ Firmicutes; ↓ Alistipes; restored neurosteroids and serotonin levels	[140]

Notes: FMT involved transfer of microbiota from hypoxia-exposed donors to naïve or antibiotic-pretreated recipients, as specified in the original study.

Abbreviations: AHI, apnea–hypopnea index; BP, blood pressure; CFU, colony-forming unit; CIH, chronic intermittent hypoxia; EEG, electroencephalography; FMT, fecal microbiota transplantation; GABA, gamma-aminobutyric acid; IH, intermittent hypoxia; LGG, Lactobacillus rhamnosus GG; NREM, non-rapid eye movement; ODI, oxygen desaturation index; PCPA, p-chlorophenylalanine; PSG, polysomnography; QNP@HMs, quercetin nanoparticle-loaded hydrogel microspheres; RA, room air; SCFA, short-chain fatty acid; SpO₂, peripheral oxygen saturation; STAT3, signal transducer and activator of transcription 3; TCM, traditional Chinese medicine; Th, T-helper; TMAO, trimethylamine N-oxide; TNF-α, tumor necrosis factor-alpha. “Not reported” indicates that the outcome was not measured or was not reported in the original publication.

Human evidence for probiotics remains limited to a small randomized, double-blind, placebo-controlled trial involving 17 healthy adults exposed to an altitude of 3,800 m. Compared with placebo, the multi-strain probiotic increased mean daytime SpO₂ (90.2 ± 2.8% vs 86.7 ± 4.4%; p < 0.0001) and mean nocturnal SpO₂ (81.9 ± 4.1% vs 76.9 ± 6.6%; p = 0.011), and reduced acute mountain sickness scores. However, the apnea–hypopnea index and oxygen desaturation index did not differ between groups, and neither insomnia-specific outcomes nor gut microbial changes were assessed.¹³⁷ Animal studies provide more mechanistically informative evidence. In a C57BL/6J mouse model of high-altitude sleep disturbance, quercetin nanoparticles encapsulated in calcium alginate hydrogel microspheres (QNP@HMs; 50 mg/kg) were administered by oral gavage for 7 days before hypobaric hypoxia exposure. This pretreatment prolonged sleep duration, improved short-term memory, increased the abundance of Lactobacillus and Lachnospira, and reduced intestinal and systemic inflammatory responses. These benefits were abolished following antibiotic-mediated depletion of the gut microbiota, supporting a microbiota-dependent mechanism.¹¹⁹

Traditional Chinese medicines (TCM) have predominantly been investigated in normoxic rodent models of insomnia induced by p-chlorophenylalanine (PCPA), an inhibitor of serotonin synthesis, or by sleep deprivation. Under normoxic conditions, Suanzaoren Decoction increased SCFA-producing genera and restored fecal SCFA and GABA/glutamate-related metabolic profiles in an insomnia rat model.¹³⁸ In a separate PCPA-induced rat model, Suanzaoren Tang restored selected microbial taxa, neurotransmitter balance, and inflammatory abnormalities.¹³⁹ Baihe Dihuang Tang altered gut microbial composition and restored neurosteroid and monoamine neurotransmitter profiles in PCPA-induced insomnia mice.¹⁴⁰ However, none of these classic formulations have been assessed under hypobaric hypoxia. An exception is Danggui Buxue Decoction, which increased total sleep by 60% and suppressed neuroinflammatory pathways in hypoxic Drosophila.¹⁴¹ Compared with live probiotics, postbiotics, particularly butyrate, offer greater stability and standardizability and do not depend on intestinal colonization; however, they may not reproduce the broader community-level effects of live probiotics. A pivotal mechanistic study revealed that portal injection of sodium butyrate resulted in a 70% increase in NREM sleep in rats within 6 hours.²⁶ Nevertheless, no studies have evaluated postbiotics in humans under hypoxic conditions. FMT also provides proof-of-concept evidence for microbiota-mediated effects under hypoxic conditions. Transfer of microbiota from plateau-adapted donors to hypoxic rats reduced mean pulmonary arterial pressure, improved growth performance, and enriched short-chain fatty acid-producing bacteria, including members of the Lachnospiraceae family.^72,142 Preliminary clinical evidence has also emerged in normoxic chronic insomnia. In a recent randomized, double-blind, placebo-controlled trial, an FMT-based protocol comprising short-course antibiotic pretreatment followed by oral donor-microbiota capsules improved polysomnography-measured sleep efficiency compared with placebo (adjusted between-group difference, 13.9 percentage points; 95% CI, 7.29–20.41; p = 0.003).¹⁴³ However, FMT remains investigational for insomnia and has not been evaluated for high-altitude insomnia. Current evidence regarding prebiotics, time-restricted feeding, and exercise is indirect and pertains solely to normoxic conditions, rendering these interventions unsuitable for recommendation at this time. In summary, probiotics have provided preliminary human evidence for improved oxygenation and acclimatization at HA, but their effects on insomnia and gut microbial composition remain untested; postbiotics show mechanistic sleep-promoting potential but lack human evidence under hypoxic conditions, while evidence for the remaining approaches is predominantly preclinical or indirect.

Translational Barriers and Research Roadmap

Before proposing a way forward, it is important to acknowledge that interventions not targeting the GBA have shown effectiveness in treating high-altitude insomnia. For instance, a randomized controlled trial involving transcutaneous vagus nerve stimulation (n=100, with polysomnography endpoints) resulted in significant improvements in sleep quality and decreased sleep latency.¹⁴⁷ Additionally, hyperbaric oxygen therapy reduced PSQI scores from 9.1 to 4.6 in a prospective open-label trial with 80 participants.¹⁴⁸ These interventions act through direct neuromodulation or oxygen delivery mechanisms, highlighting a clear disparity: while non-GBA strategies have attained robust evidence through randomized controlled trials, the field targeting the GBA remains in its early stages.

Clinical translation of FMT requires caution. Current guidelines and regulatory frameworks primarily support fecal microbiota-based therapies for recurrent Clostridioides difficile infection, whereas their use for insomnia remains investigational. The potential transmission of enteric pathogens and antimicrobial-resistant organisms necessitates rigorous donor screening and safety surveillance, while heterogeneity in donor selection, preparation, administration, and microbial engraftment may result in variable efficacy. Thus, FMT should currently be regarded as an experimental rather than clinically applicable intervention for high-altitude insomnia.¹⁴⁹ In light of these evidentiary, safety, and standardization barriers, we advocate for a methodical research plan rather than premature clinical implementation. The proposed agenda consists of three steps. Step 1 involves preclinical optimization, where the dose-response and pharmacokinetics of potential postbiotics will be evaluated in rodents exposed to hypobaric chambers with telemetric EEG. The aim is to ascertain if oral administration can achieve adequate portal or systemic levels to replicate the NREM-enhancing effects observed with portal injection. Moving on to Step 2, a Phase 1 trial in humans will be conducted, enrolling 20–30 healthy participants for a randomized, double-blind, placebo-controlled crossover study in a hypobaric chamber (simulated 4,000 m altitude, 3-day exposure). The trial will compare an optimized postbiotic with a placebo, with the primary outcome being NREM duration and EEG delta power derived from polysomnography. Secondary outcomes will include actigraphy, sleep questionnaires, serum LPS and I-FABP levels, and gut metagenomics analysis. Finally, Step 3 entails field validation, where, if the phase 1 trial demonstrates efficacy, a RCT will be conducted at actual high altitudes (≥3,500 m) with larger sample sizes and extended intervention durations.

Based on existing evidence, we do not support the routine use of any GBA-targeted intervention, such as probiotics, postbiotics, prebiotics, or dietary changes, for high-altitude insomnia outside approved research settings. The primary urgent step is a rigorous RCT comparing a scientifically designed postbiotic with a placebo in a controlled setting, with polysomnography as the key measure. Until findings from this trial are accessible, all GBA-centered strategies are merely speculative.

