Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics.

ABSTRACT:

Background

Major depressive disorder (MDD) is a leading cause of disability worldwide, yet its diagnosis relies on clinical symptoms alone.

Methods

Using the semi-supervised machine learning algorithm, Heterogeneity through Discriminative Analysis (HYDRA), we had identified two neuroanatomical dimensions in deeply phenotyped (i.e., comprehensively assessed across neuroimaging, clinical, and behavioural domains), medication-free participants with MDD from the COORDINATE-MDD consortium. In the present study, we apply this pre-trained HYDRA model to the UK Biobank (UKB) to validate these dimensions in a large general population and a subsample with current depressive symptoms.

Results

Dimension 2 (D2), compared to Dimension 1 (D1), is characterized by reduced grey and wh

SUBMITTER: Xiao W 

PROVIDER: S-EPMC12663290 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature