Ethnic Diversity and Warfarin Pharmacogenomics

Abstract

Warfarin has remained the most commonly prescribed vitamin K oral anticoagulant worldwide since its approval in 1954. Dosing challenges including having a narrow therapeutic window and a wide interpatient variability in dosing requirements have contributed to making it the most studied drug in terms of genotype-phenotype relationships. However, most of these studies have been conducted in Whites or Asians which means the current pharmacogenomics evidence-base does not reflect ethnic diversity. Due to differences in minor allele frequencies of key genetic variants, studies conducted in Whites/Asians may not be applicable to underrepresented populations such as Blacks, Hispanics/Latinos, American Indians/Alaska Natives and Native Hawaiians/other Pacific Islanders. This may exacerbate health inequalities when Whites/Asians have better anticoagulation profiles due to the existence of validated pharmacogenomic dosing algorithms which fail to perform similarly in the underrepresented populations. To examine the extent to which individual races/ethnicities are represented in the existing body of pharmacogenomic evidence, we review evidence pertaining to published pharmacogenomic dosing algorithms, including clinical utility studies, cost-effectiveness studies and clinical implementation guidelines that have been published in the warfarin field.

Pharmacogenomics implementation in cardiovascular disease in a highly diverse population: initial findings and lessons learned from a pilot study in United Arab Emirates

“…A recent review highlighted that the current PGx evidence of warfarin does not reflect populations' diversity and probably exacerbates health inequalities. The authors warrened that understudied populations exhibit different minor allele frequencies, an observation we reported here and in previous reports from our population [30], which threatens the applicability of warfarin dosing algorithms [31]. Herein, the planned inclusion of more clinical sites can recruit more patients to the warfarin group, which may enable further validation of genotype-guided warfarin dosing in our population.…”

Drug–Drug–Gene Interactions in Cardiovascular Medicine

“… 74 However, most of the existing pharmacogenetic evidence is applicable to Whites and Asians, which means existing databases or guidelines may not be useful for other races. 74 , 169 As of 8 July 2021, 86% of the genome-wide association studies had been conducted in individuals of European ancestry, 170 , 171 which demonstrates a lack of ethnic diversity in genomic evidence. Based on the CPIC guidelines, warfarin, clopidogrel and statins are the three cardiovascular medicine drug classes ready for clinical implementation; however, there is also a lack of diversity in these medicine fields.…”

“…For example, the CPIC, 172 CPNDS, 173 and DPWG 174 clinical implementation guidelines for warfarin DGIs rely on two algorithms (Gage and International Warfarin Pharmacogenetics Consortium) 175 , 176 that mostly rely on genetic variants discovered in Whites (rs1799853 [ CYP2C9*2 ], rs1057910 [ CYP2C9*3 ] and rs9923231 [ VKORC1 −1639G>A ]) and miss out important variants such as rs7900194 [ CYP2C9*8 ], rs28371685 [ CYP2C9*11 ], and CYP2C rs12777823 that are likely to be more relevant to Blacks and some Hispanic populations. 169 Like for warfarin, where the key genetic variants have varying MAFs ( CYP2C9*2 African = 0.01, American = 0.10, East Asian ~ 0.00, European = 0.12, South Asian = 0.04; CYP2C9*3 African ~ 0.00, American = 0.04, East Asian = 0.03, European = 0.07, South Asian = 0.11; CYP2C9*8 African = 0.05, Other ~ 0.00; and CYP2C9*11 African = 0.02, Other ~ 0.00; VKORC1 −1639G>A African = 0.05, American = 0.41, East Asian = 0.89, European = 0.39, South Asian = 0.15), the MAFs for the key genetic variants for clopidogrel (rs4244285 [ CYP2C19*2 ] African = 0.17, American = 0.11, East Asian = 0.31, European = 0.15, South Asian = 0.36; rs4986893 [ CYP2C19*3 ] East Asian = 0.06, South Asian = 0.01, Other ~ 0.00; and rs12248560 [ CYP2C19*17 ] African = 0.24, American = 0.12, East Asian = 0.02, European = 0.22, South Asian = 0.14) and statins (rs4149056 [ SLCO1B1*5 ] African = 0.01, American = 0.13, East Asian = 0.12, European = 0.16, South Asian = 0.04) also differ, 177 with clinical implications in terms of translating evidence from one population to another. As DGIs are a component of DDGIs, non-representative DGI evidence directly impacts the relevance of existing/future DDGIs in underserved populations.…”

A genome-wide association study of plasma concentrations of warfarin enantiomers and metabolites in sub-Saharan black-African patients

“…In exploratory work, we conducted the first warfarin pharmacokinetics-related GWAS in sub-Saharan Africans and identified novel SNPs that will require external replication and functional characterization before they can be considered for inclusion in warfarin dosing algorithms. There is increasing acceptance of the need to increase diversity in genomic studies including in pharmacogenomics (Sirugo et al, 2019;Asiimwe and Pirmohamed, 2022;Fatumo et al, 2022). This is especially true in relation to the inclusion of black African patients, who have not been well-represented in previous studies (Sirugo et al, 2019;Asiimwe and Pirmohamed, 2022;Fatumo et al, 2022).…”

“…There is increasing acceptance of the need to increase diversity in genomic studies including in pharmacogenomics (Sirugo et al, 2019;Asiimwe and Pirmohamed, 2022;Fatumo et al, 2022). This is especially true in relation to the inclusion of black African patients, who have not been well-represented in previous studies (Sirugo et al, 2019;Asiimwe and Pirmohamed, 2022;Fatumo et al, 2022). Pharmacogenomic studies in sub-Saharan Africa have been hampered for several reasons: lack of critical mass of researchers in Africa interested in pharmacogenomics; lack of suitable funding; difficulties in recruiting patients because of the lack of infrastructure, which is especially important in pharmacogenomics, where there is often a need for deep phenotyping; and the huge genetic diversity in the African population which therefore requires large sample sizes (Tishkoff et al, 2009;Teo et al, 2010).…”