Lin Shih-Kai Kevin, Chen Hsi-Chung, Chen I-Ming, Hsu Cheng-Dien, Huang Ming-Chyi, Liu Chih-Min, Wu Shu-I, Chen Po-Yu, Chen Chun-Hsin, Kuo Po-Hsiu
Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan.
Transl Psychiatry. 2025 Aug 18;15(1):290. doi: 10.1038/s41398-025-03521-1.
Depression, a common mood disorder, has been associated with gut microbiota alterations, though the underlying microbial mechanisms remain unclear. This study investigated potential gut microbiota biomarkers and functional pathways in 106 antidepressant-naïve depressive patients and 151 healthy controls, with careful of confounding factors. Stool samples were analyzed using 16S rRNA sequencing, revealing significantly lower alpha diversity and distinct beta diversity in depressive patients. Eleven taxa with differential abundance were identified, including Dialister and Lactococcus (decreased) and Hungatella, Sellimonas, and Lachnoclostridium (elevated), which may relate to gut inflammation and depressive symptom severity. Functional pathway analysis highlighted 36 altered pathways, including those involved in purine degradation, lipopolysaccharide biosynthesis, and amino acid metabolism. A random forest classification model built using the identified taxa achieved moderate accuracy (~0.72) in distinguishing depressive patients from controls. Additionally, we developed a novel Depression Dysbiosis Index (DDI), which positively correlated with depression severity and effectively differentiated between groups. The DDI was robust across analyses, emphasizing its potential clinical value. Future research should incorporate longitudinal designs, advanced sequencing techniques, and additional clinical factors to deepen our understanding of the gut-brain axis in depression and improve diagnostic and therapeutic strategies.
抑郁症是一种常见的情绪障碍，虽其潜在的微生物机制尚不清楚，但已发现与肠道微生物群改变有关。本研究在仔细考虑混杂因素的情况下，对106例未服用过抗抑郁药的抑郁症患者和151例健康对照者的潜在肠道微生物群生物标志物和功能途径进行了研究。使用16S rRNA测序分析粪便样本，结果显示抑郁症患者的α多样性显著降低，β多样性明显不同。鉴定出11个丰度有差异的分类群，包括戴阿利斯特菌属和乳球菌属（丰度降低）以及亨盖特菌属、塞尔利莫纳斯菌属和布劳特氏菌属（丰度升高），这些分类群可能与肠道炎症和抑郁症状严重程度有关。功能途径分析突出了36条改变的途径，包括参与嘌呤降解、脂多糖生物合成和氨基酸代谢的途径。使用鉴定出的分类群构建的随机森林分类模型在区分抑郁症患者和对照者方面达到了中等准确率（约0.72）。此外，我们开发了一种新的抑郁症生态失调指数（DDI），该指数与抑郁症严重程度呈正相关，并能有效区分不同组。DDI在各项分析中都很稳健，强调了其潜在的临床价值。未来的研究应纳入纵向设计、先进的测序技术和其他临床因素，以加深我们对抑郁症中肠-脑轴的理解，并改进诊断和治疗策略。
