Leverage drug perturbation to reveal genetic regulators of hepatic gene expression in African Americans
Yizhen Zhong, Tanima DeiD, Juan Avitia, Cristina AlarcóniD, Minoli A. PereraiD
Abstract
BackgroundExpression quantitative loci (eQTL) studies have paved the way in identifying genetic variation impacting gene expression levels. African Americans (AAs) are disproportionately underrepresented in eQTL studies, resulting in a lack of power to identify population-specific regulatory variations especially related to drug response. Specific drugs are known to affect the biosynthesis of drug metabolism enzymes as well as other genes. We used drug perturbation in cultured primary hepatocytes derived from AAs to determine the effect of drug treatment on eQTL mapping and to identify the drug response eQTLs (reQTLs) that show altered effect size following drug treatment. MethodsWhole-genome genotyping (Illumina MEGA array) and RNA-sequencing were performed on 60 primary hepatocyte cultures after treatment with 6 drugs (Rifampin, Phenytoin, Carbamazepine, Dexamethasone, Phenobarbital, and Omeprazole) and at baseline (no treatment). eQTLs were mapped by treatment and jointly using Meta Tissue. ResultsWe found varying transcriptional changes across different drug treatments and identified Nrf2 as a potential general transcriptional regulator. We jointly mapped eQTL with gene expression data for across all drug treatments and baseline which increased our power to detect eQTLs by 2.7-fold. We also identified 2,988 reQTLs (eQTLs with altered effect size after drug treatment), which were more likely to overlap transcription factor binding sites and uncovered a novel reQTL, rs61017966 that increases CYP3A5 gene expression, a major drug metabolizing enzyme responsible for both drug response and adverse events across several drug classes. ConclusionsOur results provide novel insights into the genetic regulation of gene expression in hepatocytes through drug perturbation and provide insight into SNPs that effect the livers ability to respond to transcription upregulation.
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