A score test for genetic class-level association with nonlinear biomarker trajectories.

Emerging data suggest that the genetic regulation of the biological response to inflammatory stress may be fundamentally different to the genetic underpinning of the homeostatic control (resting state) of the same biological measures. In this paper, we interrogate this hypothesis using a single-SNP score test and a novel class-level testing strategy to characterize protein-coding gene and regulatory element-level associations with longitudinal biomarker trajectories in response to stimulus. Using the proposed class-level association score statistic for longitudinal data, which accounts for correlations induced by linkage disequilibrium, the genetic underpinnings of evoked dynamic changes in repeatedly measured biomarkers are investigated. The proposed method is applied to data on two biomarkers arising from the Genetics of Evoked Responses to Niacin and Endotoxemia study, a National Institutes of Health-sponsored investigation of the genomics of inflammatory and metabolic responses during low-grade endotoxemia. Our results suggest that the genetic basis of evoked inflammatory response is different than the genetic contributors to resting state, and several potentially novel loci are identified. A simulation study demonstrates appropriate control of type-1 error rates, relative computational efficiency, and power.