How the gut microbiome affects depression through immune, hormone, and brain systems and potential treatment targets

Population-based studies using 16S rRNA sequencing and metagenomic approaches generally suggest that depressive disorders are closely associated with disturbances in gut microbial diversity and community structure; however, findings regarding specific α-diversity metrics remain inconsistent (10). Several early case–control studies reported that, compared with healthy controls, patients with major depressive disorder (MDD) exhibited reduced gut microbial α-diversity and marked separation in β-diversity, suggesting a reconfiguration of the overall microbial ecological landscape (11). However, systematic reviews and meta-analyses integrating multiple studies have shown that, across diverse populations and analytical platforms, differences in α-diversity are often inconsistent. Reductions in richness indices such as Chao1 have been observed only in certain subgroups, such as antidepressant-free Western participants, highlighting the substantial influence of dietary patterns, medication exposure, and methodological approaches on microbial diversity metrics (12). Multiple case–control studies and systematic reviews have consistently reported a depletion of anti-inflammatory, butyrate-producing commensal genera in patients with depressive disorders, accompanied by the relative enrichment of several genera associated with inflammatory responses and mucin degradation. Typical findings include reduced abundances of short-chain fatty acid-producing genera, such as Faecalibacterium, Coprococcus, and Butyricicoccus, with decreases in Faecalibacterium showing a negative association with depression severity across multiple cohorts. Conversely, Eggerthella, Flavonifractor, Enterobacteriaceae, and certain Streptococcus and Alistipes taxa, which are considered potentially pro-inflammatory or opportunistic pathobionts, tend to be enriched in depressive populations (13).

Large-scale cohort-based metagenomic studies have further strengthened this view at a higher taxonomic and functional resolution. Analyses based on population cohorts such as the Flemish Gut Flora Project and LifeLines DEEP showed that the relative abundances of several butyrate-producing genera were not only reduced in individuals with depression or higher depression scores, but also positively associated with quality-of-life scores and negatively associated with depressive symptoms. These studies also highlighted the importance of confounding factors, including dietary patterns, body mass index, and psychotropic medication use, in interpreting associations between the gut microbiota and psychiatric phenotypes (14). Consistent with findings from umbrella meta-analyses across psychiatric populations, depressive disorders may not be characterized by a single, stable, and depression-specific microbial signature at the level of gut microbial ecology. Instead, they appear to reflect a shared dysbiotic pattern characterized by the depletion of butyrate-producing bacteria and the enrichment of pro-inflammatory taxa, shifting toward a state of low-grade inflammation and impaired barrier function, with several variants emerging under different host backgrounds and environmental exposures (15). It should be noted that the evidence for the above-mentioned differences in microbial composition is still derived primarily from cross-sectional and case–control studies, and the findings are susceptible to the influence of dietary patterns, geographic and population characteristics, medication exposure, sample size, and the extent to which psychiatric comorbidities are controlled. Therefore, at the current stage, these findings are better interpreted as signals of depression-related community dysbiosis, rather than as stable microbial signatures that can be directly applied to stratified diagnosis.

Compared with the substantial between-study heterogeneity observed in the taxonomic composition of the gut microbiota, abnormalities in the functional and metabolic pathways of the gut microbial ecosystem associated with depressive disorders appear to be more consistent and may be more closely linked to potential mechanistic hubs and clinically translatable endpoints (12). Current metagenomic and targeted or untargeted metabolomic studies generally indicate that microbial functional remodeling in individuals with depression is mainly concentrated in the tryptophan–kynurenine pathway, short-chain fatty acid production, bile acid transformation, and other key pathways related to nitrogen metabolism, energy metabolism, and cofactor biosynthesis. These alterations are closely associated with inflammatory burden, hypothalamic–pituitary–adrenal (HPA) axis activity, affective–cognitive phenotypes, and certain somatic comorbidities (15–19). Compared with the increase or decrease of a specific bacterial genus, these functional readouts are more likely to exhibit directionally consistent abnormal patterns across different cohorts. This suggests that the core of depression-related microbial dysbiosis may not lie in the presence of a single, stable, and depression-specific microbial signature, but rather in the convergence of diverse microbial configurations onto several relatively convergent abnormalities in metabolic and signaling pathways.

From a research perspective, abnormalities at the functional and metabolic levels deserve particular attention not only because they facilitate the integration of immune-inflammatory processes, stress-related neuroendocrine regulation, and central neural plasticity, but also because they are more suitable as candidate readouts for monitoring, stratification, and intervention. Particularly in the context of the marked clinical heterogeneity of depressive disorders and the recurrent inconsistency of findings on microbial composition, constructing a microbial ecology–host response framework around key metabolic hubs may be more informative than merely cataloguing microbial alterations for explaining interindividual differences in symptom profiles, comorbidity burden, and treatment responses. Table 1 summarizes the key metabolic pathways repeatedly reported in depressive disorders and their major host-related effects.

In real-world populations, depressive disorders frequently coexist with metabolic diseases, such as metabolic syndrome, obesity, and type 2 diabetes, as well as irritable bowel syndrome (IBS) and functional gastrointestinal disorders (FGIDs). These comorbid conditions may themselves influence the gut microbial ecosystem through chronic low-grade inflammation, insulin resistance, and altered visceral sensitivity (27). In patients with depressive disorders accompanied by metabolic abnormalities, the gut microbiota and metabolic profiles are often jointly shaped by both the depressive state and the background of metabolic comorbidity; therefore, these abnormal patterns should not be simply interpreted as depression-specific alterations. Existing studies suggest that individuals with MDD and overweight/obesity may exhibit enrichment of fatty acid metabolism-related genera, such as Succinivibrio and Megamonas, along with a reduction in potentially beneficial taxa such as Bifidobacterium, accompanied by systematic remodeling of lipid and bile acid pathways. However, it should be noted that these changes partially overlap with microbial alterations observed in individuals with obesity or metabolic syndrome alone; therefore, they are better regarded as risk-enhancing signals in the context of depression with metabolic dysregulation, rather than as established depression-specific microbial markers (28). With respect to gastrointestinal comorbidity, IBS frequently coexists with anxiety and depressive symptoms. Fecal 16S rRNA sequencing and metagenomic studies have shown that patients with diarrhea-predominant IBS (IBS-D) and those with depression share similar microbial signatures, including reduced α-diversity, enrichment of certain opportunistic pathobionts, and depletion of short-chain fatty acid-producing bacteria (29). Integrated fecal microbiome–metabolome multi-omics analyses further indicate that IBS patients with prominent psychological symptoms or high stress levels also exhibit distinct metabolic patterns involving tryptophan/5-HT metabolism and lipid metabolism-related metabolites (30).

Taken together, studies of populations with metabolic and gastrointestinal comorbidities suggest that patients with depressive disorders differ in their metabolic–inflammatory burden, gastrointestinal symptom profiles, and corresponding microbial and metabolic features, with some subgroups showing relatively stable combinatorial patterns. The correspondence of these patterns with immune and endocrine activation pathways and clinical presentations, such as affective symptom-dominant or somatic/gastrointestinal symptom-dominant profiles, suggests the existence of candidate subtypes of depressive disorders defined by microbial ecological and metabolic characteristics. However, these candidate subtypes should not necessarily be equated with depression-specific biological stratification, as they may also partly reflect host–microbiota co-shifts driven by metabolic comorbidity. Therefore, whether these subtypes reflect upstream etiological factors, downstream stress- or metabolism-related manifestations, or the combined effects of multiple comorbid conditions remains to be determined through longitudinal follow-up and interventional studies.

