Emerging evidence has shown the age-related changes in gut microbiota, but few studies were conducted to explore the effects of age on the gut microbiota in patients with major depressive disorder (MDD). This study was performed to identify the age-specific differential gut microbiota in MDD patients. In total, 70 MDD patients and 71 healthy controls (HCs) were recruited and divided into two groups: young group (age 18-29 years) and middle-aged group (age 30-59 years). The 16S rRNA gene sequences were extracted from the collected fecal samples. Finally, we found that the relative abundances of Firmicutes and Bacteroidetes were significantly decreased and increased, respectively, in young MDD patients as compared with young HCs, and the relative abundances of Bacteroidetes and Actinobacteria were significantly decreased and increased, respectively, in middle-aged MDD patients as compared with middle-aged HCs. Meanwhile, six and 25 differentially abundant bacterial taxa responsible for the differences between MDD patients (young and middle-aged, respectively) and their respective HCs were identified. Our results demonstrated that there were age-specific differential changes on gut microbiota composition in patients with MDD. Our findings would provide a novel perspective to uncover the pathogenesis underlying MDD.

Available data indicate that patients with depression and anxiety disorders are likely to be at greater risk for suicide. Therefore, it is important to correctly diagnose patients with depression and anxiety disorders. However, there are still no empirical laboratory methods to objectively diagnose these patients. In this study, the multiple metabolomics platforms were used to profile the urine samples from 32 healthy controls and 32 patients with depression and anxiety disorders for identifying differential metabolites and potential biomarkers. Then, 16 healthy controls and 16 patients with depression and anxiety disorders were used to independently validate the diagnostic performance of the identified biomarkers. Finally, a panel consisting of four biomarkers—N-methylnicotinamide, aminomalonic acid, azelaic acid and hippuric acid—was identified. This panel was capable of distinguishing patients with depression and anxiety disorders from healthy controls with an area under the receiver operating characteristic curve of 0.977 in the training set and 0.934 in the testing set. Meanwhile, we found that these identified differential metabolites were mainly involved in three metabolic pathways and five molecular and cellular functions. Our results could lay the groundwork for future developing a urine-based diagnostic method for patients with depression and anxiety disorders.

Major depressive disorder (MDD) is a severe psychiatric disease that has critically affected life quality for millions of people. Chronic stress is gradually recognized as a primary pathogenesis risk factor of MDD. Despite the remarkable progress in mechanism research, the pathogenesis mechanism of MDD is still not well understood. Therefore, we conducted a liquid chromatography-tandem mass spectrometry (LC-MS/MS) detection of 25 major metabolites of tryptophanic, GABAergic, and catecholaminergic pathways in the prefontal cortex (PFC) of mice in chronic social defeat stress (CSDS). The depressed mice exhibit significant reduction of glutamate in the GABAergic pathway and an increase of L-DOPA and vanillylmandelic acid in catecholaminergic pathways. The data of real-time-quantitative polymerase chain reaction (RT-qPCR) and Western blotting analysis revealed an altered level of glutamatergic circuitry. The metabolomic and molecular data reveal that the glutamatergic disorder in mice shed lights to reveal a mechanism on depression-like and stress resilient phenotype.

Early perturbation of lipid metabolism and immunoregulation may be involved in the pathophysiology of PSD. The combination of increased gelsolin levels accompanied by decreased haptoglobin levels shows promise as a plasma-based diagnostic biomarker panel for detecting increased PSD risk in post-stroke patients.