Chen Jian-Jun, Zheng Peng, Liu Yi-Yun, Zhong Xiao-Gang, Wang Hai-Yang, Guo Yu-Jie, Xie Peng
Institute of Life Sciences.
Department of Neurology, First Affiliated Hospital.
Neuropsychiatr Dis Treat. 2018 Feb 26;14:647-655. doi: 10.2147/NDT.S159322. eCollection 2018.
Our previous studies found that disturbances in gut microbiota might have a causative role in the onset of major depressive disorder (MDD). The aim of this study was to investigate whether there were sex differences in gut microbiota in patients with MDD.
First-episode drug-naïve MDD patients and healthy controls were included. 16S rRNA gene sequences extracted from the fecal samples of the included subjects were analyzed. Principal-coordinate analysis and partial least squares-discriminant analysis were used to assess whether there were sex-specific gut microbiota. A random forest algorithm was used to identify the differential operational taxonomic units. Linear discriminant-analysis effect size was further used to identify the dominant sex-specific phylotypes responsible for the differences between MDD patients and healthy controls.
In total, 57 and 74 differential operational taxonomic units responsible for separating female and male MDD patients from their healthy counterparts were identified. Compared with their healthy counterparts, increased Actinobacteria and decreased Bacteroidetes levels were found in female and male MDD patients, respectively. The most differentially abundant bacterial taxa in female and male MDD patients belonged to phyla Actinobacteria and Bacteroidia, respectively. Meanwhile, female and male MDD patients had different dominant phylotypes.
These results demonstrated that there were sex differences in gut microbiota in patients with MDD. The suitability of Actinobacteria and Bacteroidia as the sex-specific biomarkers for diagnosing MDD should be further explored.
我们之前的研究发现,肠道微生物群紊乱可能在重度抑郁症(MDD)的发病中起因果作用。本研究的目的是调查MDD患者的肠道微生物群是否存在性别差异。
纳入首次发作、未服用过药物的MDD患者和健康对照。对纳入受试者粪便样本中提取的16S rRNA基因序列进行分析。主坐标分析和偏最小二乘判别分析用于评估是否存在性别特异性肠道微生物群。随机森林算法用于识别差异可操作分类单元。线性判别分析效应大小进一步用于识别导致MDD患者与健康对照之间差异的主要性别特异性系统发育型。
总共识别出57个和74个差异可操作分类单元,它们分别负责将女性和男性MDD患者与其健康对照区分开来。与健康对照相比,女性和男性MDD患者的放线菌水平分别升高,拟杆菌水平分别降低。女性和男性MDD患者中差异最丰富的细菌类群分别属于放线菌门和拟杆菌纲。同时,女性和男性MDD患者具有不同的优势系统发育型。
这些结果表明,MDD患者的肠道微生物群存在性别差异。放线菌门和拟杆菌纲作为诊断MDD的性别特异性生物标志物的适用性应进一步探索。