MGBA is essentially a hierarchical network composed of multiple anatomical structures and cellular–tissue units. At its peripheral end, the MGBA comprises the extensive microbial communities within the intestinal lumen, the mucus layer covering the epithelial surface, and the single-layer intestinal epithelial barrier whose integrity is maintained by tight junctions. Beneath this barrier, the lamina propria contains abundant gut-associated lymphoid tissue (GALT), dendritic cells, macrophages, and various T- and B-cell subsets, which together constitute the first line of mucosal immune defense (31). At the neural level, the enteric nervous system (ENS) embedded within the intestinal wall finely regulates intestinal motility, secretion, and local blood flow through the myenteric and submucosal plexuses. It can function as a local integrative system often referred to as the “second brain”, while also engaging in bidirectional information exchange with the central nervous system (CNS) via the vagus nerve and sympathetic pathways (32). The autonomic nervous system, including its sympathetic and parasympathetic branches, together with the hypothalamic–pituitary–adrenal (HPA) axis, constitutes the major effector pathways of the stress response and represents a core component of the central arm of the MGBA.

In addition, enteroendocrine cells scattered throughout the intestinal epithelium, including 5-HT-secreting enterochromaffin cells and L cells that secrete GLP-1, PYY, and other peptides, act as sensory–effector transducers within the MGBA. These cells detect changes in luminal nutrients and microbial metabolites and transmit signals to the brainstem and higher brain centers through hormone secretion and synapse-like contacts with vagal nerve terminals. Conversely, neural and hormonal signals from the central nervous system can regulate intestinal function and the local microenvironment through these cells (33).

On the basis of the structural framework described above, information transfer within MGBA relies primarily on the coordinated actions of multiple molecular signals and metabolic mediators. These signals can be broadly categorized into three interconnected levels: immune signaling, metabolic signaling, and neuroendocrine signaling (34). These three categories do not operate in isolation; rather, they form a continuous communication network spanning the intestinal mucosal barrier, local microenvironment, peripheral circulation, and central nervous system. Together, they determine how intestinal signals are sensed, amplified, and integrated by the host into responses at the levels of brain function and behavior. Among these, immune signaling mainly arises from interactions between the gut microbiota and its associated molecules and the host mucosal immune system. Microbe-associated molecular patterns and the inflammatory mediators they induce not only participate in maintaining local intestinal immune homeostasis, but may also, under specific conditions, promote the spread of inflammatory signals from the gut to the systemic compartment, thereby serving as important mediators linking peripheral microbial ecological alterations to systemic host responses (35, 36). Metabolic signaling mainly reflects the ability of the gut microbiota to remodel nutritional substrates and host metabolic networks, involving short-chain fatty acids, bile acids, tryptophan-related metabolites, and other molecules related to energy metabolism and one-carbon metabolism. These mediators not only reflect the functional status of the microbiota, but also serve as important bridges linking microbial activity to intestinal barrier homeostasis, immune tone, and the regulation of brain function (18, 35).

Neuroendocrine information transfer is closely intertwined with the two categories of signaling described above. Enteroendocrine cells, the enteric nervous system, autonomic neural pathways, and the HPA axis together constitute key effector systems within the MGBA, mediating gut-to-brain signaling and subsequent central-to-gut feedback regulation. Neurotransmitters and their precursors, gut-derived hormones, and stress-related hormones do not act in isolation; rather, they form dynamic coupling among local sensory apparatuses, vagal afferent signaling, autonomic efferent output, and neuroendocrine regulation, thereby transforming microbial signals within the intestinal lumen into higher-order physiological and behavioral responses (37). Taken together, the key feature of the MGBA does not lie in the increase or decrease of any single signaling molecule, but rather in the dysregulated coupling among immune, metabolic, and neuroendocrine networks. Figure 1 provides a schematic overview of the overall dysregulation framework of the MGBA in depressive disorders, facilitating a systems-level understanding of the interactions among intestinal barrier disruption, immune-inflammatory activation, key metabolic abnormalities, HPA axis hyperresponsiveness, and impaired neuroplasticity. Based on the structural foundations and molecular mediators described above, MGBA abnormalities associated with depressive disorders can be broadly categorized into two interrelated pathways: first, a gut-to-brain ascending pathway, in which local intestinal disturbances are transmitted to the central nervous system through immune-inflammatory and neural signaling; and second, a brain-to-gut descending pathway, in which chronic stress and brain network abnormalities reshape the intestinal microenvironment through autonomic and neuroendocrine regulation. These two pathways do not operate in isolation, but jointly contribute to the onset and maintenance of depressive disorders through continuous reciprocal interactions.

The intestinal barrier is maintained in part by tight junction proteins, such as ZO-1 and occludin, which regulate intestinal permeability and prevent the translocation of harmful luminal substances. The “leaky gut” phenomenon refers to increased intestinal epithelial permeability and reduced expression of tight junction proteins, allowing microbial components and metabolites from the intestinal lumen to enter the systemic circulation and trigger low-grade systemic inflammation (38). Lipopolysaccharide (LPS), a prototypical endotoxin derived from gut Gram-negative bacteria, can enter the systemic circulation through the portal venous system under conditions of increased intestinal permeability, thereby activating immune responses and further exacerbating central nervous system inflammation (39). Increased intestinal permeability, often referred to as “leaky gut,” appears to be relatively common in patients with depression. Studies have shown that patients with depression exhibit elevated plasma levels of LPS, intestinal fatty acid-binding protein (I-FABP), and soluble CD14 (sCD14), suggesting intestinal barrier disruption and the translocation of microbial components into the bloodstream (40). LPS can activate the peripheral immune system and exacerbate neuroinflammation, ultimately affecting mood and cognitive function. Meanwhile, leaky gut may further promote immune–neural axis dysregulation and increase the risk of neuroinflammation by altering the levels of metabolites such as short-chain fatty acids (SCFAs) (41).

After endotoxins such as LPS translocate into the bloodstream through increased intestinal permeability, they can activate peripheral immune cells and induce the release of cytokines, including IL-6 and TNF-α. These inflammatory signals may affect the brain through blood–brain barrier (BBB)-dependent and BBB-independent routes, thereby promoting neuroinflammation. Pro-inflammatory cytokines can activate the hypothalamic–pituitary–adrenal (HPA) axis, leading to excessive glucocorticoid secretion and, under chronic stress conditions, glucocorticoid resistance or impaired negative feedback. This process may sustain immune activation and contribute to an inflammation–stress positive feedback loop (42). Excessive glucocorticoid secretion may, in turn, aggravate intestinal barrier disruption, further facilitating the translocation of harmful luminal substances such as LPS and thereby forming a vicious cycle between stress activation, barrier impairment, and inflammatory signaling (43). Activation of the HPA axis exerts important effects on the BBB. Studies suggest that glucocorticoids can modulate BBB permeability by affecting endothelial transport pathways and barrier-regulating structures, thereby facilitating the entry or signaling of inflammatory mediators across the BBB and exacerbating central immune responses (44).

