title: Using the gene ontology to scan multilevel gene sets for associations in genome wide association studies.
abstract: Gene-set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene-set, have plagued current approaches, often leading to ad hoc "fixes." To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene-level and gene-set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene-sets. However, other types of gene-set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene-sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene-sets, we use an efficient computational strategy that accounts for LD and provides accurate step-down adjusted P-values for each gene-set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene-set analyses.
authors.affiliation: Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA. schaid@mayo.edu
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Schaid
authors.forename: Jason P
authors.initials: JP
authors.lastname: Sinnwell
authors.forename: Gregory D
authors.initials: GD
authors.lastname: Jenkins
authors.forename: Shannon K
authors.initials: SK
authors.lastname: McDonnell
authors.forename: James N
authors.initials: JN
authors.lastname: Ingle
authors.forename: Michiaki
authors.initials: M
authors.lastname: Kubo
authors.forename: Paul E
authors.initials: PE
authors.lastname: Goss
authors.forename: Joseph P
authors.initials: JP
authors.lastname: Costantino
authors.forename: D Lawrence
authors.initials: DL
authors.lastname: Wickerham
authors.forename: Richard M
authors.initials: RM
authors.lastname: Weinshilboum
mesh_terms: D000077384:Anastrozole; D000730:Androstadienes / Q000009:adverse effects / Q000627:therapeutic use; D047072:Aromatase Inhibitors / Q000009:adverse effects / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000188:drug therapy / Q000235:genetics / Q000517:prevention & control; D016022:Case-Control Studies; D057225:Data Mining / Q000379:methods*; D005260:Female; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D009570:Nitriles / Q000009:adverse effects / Q000627:therapeutic use; D020641:Polymorphism, Single Nucleotide; D020849:Raloxifene Hydrochloride / Q000627:therapeutic use; D012984:Software; D013629:Tamoxifen / Q000627:therapeutic use; D014230:Triazoles / Q000009:adverse effects / Q000627:therapeutic use
chemical_list: D000730:Androstadienes; D047072:Aromatase Inhibitors; D009570:Nitriles; D014230:Triazoles; D013629:Tamoxifen; D000077384:Anastrozole; D020849:Raloxifene Hydrochloride; C056516:exemestane