RT Journal Article
SR Electronic
T1 Population-specific imputation of gene expression improves prediction of pharmacogenomic traits for African Americans
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 115451
DO 10.1101/115451
A1 Assaf Gottlieb
A1 Roxana Daneshjou
A1 Marianne DeGorter
A1 Stephen B. Montgomery
A1 Russ B. Altman
YR 2017
UL http://biorxiv.org/content/early/2017/03/09/115451.abstract
AB Genome-wide association studies (GWAS) are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power, and allows the effects of both protein coding variation as well as variation in expression to be combined into “gene level” effects.Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein coding regions. Here, we introduce a method that improves the predicted dose by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic (PK) and pharmacodynamic (PD) pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose, and identify a signature of eleven gene-tissue pairs that significantly augment the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction, in a population-specific manner.