Effects of diet on the gut microbiome in patients with depression

Zorkina, Yana; Syunyakov, Timur; Abramova, Olga; Yunes, Roman А.; Averina, Olga V.; Kovtun, Alexey S.; Angelova, Irina Y.; Khobta, Elena B.; Susloparova, Daria; Pavlichenko, Aleksey Viktorovich; Andreyuk, D. S.; Tovmasyan, A.S.; Даниленко, В. Н.; Gurina, O. I.; Kostyuk, Georgiy; Morozova, Аnna

doi:10.17116/jnevro202212201259

Cited by 5 publications

(6 citation statements)

References 23 publications

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“…4A, Table S2). This finding is consistent with prior studies proposing Erysipelatoclostridium as a depression marker 139,140 and its positive association with anorexia nervosa 141 and radiation-induced intestinal injury 142 . These data shed light on the potentially beneficial effects of the Prevotella genus, notably in modulating CXCL-1 expression and its significant role in enhancing perceptions of the world as enticing (Fig.…”

Section: Resultssupporting

confidence: 93%

Dynamic Human Gut Microbiome and Immune Shifts During an Immersive Psychosocial Therapeutic Program

Zhou,

Ganz,

Rayner

et al. 2024

Preprint

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BackgroundDepression is a leading cause of disability worldwide yet its underlying factors, particularly microbial associations, are poorly understood.MethodsWe examined the longitudinal interplay between the microbiome and immune system in the context of depression during an immersive psychosocial intervention. 142 multi-omics samples were collected from 52 well-characterized participants before, during, and three months after a nine-day inquiry-based stress reduction program.ResultsWe found that depression was associated with both an increased presence of putatively pathogenic bacteria and reduced microbial beta-diversity. Following the intervention, we observed reductions in neuroinflammatory cytokines and improvements in several mental health indicators. Interestingly, participants with aPrevotella-dominant microbiome showed milder symptoms when depressed, along with a more resilient microbiome and more favorable inflammatory cytokine profile, including reduced levels of CXCL-1.ConclusionsOur findings reveal a protective link between the Prevotella-dominant microbiome and depression, associated with a less inflammatory environment and moderated symptoms. These insights, coupled with observed improvements in neuroinflammatory markers and mental health from the intervention, highlight potential avenues for microbiome-targeted therapies in depression management.

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Section: Resultssupporting

confidence: 93%

Dynamic Human Gut Microbiome and Immune Shifts During an Immersive Psychosocial Therapeutic Program

Zhou,

Ganz,

Rayner

et al. 2024

Preprint

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“…A previous study showed that patients with type 2 diabetes had higher Erysipelotrichaceae levels than patients with normal glucose tolerance [ 41 ]. There is growing evidence showing the adverse roles of Erysipelotrichaceae and Erysipelatoclostridium play in host lipid metabolism [ 42 ], immune response [ 43 ], inflammation [ 44 ], depression [ 45 ], metabolic-associated fatty liver disease [ 46 ], cancer [ 47 ], and response to cancer immune therapy [ 48 , 49 ]. However, in a human-based study, increased physical activity was associated with a higher relative abundance of Erysipelotrichaceae [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

The Association between Caffeine Intake and the Colonic Mucosa-Associated Gut Microbiota in Humans—A Preliminary Investigation

Dai

Hoffman

et al. 2023

Nutrients

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We examined the association between caffeine and coffee intake and the community composition and structure of colonic microbiota. A total of 34 polyp-free adults donated 97 colonic biopsies. Microbial DNA was sequenced for the 16S rRNA gene V4 region. The amplicon sequence variant was assigned using DADA2 and SILVA. Food consumption was ascertained using a food frequency questionnaire. We compared the relative abundance of taxonomies by low (<82.9 mg) vs. high (≥82.9 mg) caffeine intake and by never or <2 cups vs. 2 cups vs. ≥3 cups coffee intake. False discovery rate-adjusted p values (q values) <0.05 indicated statistical significance. Multivariable negative binomial regression models were used to estimate the incidence rate ratio and its 95% confidence interval of having a non-zero count of certain bacteria by intake level. Higher caffeine and coffee intake was related to higher alpha diversity (Shannon index p < 0.001), higher relative abundance of Faecalibacterium and Alistipes, and lower relative abundance of Erysipelatoclostridium (q values < 0.05). After adjustment of vitamin B2 in multivariate analysis, the significant inverse association between Erysipelatoclostridium count and caffeine intake remained statistically significant. Our preliminary study could not evaluate other prebiotics in coffee.

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“…F. prausnitzii is one of the most common microbial species in the colon of healthy adults and constitutes over 5-15% of the overall total bacterial population [33]. Faecalibacterium is prevalent in human populations across the world-it was detected in 85% of gut samples [34].…”

Section: Discussionmentioning

confidence: 99%

“…Short-chain fatty acids are important for intestinal health, because they serve as the main source of energy for the cells of the intestinal wall and contribute to healthy functioning. In addition, Faecalibacterium can have an anti-inflammatory effect by reducing the level of inflammatory cytokines in the intestine [33,34]. The link between the reduced Faecalibacterium levels and depression may be associated with the violation of the balance of gut microbiota, which may affect neuroinflammation and neuromodulation through complex signaling mechanisms [34,35].…”

Section: Discussionmentioning

confidence: 99%

Unveiling the Connection between Microbiota and Depressive Disorder through Machine Learning

Angelova,

Kovtun,

Averina

et al. 2023

IJMS

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In the last few years, investigation of the gut–brain axis and the connection between the gut microbiota and the human nervous system and mental health has become one of the most popular topics. Correlations between the taxonomic and functional changes in gut microbiota and major depressive disorder have been shown in several studies. Machine learning provides a promising approach to analyze large-scale metagenomic data and identify biomarkers associated with depression. In this work, machine learning algorithms, such as random forest, elastic net, and You Only Look Once (YOLO), were utilized to detect significant features in microbiome samples and classify individuals based on their disorder status. The analysis was conducted on metagenomic data obtained during the study of gut microbiota of healthy people and patients with major depressive disorder. The YOLO method showed the greatest effectiveness in the analysis of the metagenomic samples and confirmed the experimental results on the critical importance of a reduction in the amount of Faecalibacterium prausnitzii for the manifestation of depression. These findings could contribute to a better understanding of the role of the gut microbiota in major depressive disorder and potentially lead the way for novel diagnostic and therapeutic strategies.

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Effects of diet on the gut microbiome in patients with depression

Cited by 5 publications

References 23 publications

Dynamic Human Gut Microbiome and Immune Shifts During an Immersive Psychosocial Therapeutic Program

Dynamic Human Gut Microbiome and Immune Shifts During an Immersive Psychosocial Therapeutic Program

The Association between Caffeine Intake and the Colonic Mucosa-Associated Gut Microbiota in Humans—A Preliminary Investigation

Unveiling the Connection between Microbiota and Depressive Disorder through Machine Learning

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