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Novel variants of major drug-metabolising enzyme genes in diverse African populations and their predicted functional effects.

ABSTRACT: Pharmacogenetics enables personalised therapy based on genetic profiling and is increasingly applied in drug discovery. Medicines are developed and used together with pharmacodiagnostic tools to achieve desired drug efficacy and safety margins. Genetic polymorphism of drug-metabolising enzymes such as cytochrome P450s (CYPs) and N-acetyltransferases (NATs) has been widely studied in Caucasian and Asian populations, yet studies on African variants have been less extensive. The aim of the present study was to search for novel variants of CYP2C9 , CYP2C19 , CYP2D6 and NAT2 genes in Africans, with a particular focus on their prevalence in different populations, their relevance to enzyme functionality and their potential for personalised therapy. Blood samples from various ethnic groups were obtained from the AiBST Biobank of African Populations. The nine exons and exon-intron junctions of the CYP genes and exon 2 of NAT2 were analysed by direct DNA sequencing. Computational tools were used for the identification, haplotype analysis and prediction of functional effects of novel single nucleotide polymorphisms (SNPs). Novel SNPs were discovered in all four genes, grouped to existing haplotypes or assigned new allele names, if possible. The functional effects of non-synonymous SNPs were predicted and known African-specific variants were confirmed, but no significant differences were found in the frequencies of SNPs between African ethnicities. The low prevalence of our novel variants and most known functional alleles is consistent with the generally high level of diversity in gene loci of African populations. This indicates that profiles of rare variants reflecting interindividual variability might become the most relevant pharmacodiagnostic tools explaining Africans' diversity in drug response.

SUBMITTER: Matimba A

PROVIDER: S-EPMC3525272 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

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Novel variants of major drug-metabolising enzyme genes in diverse African populations and their predicted functional effects.

Matimba Alice A Del-Favero Jurgen J Van Broeckhoven Christine C Masimirembwa Collen C

Human genomics 20090101 2

Pharmacogenetics enables personalised therapy based on genetic profiling and is increasingly applied in drug discovery. Medicines are developed and used together with pharmacodiagnostic tools to achieve desired drug efficacy and safety margins. Genetic polymorphism of drug-metabolising enzymes such as cytochrome P450s (CYPs) and N-acetyltransferases (NATs) has been widely studied in Caucasian and Asian populations, yet studies on African variants have been less extensive. The aim of the present ...[more]

PMID: 19164093

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Project description:With the advent of the post genomic era, the research for the genetic mechanism of the diseases has found to be increasingly depended on the studies of the genes, the gene-networks and gene-protein interaction networks. To explore gene expression and regulation, the researchers have carried out many studies on transcription factors and their binding sites (TFBSs). Based on the large amount of transcription factor binding sites predicting values in the deep learning models, further computation and analysis have been done to reveal the relationship between the gene mutation and the occurrence of the disease. It has been demonstrated that based on the deep learning methods, the performances of the prediction for the functions of the noncoding variants are outperforming than those of the conventional methods. The research on the prediction for functions of Single Nucleotide Polymorphisms (SNPs) is expected to uncover the mechanism of the gene mutation affection on traits and diseases of human beings.We reviewed the conventional TFBSs identification methods from different perspectives. As for the deep learning methods to predict the TFBSs, we discussed the related problems, such as the raw data preprocessing, the structure design of the deep convolution neural network (CNN) and the model performance measure et al. And then we summarized the techniques that usually used in finding out the functional noncoding variants from de novo sequence.Along with the rapid development of the high-throughout assays, more and more sample data and chromatin features would be conducive to improve the prediction accuracy of the deep convolution neural network for TFBSs identification. Meanwhile, getting more insights into the deep CNN framework itself has been proved useful for both the promotion on model performance and the development for more suitable design to sample data. Based on the feature values predicted by the deep CNN model, the prioritization model for functional noncoding variants would contribute to reveal the affection of gene mutation on the diseases.

Project description:Aims/hypothesisWe examined the contribution of rare HNF1A variants to type 2 diabetes risk and age of diagnosis, and the extent to which their impact is affected by overall genetic susceptibility, across three ancestry groups.MethodsUsing exome sequencing data of 160,615 individuals of the UK Biobank and 18,797 individuals of the BioMe Biobank, we identified 746 carriers of rare functional HNF1A variants (minor allele frequency ≤1%), of which 507 carry variants in the functional domains. We calculated polygenic risk scores (PRSs) based on genome-wide association study summary statistics for type 2 diabetes, and examined the association of HNF1A variants and PRS with risk of type 2 diabetes and age of diagnosis. We also tested whether the PRS affects the association between HNF1A variants and type 2 diabetes risk by including an interaction term.ResultsRare HNF1A variants that are predicted to impair protein function are associated with increased risk of type 2 diabetes in individuals of European ancestry (OR 1.46, p=0.049), particularly when the variants are located in the functional domains (OR 1.89, p=0.002). No association was observed for individuals of African ancestry (OR 1.10, p=0.60) or Hispanic-Latino ancestry (OR 1.00, p=1.00). Rare functional HNF1A variants were associated with an earlier age at diagnosis in the Hispanic-Latino population (β=-5.0 years, p=0.03), and this association was marginally more pronounced for variants in the functional domains (β=-5.59 years, p=0.03). No associations were observed for other ancestries (African ancestry β=-2.7 years, p=0.13; European ancestry β=-3.5 years, p=0.20). A higher PRS was associated with increased odds of type 2 diabetes in all ancestries (OR 1.61-2.11, p<10-5) and an earlier age at diagnosis in individuals of African ancestry (β=-1.4 years, p=3.7 × 10-6) and Hispanic-Latino ancestry (β=-2.4 years, p<2 × 10-16). Furthermore, a higher PRS exacerbated the effect of the functional HNF1A variants on type 2 diabetes in the European ancestry population (pinteraction=0.037).Conclusions/interpretationWe show that rare functional HNF1A variants, in particular those located in the functional domains, increase the risk of type 2 diabetes, at least among individuals of European ancestry. Their effect is even more pronounced in individuals with a high polygenic susceptibility. Our analyses highlight the importance of the location of functional variants within a gene and an individual's overall polygenic susceptibility, and emphasise the need for more genetic data in non-European populations.

Dataset Information

Novel variants of major drug-metabolising enzyme genes in diverse African populations and their predicted functional effects.

Publications

Novel variants of major drug-metabolising enzyme genes in diverse African populations and their predicted functional effects.

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