Pub Date : 2022-09-06DOI: 10.1038/s41397-022-00288-2
Yitian Zhou, Volker M. Lauschke
Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.
{"title":"The genetic landscape of major drug metabolizing cytochrome P450 genes—an updated analysis of population-scale sequencing data","authors":"Yitian Zhou, Volker M. Lauschke","doi":"10.1038/s41397-022-00288-2","DOIUrl":"10.1038/s41397-022-00288-2","url":null,"abstract":"Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 5-6","pages":"284-293"},"PeriodicalIF":2.8,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674520/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40354369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-13DOI: 10.1038/s41397-022-00286-4
Alireza Tafazoli, Maaike van der Lee, Jesse J. Swen, Anna Zeller, Natalia Wawrusiewicz-Kurylonek, Hailiang Mei, Ruben H. P. Vorderman, Krzysztof Konopko, Andrzej Zankiewicz, Wojciech Miltyk
This pilot study is aimed at implementing an approach for comprehensive clinical pharmacogenomics (PGx) profiling. Fifty patients with cardiovascular diseases and 50 healthy individuals underwent whole-exome sequencing. Data on 1800 PGx genes were extracted and analyzed through deep filtration separately. Theoretical drug induced phenoconversion was assessed for the patients, using sequence2script. In total, 4539 rare variants (including 115 damaging non-synonymous) were identified. Four publicly available PGx bioinformatics algorithms to assign PGx haplotypes were applied to nine selected very important pharmacogenes (VIP) and revealed a 45–70% concordance rate. To ensure availability of the results at point-of-care, actionable variants were stored in a web-hosted database and PGx-cards were developed for quick access and handed to the study subjects. While a comprehensive clinical PGx profile could be successfully extracted from WES data, available tools to interpret these data demonstrated inconsistencies that complicate clinical application.
{"title":"Development of an extensive workflow for comprehensive clinical pharmacogenomic profiling: lessons from a pilot study on 100 whole exome sequencing data","authors":"Alireza Tafazoli, Maaike van der Lee, Jesse J. Swen, Anna Zeller, Natalia Wawrusiewicz-Kurylonek, Hailiang Mei, Ruben H. P. Vorderman, Krzysztof Konopko, Andrzej Zankiewicz, Wojciech Miltyk","doi":"10.1038/s41397-022-00286-4","DOIUrl":"10.1038/s41397-022-00286-4","url":null,"abstract":"This pilot study is aimed at implementing an approach for comprehensive clinical pharmacogenomics (PGx) profiling. Fifty patients with cardiovascular diseases and 50 healthy individuals underwent whole-exome sequencing. Data on 1800 PGx genes were extracted and analyzed through deep filtration separately. Theoretical drug induced phenoconversion was assessed for the patients, using sequence2script. In total, 4539 rare variants (including 115 damaging non-synonymous) were identified. Four publicly available PGx bioinformatics algorithms to assign PGx haplotypes were applied to nine selected very important pharmacogenes (VIP) and revealed a 45–70% concordance rate. To ensure availability of the results at point-of-care, actionable variants were stored in a web-hosted database and PGx-cards were developed for quick access and handed to the study subjects. While a comprehensive clinical PGx profile could be successfully extracted from WES data, available tools to interpret these data demonstrated inconsistencies that complicate clinical application.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 5-6","pages":"276-283"},"PeriodicalIF":2.8,"publicationDate":"2022-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674517/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40720493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-22DOI: 10.1038/s41397-022-00285-5
F. Albalwy, J. H. McDermott, W. G. Newman, A. Brass, A. Davies
The successful implementation of pharmacogenetics (PGx) into clinical practice requires patient genomic data to be shared between stakeholders in multiple settings. This creates a number of barriers to widespread adoption of PGx, including privacy concerns related to the storage and movement of identifiable genomic data. Informatic solutions that support secure and equitable data access for genomic data are therefore important to PGx. Here we propose a methodology that uses smart contracts implemented on a blockchain-based framework, PGxChain, to address this issue. The design requirements for PGxChain were identified through a systematic literature review, identifying technical challenges and barriers impeding the clinical implementation of pharmacogenomics. These requirements included security and privacy, accessibility, interoperability, traceability and legal compliance. A proof-of-concept implementation based on Ethereum was then developed that met the design requirements. PGxChain’s performance was examined using Hyperledger Caliper for latency, throughput, and transaction success rate. The findings clearly indicate that blockchain technology offers considerable potential to advance pharmacogenetic data sharing, particularly with regard to PGx data security and privacy, large-scale accessibility of PGx data, PGx data interoperability between multiple health care providers and compliance with data-sharing laws and regulations.
