Bioscience of Microbiota, Food and Health
Online ISSN : 2186-3342
ISSN-L : 2186-3342
Full Paper
Differences in the human gut microbiota with varying depressive symptom severity scores
Yuka MASAMURARyuichi KUBOYuki MIDORIKAWANatsuko O. SHINOZAKISatoshi WATANABESayumi MAEKAWAAya K TAKEDATazro OHTA
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ジャーナル オープンアクセス
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2024 年 43 巻 4 号 p. 336-341

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Depression is a prevalent mental health disorder, and its incidence has increased further because of the coronavirus disease 2019 (COVID-19) pandemic. The gut microbiome has been suggested as a potential target for mental health treatment because of the bidirectional communication system between the brain and gastrointestinal tract, known as the gut-brain axis. We aimed to investigate the relationship between the human gut microbiome and depression screening by analyzing the abundance and types of microbiomes among individuals living in Japan, where mental health awareness and support may differ from those in other countries owing to cultural factors. We used a data-driven approach to evaluate the gut microbiome of participants who underwent commercial gut microbiota testing services and completed a questionnaire survey that included a test for scoring depressive tendencies. Our data analysis results indicated that no significant differences in gut microbiome composition were found among the groups based on their depression screening scores. However, the results also indicated the potential existence of a few differentially abundant bacterial taxa. Specifically, the detected bacterial changes in abundance suggest that the Bifidobacteriaceae, Streptococcaceae, and Veillonellaceae families are candidates for differentially abundant bacteria. Our findings should contribute to the growing body of research on the relationship between gut microbiome and mental health, highlighting the potential of microbiome-based interventions for depression treatment. The limitations of this study include the lack of clear medical information on the participants’ diagnoses. Future research could benefit from a larger sample size and more detailed clinical information.

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© 2024 by BMFH Press

This article is licensed under a Creative Commons [Attribution-NonCommercial-NoDerivatives 4.0 International] license.
https://creativecommons.org/licenses/by-nc-nd/4.0/
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