Peripheral inflammatory signals can affect brain-resident immune cells, such as microglia, through BBB-dependent mechanisms, thereby activating neuroinflammatory responses. Microglia are the principal immune cells of the brain and can sense peripheral immune signals while regulating the neural microenvironment. Neuroinflammation may aggravate depressive symptoms by impairing neuroplasticity, disrupting synaptic connectivity, and inhibiting neuronal growth (45). In specific brain regions, such as the prefrontal cortex (PFC), hippocampus, and amygdala, neuroinflammation and structural and functional alterations are closely associated with depressive symptoms (46). In patients with depressive disorders, these brain regions often show reduced gray matter density and abnormal functional activity, which are significantly associated with peripheral immune responses and gut microbial dysbiosis (47). In this process, reduced neuroplasticity is considered a key factor affecting emotional regulation and cognitive function.

In addition to inflammation-mediated ascending pathways, intestinal signals can also influence central function through the ENS, the vagus nerve, and neurotransmitter-related mechanisms, thereby constituting another important route of gut-to-brain communication in depressive disorders. The ENS consists of dense networks of neurons and glial cells distributed within the gastrointestinal wall and can regulate intestinal motility, secretion, and local blood flow to a considerable extent independently of the CNS (48). The ENS is extensively connected to the central nervous system through the vagus nerve and spinal afferent fibers. As the major parasympathetic pathway, the vagus nerve rapidly transmits mechanical, chemical, and inflammatory signals from the intestinal lumen to the nucleus tractus solitarius in the medulla and higher brain regions, thereby participating in the regulation of stress responses, emotion, and homeostasis (49). Recent morphological and functional studies further suggest that a subset of enteroendocrine cells can form neuropod-like structures and establish synapse-like contacts with vagal nerve terminals, thereby translating luminal nutrients, microbe-associated molecules, and their metabolites into neuroelectrochemical signals that modulate vagal afferent firing patterns and ENS activity (50). This suggests that intestinal sensing of external and internal environmental changes does not rely solely on slow humoral pathways, but can also dynamically regulate brain function and behavioral states through rapid neural transmission.

The role of the vagus nerve in the ascending transmission of microbial signals has been supported relatively directly by preclinical studies. A classic animal study showed that chronic oral administration of Lactobacillus rhamnosus JB-1 altered the expression of GABA receptor subunits in the mouse brain and reduced anxiety- and depression-like behaviors. However, these behavioral and neurochemical effects were abolished after subdiaphragmatic vagotomy, indicating a clear vagus nerve-dependent mechanism by which specific bacterial strains modulate emotional behavior (51, 52). Further electrophysiological studies have also shown that JB-1 can rapidly increase the firing frequency of mesenteric vagal afferent fibers, providing direct evidence for a fast communication route along the luminal signal–vagus nerve–brain pathway (53).

By contrast, current human studies provide mainly indirect supportive evidence. Some studies have observed improvements in heart rate variability indices after probiotic or multi-strain psychobiotic interventions, accompanied by partial alleviation of depressive symptoms or improvement in sleep quality, suggesting that vagus nerve-related measures may be involved in host responses to microbiota-based interventions (54). However, it should be noted that measures such as heart rate variability cannot be directly equated with the vagus nerve dependence demonstrated in animal experiments, and current evidence is still insufficient to prove the existence of a vagus nerve-dependent mechanism in human depressive disorders at the same level as that observed in the JB-1 animal model. Therefore, the vagus nerve is better regarded as a biologically plausible neural interface within the MGBA, whereas its specific effect size, target populations, and clinical translational relevance in human depressive disorders remain to be clarified through more rigorous mechanistic studies.

Within the MGBA, neurotransmitters and the metabolism of their precursors constitute an important molecular bridge linking intestinal signals to changes in brain function. Among these, the 5-hydroxytryptamine (5-HT) system is one of the most extensively studied pathways. More than 90% of peripheral 5-HT is synthesized by enterochromaffin cells in the intestinal mucosa under the catalysis of tryptophan hydroxylase 1 (TPH1). This gut-derived 5-HT participates in the regulation of intestinal motility and visceral sensation and may indirectly influence the central 5-HT system and emotion-related brain regions through vagal and humoral pathways (55). Animal and in vitro studies have shown that microbial metabolites, such as short-chain fatty acids, can upregulate TPH1 expression in enterochromaffin cells and promote colonic 5-HT production, suggesting that specific gut microbes and their metabolites may influence host emotional states by regulating tryptophan utilization and 5-HT availability (56, 57). Meanwhile, a shift in tryptophan metabolism from the 5-HT synthetic branch toward the kynurenine (KYN) pathway has been repeatedly reported in cohorts of patients with depressive disorders and in animal models, characterized by reduced peripheral TRP levels, an increased KYN/TRP ratio, and the accumulation of neurotoxic metabolites. The gut microbiota may participate in this critical metabolic diversion by modulating tryptophan availability, local inflammation, and IDO/TDO activity (58, 59).

Beyond 5-HT, gut microbes may also participate in the regulation of pathways related to amino acid neurotransmitters, including γ-aminobutyric acid (GABA) and glutamate (60). Various Lactobacillus and Bifidobacterium species possess the potential to produce GABA, and some preclinical studies suggest that strain-mediated regulation of GABA signaling and emotional behavior may be vagus nerve-dependent. However, the translational relevance of this mechanism in human depressive disorders remains to be further validated (60, 61). Therefore, in research on the depression-related MGBA, the key issue is not simply how much bioactive neurotransmitter is directly produced by bacteria, but rather how the microbiota and its metabolites indirectly shape the functional state of central neurotransmitter networks by regulating neurotransmitter precursor availability, receptor expression, local neural transmission, and the inflammatory milieu.

Brain-derived neurotrophic factor (BDNF) represents another key node linking alterations in the gut microbial ecosystem to abnormalities in neuroplasticity. Animal studies have shown that SCFAs, particularly butyrate, can improve depression-like behaviors by regulating histone acetylation, upregulating hippocampal BDNF/cAMP response element-binding protein (CREB) signaling, and suppressing neuroinflammation (62). In human studies, several randomized controlled trials and subsequent meta-analyses have suggested that specific psychobiotic interventions, particularly multi-strain formulations containing Lactobacillus and Bifidobacterium, may modestly reduce depression scores. A limited number of mechanistic studies have also observed increased serum BDNF levels or reduced KYN/TRP ratios, providing preliminary clinical support for the hypothesis that the microbiota may influence depressive symptoms by modulating neurotransmitter–neuroplasticity pathways (63, 64). Overall, 5-HT/TRP–KYN metabolism, GABA-related signaling, and the SCFA–BDNF axis together constitute representative networks involved in neurotransmitter and neuroplasticity regulation in depressive disorders, providing biological clues for understanding therapeutic heterogeneity and potential stratified intervention strategies from the perspective of the MGBA.

From the perspective of ascending pathways as a whole, immune-inflammatory processes, vagal signaling, and endocrine regulation do not operate independently; instead, they continuously intersect and amplify one another during the transmission of local intestinal abnormalities to the central nervous system, together forming an integrated network of gut-to-brain communication in depressive disorders. Intestinal barrier disruption and microbial metabolic abnormalities can alter peripheral inflammatory tone and influence central responses through vagal afferent signaling and brainstem integration. Meanwhile, stress-related endocrine states may further modulate inflammatory signaling and neurotransmitter-related pathways, thereby strengthening the effects of gut-derived abnormalities on brain function (65, 66). Therefore, gut-to-brain ascending abnormalities in depressive disorders are better understood as a network-level dysregulation involving multiple systems, rather than as several isolated single-mechanism chains. Interpreting immune, neural, and endocrine signals within a unified framework not only helps explain interindividual differences in symptom spectra and phenotypes, but also provides a logical basis for understanding brain-to-gut descending remodeling from the perspective of bidirectional communication. Figure 2 summarizes this gut-to-brain ascending regulatory framework in depressive disorders.

Chronic stress-induced abnormalities in brain-to-gut descending regulation are first manifested as sustained activation of the HPA axis. Persistent psychological or physiological stress can promote the release of corticotropin-releasing hormone (CRH) from the hypothalamic paraventricular nucleus, subsequently driving pituitary secretion of adrenocorticotropic hormone (ACTH) and ultimately increasing adrenal glucocorticoid secretion (67). In depressive disorders and stress-related phenotypes, this axis often exhibits increased basal activity, impaired negative feedback regulation, and circadian rhythm disruption (68). This hyperresponsive state of the HPA axis is not only an important marker of central stress responses, but also a key upstream driver of descending remodeling of the intestinal microenvironment.

At the gastrointestinal level, HPA axis activation and concomitant sympathetic excitation can jointly alter intestinal motility, secretion, and mucosal blood flow, thereby affecting the stability of the intestinal luminal ecological niche (69). Glucocorticoid and catecholamine signaling can also act on intestinal epithelial cells, the ENS, and mucosal immune cells, inducing disruption of tight junction homeostasis, weakening of mucus layer defense, and shifts in local immune responses, ultimately leading to increased intestinal permeability and impaired barrier function (70). It should be emphasized that chronic stress does not affect the intestine solely through direct hormonal actions; rather, it continuously reshapes the intestinal motility, secretory, defensive, and metabolic milieu through a coupled HPA axis–autonomic nervous system–mucosal immunity–epithelial barrier network (71, 72). Therefore, from the perspective of the brain-to-gut descending pathway, the central significance of chronic stress lies in its ability to chronically shape an intestinal internal environment that is more prone to microbial dysbiosis and functional disturbance, rather than merely inducing transient intestinal responses.

Brain network abnormalities associated with depressive disorders are not limited to emotional processing, but also involve the higher-order integration of interoception, autonomic output, and visceral homeostatic regulation. Structures such as the prefrontal cortex, anterior cingulate cortex, insula, amygdala, and hypothalamus constitute key nodes of the central autonomic network (CAN) (73). Among these structures, the insula–anterior cingulate system plays a hub-like role in salience detection and interoceptive prediction. Under stress conditions, this network can synchronously drive autonomic and neuroendocrine responses; therefore, its functional deviation may constitute an important central basis for brain-to-gut descending signaling (74). In the context of depressive disorders, such network abnormalities are commonly manifested as sympathetic–parasympathetic imbalance and corresponding alterations in visceral regulatory patterns, thereby affecting intestinal blood flow, motility, secretion, mucosal immunity, and barrier homeostasis. Cohort studies of first-episode, drug-naïve MDD have shown that patients exhibit not only alterations in gut microbial composition, but also abnormal local functional activity in prefrontal regions, with certain microbial features associated with prefrontal functional indices and depression/anxiety scores (75). These findings suggest that depression-related brain network abnormalities may participate in the remodeling of the intestinal microenvironment through autonomic output. However, current evidence more strongly supports this as an associative framework of central regulation–intestinal response, rather than as a fully established single mechanistic pathway.

In depressive disorders, changes in dietary patterns, circadian rhythm disruption, reduced physical activity, and increased exposure to smoking and alcohol accompanying the depressive state can also continuously reshape luminal substrate availability, intestinal transit, mucosal immunity, and the metabolic milieu, thereby amplifying microbial dysbiosis and its metabolic consequences (76). Therefore, within the MGBA framework, these factors should not be regarded merely as confounders, but rather as important behavioral and environmental effector layers through which brain states influence the intestinal microenvironment. Studies in adults have shown that social jetlag is associated with poorer diet quality and alterations in gut microbial composition, suggesting that circadian misalignment may affect the microbial ecosystem through both behavioral and metabolic pathways. Sedentary behavior and moderate-to-vigorous physical activity show opposite associations with a similar set of microbial taxa and functional pathways, including SCFA-related functional potential, indicating that reduced activity may serve as an important amplifying factor in the shift from depressive states toward an unfavorable microbial profile (77, 78).

Medication exposure is another important modulatory factor that may amplify the effects of brain-to-gut descending pathways, and it is of particular relevance in populations with depressive disorders. Compared with the general population, patients with depressive disorders are more likely to experience long-term, combined, or sequential medication use. Studies have shown that multiple classes of medications, including antidepressants, anxiolytics/benzodiazepines, proton pump inhibitors (PPIs), glucocorticoids, and antibiotics, are significantly associated with alterations in gut microbial composition and diversity (79, 80). Studies have shown that the microbiota-related effects of certain medications can remain detectable for several years after discontinuation, with evident carryover effects and additive effects. These medications include antidepressants, benzodiazepines or other psycholeptics, and glucocorticoids, among others (81). This suggests that in MGBA research, recording only medication use at the time of sampling may substantially underestimate the true impact of medications on microbial community structure. This issue may be particularly prominent in populations with psychiatric disorders. Studies have shown that antidepressant use is significantly associated with differences in gut microbial β-diversity, and its effect size may exceed that of certain diagnostic factors in overall analyses. Further stratified analyses indicate that some apparent disease-associated microbial differences are markedly attenuated after controlling for medication exposure (82). This suggests that many previously reported MDD-associated microbial features may have been confounded by medication-related signals. Thus, medication–microbiota interactions are not marginal phenomena, but important components influencing the interpretation of microbial ecological phenotypes, treatment responses, and therapeutic heterogeneity in patients with depressive disorders. Overall, the brain-to-gut descending pathway is not driven by any single factor, but rather results from the combined effects of chronic stress, brain network abnormalities, behavioral exposures, and medication-related factors. These upstream central drivers continuously act on intestinal motility, secretion, mucosal blood flow, barrier function, and local immune homeostasis through autonomic and neuroendocrine signaling, ultimately promoting intestinal microenvironment remodeling, microbial dysbiosis, and the maintenance of maladaptive host responses. Figure 3 summarizes this brain-to-gut descending regulatory framework in depressive disorders.

The tryptophan metabolic network occupies a central position in MGBA research on depressive disorders because it is not limited to the simple dichotomy of reduced 5-HT synthesis and enhanced KYN pathway activity. Rather, it encompasses the 5-HT branch, the kynurenine branch, and the indole branch directly involving gut microbial metabolism (23). The more informative question is no longer simply whether tryptophan metabolism shifts from 5-HT synthesis toward the KYN pathway, but rather how tryptophan is redistributed among different metabolic branches and whether an imbalance occurs between neurotoxic and neuroprotective downstream kynurenine metabolites.

