AUTHOR=Okuma Kana , Hatayama Kouta , Tokuno Hidetaka , Ebara Aya , Odachi Ayano , Masuyama Hiroaki , Hoshiko Naomi , Tanaka Nobuaki 

TITLE=A risk estimation method for depression based on the dysbiosis of intestinal microbiota in Japanese patients

JOURNAL=Frontiers in Psychiatry

VOLUME=15

YEAR=2024

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2024.1382175

DOI=10.3389/fpsyt.2024.1382175

ISSN=1664-0640

ABSTRACT=<sec><title>Introduction</title><p>Early detection of depression is important for preventing depression-related suicides and reducing the risk of recurrence. This study explored the association between depression and intestinal microbiota and developed a depression risk-estimation method based on this.</p></sec><sec><title>Methods</title><p>The intestinal microbiota of Japanese patients with depression (33 males and 35 females) and disease-free controls (246 males and 384 females) in their 20’s to 60’s were compared by sex using 16S rRNA gene amplicon sequencing. A depression-risk estimation method was developed using structural equation modeling.</p></sec><sec><title>Results</title><p>Intestinal bacteria taxa that differed between depression and control groups were identified based on effect size (absolute value greater than 0.2). <italic>Neglecta</italic> was more abundant, while <italic>Coprobacter</italic>, <italic>Butyricimonas</italic>, <italic>Clostridium</italic>_XlVb, and <italic>Romboutsia</italic> were less abundant in the male depression group compared to the male control group. In the female depression group, <italic>Massilimicrobiota</italic>, <italic>Merdimonas</italic>, and <italic>Sellimonas</italic> were more abundant, whereas <italic>Dorea</italic> and <italic>Agathobacter</italic> were less abundant compared to the female control group. Several of the intestinal bacterial taxa that were less abundant in depression were associated with butyrate or hydrogen production. Using these depression-associated intestinal bacteria as indicators, risk-estimation models using structural equation modeling for depression were developed. In the risk-estimation models for males and females, the areas under the receiver operating characteristic curve were 0.72 and 0.70, respectively, indicating that these models can distinguish between individuals with and without depression.</p></sec><sec><title>Conclusions</title><p>This study provides insights into depression etiology and aids in its early detection and treatment.</p></sec>