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Updated: Oct 22, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
A polygenic risk score for asthma in a large racially diverse population
Joanne E Sordillo1, Sharon M Lutz1, Eric Jorgenson2
1PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care, Boston, Massachusetts, USA.
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.
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