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Nat Genet. 2015 Sep;47(9):1091-8. doi: 10.1038/ng.3367. Epub 2015 Aug 10.

A gene-based association method for mapping traits using reference transcriptome data.

Author information

1
Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
2
Division of Genetic Medicine, Vanderbilt University, Nashville, Tennessee, USA.
3
Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
4
Department of Human Genetics, University of Chicago, Chicago, Illinois, USA.
5
Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
6
Rheumatology Center, NorthCrest Medical Center, Springfield, Tennessee, USA.
7
Department of Statistics, University of Chicago, Chicago, Illinois, USA.

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.

PMID:
26258848
PMCID:
PMC4552594
DOI:
10.1038/ng.3367
[Indexed for MEDLINE]
Free PMC Article

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