Peripheral non-enzymatic antioxidants as biomarkers for mood disorders: Evidence from a machine learning prediction model.

ABSTRACT:

Background

Oxidative stress is related to the pathogenesis of mood disorders, and the level of oxidative stress may differ between bipolar disorder (BD) and major depressive disorder (MDD). This study aimed to detect the differences in non-enzymatic antioxidant levels between BD and MDD and assess the predictive values of non-enzymatic antioxidants in mood disorders by applying a machine learning model.

Methods

Peripheral uric acid (UA), albumin (ALB), and total bilirubin (TBIL) were measured in 1,188 participants (discover cohort: 157 with BD and 544 with MDD; validation cohort: 119 with BD and 95 with MDD; 273 healthy controls). An extreme gradient boosting (XGBoost) model and a logistic regression model were used to assess the predictive effect.

Results

All three i

SUBMITTER: Gong Y 

PROVIDER: S-EPMC9676245 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature