New findings suggest that schizophrenia may be linked to gut bacteria.

Objective: 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. Patients and methods: 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. Results: 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. Conclusion: 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.

Major depressive disorder (MDD) is a debilitating psychiatric illness. However, there is currently no objective laboratory-based diagnostic tests for this disorder. Although, perturbations in multiple neurotransmitter systems have been implicated in MDD, the biochemical changes underlying the disorder remain unclear, and a comprehensive global evaluation of neurotransmitters in MDD has not yet been performed. Here, using a GC-MS coupled with LC-MS/MS-based targeted metabolomics approach, we simultaneously quantified the levels of 19 plasma metabolites involved in GABAergic, catecholaminergic, and serotonergic neurotransmitter systems in 50 first-episode, antidepressant drug-naïve MDD subjects and 50 healthy controls to identify potential metabolite biomarkers for MDD (training set). Moreover, an independent sample cohort comprising 49 MDD patients, 30 bipolar disorder (BD) patients and 40 healthy controls (testing set) was further used to validate diagnostic generalizability and specificity of these candidate biomarkers. Among the 19 plasma neurotransmitter metabolites examined, nine were significantly changed in MDD subjects. These metabolites were mainly involved in GABAergic, catecholaminergic and serotonergic systems. The GABAergic and catecholaminergic had better diagnostic value than serotonergic pathway. A panel of four candidate plasma metabolite biomarkers (GABA, dopamine, tyramine, kynurenine) could distinguish MDD subjects from health controls with an AUC of 0.968 and 0.953 in the training and testing set, respectively. Furthermore, this panel distinguished MDD subjects from BD subjects with high accuracy. This study is the first to globally evaluate multiple neurotransmitters in MDD plasma. The altered plasma neurotransmitter metabolite profile has potential differential diagnostic value for MDD.

Mounting evidence suggests that gut microbiota can play an important role in pathophysiology of depression, but its specific molecular mechanisms are still unclear. This study was conducted to explore the associations between changes in neurotransmitters and short-chain fatty acids (SCFAs) and altered gut microbiota in depressed mice. Here, the chronic restraint stress (CRS) model of depression was built. The classical behavioral tests were conducted to assess the depressive-like behaviors of mice. The 16S rRNA gene sequence extracted from fecal samples was used to assess the gut microbial composition. Liquid and gas chromatography mass spectroscopy were used to identify neurotransmitters in hypothalamus and SCFAs in fecal samples, respectively. Finally, 29 differential bacteria taxa between depressed mice and control mice were identified, and the most differentially abundant bacteria taxa were genus Allobaculum and family Ruminococcaceae between the two groups. The acetic acid, propionic acid, pentanoic acid, norepinephrine, 5-HIAA and 5-HT were significantly decreased in depressed mice compared to control mice. Genus Allobaculum was found to be significantly positively correlated with acetic acid and 5-HT. Taken together, these results provided novel microbial and metabolic frameworks for understanding the role of microbiota-gut-brain axis in depression, and suggested new insights to pave the way for novel therapeutic methods.

Major depressive disorder (MDD) is a highly prevalent and debilitating mental illness, which is associated with disorder of gut microbiota. However, few studies focusing on detection of the signatures of bacteria in feces of MDD patients using proteomics approach have been carried out. Here, a comparative metaproteomics analysis on the basis of an isobaric tag for relative and absolute quantification coupled with tandem mass spectrometry was carried out to explore the signature of gut microbiota in patients with MDD. Ten patients (age: 18–56 years, five women) who had MDD and a score over 20 on the Hamilton’s Depression Scale and 10 healthy controls (age: 24–65 years, five women) group matched for sex, age, and BMI were enrolled. As a result, 279 significantly differentiated bacterial proteins (P<0.05) were detected and used for further bioinformatic analysis. According to phylogenetic analysis, statistically significant differences were observed for four phyla: Bacteroidetes, Proteobacteria, Firmicutes, Actinobacteria (P<0.05, for each). Abundances of 16 bacterial families were significantly different between the MDD and healthy controls (P<0.05). Furthermore, Cluster of Orthologous Groups analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that disordered metabolic pathways of bacterial proteins were mainly involved in glucose metabolism and amino acid metabolism. In conclusion, fecal microbiota signatures were altered significantly in MDD patients. Our findings provide a novel insight into the potential connection between gut microbiota and depression.