Alzheimer's disease GWAS weighted by multi‐omics and endophenotypes identifies novel risk loci

AbstractBackgroundWe have increasing information on the role of certain genetic variants in a wide variety of molecular traits and endophenotypes of Alzheimer’s disease (AD), but their impacts on the prioritization of AD risk gene are unknown.MethodBased on the summary statistics of the genome‐wide association study (GWAS) of AD published by the International Genomics of Alzheimer’s Project (IGAP) consortium (Kunkle et al., 2019), we have weighted each SNP by their associations with traits of eQTL (RNA expression), mQTL (DNA methylation), haQTL (histone acetylation), brain phosphorylated tangles (TAU), β‐amyloid protein (Aβ), and cognitive decline derived from the ROS‐MAP samples of postmortem dorsal‐lateral prefrontal cortex of AMP‐AD. Then, we collapsed all of the weighted SNPs found in each gene using the SKATO test, based on the 1000 reference genome.Result38∼43% of genes (n = 12,899) have an increase in their statistical significance level after incorporating the weights of their genetic effects on omic molecular traits and AD endophenotypes. A subset of these gene‐level assessments reach the trait‐specific Bonferroni corrected genome‐wide significance threshold (P < 0.05/number of genes for each trait). The burden of TAU pathology has the strongest effect with RASGRF2, FCF1, ZCWPW1, C6orf10, VAC14, ADGRF2, ACP2, DDB2, and CR1L being prioritized. Similarly, we have results prioritized by weighting by (1) Amyloid β: FCF1, NRXN1, PLCB1, and DLG2; (2) cognitive decline: AKAP13, CR1L, KIAA1671, and CR2; and (3) eQTL: TRIT1, RAPSN, and C6orf10. The latter also emerges from the haQTL analysis, and no results emerge from the mQTL analysis.ConclusionWeighting by omic molecular traits and endophenotypes leading to AD is able to prioritize additional genes that could contribute to AD susceptibility. Functional validation is ongoing.