Prediction of treatment-resistant depression using the 23andMe survey data.

ABSTRACT: Patient-reported drug responses offer an alternative approach to design and develop a predictive model for treatment-resistant depression (TRD) in major depressive disorder (MDD). The variables described in phenotypic analysis (i.e., demographics, depression clinical characteristics, psychiatric comorbidities, and vulnerability characteristics) of the antidepressant efficacy survey from previously reported study among 23andMe, Inc. research participants were identified as predictors to classify TRD or non-TRD. A total of 101 features were engineered for 23,779 participants, with stratified split between training (80% of the total participants included in the model) and holdout (20% of the participants) datasets. Significant predictors included residual symptoms, years in life having ≥ 2 we

SUBMITTER: Vairavan S 

PROVIDER: S-EPMC12484750 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature