Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

ABSTRACT:

Background

Incorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not.

Methods

Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based so

SUBMITTER: Wani AH 

PROVIDER: S-EPMC11429352 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature