A comparison of combinatorial partitioning and linear regression for the detection of epistatic effects of theACE I/DandPAI‐1 4G/5Gpolymorphisms on plasma PAI‐1 levels

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Abstract
The detection and characterization of epistasis or non‐additive gene–gene interactions remains a statistical challenge in genetic epidemiology. The recently developed combinatorial partitioning method (CPM) may overcome some of the limitations of linear regression for the exploratory analysis of non‐additive epistatic effects. The goal of this study was to compare CPM with linear regression analysis for the exploratory analysis of non‐additive interactive effects of theangiotensin converting enzyme (ACE) insertion/deletion (I/D)andplasminogen activator inhibitor 1 (PAI‐1) 4G/5Gpolymorphisms on plasma PAI‐1 levels in a sample of 50 unrelated African Americans and 117 unrelated Caucasians. Using linear regression, we documented the additive effects of theACEandPAI‐1genes on plasma PAI‐1 levels in African American females (R2 = 0.10), African American males (R2 = 0.16), Caucasian females (R2 = 0.11), and Caucasian males (R2 = 0.09). Using CPM, we found evidence for non‐additive effects of theACEandPAI‐1genes in both African American females (R2 = 0.22) and African American males (R2 = 0.24) but not in Caucasian females (R2 = 0.10) or Caucasian males (R2 = 0.11). The results of this exploratory data analysis support previous experimental, clinical, and epidemiological studies that have proposed as a working hypothesis that theACEgene mediates interaction effects of the fibrinolytic and renin‐angiotensin systems on plasma levels of PAI‐1.