AUTHOR=Dong Zaiquan , Shen Xiaoling , Hao Yanni , Li Jin , Li Haoran , Xu Haizheng , Yin Li , Kuang Weihong 

TITLE=Gut Microbiome: A Potential Indicator for Differential Diagnosis of Major Depressive Disorder and General Anxiety Disorder

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2021.651536

DOI=10.3389/fpsyt.2021.651536

ISSN=1664-0640

ABSTRACT=Background. Major depressive disorder (MDD) and general anxiety disorder (GAD) share many common features, leading to many challenges in their differential diagnosis. Given the importance of the microbiota-gut-brain axis, we aimed to investigate the differences in gut microbiota between representative cases of these two diseases and sought to develop a microbiome-based approach for their differential diagnosis.
Methods. We enrolled 23 patients with MDD, 21 patients with GAD, and 10 healthy subjects (normal control, HC) in the present study. We used 16S rRNA gene sequencing analysis to determine the microbial compositions of gut microbiome based on Illumina Miseq according to Illumina’s standard protocol.
Results. We found that patients with MDD or GAD exhibited significant differences in the relative abundance of gut microbiota. We identified the microbial signatures of subjects with MDD and GAD relative to HC and found significant differences at the genus level for Fusicatenibacter and Christensenellaceae_R7_group in MDD patients. Moreover, Christensenellaceae_R7_group negatively correlated with HAMD_total, Hopelessness and ACTH, Fusicatenibacter negatively correlated with FT4, and other key phylotypes showed no strong correlation. Further, the GAD group showed significant differences at the genus level for Faecalibacterium, which negatively correlated with PTC, whereas other key phylotypes showed no strong correlation (all p < 0.05).
Conclusions. The present study elucidated a unique gut microbiome signature associated with MDD and GAD that could facilitate differential diagnosis and targeted therapy.