Gut microbiome, a potential indicator for differential diagnosis of major depressive disorder and general anxiety disorder

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 (health 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 differences in levels of Faecalibacterium and LachnospiraceaeND3007group. Moreover, we also found correlations between the bacteria and neuroendocrine and clinical symptoms, namely, a significant negative correlation between Fusicatenibacter and free thyroxine(FT4) in MDD, significant negative correlation between Fusicatenibacter and cortisol (PTC) in GAD, positive correlation between LachnospiraceaeND3007group and sleep disturbance factor of Hamilton Depression Rating Scale, and negative correlation between LachnospiraceaeND3007group and PTC (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.

A systematic review of gut microbiota composition in observational studies of major depressive disorder, bipolar disorder and schizophrenia

“…One study only investigated pathways associated with tryptophan metabolism and biosynthesis, identifying differences between cases and controls [75]. Another study observed correlations between specific bacterial taxa and functional pathways within the KEGG orthologue database; however, they did not report what the specific pathways were, only providing the KEGG identification number [88]. Of the studies that examined multiple pathways and reported differences (N = 9), MDD was associated with an enrichment of: glycan biosynthesis and metabolism (33%; N = 3/ 9 reported studies) [86,89]; lipopolysaccharide biosynthesis and biosynthesis proteins (33%; N = 3/9 reported studies) [72,85]; and transport and catabolism pathways (33%; N = 3/9 reported studies) [86,89], compared to controls.…”

“…Of the studies that collected additional biomarker data (27%; N = 12/44 studies), immune-related and inflammatory markers, such as interleukin 6 and C-reactive protein, were the most commonly reported (58%; N = 7/12 reporting studies). Five studies conducted metabolomic analyses: two studies in MDD found no differences in faecal metabolites [74] or neuroendocrine hormones [88]; two studies observed differences in multiple faecal metabolites in MDD cases compared to controls, mainly related to amino acid, nucleotide, carbohydrate, and lipid metabolism [86], and inflammatory pathways [87]; and a fifth study in SZ observed differences in tryptophan and kynurenine pathway metabolites [106] (Table S5).…”