Characterization of pharmacogenomic variants in a Brazilian admixed cohort of elderly individuals based on whole-genome sequencing data

被引:3
|
作者
Bertholim-Nasciben, Luciana [1 ,2 ]
Scliar, Marilia O. [2 ]
Debortoli, Guilherme [3 ]
Thiruvahindrapuram, Bhooma [4 ]
Scherer, Stephen W. [4 ,5 ]
Duarte, Yeda A. O. [6 ]
Zatz, Mayana [2 ,7 ]
Suarez-Kurtz, Guilherme [8 ]
Parra, Esteban J. [3 ]
Naslavsky, Michel S. [2 ,7 ,9 ]
机构
[1] Univ Sao Paulo, Sch Publ Hlth, Sao Paulo, SP, Brazil
[2] Univ Sao Paulo, Human Genome & Stem Cell Res Ctr, Sao Paulo, Brazil
[3] Univ Toronto Mississauga, Dept Anthropol, Mississauga, ON, Canada
[4] Hosp Sick Children, Ctr Appl Genom, Toronto, ON, Canada
[5] Univ Toronto, Fac Med, Dept Mol Genet, Toronto, ON, Canada
[6] Univ Sao Paulo, Sch Nursing, Med Surg Nursing Dept, Sao Paulo, Brazil
[7] Univ Sao Paulo, Biosci Inst, Dept Genet & Evolut Biol, Sao Paulo, SP, Brazil
[8] Inst Nacl Canc, Div Pesquisa Clin & Desenvolvimento Tecnol, Rio De Janeiro, Brazil
[9] Hosp Israelita Albert Einstein, Sao Paulo, Brazil
基金
巴西圣保罗研究基金会;
关键词
pharmacogenomics; admixture; population cohort; whole-genome sequencing; PharmGKB; CPIC guidelines; IMPLEMENTATION CONSORTIUM; STRUCTURAL VARIATION; DIVERSITY;
D O I
10.3389/fphar.2023.1178715
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Introduction: Research in the field of pharmacogenomics (PGx) aims to identify genetic variants that modulate response to drugs, through alterations in their pharmacokinetics (PK) or pharmacodynamics (PD). The distribution of PGx variants differs considerably among populations, and whole-genome sequencing (WGS) plays a major role as a comprehensive approach to detect both common and rare variants. This study evaluated the frequency of PGx markers in the context of the Brazilian population, using data from a population-based admixed cohort from Sao Paulo, Brazil, which includes variants from WGS of 1,171 unrelated, elderly individuals.Methods: The Stargazer tool was used to call star alleles and structural variants (SVs) from 38 pharmacogenes. Clinically relevant variants were investigated, and the predicted drug response phenotype was analyzed in combination with the medication record to assess individuals potentially at high-risk of gene-drug interaction.Results: In total, 352 unique star alleles or haplotypes were observed, of which 255 and 199 had a frequency < 0.05 and < 0.01, respectively. For star alleles with frequency > 5% (n = 97), decreased, loss-of-function and unknown function accounted for 13.4%, 8.2% and 27.8% of alleles or haplotypes, respectively. Structural variants (SVs) were identified in 35 genes for at least one individual, and occurred with frequencies >5% for CYP2D6, CYP2A6, GSTM1, and UGT2B17. Overall 98.0% of the individuals carried at least one high risk genotype-predicted phenotype in pharmacogenes with PharmGKB level of evidence 1A for drug interaction. The Electronic Health Record (EHR) Priority Result Notation and the cohort medication registry were combined to assess high-risk gene-drug interactions. In general, 42.0% of the cohort used at least one PharmGKB evidence level 1A drug, and 18.9% of individuals who used PharmGKB evidence level 1A drugs had a genotype-predicted phenotype of high-risk gene-drug interaction.Conclusion: This study described the applicability of next-generation sequencing (NGS) techniques for translating PGx variants into clinically relevant phenotypes on a large scale in the Brazilian population and explores the feasibility of systematic adoption of PGx testing in Brazil.
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页数:11
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