Justine Po, John Morrison, Brittney Marian, Zhanghua Chen, W. James Gauderman, Erika Garcia
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引用次数: 0
Abstract
Gene−environment interactions have been observed for childhood asthma, however few have been assessed in ethnically diverse populations. Thus, we examined how polygenic risk score (PRS) modifies the association between ambient air pollution exposure (nitrogen dioxide [NO2], ozone, particulate matter < 2.5 and < 10 μm) and childhood asthma incidence in a diverse cohort. Participants (n = 1794) were drawn from the Southern California Children's Health Study, a multi-wave prospective cohort followed from 4th to 12th grade. PRS was developed using single nucleotide polymorphisms previously associated with childhood asthma. PRS−asthma associations and PRS−air pollutant interactions were estimated using Poisson regression. An interquartile range PRS increase was associated with 36% (95% CI: 9%, 70%) higher asthma incidence among non-Hispanic children, but not associated with asthma among Hispanic children (rate ratio: 0.81 [95% CI: 0.62, 1.04]). NO2−PRS interaction was borderline significant in the overall sample (coefficient: 0.23 [95% CI: −0.03, 0.49]). Limited evidence was observed for a positive interaction between PRS and NO2 exposure associated with asthma incidence; however, the literature-based PRS was not associated with asthma among Hispanic participants. Equitable, diverse genetic sampling approaches are needed to better identify clinically relevant SNPs in this population.
期刊介绍:
Genetic Epidemiology is a peer-reviewed journal for discussion of research on the genetic causes of the distribution of human traits in families and populations. Emphasis is placed on the relative contribution of genetic and environmental factors to human disease as revealed by genetic, epidemiological, and biologic investigations.
Genetic Epidemiology primarily publishes papers in statistical genetics, a research field that is primarily concerned with development of statistical, bioinformatical, and computational models for analyzing genetic data. Incorporation of underlying biology and population genetics into conceptual models is favored. The Journal seeks original articles comprising either applied research or innovative statistical, mathematical, computational, or genomic methodologies that advance studies in genetic epidemiology. Other types of reports are encouraged, such as letters to the editor, topic reviews, and perspectives from other fields of research that will likely enrich the field of genetic epidemiology.