In the context of chronic low-grade inflammation and HPA axis hyperresponsiveness, increased IDO and TDO activity promotes the diversion of tryptophan toward kynurenine metabolism, as reflected by reduced peripheral tryptophan availability and an elevated KYN/TRP ratio. This shift may translate immune activation and stress burden into depression-related neurobiological abnormalities (83). However, what may be more functionally informative for depressive phenotypes is often not the overall enhancement of the KYN pathway itself, but whether its downstream metabolic profile shifts toward the neurotoxic branch. Further metabolism of kynurenine can generate metabolites with divergent biological effects: some, such as KYNA, have relatively neuroprotective properties, whereas QUIN and 3-HK are more likely to participate in NMDA receptor-related excitotoxicity, oxidative stress, and glial activation (84, 85). Therefore, in depressive disorders, the key issue is not the absolute increase or decrease of any single metabolite, but whether the QUIN/KYNA balance shifts toward neurotoxicity and how this shift relates to symptom severity, cognitive impairment, and differences in treatment response. The role of the gut microbiota in this network lies not simply in the depletion or enrichment of a single substrate, but rather in reshaping the overall metabolic fate of tryptophan. On the one hand, microbial dysbiosis and intestinal barrier disruption can enhance local and systemic inflammation, promote IDO activation, and thereby drive tryptophan metabolism toward the kynurenine branch. On the other hand, gut microbes can directly participate in tryptophan metabolism by producing various indole derivatives, such as IPA, IAA, and ILA, thereby forming a microbiota-related branch that is not entirely dependent on host IDO/TDO activity (83, 86). Compared with the traditional TRP–KYN framework, the significance of the indole branch lies not merely in adding an additional category of metabolites, but in providing another mechanistic clue for understanding host–microbiota differences across depressive phenotypes. In some patients, phenotypic differences may not be explained solely by reduced 5-HT synthesis or enhanced KYN pathway activity, but may also be related to shifts in the overall allocation of tryptophan among the neurotoxic KYN branch, the protective KYN branch, and the microbial indole branch (87).

From an integrative MGBA perspective, the value of the tryptophan metabolic network lies in its ability to place inflammation, stress, barrier function, and neuroplasticity within a unified framework. Future stratified analyses integrating microbiome profiling, metabolomics, and clinical phenotypes may enable the tryptophan metabolic network to provide important clues for more mechanistically targeted monitoring and interventions in depressive disorders.

SCFAs are core metabolites produced by the gut microbiota through the fermentation of dietary fiber, mainly including acetate, propionate, and butyrate. Unlike the tryptophan–kynurenine pathway, which more prominently reflects inflammatory activation and neurotoxic metabolic diversion, the key significance of SCFAs lies in their simultaneous effects on intestinal barrier homeostasis, mucosal immune regulation, host energy metabolism, and neuroplasticity. Therefore, SCFAs may be regarded as a homeostasis-maintaining hub that connects peripheral stability with central plasticity (88). Recent studies generally suggest that the protective effects of SCFAs are not confined to a single process, but extend across multiple levels of the MGBA. They can maintain epithelial barrier integrity, regulate immune tone, and influence brain function through neuroinflammatory and neurotrophic signaling (89). At the central level, one of the important mechanisms of SCFAs involves the regulation of neuroinflammation and neuroplasticity. Existing studies have shown that SCFAs may contribute to the maintenance of plasticity in brain regions such as the hippocampus and prefrontal cortex by inhibiting histone deacetylases (HDACs), modulating microglial activation, and influencing BDNF- and neurogenesis-related signaling (90). Recent human neurogenesis models further suggest that SCFAs can counteract IL-1β- and IL-6-induced reductions in neurogenesis and increases in apoptosis, indicating a direct protective role at the inflammation–neuroplasticity interface (91). In other words, the value of SCFAs lies not merely in their association with depressive disorders, but in their ability to integrate peripheral inflammatory buffering and central neuroplasticity protection within a unified mechanistic framework.

From the perspective of human evidence, SCFAs are among the few candidate metabolic markers that possess both mechanistic plausibility and practical measurability. A 2025 prospective study showed that circulating SCFA levels were associated with depression severity, and that baseline SCFA levels could predict MDD remission over a 6-month period (92). This suggests that SCFAs may not only participate in pathological processes, but also possess potential prognostic value. However, the direction of associations between specific SCFA subtypes and depressive phenotypes is not fully consistent across studies, indicating that their clinical interpretation should take into account background factors such as dietary patterns, BMI, metabolic status, and medication exposure (93, 94). Such inconsistency does not necessarily weaken the research value of SCFAs; rather, it suggests that SCFA-related findings are particularly susceptible to the combined influence of study design and host background. Differences across studies may arise from multiple factors, including sample type (feces, serum, or plasma), analytical platform, targeted SCFA subtypes, dietary status at sampling, obesity/metabolic comorbidity burden, and medication exposure. Therefore, a more appropriate future strategy is not to continue comparing a single SCFA as an isolated marker across studies, but to prioritize stratified study designs and conduct integrated analyses of fecal and circulating SCFA levels, SCFA-producing microbial features, and intestinal barrier/inflammatory indicators, with standardized recording of dietary and metabolic backgrounds. Only by placing SCFAs back into an integrated microbial function–host response framework can their heterogeneous patterns across different depressive subtypes be more accurately interpreted. Overall, SCFAs are better regarded as functional readouts within a combined intestinal barrier integrity–immune tone–neuroplasticity framework, rather than being simplified as single, universal biomarkers with fixed directional changes.

Bile acids not only participate in lipid absorption, but also act as important signaling molecules. Within their receptor axes, the nuclear receptor FXR and the membrane receptor TGR5 are regarded as key hubs linking metabolism, inflammation, and neural function (95). Recent pathophysiological and mechanistic reviews have systematically summarized the roles of bile acid–FXR/TGR5 signaling in immune regulation, energy metabolism, and the nervous system, providing a clear theoretical basis for incorporating this pathway into the framework of psychiatric disorders. At the population level, existing studies suggest that patients with MDD, particularly those with a cognitive impairment phenotype, exhibit coupled features of gut microbial dysbiosis and abnormal bile acid metabolism. These findings further indicate that targeting the microbiota–bile acid metabolism axis may have potential therapeutic significance (25). At the animal level, recent studies have further linked bile acid signaling to stress susceptibility. Chronic social defeat stress (CSDS) may be accompanied by bile acid-related metabolic disturbances, while abnormal hippocampal TGR5 signaling is thought to contribute to depression-like behaviors and alterations in synaptic function (96). Thus, bile acids may not only reflect the background of metabolic comorbidity, but also participate in the regulation of inflammatory tone and central nervous system function through multiple pathways.

Trimethylamine N-oxide (TMAO) is a representative product of the dietary substrate–microbial metabolism–host oxidation axis and has long been primarily investigated in the context of cardiovascular and metabolic diseases. In relation to depressive disorders, TMAO more often appears as a metabolic signal associated with comorbidity risk and inflammatory amplification. It is closely coupled with factors such as metabolic syndrome, vascular risk, and sleep/inflammatory status, which themselves represent important sources of heterogeneity in depressive disorders (97). Recent studies in populations with post-stroke depression (PSD) and in animal models suggest that TMAO levels are associated with the severity of depressive symptoms. Further animal experiments have shown that TMAO can exacerbate pro-inflammatory responses and worsen depression-like behaviors, thereby providing more specific mechanistic clues for the TMAO–inflammation–affective phenotype axis (98). Vitamins, particularly folate and B vitamins, jointly regulate methyl donor availability, homocysteine levels, and the availability of neurotransmitter substrates through one-carbon metabolism, and have increasingly been incorporated into the diet–microbiota–inflammation–mood framework in recent years. Recent studies have indicated that certain vitamins are derived not only from the diet, but may also be synthesized or transformed by gut microbes. Alterations in these vitamins may indirectly influence mood disorders through immune regulation and neurotransmitter synthesis (99).

MGBA dysregulation associated with depressive disorders can be conceptualized as abnormalities in multiple interconnected functional nodes, including impaired intestinal barrier integrity and increased endotoxin translocation, elevated peripheral inflammatory tone, dysregulated stress-related neuroendocrine states, particularly abnormal HPA axis activation, disrupted outputs from key microbial metabolic hubs, and impaired neuroplasticity. This perspective helps consolidate dispersed mechanistic pathways into a limited set of trackable functional readouts and provides mechanistic endpoints for future interventional studies.

In translational research, a single biomarker is often insufficient to reliably characterize the state of this network. A more appropriate approach is to establish a combinatorial monitoring framework centered on intestinal barrier function, inflammatory tone, HPA axis status, and outputs from key metabolic hubs, and to interpret these readouts in the context of clinical backgrounds such as gastrointestinal symptom profiles, metabolic comorbidities, sleep/stress burden, and long-term medication use. Table 2 summarizes candidate combinations of monitoring indicators for key functional nodes of the MGBA.

The advantages of dietary and lifestyle interventions within the MGBA framework lie in their upstream positioning and multi-target nature. By modifying substrate availability and the intestinal luminal ecological niche, these interventions can simultaneously influence microbial functional outputs, such as SCFAs, barrier homeostasis, and inflammatory tone, while also modulating stress reactivity and circadian rhythms to some extent, thereby affecting multiple depressive phenotypes, including mood, cognition, sleep, and somatic/gastrointestinal symptoms. Randomized controlled trials have shown that improving diet quality can significantly enhance symptom improvement in patients with moderate-to-severe depression, with higher remission rates observed in some studies. Therefore, dietary improvement may be regarded as a promising lifestyle intervention strategy for the adjunctive treatment of moderate-to-severe depression (101). Systematic reviews and meta-analyses further support that healthy dietary patterns, such as the Mediterranean diet, can improve depressive outcomes, and that their effect sizes may be influenced by intervention adherence, baseline metabolic risk, and inflammatory burden (102).

Evidence for exercise interventions is also moving toward the incorporation of mechanistic and microbiota-related endpoints. Randomized controlled trials have observed that aerobic exercise can improve depressive symptoms while being accompanied by changes in gut microbial composition, suggesting that exercise may act as a highly adaptable ecological niche modulator, with its effects partly mediated through microbial and metabolic pathways (103). Recent studies have further indicated that physical activity levels are associated with mild depressive states and microbial features, supporting the existence of detectable associations along the activity–microbiota–mood/brain function axis in real-world populations (104). It should be noted that different exercise prescriptions, including type, intensity, and duration, do not produce consistent directions of microbial change, which may partly explain the heterogeneity of the antidepressant effects of exercise. Therefore, higher-quality studies should simultaneously incorporate microbial and metabolic endpoints to enhance mechanistic interpretability (105).

Sleep and stress management are more closely aligned with the brain-to-gut descending pathway, but they may also influence the microbiota through circadian and inflammatory mediators. Animal and experimental studies have shown that sleep deprivation can disrupt circadian rhythmicity of the gut microbiota and is accompanied by disturbances in the rhythmic patterns of peripheral inflammatory cytokines, suggesting that circadian misalignment may amplify mood- and anxiety-related phenotypes through a microbial rhythmicity–inflammatory tone pathway (106). Large-scale cohort studies have also found that social jetlag is associated with gut microbial composition and dietary/metabolic features, underscoring the importance of regular sleep patterns and circadian alignment for the stability of the intestinal ecological niche (77).

Overall, dietary and exercise interventions act more directly on luminal substrates and microbial functional outputs, whereas sleep and stress management more directly target stress and circadian homeostasis. Combining these two types of strategies is therefore more consistent with the biological logic of bidirectional coupling within the MGBA. Current evidence also suggests that the effect sizes of lifestyle interventions are highly dependent on baseline phenotypes and exposure backgrounds. Therefore, incorporating phenotype-based stratification and microbiota/metabolism-related mechanistic endpoints into clinical trials and translational studies is a key strategy for improving reproducibility and interpretability.

In clinical research, psychobiotics primarily refer to microbiota-based therapeutic strategies, represented by probiotics, prebiotics, and synbiotics, that target emotional and cognitive outcomes; postbiotics are also gradually being incorporated into this research framework. Recent randomized controlled trials and systematic reviews suggest that these interventions may produce small-to-moderate improvements in depressive symptoms overall, although between-study heterogeneity remains substantial. Some trials have observed reductions in depression scale scores accompanied by improvements in anxiety symptoms, whereas others have not demonstrated significant between-group differences (107, 108). These findings suggest that therapeutic efficacy is closely related to baseline population characteristics, strain/substrate combinations, and the selection of outcome measures.

In populations with depressive disorders, one important line of evidence comes from studies using probiotics as an adjunctive intervention to standard antidepressant treatment. In an 8-week randomized controlled trial, multi-strain probiotics used as an adjunct to antidepressant therapy showed a greater trend toward symptom improvement than placebo, while acceptability and tolerability were systematically evaluated. These findings suggest that this strategy is feasible within clinical care pathways, although larger studies are needed to confirm its robust and reproducible effects (109). It should be noted that meta-analyses suggest that the depression rating scales used across different trials can substantially influence pooled conclusions. Taking microbiota-based interventions such as probiotics and synbiotics as an example, scale-stratified analyses may show significant improvement in subgroups assessed using the Beck Depression Inventory (BDI), whereas subgroups assessed using the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) or the Hamilton Depression Rating Scale (HAM-D) do not necessarily yield consistently significant results. This may partly explain the inconsistency of conclusions across different systematic reviews (110). Therefore, the overall effects of psychobiotics in depressive disorders appear to be generally positive, but are highly dependent on study design and population characteristics, and are not yet sufficient to support a universal prescription. Compared with probiotics, prebiotics and synbiotics place greater emphasis on regulating microbial function through substrate provision, particularly by influencing fermentation-related pathways such as SCFA production; therefore, their clinical effects may be more strongly affected by dietary patterns, metabolic background, and baseline microbiota status. Existing studies suggest that prebiotics and synbiotics may provide some benefit for depressive and anxiety symptoms, although between-study heterogeneity remains substantial. This indicates that future trials should systematically record dietary patterns, body weight/metabolic status, and medication history, and incorporate these factors into stratified or adjusted analyses (111). Evidence on postbiotics remains relatively recent and fragmented, and postbiotics are currently better regarded as an exploratory direction rather than a conclusive therapeutic strategy. Some clinical trials have begun to evaluate the effects of postbiotics on mood- or psychiatry-related outcomes; however, the study populations are often not limited to MDD, including, for example, critically ill populations, and both outcome measures and mechanistic endpoints remain insufficiently standardized (112). Therefore, more randomized controlled trials specifically targeting depressive disorders are needed, with simultaneous collection of microbiota and metabolic pathway readouts. In addition, existing psychobiotic trials commonly suffer from small sample sizes, substantial differences in strain combinations, insufficient control of baseline medication use and dietary intake, short follow-up durations, and inconsistent mechanistic endpoints, which are important reasons why findings across studies remain difficult to reproduce and corroborate consistently (113, 114).

FMT more closely resembles a global reconstruction of the intestinal ecosystem; therefore, in research on depressive disorders, it is regarded not only as a potential intervention, but also as a tool for exploring whether depression-related microbial abnormalities have transferable biological effects and may provide clues to causal relevance. Existing preclinical studies have shown that transplantation of microbiota from patients with depression into recipient animals can induce more pronounced depression-like behaviors, such as increased immobility time and reduced struggling behavior in the forced swim test. Some studies have further observed that, compared with animals receiving microbiota from healthy donors, those receiving depression-derived microbiota exhibit divergence in certain microbial members and related metabolic phenotypes. This suggests that these effects are not merely nonspecific stimuli induced by transplantation itself, but may reflect differences in the functional status of donor microbiota (5, 6). The significance of these findings does not lie simply in determining whether FMT can treat depression, but rather in advancing depression-related microbial abnormalities from a correlative phenomenon to the level of a transferable biological phenotype. Therefore, FMT-related findings are better interpreted as important clues that depression-related microbial abnormalities may exert transferable biological effects, rather than as direct evidence at the population level that they represent a primary etiological cause.

At the population level, evidence for the use of FMT in depressive disorders remains limited, but noteworthy early clinical signals have begun to emerge. Early case reports of patients with major depressive disorder receiving FMT as an adjunctive treatment showed reductions in depression scores as early as 4 weeks after transplantation. In two patients, Beck Depression Inventory-II (BDI-II) scores decreased from 50 to 31 and from 24 to 12, respectively; at the 8-week follow-up, these improvements were partially maintained, accompanied by alleviation of gastrointestinal symptoms (115). This suggests that FMT may not act solely on mood-related scores, but may also indirectly reduce the overall disease burden by improving gastrointestinal symptoms such as constipation and abdominal bloating. More recent randomized studies have begun to show short-term signals of enhanced efficacy. A randomized study involving 46 patients with depressive episodes showed that, after 2 weeks, the FMT combined with pharmacotherapy group had a greater reduction in 24-item Hamilton Depression Rating Scale (HAMD-24) scores and a higher score reduction rate than the pharmacotherapy-alone group. Meanwhile, after FMT, increased levels of Enterococcus, Lactobacillus, Bifidobacterium, and Butyricicoccus were observed. Correlation analysis further suggested that baseline enrichment of Faecalibacterium prausnitzii and Eubacterium rectale was associated with lower HAMD-24 scores (116). This suggests that the potential benefits of FMT may not be limited to microbial supplementation, but may more likely involve the reconstruction of SCFA-producing bacteria and commensal taxa associated with ecological homeostasis. Overall, research on FMT in depressive disorders remains at an early exploratory stage. Existing evidence suggests that FMT provides important clues for evaluating the transferability and causal relevance of depression-related microbial abnormalities, but remains insufficient to directly establish them as a primary etiological cause at the population level. At the same time, FMT may improve depressive symptoms and gastrointestinal discomfort in some patients by reconstructing SCFA-producing and homeostasis-associated commensal bacteria. However, current clinical studies still have small sample sizes and short follow-up durations, and the efficacy and safety of FMT require further confirmation in more high-quality studies. In terms of the current evidence base, population-level data on FMT are still mainly derived from case reports, small single-center studies, and short-term randomized trials. Moreover, donor screening, transplantation protocols, concomitant treatment backgrounds, and outcome assessment methods remain insufficiently standardized; therefore, FMT is currently better regarded as an exploratory strategy with mechanistic implications, rather than a routine intervention with a fully mature evidence base.

Existing studies suggest that interventions targeting MGBA have overall antidepressant potential, but their therapeutic effects are not uniform and show substantial heterogeneity. Meta-analyses have shown that microbiome-targeted therapies may improve depressive symptoms to some extent; however, the overall effect sizes are limited, and substantial heterogeneity exists across studies in terms of population characteristics, intervention types, strain combinations, treatment duration, and outcome assessment (117). These findings suggest that such interventions are more likely to be applicable to specific patient subgroups, rather than constituting a universal standardized regimen.

Based on current evidence, patients with depressive disorders who present with prominent gastrointestinal symptoms, metabolic abnormalities, or low-grade inflammatory states may be more likely to represent priority responder subgroups for MGBA-targeted interventions. These patients often exhibit concurrent intestinal barrier disruption, microbial metabolic abnormalities, and immune-inflammatory activation, suggesting that gut microbial dysbiosis may play a more prominent role in their disease process and that they may, in theory, be more responsive to microbiome-targeted interventions. However, this assumption is still based mainly on mechanistic inference, secondary outcomes, and subgroup signals, and requires validation in further prospective stratified studies (118). Meanwhile, existing studies suggest that patients who achieve remission and those who do not may already differ in their baseline microbial features. In older adults with depression, a prospective pilot study showed that a baseline microbiota-based random forest model constructed using nine genera achieved an AUC of 0.857 for predicting remission. In this model, baseline enrichment of SCFA-producing taxa such as Faecalibacterium, Agathobacter, and Roseburia was associated with subsequent remission (119). Therefore, it can be hypothesized that treatment efficacy may be influenced not by broadly defined microbial dysbiosis per se, but by whether patients possess a potentially modifiable microbiota-responsive phenotype.

This heterogeneity is also evident across different intervention modalities. Dietary and lifestyle interventions are more suitable as long-term management strategies and foundational background interventions; psychobiotics, including probiotics, prebiotics, and synbiotics, generally exert relatively modest symptom-improving and modulatory effects; whereas FMT and other microbiota reconstruction strategies may be more appropriate for populations with more pronounced microbial dysbiosis who require stronger ecological remodeling (120). A study involving 46 patients with depressive episodes showed that, after 2 weeks, the FMT combined with pharmacotherapy group had a greater reduction in HAMD-24 scores and a higher score reduction rate than the pharmacotherapy-alone group, accompanied by increased levels of Lactobacillus, Bifidobacterium, and Butyricicoccus (116). Although these findings suggest that more intensive microbiota reconstruction may provide additional benefits for some patients, the current evidence is still mainly derived from small-sample studies with short follow-up durations. Therefore, at the current stage, gut microbiota-targeted interventions are better positioned as stratified and individualized adjunctive therapeutic strategies, and their clinical application still requires careful balancing between potential benefits and safety boundaries.

Although research on MGBA and depressive disorders has increased substantially in recent years, the current evidence remains largely dominated by correlative descriptions, and a stable and clearly defined causal chain has not yet been established. Existing studies suggest that patients with depressive disorders are often accompanied by gut microbial dysbiosis, abnormalities in key metabolites, inflammatory activation, and neuroendocrine dysregulation. Meanwhile, animal experiments and FMT studies have, to some extent, supported the transferability of depression-related microbial abnormalities and associated phenotypes (12). However, these findings more strongly indicate that the gut microbiota participates in the onset and progression of depressive disorders, rather than simply proving that it occupies an equally central etiological position in all patients. In other words, the gut microbiota is more likely to serve as an important modulatory factor within the pathological network of depressive disorders, rather than as a single independent cause.

Future research should further focus on the integrative interpretation of key pathways. Current evidence indicates that SCFAs, the tryptophan–kynurenine pathway, bile acid signaling, intestinal barrier disruption, and neuroinflammatory responses remain key directions worthy of continued investigation in research on the MGBA and depressive disorders (121). Compared with merely comparing differences in microbial composition, these functional and metabolic pathways are closer to key nodes linking microbial alterations, host responses, brain functional abnormalities, and depressive phenotypes, and therefore have greater value for mechanistic interpretation and clinical translation. In particular, SCFAs exert multiple effects in maintaining intestinal barrier homeostasis, regulating immune-inflammatory responses, and influencing brain plasticity, whereas shifts in tryptophan metabolism link microbial alterations to neurotransmitter imbalance and the accumulation of neurotoxic metabolites. These findings suggest that different pathways may not operate in isolation, but instead jointly participate in the onset and progression of depressive disorders. At the same time, the interrelationships among these pathways require further clarification. Many current studies explain the relationship between the MGBA and depressive disorders from separate perspectives, such as inflammation, the HPA axis, neurotransmitters, or the intestinal barrier. However, in real disease processes, these mechanisms are often intertwined and mutually amplifying, rather than existing in isolation. Future studies should use longitudinal designs and multi-level integrative analyses to further clarify the relative contributions of different key pathways at different stages of disease. This will help gradually establish a more continuous and reliable mechanistic evidence chain, providing a stronger theoretical basis for subsequent biomarker screening and precision interventions.

Another key issue in current research on the MGBA and depressive disorders is the lack of sufficiently unified standards across studies in terms of sample inclusion, technical approaches, and analytical frameworks, which is an important contributor to the limited reproducibility of findings. Taking microbiome research itself as an example, differences in multiple steps, ranging from fecal sample collection time, storage conditions, and DNA extraction methods to sequencing platforms, bioinformatics pipelines, and statistical strategies, may all influence the final results. Meanwhile, 16S rRNA sequencing, metagenomic sequencing, and 16S-based functional prediction analyses each have limitations in resolution and depth of information, meaning that different studies may obtain inconsistent microbial features even when investigating similar populations (122). Similar issues are also present in metabolomic studies. Differences in analytical platforms, such as targeted and untargeted metabolomics, LC–MS, and GC–MS, as well as sample pretreatment methods, quantification strategies, and metabolite annotation standards, may all lead to inconsistent metabolite profile features for the same study population across different studies (123, 124).

On the other hand, reliance solely on taxonomic information of the gut microbiota has become increasingly insufficient for explaining the complex pathological processes of depressive disorders. Compared with static descriptions of which taxa increase or decrease, abnormalities at the functional and metabolic levels are often more stable and are closer to the key links connecting microbial alterations, host responses, brain functional abnormalities, and depressive phenotypes. SCFAs, the tryptophan–kynurenine pathway, bile acid signaling, and inflammatory responses all suggest that the influence of the gut microbiota on depressive disorders is not reflected merely in changes in community composition, but is more likely mediated through multi-level mechanisms, including metabolic remodeling, immune regulation, and neuroendocrine dysregulation (121). Therefore, a more valuable future direction is to integrate the microbiome with metabolomics, inflammatory indicators, endocrine status, neuroimaging data, and genetic/epigenetic information, thereby establishing a multi-level integrative framework centered on key functional axes. At the same time, multi-omics integration does not merely involve increasing the dimensionality of data; more importantly, it requires an appropriate study design that can meaningfully link information across different biological levels. For depressive disorders, factors such as diet, medication use, sleep, metabolic status, and gastrointestinal comorbidities may simultaneously influence microbial, metabolic, and inflammatory outcomes. Without systematic recording and adjustment for these variables, even large-scale omics datasets may fail to yield stable and biologically interpretable signals. Overall, the establishment of multi-omics integration and standardized research frameworks is an essential prerequisite for advancing MGBA–depression research from descriptive associations toward mechanistic integration and clinical translation. Only by standardizing research procedures, improving technical comparability, strengthening functional readouts, and integrating clinical phenotypes can research findings be more effectively translated into stable and reproducible biomarkers and clinically meaningful intervention targets.

As research on the MGBA continues to deepen, the future focus of clinical translation is no longer simply to determine whether gut microbiota-targeted interventions are effective, but to identify which patients are more likely to benefit and to develop more targeted intervention strategies accordingly. Depressive disorders are inherently highly heterogeneous, with substantial interindividual differences in symptom spectra, gastrointestinal comorbidities, inflammatory levels, metabolic status, and microbial functional features (125). This also means that patients may differ in their responsiveness to interventions such as dietary modification, probiotics/prebiotics, postbiotics, and FMT. Therefore, a more rational future direction is to move beyond crude comparisons between patients with depressive disorders and healthy controls, and toward stratified identification based on clinical phenotypes and microbial ecological features. On this basis, the implementation of precision intervention depends on the integrated assessment of symptom profiles, comorbidity burden, and key biological indicators. For example, patients with prominent gastrointestinal symptoms, metabolic abnormalities, or low-grade inflammatory states are more likely to exhibit intestinal barrier disruption, microbial metabolic abnormalities, and immune-inflammatory activation, and may therefore deserve priority consideration in evaluations of MGBA-targeted interventions. However, this judgment is still based mainly on mechanistic inference, secondary outcomes, and subgroup signals, and requires validation in further prospective stratified studies. Meanwhile, existing studies suggest that patients who achieve remission and those who do not may already differ in their baseline microbial features. This suggests that treatment efficacy may be influenced not by broadly defined microbial dysbiosis per se, but by whether patients possess a potentially modifiable microbiota-related phenotype (126). It should be further emphasized that a “microbiota-responsive phenotype” should not be simply understood as an alternative term for a “high-stress phenotype.” For this issue, a more appropriate population-level identification framework should include at least three dimensions. First, temporal precedence should be assessed through longitudinal follow-up and repeated measurements to determine whether microbial and metabolic abnormalities precede symptom fluctuations or primarily change in parallel with stress burden and disease status. Second, interventional reversibility should be evaluated by determining whether interventions targeting the microbiota or metabolic pathways can induce biological reversal consistent with symptom improvement in specific subgroups. Third, stratification specificity should be examined by assessing whether subgroups defined by gastrointestinal symptoms, metabolic/inflammatory status, and microbiota–metabolite features retain independent predictive value after controlling for stress burden, HPA axis status, medication exposure, diet, and related factors. Only on this basis can a microbiota-responsive phenotype be more reliably distinguished from a simple high-stress phenotype. Overall, the future development of MGBA–depression research does not lie merely in continuing to accumulate evidence of microbial differences, but in advancing along the main trajectory of causal mechanism elucidation, multi-omics integration and standardization, stratified identification of priority populations, and precision intervention with clinical translation. Only by simultaneously improving mechanistic understanding, methodological rigor, and clinical stratification can research findings be more effectively translated into stable and reproducible biomarkers and intervention strategies with practical clinical value. Figure 4 summarizes the overall framework of these research challenges and future directions.