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Multimodal Machine Learning-Based Prediction of Relapse in Major Depressive Disorder.
IMPORTANCE: Early identification of patients at high risk of relapse is key to personalized preventive strategies in major depressive disorder (MDD). However, current predictive models do not adequately account for the multimodal factors contributing to MDD relapse and fail to provide clinically meaningful predictions. OBJECTIVE: To predict relapse within 2 years in patients with MDD by using a comprehensive machine learning pipeline that integrates an unprecedented set of multimodal data. DESIGN, SETTING, AND PARTICIPANTS: This naturalistic longitudinal prognostic study used data from the Marburg-Münster Affective Disorders Cohort Study, with baseline assessments collected from October 2014 to May 2019 and follow-up approximately 2 years later, between October 2016 and June 2021. Data analysis was conducted between July 2024 and June 2026. The study was performed at 2 sites in Germany (Marburg and Münster), with participants recruited from psychiatric inpatient and outpatient departments and the general population. Patients meeting diagnostic criteria for current or lifetime MDD without history of neurological or severe somatic conditions were included. EXPOSURE: Natural course of illness in patients with MDD. MAIN OUTCOMES AND MEASURES: Balanced accuracy (BACC) for binary prediction of relapse vs no relapse during 2-year follow-up served as the primary outcome. Baseline features comprised 9 modalities including clinical and psychometric data, 4 structural and functional magnetic resonance imaging modalities, genetics, neurocognition, blood markers, and gut microbiome. RESULTS: A total of 564 patients with a current or lifetime MDD diagnosis were included (367 female [65.1%]; mean [SD] age, 37.34 [13.38] years). A total of 270 patients relapsed during the 2-year follow-up, while 294 did not. Mean (SD) BACC for the prediction of relapse ranged from 47.21% (5.85%) to 64.43% (6.63%). The best-performing model was solely based on few clinical relapse risk factors, while multimodal data integration did not improve performance. CONCLUSIONS AND RELEVANCE: In this prognostic study, the models achieved moderate accuracy, yet the results suggest limited scope for guiding individual-level clinical decision-making. Predictive performance was largely driven by established clinical risk factors, indicating limited incremental value of multimodal measures when assessed at a single time point. Future advances may instead benefit from dynamic modeling approaches that more closely align temporally evolving multimodal markers with longitudinal clinical outcomes.
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Nose-to-brain axis: mechanistic links between nasal microbiome dysbiosis, neuroinflammation, and brain disorders.
The nasal microbiome has emerged as a previously underrecognized modulator of neuroinflammation and central nervous system (CNS) homeostasis. Beyond its role in respiratory host defense, this microbial niche is anatomically positioned to directly influence brain physiology through olfactory neuronal pathways, systemic immune signaling, and inter-organ communication within the gut-lung-brain axis. Accumulating evidence indicates that nasal microbiome dysbiosis contributes to blood-brain barrier (BBB) dysfunction, microglial activation, and propagation of neurotoxic protein aggregates, processes implicated in neurodegenerative and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and major depressive disorder. This review synthesizes experimental and clinical studies elucidating key mechanisms by which nasal microbial imbalance may impact CNS pathology, including microbial translocation along olfactory neurons, release of pathogen-associated molecular patterns and inflammatory mediators, extracellular vesicle-mediated signaling, and peripheral immune crosstalk. We further highlight clinical observations linking nasal microbiome signatures with olfactory dysfunction, cognitive decline, and altered inflammatory profiles, particularly in systemic conditions such as sepsis. Despite rapid advances in this field, significant knowledge gaps persist, including the limited availability of longitudinal human cohorts capable of establishing causality, incomplete mechanistic validation in translational models, and insufficient characterization of how environmental exposures and aging reshape the nasal microbiome-brain interface. By integrating current evidence and defining these unmet needs, this review positions the nasal microbiome as a promising source of diagnostic biomarkers and a therapeutic target for modulating neuroinflammation and mitigating neurodegenerative progression.
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Gut Microbiota in Neuroinflammation, Neurodegenerative Disorders, and Neuropsychiatric Disorders: A Comprehensive Narrative Review.
Neurodegenerative and neuropsychiatric illnesses are characterized by neuroinflammation, which is driven by microglial activation, cytokine production, and breakdown of the blood-brain barrier (BBB). It is currently known that the gut microbiota plays an important role in modulating neuroimmune signaling, which in turn may trigger anxiety-like behaviors and depressive phenotypes through the microbiota-gut-brain axis. This review aims to integrate the most recent mechanistic knowledge on treatment strategies targeting the gut microbiota to modulate neuroinflammation. This review article discusses preclinical and clinical studies that investigated microbial composition, metabolite profiles, and host-microbe interactions involved in neuroinflammatory processes. However, special attention was given to signaling via the vagus nerves and bile acids, as well as to tryptophankynurenine metabolism and short-chain fatty acids (SCFAs). To examine the potential connection between the two, researchers used animal models such as germ-free animals and antibiotic-injected mice for fecal microbiota transplantation (FMT). This article defines dysbiosis as amplifying neuroinflammatory responses by altering microglial phenotypes, disrupting the blood-brain barrier, and triggering the production of pro-inflammatory cytokines. In contrast, microbiome diversity rehabilitation through the use of probiotics, prebiotics, synbiotics, and dietary modifications reduces neuroinflammatory markers and enhances cognitive and behavioral status. Clinical trials have shown considerable promise in diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), autism spectrum disorder (ASD), and depression. However, variability in treatment protocols, treatment resistance, and host-specific factors continue to pose significant challenges. This narrative review integrates mechanistic insights into microglial activation, cytokine signaling, blood-brain barrier regulation, vagal pathways, tryptophan metabolism, and short-chain fatty acids with emerging clinical evidence and therapeutic strategies, including probiotics, prebiotics, dietary modulation, and personalized microbiome-based interventions. Despite promising therapeutic potential, microbiome engineering faces important challenges, including safety concerns, lack of standardized intervention protocols, and substantial inter-individual variability in host-microbiome responses, which currently limit clinical translation. This review focuses on both neurodegenerative and neuropsychiatric disorders, examining shared neuroinflammatory mechanisms mediated by the gut-brain axis and evaluating microbiotatargeted therapeutic strategies across these disease categories. The review discusses both preventive strategies, including dietary modulation, prebiotics, and lifestyle-based microbiome interventions, as well as therapeutic approaches such as microbiota-targeted treatments aimed at mitigating neuroinflammation and disease progression.
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Distinct Gut Microbiome Characteristics Associated with Mental Health Symptoms of Healthy Adults.
Background/Objectives: Mental health conditions, including stress, anxiety, depression, and sleep problems, represent a significant health concern globally. Mounting evidence suggests a link between mental health and the gut microbiome via the gut-brain axis. However, discrepancies in human microbiome data exist due to the heterogeneity in study design and analytical approaches. Thus, this study aimed to explore the gut microbial characteristics associated with self-reported mental health symptoms using multiple analytical methods. Methods: A total of 44 healthy adults, defined as individuals without any major chronic medical conditions, were assessed for mental health symptoms using self-reported questionnaire data. To evaluate gut microbial characteristics, stool samples were collected at six time points over 28 days and underwent 16S rRNA gene sequencing. Differential abundance was assessed via ANCOM-BC, and a random forest classifier was implemented to rank features important for the classification of mental health symptoms. Participants who did not report anxiety, stress, depression, or sleep problems served as the reference group for microbiome comparisons. Results: The proportion of participants with self-reported mental health symptoms was 11.4% (stress), 27.3% (depression), 31.8% (anxiety), and 15.9% (sleep problems). Participants reporting mental health symptoms showed differences in gut microbiome composition compared to asymptomatic participants, including variation in alpha- and beta-diversity. Differential analysis identified specific taxa with higher or lower relative abundance in participants reporting specific mental health symptoms. Random forest feature ranking identified partially overlapping taxa across methods, suggesting candidate associations warranting further investigation. Conclusions: These exploratory findings suggest that self-reported mental health symptoms in otherwise healthy adults are associated with differences in the gut microbiome. The taxa identified in this study represent candidates for validation in larger, independent cohorts.
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Akkermansia muciniphila attenuates association between specific metal exposures during pregnancy and depressive symptoms in late childhood.
Emerging research suggests that exposures to metals during pregnancy and consequent disruptions in gut microbiome (GM) are associated with depressive disorders in childhood. Akkermansia muciniphila, a GM bacteria, has been studied for its potential antidepressant effects. However, its role in influencing the association between prenatal metal exposures and depressive symptoms during childhood is unknown. Leveraging a well-characterized pediatric birth cohort and its microbiome substudy (n = 112), we investigated whether a certain subgroup of children at 9-11-year-of-age (characterized by a specific pattern of prenatal exposure to groups of metals or metal-clique) had worsened depressive symptoms and if the presence of A.muciniphila in GM modifies this association. A subgroup of children characterized by the prenatal metal-clique signature of zinc-chromium-cobalt had significantly increased depression scores; however, within that subgroup, children with A.muciniphila had much lower depression scores than those without A.muciniphila in the GM. Our analysis provides exploratory evidence hypothesizing A.muciniphila as an intervention attenuating the effect of prenatal metal-exposures-associated depressive disorders in late childhood.
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How Immune-inflammatory Processes Link CNS and Psychiatric Disorders: Classification and Treatment Implications.
In this article the emerging biological overlaps of CNS disorders and psychiatric conditions are reviewed. Recent work has highlighted how immune-inflammatory processes and their interactions with oxidative and nitrosative stress, couple to drive changes in neuroregulatory tryptophan catabolites, with consequences for serotonin availability, including as a precursor for the melatonergic pathways. Subsequent alterations in the regulation of local melatonin synthesis are likely to have direct impacts on the reactivity of immune cells, both centrally and systemically. These inflammatory processes also lead to the activation of wider immune processes. Such wider processes can include the production of immunoglobulin (Ig)A and IgM antibody responses, including to tryptophan catabolites, emphasizing the importance of immune responses, and their interactions with inflammatory processes, in the etiology and course of an array of medical conditions, including CNS disorders and psychiatric conditions. Such work poses questions as to the validity and utility of current, non-biologically based classification systems for psychiatric and CNS disorders. In this article, the biological underpinnings of CNS disorders and psychiatric conditions are reviewed in the context of how recent data, in reconceptualizing key processes in these classically-conceived brain-associated disorders, provides scope for novel, and hopefully more clinically useful, treatments. These processes are looked at in detail in Alzheimer's disease and major depressive disorder. One important treatment target is the gut. Alterations in the gut, including gut permeability and the composition of the microbiome, have now become an important target for treatment across an array of medical conditions, emphasizing the importance of targeting regulators of the immune system in developing novel treatments that are based on a more comprehensive and 'wholistic' understanding of currently poorly managed medical conditions, particularly psychiatric and CNS disorders.
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Analysis of Psychological and Gut Microbiome Characteristics in Patients With Non-erosive Reflux Disease.
Objective: To assess the correlation between the incidence of non-erosive reflux disease (NERD) and psychological factors, especially somatoform disorders. To investigate the characteristics of gut microbiome in NERD patients. Methods: We enrolled 24 NERD patients and 24 healthy controls. All patients were evaluated via GerdQ, SOMS-7, SAS, HAMA, and HAMD. Fecal samples were collected and 16S rRNA sequencing was performed to evaluate the gut microbiome composition. Results: The main symptoms of the NERD patients were regurgitation (87.5%), belching (66.7%), pharyngeal discomfort (50%), and heartburn (37.5%). The average score of GerdQ was 13.42 ± 3.41. In 15 patients (62.5%), the total score of the last two items was <3 points, while the average score of 24 patients was 3.63 ± 2.32. NERD patients with somatoform disorders accounted for 50%. There were 17 patients without anxiety, 6 patients with mild anxiety (25%), 1 patient with moderate anxiety (4.2%), and no patient with severe anxiety. There were 22 patients (91.7%) without depression, 2 patients (8.3%) with mild depression, and no patient with moderate or severe depression. The alpha diversity of NERD group was higher than HC, which showed significant difference (P < 0.05). The beta-diversity was significantly different between HC and NERD patients (P = 0.026), male and female patients (P = 0.009). The beta-diversity was also significantly different between male and female patients (P = 0.009). There were several bacteria with significant differences between HC and NERD group, and NERD patients with or without somatoform disorders, such as Firmicutes, TM7 were enriched in the NERD group compared with the healthy control group, while Bacteroidetes were enriched in the healthy controls. Conclusions: NERD symptoms overlap with somatoform disorders. NERD symptoms have an impact on the daily life quality of patients. Some of them are accompanied by anxiety and depression of different degrees, and the two are significantly correlated. The diversity of gut microbiome in patients with NERD is significantly higher than healthy controls, which has its characteristics. The predominant bacteria in gut microbiome of patients with NERD are similar to the healthy population, with Firmicutes and Bacteroidetes as the main ones. The composition of gut microbiome in NERD patients with or without somatoform disorder is significantly different, which may be related to the interaction of microbiome-brain-gut axis.
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Impact of diet on human gut microbiome and disease risk.
The gut microbiome of humans comprises a diverse group of trillions of microorganisms including symbiotic organisms, opportunistic pathogens and commensal organisms. This microbiota plays a major role in digesting food; it also helps with absorbing and synthesizing some nutrients and releases their metabolites, which may deliver a variety of growth-promoting and growth-inhibiting factors that influence human health either directly or indirectly. The balance between microbial species, especially those responsible for the fermentation of different substrates within the microbial community, which are in the majority, depends on daily diet. Therefore, an unbalanced diet may lead to the progression and development of human diseases. These include metabolic and inflammatory disorders, cancer and depression, as well as infant health and longevity. We provide an overview of the effect of diet on the human microbiome and assess the related risk of disease development.
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Linking oral microbiome with mental health: A review.
The gut microbiome shapes depression and anxiety, yet the oral microbiome that seeds it daily remains overlooked. Therefore, it is of interest to review on the oral microbiome's role in the gut-brain axis. A reproducible signature emerges: enriched Prevotella with depleted Haemophilus and Rothia. Four pathways connect a dysbiotic mouth to the brain inflammation, bacterial translocation, neurotransmitter signalling and HPA-axis dysregulation. As adults see hygienists more than any other clinician, dental visits could screen, prevent and refer along this axis.
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Identification of intestinal and fecal microbial biomarkers using a porcine social stress model.
Understanding the relationships between social stress and the gastrointestinal microbiota, and how they influence host health and performance is expected to have many scientific and commercial implementations in different species, including identification and improvement of challenges to animal welfare and health. In particular, the study of the stress impact on the gastrointestinal microbiota of pigs may be of interest as a model for human health. A porcine stress model based on repeated regrouping and reduced space allowance during the last 4 weeks of the finishing period was developed to identify stress-induced changes in the gut microbiome composition. The application of the porcine stress model resulted in a significant increase in salivary cortisol concentration over the course of the trial and decreased growth performance and appetite. The applied social stress resulted in 32 bacteria being either enriched (13) or depleted (19) in the intestine and feces. Fecal samples showed a greater number of microbial genera influenced by stress than caecum or colon samples. Our trial revealed that the opportunistic pathogens Treponema and Clostridium were enriched in colonic and fecal samples from stressed pigs. Additionally, genera such as Streptococcus, Parabacteroides, Desulfovibrio, Terrisporobacter, Marvinbryantia, and Romboutsia were found to be enriched in response to social stress. In contrast, the genera Prevotella, Faecalibacterium, Butyricicoccus, Dialister, Alloprevotella, Megasphaera, and Mitsuokella were depleted. These depleted bacteria are of great interest because they synthesize metabolites [e.g., short-chain fatty acids (SCFA), in particular, butyrate] showing beneficial health benefits due to inhibitory effects on pathogenic bacteria in different animal species. Of particular interest are Dialister and Faecalibacterium, as their depletion was identified in a human study to be associated with inferior quality of life and depression. We also revealed that some pigs were more susceptible to pathogens as indicated by large enrichments of opportunistic pathogens of Clostridium, Treponema, Streptococcus and Campylobacter. Generally, our results provide further evidence for the microbiota-gut-brain axis as indicated by an increase in cortisol concentration due to social stress regulated by the hypothalamic-pituitary-adrenal axis, and a change in microbiota composition, particularly of bacteria known to be associated with pathogenicity and mental health diseases.