Mary F Feitosa1, Allison L Kuipers2, Mary K Wojczynski1, Lihua Wang1, Emma Barinas-Mitchell2, Alexander M Kulminski3, Bharat Thyagarajan4, Joseph H Lee5, Thomas Perls6, Kaare Christensen7, Anne B Newman2, Joseph M Zmuda2,8, Michael A Province1. 1. Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO (M.F.F., M.K.W., L.W., M.A.P.). 2. Department of Epidemiology (A.L.K., E.B.-M., A.B.N., J.M.Z.), University of Pittsburgh, PA. 3. Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC (A.M.K.). 4. Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (B.T.). 5. Sergievsky Center, Taub Institute, Department of Epidemiology and Department of Neurology, Columbia University, NY (J.H.L.). 6. Department of Medicine, Boston University School of Medicine, MA (T.P.). 7. Danish Aging Research Center, University of Southern Denmark, Odense C (K.C.). 8. Department of Human Genetics (J.M.Z.), University of Pittsburgh, PA.
Abstract
BACKGROUND: Polygenic risk scores (PRS) for coronary heart disease (CHD) may contribute to assess the overall risk of CHD. We evaluated how PRS may influence CHD risk when the distribution of age-at-onset, sex, and family health history differ significantly. METHODS: Our study included 3 family-based ascertainments: LLFS (Long Life Family Study, NIndividuals=4572), which represents a low CHD risk, and Family Heart Study, which consists of randomly selected families (FamHS-random, NIndividuals=1806), and high CHD risk families (FamHS-high risk, NIndividuals=2301). We examined the effects of PRS, sex, family ascertainment, PRS interaction with sex (PRS*sex) and with family ascertainment (PRS*LLFS and PRS*FamHS-high risk) on CHD, corrected for traditional cardiovascular risk factors using Cox proportional hazard regression models. RESULTS: Healthy-aging LLFS presented ≈17 years delayed for CHD age-at-onset compared with FamHS-high risk (P<1.0×10-4). Sex-specific association (P<1.0×10-17) and PRS*sex (P=2.7×10-3) predicted prevalent CHD. CHD age-at-onset was associated with PRS (hazard ratio [HR], 1.57; P=1.3×10-5), LLFS (HR, 0.54; P=2.6×10-5), and FamHS-high risk (HR, 2.86; P=6.70x10-15) in men, and with PRS (HR, 1.76; P=7.70×10-3), FamHS-high risk (HR, 4.88; P=8.70×10-10), and PRS×FamHS-high risk (HR, 0.61; P=3.60×10-2) in women. In the PRS extreme quartile distributions, CHD age-at-onset was associated (P<0.05) with PRS, FamHS-high risk, and PRS interactions with both low and high CHD risk families for women. For men, the PRS quartile results remained similar to the whole distribution. CONCLUSIONS: Differences in CHD family-based ascertainments show evidence of PRS interacting with sex to predict CHD risk. In women, CHD age-at-onset was associated with PRS, CHD family history, and interactions of PRS with family history. In men, PRS and CHD family history were the major effects on the CHD age-at-onset. Understanding the heterogeneity of risks associated with CHD end points at both the personal and familial levels may shed light on the underlying genetic effects influencing CHD and lead to more personalized risk prediction.
BACKGROUND: Polygenic risk scores (PRS) for coronary heart disease (CHD) may contribute to assess the overall risk of CHD. We evaluated how PRS may influence CHD risk when the distribution of age-at-onset, sex, and family health history differ significantly. METHODS: Our study included 3 family-based ascertainments: LLFS (Long Life Family Study, NIndividuals=4572), which represents a low CHD risk, and Family Heart Study, which consists of randomly selected families (FamHS-random, NIndividuals=1806), and high CHD risk families (FamHS-high risk, NIndividuals=2301). We examined the effects of PRS, sex, family ascertainment, PRS interaction with sex (PRS*sex) and with family ascertainment (PRS*LLFS and PRS*FamHS-high risk) on CHD, corrected for traditional cardiovascular risk factors using Cox proportional hazard regression models. RESULTS: Healthy-aging LLFS presented ≈17 years delayed for CHD age-at-onset compared with FamHS-high risk (P<1.0×10-4). Sex-specific association (P<1.0×10-17) and PRS*sex (P=2.7×10-3) predicted prevalent CHD. CHD age-at-onset was associated with PRS (hazard ratio [HR], 1.57; P=1.3×10-5), LLFS (HR, 0.54; P=2.6×10-5), and FamHS-high risk (HR, 2.86; P=6.70x10-15) in men, and with PRS (HR, 1.76; P=7.70×10-3), FamHS-high risk (HR, 4.88; P=8.70×10-10), and PRS×FamHS-high risk (HR, 0.61; P=3.60×10-2) in women. In the PRS extreme quartile distributions, CHD age-at-onset was associated (P<0.05) with PRS, FamHS-high risk, and PRS interactions with both low and high CHD risk families for women. For men, the PRS quartile results remained similar to the whole distribution. CONCLUSIONS: Differences in CHD family-based ascertainments show evidence of PRS interacting with sex to predict CHD risk. In women, CHD age-at-onset was associated with PRS, CHD family history, and interactions of PRS with family history. In men, PRS and CHD family history were the major effects on the CHD age-at-onset. Understanding the heterogeneity of risks associated with CHD end points at both the personal and familial levels may shed light on the underlying genetic effects influencing CHD and lead to more personalized risk prediction.
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