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

Abstract

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.

Figure 1.. Principle component analyses showing ancestry groups based on various genotyping panels.

Each dot represents an individual. A). Genome-wide panel PCA plot based on 871,553SNPs. Inability to visualize the CEU is a result of high clustering within individuals of European ancestry. B). Preemptive PGx panel PCA plot based on 243 SNPs. C). VIP SNP panel PCA plot based on 122 SNPs.

Figure 2.. Principle component analysis of University of Chicago patients.

The PCA plot is based on the 243 SNPs in the preemptive PGx panel. The clusters for ancestral 1000 Genomes populations are shown for comparison (red=AFR; blue=EUR; green=EAS). Each real-world patient is represented by one dot (yellow=self-reported as “Caucasian/White”; purple=selfreported as “African American/Black” and found to have ≥70% AFR ancestry by STRUCTURE; black=self-reported as “African American/Black” but found to have <70% AFR ancestry by STRUCTURE).

Figure 3.. Population-specific warfarin dosing algorithms implemented in the institutional pharmacogenomic clinical decision-support system (Genomic Prescribing System).

A). Caucasian-specific warfarin algorithm (based on International Warfarin Pharmacogenetics Consortium model). The CYP2C9 variants included in this algorithm are *2 (rs1799853) and *3 (rs1057910). The VKORC1 variant is rs9923231. B). New African American-specific warfarin algorithm. The CYP2C9 variants tested are *2, *3, *5, *8 and *11 (rs1799853, rs1057910, rs28371686, rs7900194, rs28371685, respectively) and were combined into a composite CYP2C9 star genotype call.