Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

BackgroundGenome-wide association studies 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.MethodsPrevious 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 dose prediction 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 and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals.ResultsWe build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations.ConclusionsOur results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions.MATLAB code is available at https://github.com/assafgo/warfarin-cohort

• Publication year

  2017

• Venue

  Genome Medicine

• Publication date

  2017-11-24

• Fields of study

  Biology, Medicine

• Identifiers
  DOI 10.1186/s13073-017-0495-0PMID 29178968PMCID 5702158
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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