Despite decades of intensive research on major depressive disorder (MDD), the pathogenesis of MDD is still unclear and the objectively diagnostic method remains unavailable. Therefore, we conducted this study to assess whether alpha 1-antitrypsin (AAT) could be a potential biomarker for diagnosing MDD. Here, the levels of AAT, liver function-related indicators, renal function-related indicators, blood lipids-related indicators, high sensitivity C-reactive protein, homocysteine and transferrin were detected. The orthogonal partial least-squares discriminant analysis (OPLS-DA) was used to find the differential variables, Random Forest was used to identify the simplified biomarker panel, and receiver-operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the identified panel. In total, 86 MDD patients and 99 healthy controls (HCs) were recruited. Finally, we found nine differential variables between MDD patients and HCs, and a potential biomarker panel consisting of AAT, albumin (ALB) and apolipoprotein A1 (APOA) was identified. This panel could effectively separate MDD patients from HCs in two independent samples sets. The level of AAT was significantly negatively correlated with HDRS score and improved after antidepressant treatment. Meanwhile, MDD patients with suicide idea or behavior had significantly lower AAT levels compared to MDD patients without suicide idea or behavior. Our results suggested that AAT held the promise to become a potential biomarker for diagnosing MDD, and also might be a potential novel therapeutic target for MDD.

Objectives: Lipid metabolism is closely associated with many important biological functions. Here, we conducted this study to explore the effects of gut microbiota on the lipid metabolism in the prefrontal cortex of mice. Methods: Germ-free (GF) mice, specific pathogen-free (SPF) and colonized GF (CGF) mice were used in this study. The open field test (OFT), forced swimming test (FST) and novelty suppressed feeding test (NSFT) were conducted to assess the changes in general behavioral activity. The liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) was used to obtain the lipid metabolites. Both one-way analysis of variance (one-way ANOVA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used to obtain the key differential lipid metabolites.Results: The behavioral tests showed that compared to SPF mice, GF mice had more center distance, more center time, less immobility time and less latency to familiar food. Meanwhile, 142 key differential lipid metabolites between SPF mice and GF mice were identified. These lipid metabolites mainly belonged to glycerophospholipids, glycerolipids, sphingolipids, and saccharolipids. The gut microbiota colonization did not reverse these changed behavioral phenotypes, but could restore 25 key differential lipid metabolites.Discussion: These results showed that the absence of gut microbiota could influence host behaviors and lipid metabolism. Our findings could provide original and valuable data for future studies to further investigate the microbiota-gut-brain axis.