Personalized functional topography-based multisite brain age prediction modeling reveals divergent neurodevelopment...

Area of Science:

• Neuroscience
• Psychiatry
• Genetics

Background:

• Major depressive disorder (MDD) involves widespread functional brain network alterations.
• Heterogeneity in atypical brain development within MDD patient populations is poorly understood.

Purpose of the Study:

• To characterize neurodevelopmental heterogeneity in MDD using brain age prediction.
• To identify distinct subgroups within MDD patients based on brain age gaps (BAGs).

Main Methods:

• Utilized a large, multisite resting-state functional MRI dataset (1,105 MDD patients, 1,065 controls).
• Developed a harmonized multicenter brain age prediction model based on functional topography.
• Analyzed network alterations, clinical symptoms, and gene expression patterns in identified subgroups.

Main Results:

• Identified two MDD subgroups: BAG+ (accelerated aging) and BAG- (delayed development).
• BAG+ showed SAL expansion and sensorimotor/DAN contraction; BAG- showed SAL expansion and visual/SMN contraction.
• Subgroups differed in clinical associations (mood vs. insomnia) and molecular profiles (gene expression).
• Antidepressant treatment effects were subgroup-specific.

Conclusions:

• MDD exhibits heterogeneous neurodevelopmental profiles with distinct biological and clinical signatures.
• Findings support the potential for personalized precision medicine approaches in MDD treatment.