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A Walnut-Derived Peptide WSPSGR Alleviates Depressive-Like Behaviors in Mice via IDO1 Inhibition and Gut Microbiota-Tryptophan Axis Modulation.
Depression is a complex psychiatric disorder with increasing global impact. This study explored the antidepressant mechanisms of Trp-Ser-Pro-Ser-Gly-Arg (WSPSGR), a walnut-derived peptide with indoleamine 2,3-dioxygenase 1 (IDO1) inhibitory activity. In a chronic unpredictable mild stress (CUMS)-induced mouse model, WSPSGR ameliorated depressive-like behaviors by restoring tryptophan (Trp) metabolic balance and reshaping gut microbiota composition. Notably, it reduced IDO1-mediated kynurenine (Kyn) pathway activation and corrected gut dysbiosis, including a decreased Firmicutes/Bacteroidota ratio. These effects collectively re-established microbiota-gut-brain axis homeostasis. These findings identify IDO1 as a key target of WSPSGR and suggest that peptide-based modulation of Trp metabolism and gut microbiota may be a promising strategy for depression therapy.
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The 3 Ds: Depression, Dysbiosis, and Clostridiodes difficile.
This paper explores the intricate relationship between depression, gut dysbiosis, and Clostridioides difficile infections, collectively termed "The 3 Ds". Depression is a widespread mental disorder increasing in prevalence. It is recognized for its societal burden and complex pathophysiology, encompassing genetic, environmental, and microbiome-related factors. The consequent increased use of antidepressants has led to growing concerns about their effects on the gut microbiome. Various classes of antidepressants and antipsychotics show antimicrobial activity, potentially leading to shifts in the gut microbiome and contributing to the development of dysbiosis. Dysbiosis, in turn, can predispose individuals to opportunistic infections like C. difficile, a significant healthcare concern due to its high recurrence rates and severe impact on patients' quality of life. Further, the link between antidepressant use and an increased risk of C. difficile infection (CDI) is explored and, finally, the emergence of live biotherapeutic products as novel treatment options for recurrent CDI is discussed.
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A novel framework for assessing causal effect of microbiome on health: long-term antibiotic usage as an instrument.
Assessing causality is undoubtedly one of the key questions in microbiome studies for the upcoming years. Since randomized trials in human subjects are often unethical or difficult to pursue, analytical methods to derive causal effects from observational data deserve attention. As simple covariate adjustment is not likely to account for all potential confounders, the idea of instrumental variable (IV) analysis is worth exploiting. Here we propose a novel framework of antibiotic instrumental variable regression (AB-IVR) for estimating the causal relationships between microbiome and various diseases. We rely on the recent studies showing that antibiotic treatment has a cumulative long-term effect on the microbiome, resulting in individuals with higher antibiotic usage to have a more perturbed microbiome. We apply the AB-IVR method on the Estonian Biobank data and show that the microbiome has a causal role in numerous diseases including migraine, depression and irritable bowel syndrome. We show with a plethora of sensitivity analyses that the identified causal effects are robust and propose ways for further methodological developments.
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Evaluating the interactive effects of dietary habits and human gut microbiome on the risks of depression and anxiety.
BACKGROUND: Gut microbiome and dietary patterns have been suggested to be associated with depression/anxiety. However, limited effort has been made to explore the effects of possible interactions between diet and microbiome on the risks of depression and anxiety. METHODS: Using the latest genome-wide association studies findings in gut microbiome and dietary habits, polygenic risk scores (PRSs) analysis of gut microbiome and dietary habits was conducted in the UK Biobank cohort. Logistic/linear regression models were applied for evaluating the associations for gut microbiome-PRS, dietary habits-PRS, and their interactions with depression/anxiety status and Patient Health Questionnaire (PHQ-9)/Generalized Anxiety Disorder-7 (GAD-7) score by R software. RESULTS: We observed 51 common diet-gut microbiome interactions shared by both PHQ score and depression status, such as overall beef intake × genus Sporobacter [hurdle binary (HB)] (PPHQ = 7.88 × 10-4, Pdepression status = 5.86 × 10-4); carbohydrate × genus Lactococcus (HB) (PPHQ = 0.0295, Pdepression status = 0.0150). We detected 41 common diet-gut microbiome interactions shared by GAD score and anxiety status, such as sugar × genus Parasutterella (rank normal transformed) (PGAD = 5.15 × 10-3, Panxiety status = 0.0347); tablespoons of raw vegetables per day × family Coriobacteriaceae (HB) (PGAD = 6.02 × 10-4, Panxiety status = 0.0345). Some common significant interactions shared by depression and anxiety were identified, such as overall beef intake × genus Sporobacter (HB). CONCLUSIONS: Our study results expanded our understanding of how to comprehensively consider the relationships for dietary habits-gut microbiome interactions with depression and anxiety.
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Depression phenotype identified by using single nucleotide exact amplicon sequence variants of the human gut microbiome.
Single nucleotide exact amplicon sequence variants (ASV) of the human gut microbiome were used to evaluate if individuals with a depression phenotype (DEPR) could be identified from healthy reference subjects (NODEP). Microbial DNA in stool samples obtained from 40 subjects were characterized using high throughput microbiome sequence data processed via DADA2 error correction combined with PIME machine-learning de-noising and taxa binning/parsing of prevalent ASVs at the single nucleotide level of resolution. Application of ALDEx2 differential abundance analysis with assessed effect sizes and stringent PICRUSt2 predicted metabolic pathways. This multivariate machine-learning approach significantly differentiated DEPR (n = 20) vs. NODEP (n = 20) (PERMANOVA P < 0.001) based on microbiome taxa clustering and neurocircuit-relevant metabolic pathway network analysis for GABA, butyrate, glutamate, monoamines, monosaturated fatty acids, and inflammasome components. Gut microbiome dysbiosis using ASV prevalence data may offer the diagnostic potential of using human metaorganism biomarkers to identify individuals with a depression phenotype.
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Association Between Gut Microbiota and Depressive Symptoms: A Cross-Sectional Population-Based Study in South Korea.
OBJECTIVE: This study aimed to investigate the association between gut microbiota and depressive symptoms in a large population cohort of Korean adults. METHODS: Overall, 1238 participants were included in the study. Participants were categorized into depressed or non-depressed groups, based on the depressive symptoms reported on the Center for Epidemiologic Studies Rating Scale for Depression, with a cutoff score of 16, and their fecal microbiota was profiled using 16S ribosomal RNA gene sequencing. Several alpha and beta diversity measures were also estimated. The association between depressive symptoms and gut microbiota was analyzed using generalized linear models. The inferred function of the metagenomes was compared between the two groups. RESULTS: There were no consistent differences in alpha and beta diversity between the depressed and non-depressed groups. However, the continuous measure of depressive symptoms was inversely associated with one of four measures of alpha diversity (Shannon's diversity, p = .021). We also found a substantial difference between the depressed and non-depressed groups in the Bray-Curtis dissimilarity among the four beta diversity indices ( p = .004). Participants whose depressive symptoms exceeded a clinical cutoff score had a lower relative abundance of the genus Faecalibacterium when compared with controls (coefficient = -0.025, q = 0.047). However, the depressed group had a significantly higher abundance of the genus Oscillospira than did the non-depressed group (coefficient = 0.002, q = 0.023). CONCLUSIONS: Our findings contribute to the identification of potential relationships between the gut microbiota and depressive symptoms and provide useful insights for developing microbiota-based interventions for patients with depressive symptoms.
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Exploring the Characteristics of Gut Microbiota Associated with Depression via the Depression Assessment Scales.
Depression is a prevalent mental disorder with an increasing economic burden, and its pathogenesis remains poorly understood. Given the emerging evidence linking the gut microbiota to mental health, a better understanding of microbial profiles associated with depression is necessary. Here, we explore the association between gut microbiota and depression by utilizing 16S rRNA amplicon sequencing and depression assessment scales, including the Hamilton Depression Rating Scale (HDRS) and the Beck Depression Inventory (BDI). The study cohort consisted of 46 subjects, who were categorized into depression and normal groups based on medical diagnoses and depression scale scores. Our analyses revealed that HDRS-based classification better identified distinct gut microbiota structures associated with depression than medical diagnoses alone. Notably, lower beta diversity was observed in individuals with depression, indicating a more homogeneous gut microbial community. By employing both HDRS and BDI scores simultaneously, we identified specific taxa, such as Bilophila and Alistipes, which are linked to depressive symptoms. These findings highlight the potential of using depression assessment scales in conjunction with gut microbiota data to advance our understanding of depression and inform future treatment strategies.
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The neuroactive potential of the elderly human gut microbiome is associated with mental health status.
Ageing is usually associated with physiological decline, increased mental health issues, and cognitive. deterioration, alongside specific changes in the gut microbiome. However, the relationship between the neuroactive potential of the gut microbiome and mental health and cognition among the elderly remains less explored. This study examines a cohort of 153 older Chilean adults with cognitive complaints, assessing anthropometric data, mental health via five distinct tests, and gut microbiome composition through 16SV4 sequencing. Our findings reveal associations between anthropometric factors and depression scores in mental tests of participants with their gut microbiome composition. Notably, depression was associated with changes in the abundance of Lachnospiraceae Eubacterium xylanophilum group and Fusobacteriaceae Fusobacterium. Additionally, bacterial pathways involved in metabolising neuroactive compounds such as tryptophan, short-chain fatty acids, p-cresol, glutamate, and nitric oxide were associated with participant age, sex, and cognitive performance. Moreover, participants' sex was associated with the neuroactive potential of specific bacteria, suggesting a role of the gut microbiome in sex-related mental health differences in the elderly. Altogether, this study provides the first evidence from a South American cohort linking the inferred neuroactive potential of the gut microbiome to cognitive and psychological function in older adults with cognitive complaints, offering novel insights into microbiota-based mechanisms that may contribute to mental health and ageing.
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Maternal dysbiosis produces long-lasting behavioral changes in offspring.
Advanced maternal age (AMA) is defined as a pregnancy in a woman older than 35 years of age. AMA increases the risk for both maternal and neonatal complications, including miscarriage and stillbirth. AMA has also been linked to neurodevelopmental and neuropsychiatric disorders in the offspring. Recent studies have found that age-associated compositional shifts in the gut microbiota contribute to altered microbial metabolism and enhanced inflammation in the host. We investigated the specific contribution of the maternal microbiome on pregnancy outcomes and offspring behavior by recolonizing young female mice with aged female microbiome prior to pregnancy. We discovered that pre-pregnancy colonization of young dams with microbiome from aged female donors significantly increased fetal loss. There were significant differences in the composition of the gut microbiome in pups born from dams recolonized with aged female biome that persisted through middle age. Offspring born from dams colonized with aged microbiome also had significant changes in levels of neurotransmitters and metabolites in the blood and the brain. Adult offspring from dams colonized with an aged microbiome displayed persistent depressive- and anxiety-like phenotypes. Collectively, these results demonstrate that age-related changes in the composition of the maternal gut microbiome contribute to chronic alterations in the behavior and physiology of offspring. This work highlights the potential of microbiome-targeted approaches, even prior to birth, may reduce the risk of neuropsychiatric disorders.
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Association of yoga with cognitive and gut microbiome changes in Alzheimer's disease: An exploratory case-control study.
BackgroundAlzheimer's disease (AD) is marked by cognitive decline, depressive symptoms, and gut microbial dysbiosis. Yoga may support cognitive and emotional health while modulating gut microbiota, but integrative clinical evidence is limited.ObjectiveTo evaluate the effects of a 12-week yoga intervention on cognition, depressive symptoms, and gut microbial diversity, composition, and function in Indian patients with mild AD.MethodsIn this hospital-based case-control study, 16 AD patients and 17 cognitively healthy controls (HCs) were recruited at AIIMS, New Delhi. AD diagnosis followed NIA-AA criteria, supported by Montreal Cognitive Assessment (MoCA) and Patient Health Questionnaire-9 (PHQ-9) assessments. AD participants underwent 60-min supervised yoga sessions daily for 12 weeks. Cognitive performance, depressive symptoms, and stool microbiota were assessed pre- and post-intervention. Metagenomic sequencing enabled taxonomic and functional profiling, with alpha diversity, beta diversity (Bray-Curtis distance), and differential abundance analyses performed using standard bioinformatics tools.ResultsYoga was associated with improved cognition (MoCA: 22.33 ± 2.34 → 25.44 ± 2.01; p = 0.001) and reduced depressive symptoms (PHQ-9: 5.78 ± 3.11 → 2.22 ± 1.71; p = 0.007). Alpha diversity remained stable, while beta diversity shifted post-yoga AD samples toward the HC cluster. Beneficial taxa (Faecalibacterium prausnitzii, Roseburia intestinalis, Bifidobacterium, Akkermansia) increased, whereas pro-inflammatory taxa (Collinsella aerofaciens, Klebsiella spp.) decreased. Functional analysis showed partial recovery of metabolic and short-chain fatty acid pathways.ConclusionsA 12-week yoga intervention was associated with cognitive and mood improvements and partial normalization of gut microbial function in mild AD. Larger randomized trials with lifestyle monitoring and multi-omics integration are warranted to confirm causal mechanisms.