A Generalized Combinatorial Approach for Detecting Gene-by-Gene and Gene-by-Environment Interactions with Application to Nicotine Dependence

Abstract

The determination of gene-by-gene and gene-by-environment interactions has long been one of the greatest challenges in genetics. The traditional methods are typically inadequate because of the problem referred to as the "curse of dimensionality." Recent combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, the combinatorial partitioning method, and the restricted partition method, have a straightforward correspondence to the concept of the phenotypic landscape that unifies biological, statistical genetics, and evolutionary theories. However, the existing approaches have several limitations, such as not allowing for covariates, that restrict their practical use. In this study, we report a generalized MDR (GMDR) method that permits adjustment for discrete and quantitative covariates and is applicable to both dichotomous and continuous phenotypes in various population-based study designs. Computer simulations indicated that the GMDR method has superior performance in its ability to identify epistatic loci, compared with current methods in the literature. We applied our proposed method to a genetics study of four genes that were reported to be associated with nicotine dependence and found significant joint action between CHRNB4 and NTRK2. Moreover, our example illustrates that the newly proposed GMDR approach can increase prediction ability, suggesting that its use is justified in practice. In summary, GMDR serves the purpose of identifying contributors to population variation better than do the other existing methods.

UGMDR: a unified conceptual framework for detection of multifactor interactions underlying complex traits

“…The power gain has been extensively demonstrated in the real data analyses and the simulations in the present study and other reports (Lou et al, 2007(Lou et al, , 2008Chen et al, 2011Chen et al, , 2014.…”

“…To overcome these weaknesses, MDR has been extended to survival analysis (Gui et al, 2011;Lee et al, 2012), case-control study of structured populations (Niu et al, 2011), family study (Martin et al, 2006) and inclusion of covariates (Lee et al, 2007). The existing generalized MDR (GMDR) (Lou et al, 2007(Lou et al, , 2008 is still limited in tackling diverse phenotypes and samples, specifically being unable to analyze ordinal or polytomous nominal data, survival data and multivariate phenotypes, correct for population stratification in unrelateds and unify both unrelated and family samples into a joint analysis. Recently, Chen et al (2014) developed a GMDR method for unifying analyses of both unrelateds and families for dichotomous and continuous traits based on an adjustment with the principal components on the phenotypes but not on the markers.…”

Association of variants in genes involved in environmental chemical metabolism and risk of cryptorchidism and hypospadias

“…This algorithmic tool is a nonparametric (does not assume any statistical model) and model-free (no assumption mode of genetic inheritance) exploratory method, which has been developed to detect and characterize high-order gene-gene and gene-environment interactions in studies with relatively small sample size. 19,20 Models are evaluated on the testing balanced accuracy, the cross-validation consistency and the statistical significance of the model. The testing balanced accuracy measures how often individuals are correctly classified with respect to their case/control status, and the cross-validation consistency evaluate the consistency with which individuals are classified.…”

Association and Interaction ofPPARα,δ,andγGene Polymorphisms with Low-Density Lipoprotein-Cholesterol in a Chinese Han Population

“…To investigate the possible gene-gene interactions among the SNPs, a generalized linear model was applied in the program of generalized multifactor dimensionality reduction (GMDR) (Lou et al, 2007). Crossvalidation consistency, prediction accuracies, and empirical p-values were listed in the results of GMDR.…”