Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Bertholim-Nasciben L

PROVIDER: S-EPMC10206227 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Bertholim-Nasciben Luciana L Scliar Marilia O MO Debortoli Guilherme G Thiruvahindrapuram Bhooma B Scherer Stephen W SW Duarte Yeda A O YAO Zatz Mayana M Suarez-Kurtz Guilherme G Parra Esteban J EJ Naslavsky Michel S MS

Frontiers in pharmacology 20230510

<b>Introduction:</b> 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 ...[more]

PMID: 37234706

Similar Datasets

Project description:Genetic generalized epilepsies (GGEs) include well-established epilepsy syndromes with generalized onset seizures: childhood absence epilepsy, juvenile myoclonic epilepsy (JME), juvenile absence epilepsy (JAE), myoclonic absence epilepsy, epilepsy with eyelid myoclonia (Jeavons syndrome), generalized tonic-clonic seizures, and generalized tonic-clonic seizures alone. Genome-wide association studies (GWASs) and exome sequencing have identified 48 single-nucleotide polymorphisms (SNPs) associated with GGE. However, these studies were mainly based on non-admixed, European, and Asian populations. Thus, it remains unclear whether these results apply to patients of other origins. This study aims to evaluate whether these previous results could be replicated in a cohort of admixed Brazilian patients with GGE. We obtained SNP-array data from 87 patients with GGE, compared with 340 controls from the BIPMed public dataset. We could directly access genotypes of 17 candidate SNPs, available in the SNP array, and the remaining 31 SNPs were imputed using the BEAGLE v5.1 software. We performed an association test by logistic regression analysis, including the first five principal components as covariates. Furthermore, to expand the analysis of the candidate regions, we also interrogated 14,047 SNPs that flank the candidate SNPs (1 Mb). The statistical power was evaluated in terms of odds ratio and minor allele frequency (MAF) by the genpwr package. Differences in SNP frequencies between Brazilian and Europeans, sub-Saharan African, and Native Americans were evaluated by a two-proportion Z-test. We identified nine flanking SNPs, located on eight candidate regions, which presented association signals that passed the Bonferroni correction (rs12726617; rs9428842; rs1915992; rs1464634; rs6459526; rs2510087; rs9551042; rs9888879; and rs8133217; p-values <3.55e-06). In addition, the two-proportion Z-test indicates that the lack of association of the remaining candidate SNPs could be due to different genomic backgrounds observed in admixed Brazilians. This is the first time that candidate SNPs for GGE are analyzed in an admixed Brazilian population, and we could successfully replicate the association signals in eight candidate regions. In addition, our results provide new insights on how we can account for population structure to improve risk stratification estimation in admixed individuals.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets