Development and evaluation of a genetic risk score for obesity

Abstract

Multi-locus profiles of genetic risk, so-called "genetic risk scores," can be used to translate discoveries from genome-wide association studies into tools for population health research. We developed a genetic risk score for obesity from results of 16 published genome-wide association studies of obesity phenotypes in European-descent samples. We then evaluated this genetic risk score using data from the Atherosclerosis Risk in Communities (ARIC) cohort GWAS sample (N = 10,745, 55% female, 77% white, 23% African American). Our 32-locus GRS was a statistically significant predictor of body mass index (BMI) and obesity among ARIC whites [for BMI, r = 0.13, p<1 × 10(-30); for obesity, area under the receiver operating characteristic curve (AUC) = 0.57 (95% CI 0.55-0.58)]. The GRS predicted differences in obesity risk net of demographic, geographic, and socioeconomic information. The GRS performed less well among African Americans. The genetic risk score we derived from GWAS provides a molecular measurement of genetic predisposition to elevated BMI and obesity.[Supplemental materials are available for this article. Go to the publisher's online edition of Biodemography and Social Biology for the following resource: Supplement to Development & Evaluation of a Genetic Risk Score for Obesity.].

Figure 1

Panel A. BMI for African American and White ARIC Participants Plotted Against the Weighted Obesity Genetic Risk Score Dashed outlines represent 95% confidence intervals. Pearson correlations (r) were adjusted for gender, age and ARIC Study Center where data were collected. Removal of outliers (not shown) did not alter correlation estimates at the third decimal point. Correlations were statistically significant for white (p<1×10⁻³⁰) and African American (p=0.014) ARIC participants. Panel B. Percentage White and African American ARIC Participants Who Were Obese (BMI≥30 kg/m²) at the First Study Visit, by Quintile of Genetic Risk Score. Quintiles were determined separately for whites and African Americans. Error bars represent 95% confidence intervals. Risk ratios are for comparisons of highest to lowest quintiles of genomic risk and were estimated with adjustment for gender, age, and ARIC study center where data were collected. Dashed lines represent sample means. Among white ARIC participants, all quintile to quintile differences are statistically significant (p<0.01), with the exception of the 3^rd and 4^th quintiles. Among African American ARIC participants, the percent obese in the lowest quintile was lower than in the third and fourth quintiles (p<0.05).

Figure 1

Panel A. BMI for African American and White ARIC Participants Plotted Against the Weighted Obesity Genetic Risk Score Dashed outlines represent 95% confidence intervals. Pearson correlations (r) were adjusted for gender, age and ARIC Study Center where data were collected. Removal of outliers (not shown) did not alter correlation estimates at the third decimal point. Correlations were statistically significant for white (p<1×10⁻³⁰) and African American (p=0.014) ARIC participants. Panel B. Percentage White and African American ARIC Participants Who Were Obese (BMI≥30 kg/m²) at the First Study Visit, by Quintile of Genetic Risk Score. Quintiles were determined separately for whites and African Americans. Error bars represent 95% confidence intervals. Risk ratios are for comparisons of highest to lowest quintiles of genomic risk and were estimated with adjustment for gender, age, and ARIC study center where data were collected. Dashed lines represent sample means. Among white ARIC participants, all quintile to quintile differences are statistically significant (p<0.01), with the exception of the 3^rd and 4^th quintiles. Among African American ARIC participants, the percent obese in the lowest quintile was lower than in the third and fourth quintiles (p<0.05).

Figure 2. Receiver Operating Characteristic Curves for Obesity Among White ARIC Participants (n=8,286)

Baseline Model = gender, age (quadratic), gender x age interaction, ARIC study center; Test Model = baseline model + weighted obesity genetic risk score. ROC Curves were constructed using predicted values from probit regressions of obesity (BMI≥30) on the model terms. Delta AUC (AUC_Test − AUC_Baseline) = 0.048, 95% CI 0.031–0.066, p<1×10⁻⁷. Delta Partial AUC at 80% specificity=0.007, 95% CI 0.003–0.010, p<0.001. AUCs, partial AUCs, and delta AUCs were estimated using Pepe’s method ^,.

Figure 3. Cumulative Mortality Hazards for White ARIC Participants in the Highest, Middle, and Lowest Genetic Risk Score (GRS) Qunitiles

Hazards were estimated from a Cox proportional hazard model adjusted for age, sex, the age-sex interaction, and the ARIC Study Center where data were collected. The dashed line represents sample-wide mortality at the end of follow-up (15%). By the end of follow-up, unadjusted mortality was 12.17% in the lowest GRS quintile, 15.48% in the middle GRS quintile, and 17.32% in the highest GRS quintile.