Gut Microbiome in Depression with and without REM Sleep Behavior Disorder.

Multimodal AI for predicting comorbid REM sleep behavior disorder in major depressive disorder.

REM sleep behavior disorder (RBD) is a robust prodromal marker of α-synucleinopathies: idiopathic RBD carries a 10-15-year phenoconversion risk of 80-90% to Parkinson's disease (PD) and related disorders. In major depressive disorder (MDD), comorbid RBD marks a subgroup at elevated prodromal PD risk, yet is frequently missed in psychiatric practice. Here, we developed a multimodal AI framework to detect comorbid RBD in MDD. From a clinical cohort of 329 patients, we obtained 261 video clips in 31 patients during reading and spontaneous-speech tasks, including 19 patients with MDD-RBD and 12 demographically and medication-matched MDD-only controls that, to our knowledge, formed the largest cohort of its kind worldwide. We used a dual-stream multimodal model that learned facial dynamics from video and vocal features from speech, and then combined both signals to predict comorbid RBD. In 5-fold cross-validation, our best model achieved 80.5% accuracy and 0.848 F1-score. Explainability analysis highlighted lower-face tension and variability, together with brow lowering, as candidate biomarkers requiring further validation. Predicted risk correlated with RBDQ score (r = 0.53, p = 0.005) and weakly with UPDRS motor score (r = 0.34, p = 0.067). Out-of-distribution evaluation showed broadly similar patterns, supporting the promise of multimodal AI for predicting RBD in MDD and identifying interpretable potential digital markers of prodromal synucleinopathy.

Vulnerability for new episodes in recurrent major depressive disorder: Protocol for the longitudinal DELTA-neuroimaging cohort study

The Gut–Brain Axis in Depression: A Systematic Review of Microbiota and Mental Health

Major depressive disorder (MDD) affects approximately 280 million people worldwide, yet conventional pharmacotherapy achieves remission in only 30–50% of patients, intensifying the search for novel biological substrates. This systematic review, conducted according to PRISMA 2020 guidelines across six electronic databases (2014–March 2025), synthesised 89 studies examining gut microbiota composition in adults with MDD compared to healthy controls. MDD was consistently associated with reduced alpha diversity and a recurrent dysbiotic pattern, herein proposed as a depressive dysbiosis signature, characterised by depletion of butyrate-producing genera (Faecalibacterium, Roseburia, Eubacterium, Coprococcus) and enrichment of pro-inflammatory taxa (Alistipes, Eggerthella, Streptococcus). While this pattern was observed across multiple cohorts, significant inter-study heterogeneity precludes its definition as a universal microbial signature for MDD. Beta diversity analyses demonstrated robust compositional separation between cohorts. Plausible mechanistic pathways included compromised short-chain fatty acid production, increased intestinal permeability, low-grade systemic inflammation, tryptophan shunting toward the kynurenine pathway, and hypothalamic–pituitary–adrenal axis dysregulation. Preclinical faecal microbiota transplantation provided translational evidence consistent with a causal interpretation, while randomised probiotic trials demonstrated significant reductions in depressive symptom severity compared with placebo. Probiotic effects are strain-specific according to ISAPP consensus; generalisation across strains is not warranted. Gut microbiota dysbiosis represents a biologically plausible mediator of depression pathophysiology, with a recurrent dysbiotic pattern, characterised by depletion of butyrate-producing taxa and enrichment of pro-inflammatory genera, showing emerging diagnostic and therapeutic potential.

Neuroinflammation in Major Depressive Disorder: Mechanisms, Biomarkers, and Therapeutic Implications

Background: Major depressive disorder (MDD) is heterogeneous, and low-grade systemic inflammation may contribute to illness in a clinically relevant subgroup. Methods: This narrative review examined human studies published between January 2010 and June 2026, prioritizing systematic reviews, meta-analyses, cohort studies, central biomarker research, and randomized trials. Results: Approximately one-quarter of patients with depression have CRP levels above 3 mg/L, supporting an inflammatory phenotype rather than a universal inflammatory model. Immune signals may affect brain function through blood–brain barrier, neural, neurovascular, and metabolic pathways, influencing neurotransmission, stress regulation, oxidative balance, and neuroplasticity. CRP is the most accessible clinical marker, but no biomarker reliably identifies inflammatory depression. Anti-inflammatory treatments show inconsistent benefits, with the strongest signals observed in biomarker-selected patients. Conclusion: Inflammation contributes to MDD in some patients, but single-marker diagnosis and routine anti-inflammatory treatment are not currently justified. Biomarker-stratified trials are needed to develop precision therapies.

Analysis of individualized brain–gut association networks and transcriptional patterns in major depressive disorder

The brain‒gut association patterns in major depressive disorder (MDD) and in MDD with suicidal ideation (MDDSI) remain largely unknown. This study included 118 healthy controls and 118 first‐episode, drug‐naive adolescents and young adults with MDD, including 60 MDDSI patients and 58 MDD patients without SI. First, a novel network for investigating individualized brain‒gut associations is proposed based on the algorithm of node importance coupling. Second, the graph convolutional network is applied at the individual level to identify MDD and MDDSI patients, and the GNNExplainer algorithm is used to determine key brain–gut connections. Third, analyses of transcriptional patterns and pathways are conducted to reveal multilevel brain‒gut association characteristics in MDD and MDDSI. The results suggested that associations between proinflammatory gut microbiota and the herpes simplex virus type 1 infection pathway may contribute to the onset of MDD through inflammatory processes. Furthermore, associations between the sulfur metabolism pathway and the insulin signaling pathway may be related to alterations in insulin metabolism and to the significantly increased C‐peptide levels observed in MDDSI patients. Notably, C‐peptide levels were positively correlated with SI. These findings may provide new insights into the potential neuropathological mechanisms of multilevel brain‒gut associations in MDD and MDDSI.

From gut to brain: data-driven evidence suggests causal contribution of gut-microbiota to major depressive disorder in humans

Abstract Major Depressive Disorder (MDD) is a highly prevalent, severe mental health condition that constitutes one of the leading causes of disability worldwide. While recent animal studies suggest a causal role of the gut microbiome in the pathophysiology of MDD models, evidence in humans is still unclear due to small sample sizes, inconsistent clinical assessment of MDD diagnosis, and methodological limitations regarding causal inference in cross-sectional data. Here, we explicitly address these shortcomings to investigate the potential causal link between the gut microbiome and MDD: First, we replicate previously reported microbiome-depression associations using one of the largest multicenter MDD cohorts for which microbiome data and in-depth diagnostic assessment are available (N = 1,269 MDD patients and controls). We find a significant difference between healthy controls and MDD patients for the relative abundance of four taxa: Eggerthella, Hungatella, Coprobacillus, and Lachnospiraceae FCS020. Second, we employ state-of-the-art, fully data-driven causal inference tools within Judea Pearl's framework, allowing us to derive model constraints from the data rather than relying on potentially strong, unrealistic assumptions. Using this approach, we found evidence for Eggerthella and Hungatella as potential causal contributors to MDD. Furthermore, we show that the potential causal effects of Eggerthella and Hungatella on MDD persist beyond the influence of body mass index, revealing two distinct potential causal pathways linking the gut microbiome to MDD. Finally, the difference in relative abundance of these taxa between healthy and MDD patients was independent of antidepressant medication. Our study provides the first data-driven evidence for a potential causal role of gut microbiota in the pathophysiology of depression in humans.