{"title":"A blockchain-based framework to support pharmacogenetic data sharing","authors":"F. Albalwy, J. H. McDermott, W. G. Newman, A. Brass, A. Davies","doi":"10.1038/s41397-022-00285-5","DOIUrl":"10.1038/s41397-022-00285-5","url":null,"abstract":"The successful implementation of pharmacogenetics (PGx) into clinical practice requires patient genomic data to be shared between stakeholders in multiple settings. This creates a number of barriers to widespread adoption of PGx, including privacy concerns related to the storage and movement of identifiable genomic data. Informatic solutions that support secure and equitable data access for genomic data are therefore important to PGx. Here we propose a methodology that uses smart contracts implemented on a blockchain-based framework, PGxChain, to address this issue. The design requirements for PGxChain were identified through a systematic literature review, identifying technical challenges and barriers impeding the clinical implementation of pharmacogenomics. These requirements included security and privacy, accessibility, interoperability, traceability and legal compliance. A proof-of-concept implementation based on Ethereum was then developed that met the design requirements. PGxChain’s performance was examined using Hyperledger Caliper for latency, throughput, and transaction success rate. The findings clearly indicate that blockchain technology offers considerable potential to advance pharmacogenetic data sharing, particularly with regard to PGx data security and privacy, large-scale accessibility of PGx data, PGx data interoperability between multiple health care providers and compliance with data-sharing laws and regulations.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 5-6","pages":"264-275"},"PeriodicalIF":2.8,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674519/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40639424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-02DOI: 10.1038/s41397-022-00284-6
Sigrid Haeggström, Magnus Ingelman-Sundberg, Svante Pääbo, Hugo Zeberg
Genetic variation in genes encoding cytochrome P450 enzymes influences the metabolism of drugs and endogenous compounds. The locus containing the cytochrome genes CYP2C8 and CYP2C9 on chromosome 10 exhibits linkage disequilibrium between the CYP2C8*3 and CYP2C9*2 alleles, forming a haplotype of ~300 kilobases. This haplotype is associated with altered metabolism of several drugs, most notably reduced metabolism of warfarin and phenytoin, leading to toxicity at otherwise therapeutic doses. Here we show that this haplotype is inherited from Neandertals.
{"title":"The clinically relevant CYP2C8*3 and CYP2C9*2 haplotype is inherited from Neandertals","authors":"Sigrid Haeggström, Magnus Ingelman-Sundberg, Svante Pääbo, Hugo Zeberg","doi":"10.1038/s41397-022-00284-6","DOIUrl":"10.1038/s41397-022-00284-6","url":null,"abstract":"Genetic variation in genes encoding cytochrome P450 enzymes influences the metabolism of drugs and endogenous compounds. The locus containing the cytochrome genes CYP2C8 and CYP2C9 on chromosome 10 exhibits linkage disequilibrium between the CYP2C8*3 and CYP2C9*2 alleles, forming a haplotype of ~300 kilobases. This haplotype is associated with altered metabolism of several drugs, most notably reduced metabolism of warfarin and phenytoin, leading to toxicity at otherwise therapeutic doses. Here we show that this haplotype is inherited from Neandertals.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 4","pages":"247-249"},"PeriodicalIF":2.8,"publicationDate":"2022-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363273/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40465859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-25DOI: 10.1038/s41397-022-00282-8
Hiroki Yamada, Rio Ohmori, Naoto Okada, Shingen Nakamura, Kumiko Kagawa, Shiro Fujii, Hirokazu Miki, Keisuke Ishizawa, Masahiro Abe, Youichi Sato
Vincristine treatment may cause peripheral neuropathy. In this study, we identified the genes associated with the development of peripheral neuropathy due to vincristine therapy using a genome-wide association study (GWAS) and constructed a predictive model for the development of peripheral neuropathy using genetic information-based machine learning. The study included 72 patients admitted to the Department of Hematology, Tokushima University Hospital, who received vincristine. Of these, 56 were genotyped using the Illumina Asian Screening Array-24 Kit, and a GWAS for the onset of peripheral neuropathy caused by vincristine was conducted. Using Sanger sequencing for 16 validation samples, the top three single nucleotide polymorphisms (SNPs) associated with the onset of peripheral neuropathy were determined. Machine learning was performed using the statistical software R package “caret”. The 56 GWAS and 16 validation samples were used as the training and test sets, respectively. Predictive models were constructed using random forest, support vector machine, naive Bayes, and neural network algorithms. According to the GWAS, rs2110179, rs7126100, and rs2076549 were associated with the development of peripheral neuropathy on vincristine administration. Machine learning was performed using these three SNPs to construct a prediction model. A high accuracy of 93.8% was obtained with the support vector machine and neural network using rs2110179 and rs2076549. Thus, peripheral neuropathy development due to vincristine therapy can be effectively predicted by a machine learning prediction model using SNPs associated with it.
{"title":"A machine learning model using SNPs obtained from a genome-wide association study predicts the onset of vincristine-induced peripheral neuropathy","authors":"Hiroki Yamada, Rio Ohmori, Naoto Okada, Shingen Nakamura, Kumiko Kagawa, Shiro Fujii, Hirokazu Miki, Keisuke Ishizawa, Masahiro Abe, Youichi Sato","doi":"10.1038/s41397-022-00282-8","DOIUrl":"10.1038/s41397-022-00282-8","url":null,"abstract":"Vincristine treatment may cause peripheral neuropathy. In this study, we identified the genes associated with the development of peripheral neuropathy due to vincristine therapy using a genome-wide association study (GWAS) and constructed a predictive model for the development of peripheral neuropathy using genetic information-based machine learning. The study included 72 patients admitted to the Department of Hematology, Tokushima University Hospital, who received vincristine. Of these, 56 were genotyped using the Illumina Asian Screening Array-24 Kit, and a GWAS for the onset of peripheral neuropathy caused by vincristine was conducted. Using Sanger sequencing for 16 validation samples, the top three single nucleotide polymorphisms (SNPs) associated with the onset of peripheral neuropathy were determined. Machine learning was performed using the statistical software R package “caret”. The 56 GWAS and 16 validation samples were used as the training and test sets, respectively. Predictive models were constructed using random forest, support vector machine, naive Bayes, and neural network algorithms. According to the GWAS, rs2110179, rs7126100, and rs2076549 were associated with the development of peripheral neuropathy on vincristine administration. Machine learning was performed using these three SNPs to construct a prediction model. A high accuracy of 93.8% was obtained with the support vector machine and neural network using rs2110179 and rs2076549. Thus, peripheral neuropathy development due to vincristine therapy can be effectively predicted by a machine learning prediction model using SNPs associated with it.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 4","pages":"241-246"},"PeriodicalIF":2.8,"publicationDate":"2022-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40398491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.1038/s41397-022-00283-7
Evangelia Eirini Tsermpini, Christina I. Kalogirou, George C. Kyriakopoulos, George P. Patrinos, Constantinos Stathopoulos
The heterogeneity of psychiatric disorders and the lack of reliable biomarkers for prediction and treatments follow-up pose difficulties towards recognition and understanding of the molecular basis of psychiatric diseases. However, several studies based on NGS approaches have shown that miRNAs could regulate gene expression during onset and disease progression and could serve as potential diagnostic and pharmacogenomics biomarkers during treatment. We provide herein a detailed overview of circulating miRNAs and their expression profiles as biomarkers in schizophrenia, bipolar disorder and major depressive disorder and their role in response to specific treatments. Bioinformatics analysis of miR-34a, miR-106, miR-134 and miR-132, which are common among SZ, BD and MDD patients, showed brain enrichment and involvement in the modulation of critical signaling pathways, which are often deregulated in psychiatric disorders. We propose that specific miRNAs support accurate diagnosis and effective precision treatment of psychiatric disorders.
{"title":"miRNAs as potential diagnostic biomarkers and pharmacogenomic indicators in psychiatric disorders","authors":"Evangelia Eirini Tsermpini, Christina I. Kalogirou, George C. Kyriakopoulos, George P. Patrinos, Constantinos Stathopoulos","doi":"10.1038/s41397-022-00283-7","DOIUrl":"10.1038/s41397-022-00283-7","url":null,"abstract":"The heterogeneity of psychiatric disorders and the lack of reliable biomarkers for prediction and treatments follow-up pose difficulties towards recognition and understanding of the molecular basis of psychiatric diseases. However, several studies based on NGS approaches have shown that miRNAs could regulate gene expression during onset and disease progression and could serve as potential diagnostic and pharmacogenomics biomarkers during treatment. We provide herein a detailed overview of circulating miRNAs and their expression profiles as biomarkers in schizophrenia, bipolar disorder and major depressive disorder and their role in response to specific treatments. Bioinformatics analysis of miR-34a, miR-106, miR-134 and miR-132, which are common among SZ, BD and MDD patients, showed brain enrichment and involvement in the modulation of critical signaling pathways, which are often deregulated in psychiatric disorders. We propose that specific miRNAs support accurate diagnosis and effective precision treatment of psychiatric disorders.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 4","pages":"211-222"},"PeriodicalIF":2.8,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40104450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-16DOI: 10.1038/s41397-022-00281-9
Farhana Islam, Daniel Hain, David Lewis, Rebecca Law, Lisa C. Brown, Julie-Anne Tanner, Daniel J. Müller
Although clozapine is the most effective pharmacotherapy for treatment-resistant schizophrenia, it is under-utilized, and initiation is often delayed. One reason is the occurrence of a potentially fatal adverse reaction, clozapine-induced agranulocytosis (CIA). Identifying genetic variations contributing to CIA would help predict patient risk of developing CIA and personalize treatment. Here, we (1) review existing pharmacogenomic studies of CIA, and (2) conduct meta-analyses to identify targets for clinical implementation. A systematic literature search identified studies that included individuals receiving clozapine who developed CIA and controls who did not. Results showed that individuals carrying the HLA-DRB1*04:02 allele had nearly sixfold (95% CI 2.20–15.80, pcorrected = 0.03) higher odds of CIA with a negative predictive value of 99.3%. Previously unreplicated alleles, TNFb5, HLA-B*59:01, TNFb4, and TNFd3 showed significant associations with CIA after multiple-testing corrections. Our findings suggest that a predictive HLA-DRB1*04:02-based pharmacogenomic test may be promising for clinical implementation but requires further investigation.
尽管氯氮平是治疗耐药性精神分裂症最有效的药物疗法，但它的使用率却很低，而且常常被推迟使用。其中一个原因是出现了一种可能致命的不良反应--氯氮平诱发的粒细胞减少症（CIA）。确定导致 CIA 的基因变异有助于预测患者罹患 CIA 的风险并进行个性化治疗。在此，我们（1）回顾了现有的 CIA 药物基因组学研究，（2）进行了荟萃分析，以确定临床实施的目标。通过系统性文献检索，我们找到了包括接受氯氮平治疗但出现 CIA 的患者和未出现 CIA 的对照组的研究。结果显示，携带HLA-DRB1*04:02等位基因的个体发生CIA的几率高出近6倍（95% CI 2.20-15.80, pcorrected = 0.03），阴性预测值为99.3%。之前未被复制的等位基因 TNFb5、HLA-B*59:01、TNFb4 和 TNFd3 在多重检验校正后显示与 CIA 有显著关联。我们的研究结果表明，基于 HLA-DRB1*04:02 的预测性药物基因组学检测可能有望在临床上应用，但还需要进一步研究。
{"title":"Pharmacogenomics of Clozapine-induced agranulocytosis: a systematic review and meta-analysis","authors":"Farhana Islam, Daniel Hain, David Lewis, Rebecca Law, Lisa C. Brown, Julie-Anne Tanner, Daniel J. Müller","doi":"10.1038/s41397-022-00281-9","DOIUrl":"10.1038/s41397-022-00281-9","url":null,"abstract":"Although clozapine is the most effective pharmacotherapy for treatment-resistant schizophrenia, it is under-utilized, and initiation is often delayed. One reason is the occurrence of a potentially fatal adverse reaction, clozapine-induced agranulocytosis (CIA). Identifying genetic variations contributing to CIA would help predict patient risk of developing CIA and personalize treatment. Here, we (1) review existing pharmacogenomic studies of CIA, and (2) conduct