Analysis of GWAS-associated SNPs in DMRs was adapted from a recent publication (36) with the following modifications. GWAS data were obtained from the National Institutes of Health GRASP (Genome-Wide Repository of Associations Between SNPs and Phenotypes) database ( Studies with labeled phenotype categories in nine brain-related disorders (ADHD, ALS, Alzheimer’s disease, autism, bipolar disorder, depression, epilepsy, Parkinson’s disease, and schizophrenia) as well as six nonbrain diseases (celiac disease, chronic kidney disease, Crohn’s disease, lung cancer, prostate cancer, and type 1 diabetes) were selected, and only associated SNPs with reported P values of <10−6 (that is, genome-wide significant SNPs) were kept for the following analysis. For each disease category, each SNP was extended to a ±50-kb flanking region, and any regions overlapping each other were merged. The resulting merged regions were ranked in ascending order by the smallest P value of the associated SNPs within the region, and the top 50 regions were defined as the most significant risk-associated SNP regions. Then, the number of overlaps between DMRs and these SNP regions was counted. To test whether the overlaps were enriched or depleted, we compared the observed number of overlaps X with the expected number of overlaps Y if the DMRs were randomly distributed across the genome. Here, Y should follow a binomial distribution with parameters n and p where n is the number of DMRs and p is the coverage of the SNP regions in the genome. With this, the Z scores for each test were calculated, and the empirical two-tailed P values were corrected for multiple comparisons using Benjamini and Hochberg’s FDR method (61).

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