The Personalized Environment and Genes Study

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As co-PI of the Personalized Environment and Genes Study, I direct many scientific projects using the data. The PEGS data includes whole genome sequencing, extensive health and exposure questionnaires, GIS estimates of exposure based on residential histories, and very recently epigenetic data. This rich resource has allowed for several recently published projects. The summaries of these published projects are listed below. Asthma, a chronic breathing impairment, has a multifaceted origin involving genes and environment. One study explored genetic ties to late-onset asthma in a multiracial cohort in North Carolina, considering race and ethnicity. We found multiple genetic variations in the MHC region linked to late-onset asthma, with race-based variations in these associations. Concentrated animal feeding operations (CAFOs) contribute to pollution and affect health. We studied the association between living near a CAFO and immune-mediated diseases (IMD), considering specific gene variants. Our results showed an increased risk of autoimmune diseases, especially rheumatoid arthritis, for those living near a CAFO and potential genetic influences on this risk. Autoimmune skin diseases like psoriasis and eczema result from genetic and environmental factors. We analyzed the connection between these diseases and various air pollutants in 9060 subjects. Our study reveals that certain air pollutants are linked to a higher prevalence of autoimmune skin disorders, emphasizing the potential health impacts of air pollution on these conditions. Air pollution's effect on diseases other than lung and heart issues is under-researched. Our findings highlight a significant link between air pollution and skin autoimmune diseases, comparing the risk to that from smoking. This stresses the significance of understanding the risks air pollution poses to autoimmune diseases. Ongoing work includes gene mapping of gestational hypertension, disease mapping with structural variants, and methods development for methods to detect gene-environment interactions. In another study, we evaluated environmental impacts on type 2 diabetes, comparing them to genetic factors. Our findings identified 76 significant links, including new associations with asbestos and coal dust. Results showed that environmental factors might have a stronger predictive power for diabetes than genetic scores, and the outcomes varied by race. This underscores the importance of broad-based studies on genetic and environmental influences across different populations. Additionally, we analyzed the relationship between environmental exposures and cardiovascular disease (CVD) in the North Carolina-based Personalized Environment and Genes Study with 5015 participants. Through this comprehensive study, we discovered new associations such as blood type A (Rh-) with heart attacks and various paint exposures with strokes. Other findings included biohazardous material exposures linked to arrhythmia and higher paternal education reducing CVD risk. Key risk factors were sleeping issues and smoking. Our findings shed light on complex factors influencing CVD and the necessity of examining multiple exposures.