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A head-to-head comparison of gray matter morphological differences between early-onset and middle-to-late-onset
Keke Fang1, Baohong Wen2, Liang Liu2
1Department of Pharmacy, the affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, China; Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Cancer Hospital, China; Henan Provincial Key Laboratory of Anticancer Drug Research, Henan Cancer Hospital, China.
Abstract:
Neuroimaging studies have consistently identified structural brain abnormalities in major depressive disorder (MDD). However, the influence of age at onset-a key factor contributing to the structural heterogeneity of MDD-remains unclear. This study performed a head-to-head comparison of gray matter morphology between early-onset (EO) and middle-to-late-onset (MO) depression using a normative model, based on a large-scale, multi-site cohort of individuals with MDD. We analyzed brain structural magnetic resonance imaging (MRI) data acquired from 486 EO patients and 499 MO patients and matched healthy controls (HCs, n = 1101) enrolled in 25 research sites. Raw gray matter volume (GMV) values were harmonized with ComBat to remove site effects and transformed into W-scores relative to HCs. Voxel-wise analyses revealed GMV abnormality patterns in EO and MO relative to HCs. A direct comparison of W-scores between EO and MO revealed lower GMV in EO than MO, primarily within the frontoparietal and subcortical-cerebellar network. These results were robust to a leave-one-site-out validation and consistent across different EO cut-offs. Further GMV differences between EO and MO were linked to neurotransmitter receptor distributions, especially for 5HT1A and 5HTT. Moreover, transcriptional similarity of depression-related genes can inform GMV abnormalities in MO, but not in EO, suggesting different genetic underpinnings. Taken together, these findings present the gray matter morphological alterations in EO and MO and their relationship with clinical phenotype, depression-related genes, and neurotransmitter profiles.
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