Gene-environment-brain topology reveals clinical subtypes of depression in UK Biobank.

ABSTRACT: Major depressive disorder (MDD) is a leading cause of disability worldwide, affecting over 300 million people and posing a significant burden on healthcare systems. The heterogeneity of MDD can be attributed to diverse etiologic mechanisms. Characterizing MDD subtypes with distinct clinical manifestations could improve patient care through targeted personalized interventions. Topological Data Analysis (TDA) has emerged as a promising tool for identifying homogeneous subgroups of diverse medical conditions and key disease markers. Our study applied TDA to data from a UK Biobank MDD subcohort comprising 3052 samples, leveraging genetic, environmental, and neuroimaging data to assess their differential capability in predicting clinical outcomes in MDD. TDA graphs were built from unimodal and

SUBMITTER: Tassi E 

PROVIDER: S-EPMC12514272 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature