Brain Expression Genome-Wide Association Study (eGWAS) Identifies Human Disease-Associated Variants

Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimer's disease (AD, cerebellar n = 197, temporal cortex n = 202) and with other brain pathologies (non–AD, cerebellar n = 177, temporal cortex n = 197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cis SNPs within ±100 kb of the tested transcripts. We identified 2,980 cerebellar cis SNP/transcript level associations (2,596 unique cis SNPs) significant in both ADs and non–ADs (q<0.05, p = 7.70×10 −5 –1.67×10 −82 ). Of these, 2,089 were also significant in the temporal cortex (p = 1.85×10 −5 –1.70×10 −141 ). The top cerebellar cis SNPs had 2.4-fold enrichment for human disease-associated variants (p<10 −6 ). We identified novel cis SNP/transcript associations for human disease-associated variants, including progressive supranuclear palsy SLCO1A2 /rs11568563, Parkinson's disease (PD) MMRN1 /rs6532197, Paget's disease OPTN /rs1561570; and we confirmed others, including PD MAPT /rs242557, systemic lupus erythematosus and ulcerative colitis IRF5 /rs4728142, and type 1 diabetes mellitus RPS26 /rs1701704. In our eGWAS, there was 2.9–3.3 fold enrichment (p<10 −6 ) of significant cis SNPs with suggestive AD–risk association (p<10 −3 ) in the Alzheimer's Disease Genetics Consortium GWAS. These results demonstrate the significant contributions of genetic factors to human brain gene expression, which are reliably detected across different brain regions and pathologies. The significant enrichment of brain cis SNPs among disease-associated variants advocates gene expression changes as a mechanism for many central nervous system (CNS) and non–CNS diseases. Combined assessment of expression and disease GWAS may provide complementary information in discovery of human disease variants with functional implications. Our findings have implications for the design and interpretation of eGWAS in general and the use of brain expression quantitative trait loci in the study of human disease genetics.