Conclusion

In summary, exposure to high-altitude hypoxia is associated with intestinal barrier dysfunction, gut microbial dysbiosis, and systemic inflammatory alterations that may contribute to remodeling of the gut–brain axis. Microbial metabolites, circulating inflammatory mediators, and vagal signaling provide plausible routes through which intestinal changes may influence CNS function and sleep regulation. Experimental FMT studies demonstrate that transferring hypoxia-associated microbiota can reproduce sleep-related phenotypes in recipient animals, supporting a contributory role of the gut microbiota in preclinical models. However, direct evidence that intestinal HIF‑1α drives gut–brain axis remodeling or sleep disruption during high-altitude hypoxia is currently lacking. Although postbiotics, particularly butyrate, represent promising candidates for further investigation, GBA-targeted interventions remain preclinical or exploratory, and no high-altitude randomized controlled trial has evaluated such an intervention using polysomnography as the primary outcome.

Several methodological limitations should be acknowledged. First, this review heavily relies on data from patients with OSA, whose pathophysiology, characterized by intermittent hypoxia with hypercapnia, sleep fragmentation, and metabolic comorbidities, differs significantly from the sustained hypobaric hypoxia experienced at high altitudes. While these data offer valuable mechanistic insights, they do not directly prove high-altitude insomnia, requiring cautious qualification of any conclusions drawn. Secondly, most high-altitude human studies included are cross-sectional and lack objective sleep assessments using polysomnography or electroencephalography, leaving the summarized associations as correlational, without firmly established causal inferences in humans. Thirdly, being a narrative review rather than a systematic one, this work may be prone to selection bias and lacks a formal quality assessment of the studies included. Fourthly, several unresolved questions further limit the evidence base: the distinct impacts of acute versus chronic hypoxia on gut microbiota have not been directly compared, and the causal relationship between dysbiosis and insomnia in humans remains uncertain, given that sleep disturbances can themselves influence feeding behaviors and gut motility, potentially leading to secondary microbial alterations. Until these questions receive clarification, any causal framework linking the GBA to high-altitude insomnia, including the one proposed here, must be considered provisional.

Based on current evidence, we cannot recommend routine clinical use of any GBA-targeted intervention for high-altitude insomnia outside approved research protocols. Future mechanistic studies should determine whether microbiota-derived metabolites and inflammatory signals alter HPA-axis/cortisol dynamics or orexin-dependent arousal and whether these neuroendocrine changes mediate sleep disruption under hypobaric hypoxia. The single most urgent next step is a double-blind, placebo-controlled RCT comparing a rationally designed postbiotic against placebo in a controlled hypobaric chamber setting, with polysomnography as the primary endpoint. Until such data emerge, all GBA-based strategies remain hypothesis-generating only.

Funding Statement

No funding was received.

Data Sharing Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

Author Contributions

Huaxiucairang Yang: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing. Wenguang Lan: Resources, Data curation, Software, Formal analysis, Investigation, Visualization, Writing – review & editing. Jing Liu: Resources, Data curation, Software, Formal analysis, Investigation, Visualization, Writing – review & editing. Wenke Yang: Resources, Data curation, Formal analysis, Investigation, Writing – review & editing. Xiao Zou: Resources, Investigation, Writing – review & editing. Lu Yan: Resources, Investigation, Writing – review & editing. Kaiyang Zheng: Resources, Investigation, Writing – review & editing. Ting Zhang: Resources, Investigation, Writing – review & editing. Yongping Li: Resources, Investigation, Writing – review & editing. Li Tong: Resources, Investigation, Methodology, Supervision, Writing – review & editing. Chengzhu Cao: Resources, Validation, Writing – review & editing. Zhanhai Su: Resources, Validation, Methodology, Writing – review & editing. Xueman Ma (Corresponding author): Conceptualization, Supervision, Validation, Methodology, Project management, Writing – review & editing.

All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.