A Multi-Ancestry GWAS Meta-Analysis Integrated with In-Depth Silico, Systems Biology, and Pharmacogenomics Approaches...

This study aimed to perform a Meta-Analysis based on GWAS data and utilized them for multi-step analyses. Final data included 1,198,682 subjects (255,810 cases and 942,872 controls) in 26 studies among 11 ethnicities. R package utilized for GWAS Meta-Analysis, a Primary Gene List (PGL), and then a Secondary Gene List (SGL) were generated. All of the in-depth silico, systems biology, and Pharmacogenomics (PGx) analyses were performed by STRING-MODEL, miRTargetLink2, NetworkAnalyst, Enrichr, and PharmGKB. The cumulative effect size in a random effects model for the risk of AD was 1.55 [95% CI: 1.41-1.71]. APOE, APP, SPI1, hsa-miR-17-5p, hsa-miR-155-5p, hsa-miR-340, hsa-miR-125b, hsa-miR-199a-3p, hsa-miR-199a-5p, and hsa-miR-1908-5p, SP1, MYC, MAX, E2F1, Valproic acid, and Tretinoin were the most significant findings. According to the Enrichment Analysis, Immune System R-HSA-168,256 (q-value = 5.85E-07) and Amyloid Fiber Formation R-HSA-977,225 (q-value = 1.57E-05) were the most significant pathways. Amyloid-Beta Binding (GO:0001540) (q-value = 3.64E-04) in molecular function were among the most significant GOs. DDAs found Alzheimer Disease (q-value = 8.72E-45) with the highest incidence. PGx approaches, uncovered 40 potential annotations, among them, two annotations of rs429358 (APOE) were both directly associated with AD. Briefly, almost all of the findings presented in this study are supported by prior reports along with new findings.