Pharmacogenomics of Membrane Transporters

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Membrane transporters in the SLC and ABC superfamilies are of enormous pharmacological importance, serving as critical determinants of drug disposition and response. Building on the extensive infrastructure established during the previous granting cycles, the proposed research will focus on transporters in the liver and kidney, which interact with virtually all known drugs in mediating drug disposition, response and toxicity. Through computationally driven functional studies and multiple clinical studies, the proposed research will test the hypothesis that genetic variants in membrane transporters contribute to variation in drug response. The functional genomic studies will have a major emphasis on variants in noncoding regions, expanding on our current efforts, which are focused largely on nonsynonymous variants. For these studies, we propose to: (a) functionally characterize variants within regulatory regions of transporter genes; (b) associate sequence variants with transporter expression levels in liver and kidney samples; and (c) develop predictive models for substrate-dependent effects of nonsynonymous variants. In addition to common variants, we will continue to study rare variants as our previous studies have demonstrated their functional importance. Three types of clinical studies will be performed: (a) genotype-driven hypothesis testing studies in SOPHIE, a unique cohort of healthy volunteers who have provided DNA and agreed to be called back for follow-up studies; (b) a large genomewide association study in African Americans of response to the anti-diabetic drug, metformin, a drug that interacts with multiple transporters; and (c) collaborative studies on clinical samples in which a custom-designed transporter-ADME SNP chip will be used to identify genetic variants in transporters that are determinants of toxicities and response to multiple drugs. Our project has recruited a world-class multidisciplinary research team with computational, experimental and clinical expertise, who will apply innovative methodologies including RNA-seq, Next-generation sequencing and multi-stage genomewide association analysis. Three research cores, bioinformatics, biostatistics and genomics, will provide support for these highly mechanistic and clinically important studies.