Profound and reproducible patterns of reduced regional gray matter characterize major depressive disorder

Abstract

Reduced gray matter (GM) volume may represent a hallmark of major depressive disorder (MDD) neuropathology, typified by wide-ranging distribution of structural alteration. In the study, we aimed to replicate and extend our previous finding of profound and widespread GM loss in MDD, and evaluate the diagnostic accuracy of a structural biomarker derived from GM volume in an interconnected pattern across the brain. In a sub-study of the International Study to Predict Optimized Treatment in Depression (iSPOT-D), two cohorts of clinically defined MDD participants “Test” (n = 98) and “Replication” (n = 131) were assessed alongside healthy controls (n = 66). Using 3T MRI T1-weighted volumes, GM volume differences were evaluated using voxel-based morphometry. Sensitivity, specificity, and area under the receiver operating characteristic curve were used to evaluate an MDD diagnostic biomarker based on a precise spatial pattern of GM loss constructed using principal component analysis. We demonstrated a highly conserved symmetric widespread pattern of reduced GM volume in MDD, replicating our previous findings. Three bilateral dominant clusters were observed: Cluster 1: midline/cingulate (GM reduction: Test: 6.4%, Replication: 5.3%), Cluster 2: medial temporal lobe (GM reduction: Test: 8.2%, Replication: 11.9%), Cluster 3: prefrontal cortex (GM reduction: Test: 12.1%, Replication: 23.2%). We developed a biomarker reflecting the global pattern of GM reduction, achieving good diagnostic classification performance (AUC: Test = 0.75, Replication = 0.84). This study establishes that a highly specific pattern of reduced GM volume is a feature of MDD, suggestive of a structural basis for this disease. We introduce and validate a novel diagnostic biomarker based on this pattern.

Matthew Lyon

AI Research Scientist

My research interests include diffusion MRI, geometric deep learning, and computer vision.