The Promise of Selecting Individuals from the Extremes of Exposure in the Analysis of Gene-Physical Activity Interactions

TY - JOUR

T1 - The Promise of Selecting Individuals from the Extremes of Exposure in the Analysis of Gene-Physical Activity Interactions

AU - Osazuwa-Peters, Oyomoare L

AU - Schwander, Karen

AU - Waken, R J

AU - de Las Fuentes, Lisa

AU - Kilpeläinen, Tuomas O

AU - Loos, Ruth J F

AU - Racette, Susan B

AU - Sung, Yun Ju

AU - Rao, D C

PY - 2019/6/1

Y1 - 2019/6/1

N2 - BACKGROUND: Dichotomization using the lower quartile as cutoff is commonly used for harmonizing heterogeneous physical activity (PA) measures across studies. However, this may create misclassification and hinder discovery of new loci.OBJECTIVES: This study aimed to evaluate the performance of selecting individuals from the extremes of the exposure (SIEE) as an alternative approach to reduce such misclassification.METHOD: For systolic and diastolic blood pressure in the Framingham Heart Study, we performed a genome-wide association study with gene-PA interaction analysis using three PA variables derived by SIEE and two other dichotomization approaches. We compared number of loci detected and overlap with loci found using a quantitative PA variable. In addition, we performed simulation studies to assess bias, false discovery rates (FDR), and power under synergistic/antagonistic genetic effects in exposure groups and in the presence/absence of measurement error.RESULTS: In the empirical analysis, SIEE's performance was neither the best nor the worst. In most simulation scenarios, SIEE was consistently outperformed in terms of FDR and power. Particularly, in a scenario characterized by antagonistic effects and measurement error, SIEE had the least bias and highest power.CONCLUSION: SIEE's promise appears limited to detecting loci with antagonistic effects. Further studies are needed to evaluate SIEE's full advantage.

AB - BACKGROUND: Dichotomization using the lower quartile as cutoff is commonly used for harmonizing heterogeneous physical activity (PA) measures across studies. However, this may create misclassification and hinder discovery of new loci.OBJECTIVES: This study aimed to evaluate the performance of selecting individuals from the extremes of the exposure (SIEE) as an alternative approach to reduce such misclassification.METHOD: For systolic and diastolic blood pressure in the Framingham Heart Study, we performed a genome-wide association study with gene-PA interaction analysis using three PA variables derived by SIEE and two other dichotomization approaches. We compared number of loci detected and overlap with loci found using a quantitative PA variable. In addition, we performed simulation studies to assess bias, false discovery rates (FDR), and power under synergistic/antagonistic genetic effects in exposure groups and in the presence/absence of measurement error.RESULTS: In the empirical analysis, SIEE's performance was neither the best nor the worst. In most simulation scenarios, SIEE was consistently outperformed in terms of FDR and power. Particularly, in a scenario characterized by antagonistic effects and measurement error, SIEE had the least bias and highest power.CONCLUSION: SIEE's promise appears limited to detecting loci with antagonistic effects. Further studies are needed to evaluate SIEE's full advantage.

U2 - 10.1159/000499711

DO - 10.1159/000499711

M3 - Journal article

C2 - 31167214

SN - 0001-5652

VL - 83

SP - 315

EP - 332

JO - Human Heredity

JF - Human Heredity

IS - 6

ER -