H-MAGMA was constructed from four classes of brain-derived Hi-C datasets that include human cortical tissue across two developmental stages (prenatal and postnatal) and two brain cell types (neurons and astrocytes), enabling developmental and cell-type specific gene mapping. We applied H-MAGMA to five psychiatric disorders (Attention deficit hyperactivity disorders, ADHD; Autism spectrum disorders, ASD; Schizophrenia, SCZ; Bipolar disorder, BD; Major depressive disorders, MDD) and four neurodegenerative disorders (Amyotrophic lateral sclerosis, ALS, Multiple sclerosis, MS; Alzheimer’s disease, AD, and Parkinson’s disease, PD) to generate gene-level summary statistics (Fig. 1). By comparing H-MAGMA with cMAGMA, we found that non-coding SNPs often interact with distal genes, necessitating the use of functional genomic evidence in assigning SNPs to cognate genes. We also found a significant overlap between H-MAGMA and two widely used expression quantitative trait loci (eQTL)-based gene mapping tools, coloc9 and TWAS10. Gene-level association statistics from H-MAGMA closely resembled genetic relationships among brain disorders, which enabled subsequent analyses to identify biological pathways, developmental windows, and cell types critical for each brain disorder.
