A polygenic risk score for asthma in a large racially diverse population. Issue 11 (5th September 2021) - Sordillo, Joanne E.; Lutz, Sharon M.; Jorgenson, Eric; Iribarren, Carlos; McGeachie, Michael; Dahlin, Amber; Tantisira, Kelan; Kelly, Rachel; Lasky‐Su, Jessica; Sakornsakolpat, Phuwanat; Moll, Matthew; Cho, Michael H.; et al.
Abstract: Background: Polygenic risk scores (PRSs) will have important utility for asthma and other chronic diseases as a tool for predicting disease incidence and subphenotypes. Objective: We utilized findings from a large multiancestry GWAS of asthma to compute a PRS for asthma with relevance for racially diverse populations. Methods: We derived two PRSs for asthma using a standard approach (based on genome‐wide significant variants) and a lasso sum regression approach (allowing all genetic variants to potentially contribute). We used data from the racially diverse Kaiser Permanente GERA cohort (68 638 non‐Hispanic Whites, 5874 Hispanics, 6870 Asians and 2760 Blacks). Race was self‐reported by questionnaire. Results: For the standard PRS, non‐Hispanic Whites showed the highest odds ratio for a standard deviation increase in PRS for asthma (OR = 1.16 (95% CI 1.14–1.18)). The standard PRS was also associated with asthma in Hispanic (OR = 1.12 (95% CI 1.05–1.19)) and Asian (OR = 1.10 (95% CI 1.04–1.17)) subjects, with a trend towards increased risk in Blacks (OR = 1.05 (95% CI 0.97–1.15)). We detected an interaction by sex, with men showing a higher risk of asthma with an increase in PRS as compared to women. The lasso sum regression–derived PRS showed stronger associations with asthma in non‐Hispanic White subjects (OR = 1.20 (95% CI 1.18–1.23)), Hispanics (OR = 1.17 (95% 1.10–1.26)), Asians (OR = 1.18 (95% CI 1.10–1.27)) and Blacks (OR = 1.10 (95% CI 0.99–1.22)). Conclusion: Polygenic risk scores across multiple racial/ethnic groups were associated with increased asthma risk, suggesting that PRSs have potential as a tool for predicting disease development. Abstract : Polygenic risk scores (PRSs) will have important utility for asthma and other chronic diseases as a tool for predicting disease incidence and subphenotypes. In this work, we utilized findings from a large trans‐ethnic GWAS of asthma to compute a PRS for asthma with relevance for ethnically diverse populations.