A 10-YEAR case-control study has linked grey matter volume changes in major depressive disorder (MDD) to cumulative illness severity rather than acute symptoms or diagnosis alone, with trajectories ranging from progressive decline to relative stability.<\/p>\n
Repeated MRI Scans Over Up to 10 Years<\/p>\n
The single-centre case-control study, conducted within the M\u00fcnster Neuroimaging Cohort, followed inpatients with initially acute MDD and healthy volunteer controls with repeated MRI assessments over up to 10 years. Participants underwent 3 to 6 scans spaced approximately every 2 years. Gray matter volume (GMV) was assessed using longitudinal voxel-based morphometry, with region-of-interest and exploratory whole-brain analyses. Mixed-effect models examined GMV trajectories against diagnosis, cumulative illness severity (CIS) and acute illness severity.<\/p>\n
Hippocampal and Prefrontal Volume Loss Tracked Cumulative Severity<\/p>\n
The analysis included 206 individuals, mean age 38.6 years, 112 men, comprising 57 with MDD (27.67%) and 149 controls (72.33%), who underwent a mean of 3.8 scans, totalling 791 scans.<\/p>\n
Significant CIS by time interactions emerged in the hippocampus (peak \u03b7p2 0.261; FWE-corrected p<.001) and dorsolateral prefrontal cortex (peak \u03b7p2 0.216; FWE-corrected p=.02), with higher CIS associated with steeper GMV decline compared with more favourable clinical courses.<\/p>\n
These associations remained robust across sensitivity analyses controlling for acute illness severity and medication use. There was little evidence of differential GMV trajectories between patients with depression and controls overall, or of main associations for cumulative or acute severity alone.<\/p>\n
A Case for Personalised, Trajectory-Based Models<\/p>\n
These findings have reframed grey matter illness severity depression associations around individual clinical trajectories rather than diagnosis or symptom fluctuation alone, with some patients showing progressive decline and others relative stability.<\/p>\n
The results support personalised, time-sensitive neurobiological models in depression and point to a need for sustained, long-term monitoring rather than fixed risk assumptions. Future work integrating multimodal biomarkers and large consortia such as ENIGMA will be needed to replicate and generalise these trajectory-based findings.<\/p>\n
Reference<\/p>\n
Kraus A et al. Illness severity and longitudinal gray matter volumes among people with major depressive disorder. JAMA Netw Open. 2026;9(9):e2633507.<\/p>\n
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