White matter (WM) abnormalities are implicated in major depressive disorder (MDD), yet the organization of white matter morphometric similarity networks (WM-MSNs) – which capture interregional similarity in voxel-wise WM morphology – and the transcriptional mechanisms associated with their disruption remain insufficiently understood.

Using T1-weighted MRI from a large multisite sample (1,154 individuals with MDD and 1,026 healthy controls), we constructed individualized WM-MSNs. Group differences were assessed at the edge, global, and nodal levels. To identify molecular pathways underlying these alterations, nodal abnormalities were linked to regional gene expression profiles from the Allen Human Brain Atlas using spatially informed transcriptomic association, followed by functional, cell-type-specific, and developmental enrichment analyses.

MDD showed distributed but selective reorganization of WM-MSNs. Network-based statistics revealed two significant components, with 118 edges exhibiting increased morphometric similarity and 45 showing decreased similarity. Globally, MDD demonstrated higher small-worldness, clustering coefficient, global efficiency, and local efficiency, together with shorter characteristic path length. Nodal disruptions were concentrated in major commissural and association tracts – including the corpus callosum, cingulum, uncinate fasciculus, and tapetum. Transcriptomic integration indicated enrichment for gene signatures related to oligodendrocyte function, myelination, lipid metabolism, axonal organization, and cellular stress-related molecular processes, with implicated genes showing broad developmental-stage expression.

MDD is associated with robust alterations in individualized WM-MSNs that converge with transcriptional signatures linked to myelination, metabolic processes, axonal structure, and cellular stress, linking macroscale network disruption to underlying molecular architecture and providing cross-scale insights into WM pathology in depression.

Schizophrenia progresses through high-risk, first-episode, and chronic stages, each associated with altered spontaneous brain activity. Resting state functional MRI studies highlight these changes, but inconsistencies persist, and the genetic basis remains unclear.

A neuroimaging meta-analysis was conducted to assess spontaneous brain activity alterations in each schizophrenia stage. The largest available genome-wide association study (GWAS) summary statistics for schizophrenia (N = 53,386 cases, 77,258 controls) were used, followed by Hi-C-coupled multimarker analysis of genomic annotation (H-MAGMA) to identify schizophrenia-associated genes. Transcriptome-neuroimaging association and gene prioritization analyses were performed to identify genes consistently linked to brain activity alterations. Biological relevance was explored by functional enrichment.

Fifty-two studies met the inclusion criteria, covering the high-risk (Nhigh-risk = 409, Ncontrol = 475), first-episode (Ncase = 1842, Ncontrol = 1735), and chronic (Ncase = 1242, Ncontrol = 1300) stages. High-risk stage showed reduced brain activity in the right median cingulate and paracingulate gyri. First-episode stage revealed increased activity in the right putamen and decreased activity in the left gyrus rectus and right postcentral gyrus. Chronic stage showed heightened activity in the right inferior frontal gyrus and reduced activity in the superior occipital gyrus and right postcentral gyrus. Across all stages, 199 genes were consistently linked to brain activity changes, involved in biological processes such as nervous system development, synaptic transmission, and synaptic plasticity.

Brain activity alterations across schizophrenia stages and genes consistently associated with these changes highlight their potential as universal biomarkers and therapeutic targets for schizophrenia.