title: Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.
abstract: Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects.
authors.affiliation: Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, 14558, Nuthetal, Germany.
authors.forename: Sven
authors.initials: S
authors.lastname: Knüppel
authors.affiliation: Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, 14558, Nuthetal, Germany.
authors.forename: Karina
authors.initials: K
authors.lastname: Meidtner
authors.affiliation: Research Group Cardiovascular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, 14558, Nuthetal, Germany.
authors.forename: Maria
authors.initials: M
authors.lastname: Arregui
authors.affiliation: Institute of Biochemistry, University Medicine Charité Berlin, 10117, Berlin, Germany.
authors.forename: Hermann-Georg
authors.initials: HG
authors.lastname: Holzhütter
authors.affiliation: Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, 14558, Nuthetal, Germany.
authors.forename: Heiner
authors.initials: H
authors.lastname: Boeing
mesh_terms: D000328:Adult; D000368:Aged; D016022:Case-Control Studies; D015331:Cohort Studies; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D005858:Germany; D006801:Humans; D008875:Middle Aged; D008957:Models, Genetic; D058885:Multilocus Sequence Typing; D020641:Polymorphism, Single Nucleotide; D012044:Regression Analysis
keywords: LASSO; SNPs, multilocus stepwise regression, genetic risk score; type 2 diabetes mellitus