Abstract 4137518: The implications of polygenic versus phenotypic characterization of obesity for cardiovascular-kidney-metabolic health

Introduction: The overall amount and the distribution of body fat, proxied by body-mass index (BMI) and waist-to-hip ratio (WHR), are two important measures of obesity and have significant polygenic heritability. We aimed to investigate whether polygenic scores (PGS) for these traits have additional predictive utility, beyond phenotypic characterization of obesity, for cardiovascular-kidney-metabolic (CKM) health. Methods: We derived PGS for BMI (PGS BMI ) and WHR adjusted for BMI (PGS WHRadjBMI ) using PRS-CS-auto on summary statistics from ~700k individuals of European ancestry (EA) in the GIANT consortium and selecting ~1M common variants for each score. We conducted association analyses in the Atherosclerosis Risk in Communities study, a prospective cohort including 8,631 EA individuals with ascertainment of incident diabetes, hypertension, chronic kidney disease, atrial fibrillation, coronary heart disease, ischemic stroke, and heart failure. We used nested Cox models to measure the added predictive utility of PGS to BMI and WHR for incident CKM phenotypes. Results: The study cohort (age 54.4±5.7 years, 52.4% women, follow-up 24.5±7.6 years) had a baseline BMI of 26.4 kg/m 2 (median [IQR]; 21.6-29.6) and WHR of 0.94 (0.88-0.98). PGS BMI and PGS WHRadjBMI were associated with their phenotypes (partial R 2 ; BMI 0.11 and WHR 0.04, p <0.001), although with a large phenotypic variability across the distribution of PGS (IQR for 1 st and 10 th deciles of PGS; BMI 19.6-28.3 and 22.6-35.9, WHR 0.79-1.03 and 0.87-1.05). Anthropometric measures of obesity were associated with a wider gradient of risk compared to PGS for obesity–most notable for diabetes and cardiovascular phenotypes (Table 1a). Addition of PGS BMI and PGS WHRadjBMI to BMI and WHR resulted in limited improvement in risk discrimination across incident CKM phenotypes (Table 1b). Conclusions: Observed anthropometric measures of obesity are sufficient, and for certain conditions far superior, to capture the risk of incident CKM phenotypes. These findings suggest PGS for adiposity traits likely have limited clinical utility to refine risk stratification for CKM syndrome among middle aged adults.

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Journal
Circulation
Published
2024-11-12
DOI
https://doi.org/10.1161/circ.150.suppl_1.4137518
Primary Topic
Diet and metabolism studies
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article
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article

Abstract 4137518: The implications of polygenic versus phenotypic characterization of obesity for cardiovascular-kidney-metabolic health

Daniel J. Schaid, Iftikhar J. Kullo, Marwan Hamed, Matt Kosel et al.
Circulation
Diet and metabolism studies
article

Abstract 4137518: The implications of polygenic versus phenotypic characterization of obesity for cardiovascular-kidney-metabolic health

Daniel J. Schaid, Iftikhar J. Kullo, Marwan Hamed, Matt Kosel, Mohammadreza Naderian, Ozan Dikilitas
article en

Abstract

Introduction: The overall amount and the distribution of body fat, proxied by body-mass index (BMI) and waist-to-hip ratio (WHR), are two important measures of obesity and have significant polygenic heritability. We aimed to investigate whether polygenic scores (PGS) for these traits have additional predictive utility, beyond phenotypic characterization of obesity, for cardiovascular-kidney-metabolic (CKM) health. Methods: We derived PGS for BMI (PGS BMI ) and WHR adjusted for BMI (PGS WHRadjBMI ) using PRS-CS-auto on summary statistics from ~700k individuals of European ancestry (EA) in the GIANT consortium and selecting ~1M common variants for each score. We conducted association analyses in the Atherosclerosis Risk in Communities study, a prospective cohort including 8,631 EA individuals with ascertainment of incident diabetes, hypertension, chronic kidney disease, atrial fibrillation, coronary heart disease, ischemic stroke, and heart failure. We used nested Cox models to measure the added predictive utility of PGS to BMI and WHR for incident CKM phenotypes. Results: The study cohort (age 54.4±5.7 years, 52.4% women, follow-up 24.5±7.6 years) had a baseline BMI of 26.4 kg/m 2 (median [IQR]; 21.6-29.6) and WHR of 0.94 (0.88-0.98). PGS BMI and PGS WHRadjBMI were associated with their phenotypes (partial R 2 ; BMI 0.11 and WHR 0.04, p <0.001), although with a large phenotypic variability across the distribution of PGS (IQR for 1 st and 10 th deciles of PGS; BMI 19.6-28.3 and 22.6-35.9, WHR 0.79-1.03 and 0.87-1.05). Anthropometric measures of obesity were associated with a wider gradient of risk compared to PGS for obesity–most notable for diabetes and cardiovascular phenotypes (Table 1a). Addition of PGS BMI and PGS WHRadjBMI to BMI and WHR resulted in limited improvement in risk discrimination across incident CKM phenotypes (Table 1b). Conclusions: Observed anthropometric measures of obesity are sufficient, and for certain conditions far superior, to capture the risk of incident CKM phenotypes. These findings suggest PGS for adiposity traits likely have limited clinical utility to refine risk stratification for CKM syndrome among middle aged adults.

CirculationVol. 150(Suppl_1)
Mayo Clinic (US)
Good health and well-being
Openalex Percentile: Top 71%
Diet and metabolism studies
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