title: A gene-based association method for mapping traits using reference transcriptome data.
abstract: Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual's genetic profile and correlates 'imputed' gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. Genetically regulated gene expression is estimated using whole-genome tissue-dependent prediction models trained with reference transcriptome data sets. PrediXcan enjoys the benefits of gene-based approaches such as reduced multiple-testing burden and a principled approach to the design of follow-up experiments. Our results demonstrate that PrediXcan can detect known and new genes associated with disease traits and provide insights into the mechanism of these associations.
authors.affiliation: Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA.|Division of Genetic Medicine, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Eric R
authors.identifier: http://orcid.org/0000-0003-4204-8734
authors.initials: ER
authors.lastname: Gamazon
authors.affiliation: Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
authors.forename: Heather E
authors.identifier: http://orcid.org/0000-0001-6955-6021
authors.initials: HE
authors.lastname: Wheeler
authors.affiliation: Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
authors.forename: Kaanan P
authors.initials: KP
authors.lastname: Shah
authors.affiliation: Department of Human Genetics, University of Chicago, Chicago, Illinois, USA.
authors.forename: Sahar V
authors.initials: SV
authors.lastname: Mozaffari
authors.affiliation: Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
authors.forename: Keston
authors.initials: K
authors.lastname: Aquino-Michaels
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Carroll
authors.affiliation: Rheumatology Center, NorthCrest Medical Center, Springfield, Tennessee, USA.
authors.forename: Anne E
authors.initials: AE
authors.lastname: Eyler
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Joshua C
authors.initials: JC
authors.lastname: Denny
authors.affiliation: Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA.|Department of Human Genetics, University of Chicago, Chicago, Illinois, USA.|Department of Statistics, University of Chicago, Chicago, Illinois, USA.
authors.forename: Dan L
authors.initials: DL
authors.lastname: Nicolae
authors.affiliation: Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA.|Division of Genetic Medicine, Vanderbilt University, Nashville, Tennessee, USA.|Department of Human Genetics, University of Chicago, Chicago, Illinois, USA.
authors.forename: Nancy J
authors.initials: NJ
authors.lastname: Cox
authors.affiliation: Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
authors.forename: Hae Kyung
authors.identifier: http://orcid.org/0000-0003-0333-5685
authors.initials: HK
authors.lastname: Im
mesh_terms: D002874:Chromosome Mapping; D020869:Gene Expression Profiling; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide