Abstract
Gut microbes are associated with the development of depression based on extensive evidence. However, previous studies have led to conflicting reports on this association, posing challenges to the application of gut bacteria in the diagnostics and treatment of depression. To minimise heterogenicity in data analysis, the present meta-analysis adopted a standardised bioinformatics and statistical pipeline to analyse 16S rRNA sequences of 1827 samples from eight different cohorts. Although changes in the overall bacterial community were identified by our meta-analysis, depressive-correlated changes in alpha-diversity were absent. Enrichment of Bacteroidetes, Parabacteroides, Barnesiella, Bacteroides, and Bacteroides vulgatus, along with depletion in Firmicutes, Dialister, Oscillospiraceae UCG 003 and UCG 002, and Bacteroides plebeius, were observed in depressive-associated bacteria. By contrast, elevated L-glutamine degradation, and reduced L-glutamate and L-isoleucine biosynthesis were identified in depressive-associated microbiomes. After systemically reviewing the data of these collected cohorts, we have established a bacterial classifier to identify depressive symptoms with AUC 0.834 and 0.685 in the training and external validation dataset, respectively. Moreover, a low-risk bacterial cluster for depressive symptoms was identified, which was represented by a lower abundance of Escherichia-Shigella, and a higher abundance of Faecalibacterium, Oscillospiraceae UCG 002, Ruminococcus, and Christensenellaceae R.7 group.