meta-analyses to identify targets for clinical implementation. A systematic literature search identified studies that included individuals receiving clozapine who developed CIA and controls who did not. Results showed that individuals carrying the HLA-DRB1*04:02 allele had nearly sixfold (95% CI 2.20–15.80, pcorrected = 0.03) higher odds of CIA with a negative predictive value of 99.3%. Previously unreplicated alleles, TNFb5, HLA-B*59:01, TNFb4, and TNFd3 showed significant associations with CIA after multiple-testing corrections. Our findings suggest that a predictive HLA-DRB1*04:02-based pharmacogenomic test may be promising for clinical implementation but requires further investigation.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 4","pages":"230-240"},"PeriodicalIF":2.8,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41397-022-00281-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41484995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-19DOI: 10.1038/s41397-022-00280-w
Simon Verdez, Quentin Thomas, Philippine Garret, Céline Verstuyft, Emilie Tisserant, Antonio Vitobello, Frédéric Tran Mau-Them, Christophe Philippe, Marc Bardou, Maxime Luu, Abderrahmane Bourredjem, Patrick Callier, Christel Thauvin-Robinet, Nicolas Picard, Laurence Faivre, Yannis Duffourd
Beyond the identification of causal genetic variants in the diagnosis of Mendelian disorders, exome sequencing can detect numerous variants with potential relevance for clinical care. Clinical interventions can thus be conducted to improve future health outcomes for patients and their at-risk relatives, such as predicting late-onset genetic disorders accessible to prevention, treatment or identifying differential drug efficacy and safety. To evaluate the interest of such pharmacogenetic information, we designed an “in house” pipeline to determine the status of 122 PharmGKB (Pharmacogenomics Knowledgebase) variant-drug combinations in 31 genes. This pipeline was applied to a cohort of 90 epileptic patients who had previously an exome sequencing (ES) analysis, to determine the frequency of pharmacogenetic variants. We performed a retrospective analysis of drug plasma concentrations and treatment efficacy in patients bearing at least one relevant PharmGKB variant. For PharmGKB level 1A variants, CYP2C9 status for phenytoin prescription was the only relevant information. Nineteen patients were treated with phenytoin, among phenytoin-treated patients, none were poor metabolizers and four were intermediate metabolizers. While being treated with a standard protocol (10–23 mg/kg/30 min loading dose followed by 5 mg/kg/8 h maintenance dose), all identified intermediate metabolizers had toxic plasma concentrations (20 mg/L). In epileptic patients, pangenomic sequencing can provide information about common pharmacogenetic variants likely to be useful to guide therapeutic drug monitoring, and in the case of phenytoin, to prevent clinical toxicity caused by high plasma levels.
{"title":"Exome sequencing allows detection of relevant pharmacogenetic variants in epileptic patients","authors":"Simon Verdez, Quentin Thomas, Philippine Garret, Céline Verstuyft, Emilie Tisserant, Antonio Vitobello, Frédéric Tran Mau-Them, Christophe Philippe, Marc Bardou, Maxime Luu, Abderrahmane Bourredjem, Patrick Callier, Christel Thauvin-Robinet, Nicolas Picard, Laurence Faivre, Yannis Duffourd","doi":"10.1038/s41397-022-00280-w","DOIUrl":"10.1038/s41397-022-00280-w","url":null,"abstract":"Beyond the identification of causal genetic variants in the diagnosis of Mendelian disorders, exome sequencing can detect numerous variants with potential relevance for clinical care. Clinical interventions can thus be conducted to improve future health outcomes for patients and their at-risk relatives, such as predicting late-onset genetic disorders accessible to prevention, treatment or identifying differential drug efficacy and safety. To evaluate the interest of such pharmacogenetic information, we designed an “in house” pipeline to determine the status of 122 PharmGKB (Pharmacogenomics Knowledgebase) variant-drug combinations in 31 genes. This pipeline was applied to a cohort of 90 epileptic patients who had previously an exome sequencing (ES) analysis, to determine the frequency of pharmacogenetic variants. We performed a retrospective analysis of drug plasma concentrations and treatment efficacy in patients bearing at least one relevant PharmGKB variant. For PharmGKB level 1A variants, CYP2C9 status for phenytoin prescription was the only relevant information. Nineteen patients were treated with phenytoin, among phenytoin-treated patients, none were poor metabolizers and four were intermediate metabolizers. While being treated with a standard protocol (10–23 mg/kg/30 min loading dose followed by 5 mg/kg/8 h maintenance dose), all identified intermediate metabolizers had toxic plasma concentrations (20 mg/L). In epileptic patients, pangenomic sequencing can provide information about common pharmacogenetic variants likely to be useful to guide therapeutic drug monitoring, and in the case of phenytoin, to prevent clinical toxicity caused by high plasma levels.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 5-6","pages":"258-263"},"PeriodicalIF":2.8,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43150187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-28DOI: 10.1038/s41397-022-00279-3
Julia C. F. Quintanilha, Susan Geyer, Amy S. Etheridge, Alessandro Racioppi, Kelli Hammond, Daniel J. Crona, Carol E. Peña, Sawyer B. Jacobson, Federica Marmorino, Daniele Rossini, Chiara Cremolini, Hanna K. Sanoff, Ghassan K. Abou-Alfa, Federico Innocenti
No biomarkers are available to predict toxicities induced by VEGFR TKIs. This study aimed to identify markers of toxicities induced by these drugs using a discovery-validation approach. The discovery set included 140 sorafenib-treated cancer patients (TARGET study) genotyped for SNPs in 56 genes. The most significant SNPs associated with grade ≥2 hypertension, diarrhea, dermatologic toxicities, and composite toxicity (any one of the toxicities) were tested for association with grade ≥2 toxicity in a validation set of 201 sorafenib-treated patients (Alliance/CALGB 80802). The validated SNP was tested for association with grade ≥2 toxicity in 107 (LCCC 1029) and 82 (Italian cohort) regorafenib-treated patients. SNP-toxicity associations were evaluated using logistic regression, and a meta-analysis between the studies was performed by inverse variance. Variant rs4864950 in KDR increased the risk of grade ≥2 composite toxicity in TARGET, Alliance/CALGB 80802, and the Italian cohort (meta-analysis p = 6.79 × 10−4, OR = 2.01, 95% CI 1.34–3.01). We identified a predictor of toxicities induced by VEGFR TKIs. NCT00073307 (TARGET), NCT01015833 (Alliance/CALGB 80802), and NCT01298570 (LCCC 1029).
{"title":"KDR genetic predictor of toxicities induced by sorafenib and regorafenib","authors":"Julia C. F. Quintanilha, Susan Geyer, Amy S. Etheridge, Alessandro Racioppi, Kelli Hammond, Daniel J. Crona, Carol E. Peña, Sawyer B. Jacobson, Federica Marmorino, Daniele Rossini, Chiara Cremolini, Hanna K. Sanoff, Ghassan K. Abou-Alfa, Federico Innocenti","doi":"10.1038/s41397-022-00279-3","DOIUrl":"10.1038/s41397-022-00279-3","url":null,"abstract":"No biomarkers are available to predict toxicities induced by VEGFR TKIs. This study aimed to identify markers of toxicities induced by these drugs using a discovery-validation approach. The discovery set included 140 sorafenib-treated cancer patients (TARGET study) genotyped for SNPs in 56 genes. The most significant SNPs associated with grade ≥2 hypertension, diarrhea, dermatologic toxicities, and composite toxicity (any one of the toxicities) were tested for association with grade ≥2 toxicity in a validation set of 201 sorafenib-treated patients (Alliance/CALGB 80802). The validated SNP was tested for association with grade ≥2 toxicity in 107 (LCCC 1029) and 82 (Italian cohort) regorafenib-treated patients. SNP-toxicity associations were evaluated using logistic regression, and a meta-analysis between the studies was performed by inverse variance. Variant rs4864950 in KDR increased the risk of grade ≥2 composite toxicity in TARGET, Alliance/CALGB 80802, and the Italian cohort (meta-analysis p = 6.79 × 10−4, OR = 2.01, 95% CI 1.34–3.01). We identified a predictor of toxicities induced by VEGFR TKIs. NCT00073307 (TARGET), NCT01015833 (Alliance/CALGB 80802), and NCT01298570 (LCCC 1029).","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 5-6","pages":"251-257"},"PeriodicalIF":2.8,"publicationDate":"2022-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9556853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-23DOI: 10.1038/s41397-022-00271-x
Ankita Narang, Paul Lacaze, Kathlyn J. Ronaldson, John J. McNeil, Mahesh Jayaram, Naveen Thomas, Rory Sellmer, David N. Crockford, Robert Stowe, Steven C. Greenway, Christos Pantelis, Chad A. Bousman
One of the concerns limiting the use of clozapine in schizophrenia treatment is the risk of rare but potentially fatal myocarditis. Our previous genome-wide association study and human leucocyte antigen analyses identified putative loci associated with clozapine-induced myocarditis. However, the contribution of DNA variation in cytochrome P450 genes, copy number variants and rare deleterious variants have not been investigated. We explored these unexplored classes of DNA variation using whole-genome sequencing data from 25 cases with clozapine-induced myocarditis and 25 demographically-matched clozapine-tolerant control subjects. We identified 15 genes based on rare variant gene-burden analysis (MLLT6, CADPS, TACC2, L3MBTL4, NPY, SLC25A21, PARVB, GPR179, ACAD9, NOL8, C5orf33, FAM127A, AFDN, SLC6A11, PXDN) nominally associated (p < 0.05) with clozapine-induced myocarditis. Of these genes, 13 were expressed in human myocardial tissue. Although independent replication of these findings is required, our study provides preliminary insights into the potential role of rare genetic variants in susceptibility to clozapine-induced myocarditis.
在精神分裂症治疗中使用氯氮平的一个限制因素是罕见但可能致命的心肌炎风险。我们之前的全基因组关联研究和人类白细胞抗原分析确定了与氯氮平诱发心肌炎相关的假定位点。然而，细胞色素 P450 基因的 DNA 变异、拷贝数变异和罕见的有害变异的贡献尚未得到研究。我们利用 25 例氯氮平诱发的心肌炎病例和 25 例人口统计学上匹配的氯氮平耐受性对照组的全基因组测序数据，探索了这些尚未探索的 DNA 变异类别。根据罕见变异基因负担分析，我们确定了 15 个基因（MLLT6、CADPS、TACC2、L3MBTL4、NPY、SLC25A21、PARVB、GPR179、ACAD9、NOL8、C5orf33、FAM127A、AFDN、SLC6A11、PXDN）与氯氮平诱发的心肌炎存在名义相关性（p < 0.05）。这些基因中有 13 个在人类心肌组织中表达。尽管这些发现还需要独立的验证，但我们的研究提供了关于罕见基因变异在氯氮平诱发的心肌炎易感性中潜在作用的初步见解。
{"title":"Whole-genome sequencing analysis of clozapine-induced myocarditis","authors":"Ankita Narang, Paul Lacaze, Kathlyn J. Ronaldson, John J. McNeil, Mahesh Jayaram, Naveen Thomas, Rory Sellmer, David N. Crockford, Robert Stowe, Steven C. Greenway, Christos Pantelis, Chad A. Bousman","doi":"10.1038/s41397-022-00271-x","DOIUrl":"10.1038/s41397-022-00271-x","url":null,"abstract":"One of the concerns limiting the use of clozapine in schizophrenia treatment is the risk of rare but potentially fatal myocarditis. Our previous genome-wide association study and human leucocyte antigen analyses identified putative loci associated with clozapine-induced myocarditis. However, the contribution of DNA variation in cytochrome P450 genes, copy number variants and rare deleterious variants have not been investigated. We explored these unexplored classes of DNA variation using whole-genome sequencing data from 25 cases with clozapine-induced myocarditis and 25 demographically-matched clozapine-tolerant control subjects. We identified 15 genes based on rare variant gene-burden analysis (MLLT6, CADPS, TACC2, L3MBTL4, NPY, SLC25A21, PARVB, GPR179, ACAD9, NOL8, C5orf33, FAM127A, AFDN, SLC6A11, PXDN) nominally associated (p < 0.05) with clozapine-induced myocarditis. Of these genes, 13 were expressed in human myocardial tissue. Although independent replication of these findings is required, our study provides preliminary insights into the potential role of rare genetic variants in susceptibility to clozapine-induced myocarditis.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 3","pages":"173-179"},"PeriodicalIF":2.8,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41884078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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