A study on the plasma proteomics of different types of depressive disorders based on label-free data-independent acquisition proteomic technology.

Abstract

Background: Due to the high incidence and high misdiagnosis rate of depressive disorder, biomarkers for the accurate diagnosis of depressive disorder are urgently needed to reduce the misdiagnosis rate and improve the cure rate.

Methods: To obtain original data, plasma samples were collected from patients suffering from various depressive disorders, including bipolar depression (BP), major depressive disorder (MDD), and persistent depressive disorder (PDD) prior to medication treatment, as well as from participants without psychiatric diagnoses (NP). Then these samples were analyzed using nano-LC-MS/MS. According to the screening criteria, differentially expressed proteins(DEPs) corresponding to different types of depressive disorders were identified, and validation proteins were identified via bioinformatics analysis and verified.

Results: Ninety-nine DEPs were identified between BP and NP, 29 DEPs were identified between MDD and NP, and 14 DEPs were identified between PDD and NP. The plasma levels of PRDX2 in patients with depressive disorder were significantly increased. The plasma CRP level in BP patients was specifically increased, and the plasma SNCA level in MDD patients was specifically increased. CRP showed the best differential diagnostic ability in differentiating BP from NP, MDD and PDD, and SNCA showed the best differential diagnostic ability in differentiating MDD from NP, BP and PDD.

Conclusions: The mechanism of depressive disorder mainly involves biological processes and signaling pathways related to inflammation and lipid metabolism. The key biomarkers identified by proteomics and the signaling pathways involved are highly important for revealing the biological basis of depressive disorder and guiding its clinical diagnosis and treatment.