A Multinomial Ordinal Probit Model with Singular Value Decomposition Method for a Multinomial Trait

Abstract

We developed a multinomial ordinal probit model with singular value decomposition for testing a large number of single nucleotide polymorphisms (SNPs) simultaneously for association with multidisease status when sample size is much smaller than the number of SNPs. The validity and performance of the method was evaluated via simulation. We applied the method to our real study sample recruited through the Mexican-American Coronary Artery Disease study. We found 3 genes (SORCS1, AMPD1, and PPARα) to be associated with the development of both IGT and IFG, while 5 genes (AMPD2, PRKAA2, C5, TCF7L2, and ITR) with the IGT mechanism only and 6 genes (CAPN10, IL4, NOS3, CD14, GCG, and SORT1) with the IFG mechanism only. These data suggest that IGT and IFG may indicate different physiological mechanism to prediabetes, via different genetic determinants.