Predictive Models for Suicide Attempts in Major Depressive Disorder and the Contribution of <i>EPHX2</i>: A Pilot Integrative Machine Learning Study.

ABSTRACT: Suicide is a major public health problem caused by a complex interaction of various factors. Major depressive disorder (MDD) is the most prevalent psychiatric disorder associated with suicide; therefore, it is essential to prioritize suicide prediction and prevention within this population. Integrated information from different dimensions, including personality, cognitive function, and social and genetic factors, is necessary to improve the performance of predictive models. Besides, recent studies have indicated the critical roles for EPHX2/P2X2 in the pathophysiology of MDD. Our previous studies found an association of EPHX2 and P2X2 with suicide in MDD. This study is aimed at (1) establishing predictive models with integrated information to distinguish MDD from healthy volu

SUBMITTER: Zheng S 

PROVIDER: S-EPMC11918959 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature