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

被引:4
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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共 55 条
  • [1] Variation in 100 relevant pharmacogenes among emiratis with insights from understudied populations
    Al-Mahayri, Zeina N.
    Patrinos, George P.
    Wattanapokayakit, Sukanya
    Iemwimangsa, Nareenart
    Fukunaga, Koya
    Mushiroda, Taisei
    Chantratita, Wasun
    Ali, Bassam R.
    [J]. SCIENTIFIC REPORTS, 2020, 10 (01)
  • [2] A global reference for human genetic variation
    Altshuler, David M.
    Durbin, Richard M.
    Abecasis, Goncalo R.
    Bentley, David R.
    Chakravarti, Aravinda
    Clark, Andrew G.
    Donnelly, Peter
    Eichler, Evan E.
    Flicek, Paul
    Gabriel, Stacey B.
    Gibbs, Richard A.
    Green, Eric D.
    Hurles, Matthew E.
    Knoppers, Bartha M.
    Korbel, Jan O.
    Lander, Eric S.
    Lee, Charles
    Lehrach, Hans
    Mardis, Elaine R.
    Marth, Gabor T.
    McVean, Gil A.
    Nickerson, Deborah A.
    Wang, Jun
    Wilson, Richard K.
    Boerwinkle, Eric
    Doddapaneni, Harsha
    Han, Yi
    Korchina, Viktoriya
    Kovar, Christie
    Lee, Sandra
    Muzny, Donna
    Reid, Jeffrey G.
    Zhu, Yiming
    Chang, Yuqi
    Feng, Qiang
    Fang, Xiaodong
    Guo, Xiaosen
    Jian, Min
    Jiang, Hui
    Jin, Xin
    Lan, Tianming
    Li, Guoqing
    Li, Jingxiang
    Li, Yingrui
    Liu, Shengmao
    Liu, Xiao
    Lu, Yao
    Ma, Xuedi
    Tang, Meifang
    Wang, Bo
    [J]. NATURE, 2015, 526 (7571) : 68 - +
  • [3] PharmGKB summary: very important pharmacogene information for cytochrome P450, family 2, subfamily C, polypeptide 8
    Aquilante, Christina L.
    Niemi, Mikko
    Gong, Li
    Altman, Russ B.
    Klein, Teri E.
    [J]. PHARMACOGENETICS AND GENOMICS, 2013, 23 (12) : 721 - 728
  • [4] PharmGKB: A worldwide resource for pharmacogenomic information
    Barbarino, Julia M.
    Whirl-Carrillo, Michelle
    Altman, Russ B.
    Klein, Teri E.
    [J]. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE, 2018, 10 (04)
  • [5] Global distribution of CYP2C19 risk phenotypes affecting safety and effectiveness of medications
    Biswas, Mohitosh
    [J]. PHARMACOGENOMICS JOURNAL, 2021, 21 (02) : 190 - 199
  • [6] PharmVar GeneFocus: CYP2C19
    Botton, Mariana R.
    Whirl-Carrillo, Michelle
    Del Tredici, Andria L.
    Sangkuhl, Katrin
    Cavallari, Larisa H.
    Agundez, Jose A. G.
    Duconge, Jorge
    Lee, Ming Ta Michael
    Woodahl, Erica L.
    Claudio-Campos, Karla
    Daly, Ann K.
    Klein, Teri E.
    Pratt, Victoria M.
    Scott, Stuart A.
    Gaedigk, Andrea
    [J]. CLINICAL PHARMACOLOGY & THERAPEUTICS, 2021, 109 (02) : 352 - 366
  • [7] The effect of pharmacogenetic profiling with a clinical decision support tool on healthcare resource utilization and estimated costs in the elderly exposed to polypharmacy
    Brixner, D.
    Biltaji, E.
    Bress, A.
    Unni, S.
    Ye, X.
    Mamiya, T.
    Ashcraft, K.
    Biskupiak, J.
    [J]. JOURNAL OF MEDICAL ECONOMICS, 2016, 19 (03) : 213 - 228
  • [8] A One-Penny Imputed Genome from Next-Generation Reference Panels
    Browning, Brian L.
    Zhou, Ying
    Browning, Sharon R.
    [J]. AMERICAN JOURNAL OF HUMAN GENETICS, 2018, 103 (03) : 338 - 348
  • [9] Potential of whole-genome sequencing-based pharmacogenetic profiling
    Caspar, Sylvan Manuel
    Schneider, Timo
    Stoll, Patricia
    Meienberg, Janine
    Matyas, Gabor
    [J]. PHARMACOGENOMICS, 2021, 22 (03) : 177 - 190
  • [10] Standardizing CYP2D6 Genotype to Phenotype Translation: Consensus Recommendations from the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group
    Caudle, Kelly E.
    Sangkuhl, Katrin
    Whirl-Carrillo, Michelle
    Swen, Jesse J.
    Haidar, Cyrine E.
    Klein, Teri E.
    Gammal, Roseann S.
    Relling, Mary, V
    Scott, Stuart A.
    Hertz, Daniel L.
    Guchelaar, Henk-Jan
    Gaedigk, Andrea
    [J]. CTS-CLINICAL AND TRANSLATIONAL SCIENCE, 2020, 13 (01): : 116 - 124