title: A Multi-Marker Genetic Association Test Based on the Rasch Model Applied to Alzheimer's Disease.
abstract: Results from Genome-Wide Association Studies (GWAS) have shown that the genetic basis of complex traits often include many genetic variants with small to moderate effects whose identification remains a challenging problem. In this context multi-marker analysis at the gene and pathway level can complement traditional point-wise approaches that treat the genetic markers individually. In this paper we propose a novel statistical approach for multi-marker analysis based on the Rasch model. The method summarizes the categorical genotypes of SNPs by a generalized logistic function into a genetic score that can be used for association analysis. Through different sets of simulations, the false-positive rate and power of the proposed approach are compared to a set of existing methods, and shows good performances. The application of the Rasch model on Alzheimer's Disease (AD) ADNI GWAS dataset also allows a coherent interpretation of the results. Our analysis supports the idea that APOE is a major susceptibility gene for AD. In the top genes selected by proposed method, several could be functionally linked to AD. In particular, a pathway analysis of these genes also highlights the metabolism of cholesterol, that is known to play a key role in AD pathogenesis. Interestingly, many of these top genes can be integrated in a hypothetic signalling network.
authors.affiliation: Pharnext, Issy-les-Moulineaux, Ile de France, France; Inserm U897, University of Bordeaux, Bordeaux, Aquitaine, France.
authors.forename: Wenjia
authors.initials: W
authors.lastname: Wang
authors.affiliation: Pharnext, Issy-les-Moulineaux, Ile de France, France.
authors.forename: Jonas
authors.initials: J
authors.lastname: Mandel
authors.affiliation: Pharnext, Issy-les-Moulineaux, Ile de France, France.
authors.forename: Jan
authors.initials: J
authors.lastname: Bouaziz
authors.affiliation: Inserm U897, University of Bordeaux, Bordeaux, Aquitaine, France.
authors.forename: Daniel
authors.initials: D
authors.lastname: Commenges
authors.affiliation: Pharnext, Issy-les-Moulineaux, Ile de France, France.
authors.forename: Serguei
authors.initials: S
authors.lastname: Nabirotchkine
authors.affiliation: Pharnext, Issy-les-Moulineaux, Ile de France, France.
authors.forename: Ilya
authors.initials: I
authors.lastname: Chumakov
authors.affiliation: Pharnext, Issy-les-Moulineaux, Ile de France, France.
authors.forename: Daniel
authors.initials: D
authors.lastname: Cohen
authors.affiliation: Pharnext, Issy-les-Moulineaux, Ile de France, France.
authors.forename: Mickaël
authors.initials: M
authors.lastname: Guedj
mesh_terms: D000544:Alzheimer Disease / Q000235:genetics*; D056726:Genetic Association Studies / Q000706:statistics & numerical data*; D005819:Genetic Markers / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D008962:Models, Theoretical; D020641:Polymorphism, Single Nucleotide / Q000235:genetics
chemical_list: D005819:Genetic Markers