A large-scale ENIGMA multisite replication study of brain age in depression

Area of Science:

• Neuroimaging
• Psychiatry
• Aging

Background:

• Previous studies suggest a
• brain age gap
• in individuals with depression, but findings vary due to methodological differences.
• The ENIGMA brain age model aimed to validate previous findings on the brain age gap in depression.

Purpose of the Study:

• To validate the ENIGMA brain age model by replicating the brain age gap in depression in independent cohorts.
• To assess the effect size of the brain age gap in depression across diverse datasets.
• To investigate potential moderating factors influencing the brain age gap in depression.

Main Methods:

• Utilized a pre-trained ENIGMA brain age model based on 77 FreeSurfer brain regions.
• Applied the model to predict brain age in 751 controls and 766 individuals with depression from 13 new cohorts.
• Employed meta-regressions to analyze the impact of cohort characteristics on the brain age gap.

Main Results:

• The ENIGMA brain age model demonstrated reasonable generalization to new control cohorts (R² = 0.47).
• Depressed individuals exhibited a significantly higher brain age gap (+1 year, Cohen's d = 0.15), consistent with prior research.
• FreeSurfer version and scanner vendor (Philips) significantly moderated the brain age gap estimates.

Conclusions:

• The study validates the ENIGMA brain age algorithm and replicates the brain age gap in depression with a similar effect size.
• Large-scale analyses across 32 cohorts confirm reliable, subtle brain aging effects in adult depression.
• Further research is needed to identify factors contributing to the observed variance in the brain age gap between cohorts.