1. Exploration of microbiota targets for major depressive disorder and mood related traits.
- Author
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Chung YE, Chen HC, Chou HL, Chen IM, Lee MS, Chuang LC, Liu YW, Lu ML, Chen CH, Wu CS, Huang MC, Liao SC, Ni YH, Lai MS, Shih WL, and Kuo PH
- Subjects
- Adult, Anxiety microbiology, Dietary Fats, Feces microbiology, Female, Humans, Male, Middle Aged, Stress, Psychological microbiology, Taiwan, Depressive Disorder, Major microbiology, Gastrointestinal Microbiome, RNA, Ribosomal, 16S isolation & purification
- Abstract
Growing evidence suggests the link between gut microbiota and mood regulation. The current study aimed to identify microbiota targets for major depressive disorder (MDD) and mood-related traits in Taiwanese samples, while taking into account the influence of dietary patterns. We recruited 36 MDD patients and 37 healthy controls for 16S rRNA gene sequencing. We assessed nutrient content using food frequency questionnaire, and mood related phenotypes, including depressive severity, anxiety, and perceived stress. Analysis of composition of microbiomes (ANCOM) models were performed to evaluate microbiota compositions between patients and controls, while adjusted for fat intake% and sequencing platforms. We found 23 taxa (4 phyla, 7 families and 12 genera) to be associated with depression and beta diversity was differed between groups. Phylum Actinobacteria and Firmicutes were overrepresented in MDD patients. At genus level, Bifidobacterium (7%) and Blautia (8%) had relatively high abundance among MDD patients, while Prevotella (16%) had high abundance in controls. Holdemania exhibited moderate correlation with anxiety (r = 0.65) and perceived stress level (r = 0.49) mainly in MDD patients but not controls. Pathway analyses revealed that pentose phosphate and starch and sucrose metabolism processes were important pathways for depression via microbiota functions. In conclusion, our results revealed microbiota targets for depression that are independent of fat intake. It is worthwhile to conduct further studies to replicate the current findings and to integrate with biochemistry and metabolomics data to better understand the functions of identified targets., (Copyright © 2019 Elsevier Ltd. All rights reserved.)
- Published
- 2019
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