Pharmacogenomic genotypes define genetic ancestry in patients and enable population-specific genomic implementation

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作者
Wenndy Hernandez
Keith Danahey
Xun Pei
Kiang-Teck J. Yeo
Edward Leung
Samuel L. Volchenboum
Mark J. Ratain
David O. Meltzer
Barbara E. Stranger
Minoli A. Perera
Peter H. O’Donnell
机构
[1] Section of Cardiology,University of Chicago, Department of Medicine, Section of Genetic Medicine
[2] University of Chicago,University of Chicago, Department of Pathology
[3] Center for Personalized Therapeutics,undefined
[4] University of Chicago,undefined
[5] Center for Research Informatics,undefined
[6] UChicago Advanced Technology Clinical Pharmacogenomics Laboratory,undefined
[7] University of Chicago,undefined
[8] Department of Medicine,undefined
[9] University of Chicago,undefined
[10] Committee on Clinical Pharmacology and Pharmacogenomics,undefined
[11] University of Chicago,undefined
[12] Institute of Genomics and Systems Biology,undefined
[13] and Center for Data Intensive Science,undefined
[14] Northwestern University,undefined
[15] Department of Pharmacology,undefined
[16] University of Southern California,undefined
[17] Keck School of Medicine,undefined
[18] Department of Pathology and Laboratory Medicine,undefined
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摘要
The importance of genetic ancestry characterization is increasing in genomic implementation efforts, and clinical pharmacogenomic guidelines are being published that include population-specific recommendations. Our aim was to test the ability of focused clinical pharmacogenomic SNP panels to estimate individual genetic ancestry (IGA) and implement population-specific pharmacogenomic clinical decision-support (CDS) tools. Principle components and STRUCTURE were utilized to assess differences in genetic composition and estimate IGA among 1572 individuals from 1000 Genomes, two independent cohorts of Caucasians and African Americans (AAs), plus a real-world validation population of patients undergoing pharmacogenomic genotyping. We found that clinical pharmacogenomic SNP panels accurately estimate IGA compared to genome-wide genotyping and identify AAs with ≥70 African ancestry (sensitivity >82%, specificity >80%, PPV >95%, NPV >47%). We also validated a new AA-specific warfarin dosing algorithm for patients with ≥70% African ancestry and implemented it at our institution as a novel CDS tool. Consideration of IGA to develop an institutional CDS tool was accomplished to enable population-specific pharmacogenomic guidance at the point-of-care. These capabilities were immediately applied for guidance of warfarin dosing in AAs versus Caucasians, but also provide a real-world model that can be extended to other populations and drugs as actionable genomic evidence accumulates.
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页码:126 / 135
页数:9
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