Date of Award
Master of Public Health (MPH)
School of Public Health
Andrew T. DeWan
Background: Previous studies have attempted to identify gene-gene interactions for asthma. However, most of these studies suffered from lack of replication or insufficient statistical power. In this study, we aimed to explore the gene-gene interactions affecting asthma susceptibility and tried to replicate the results. Both the discovery and replication datasets were nested in UK Biobank data.
Methods: Nested case-control design was used. In the discovery analysis (N= 306,859, cases = 35,483, controls = 271,376), Univariate genome-wide association analysis was performed to prioritize loci for the interaction analysis. Pairwise search for epistasis was conducted among 5,389 SNPs. Replication of the top interactions was then conducted (N = 40,945, cases = 5,623, controls = 35,322).
Results: Two interactions met statistical significance (rs1496042 x rs6674451, rs10793149 x rs1939469) after Bonferroni correction. In the replication analysis, one of the interactions detected (rs10793149 x rs1939469) achieved statistical significance. Both interactions showed consistent effect size and direction in the replication dataset.
Conclusion: In this study, we identified two interactions associated with asthma susceptibility and successfully replicated one of them. In the interaction that replicated, rs1939469 is located in or near EMSY, which has previously been reported associated with asthma. This result provided suggestive evidence that the interaction detected has possible biological mechanisms behind it.
Lin, Yuyuan, "Gene-Gene Interactions Contributing To Asthma Susceptibility, An Exploration Using Uk Biobank Dataset" (2021). Public Health Theses. 2070.