A Personalized Medicine Approach to Improve the Prediction of Azathioprine Toxicity

改善硫唑嘌呤毒性预测的个性化医疗方法

• 批准号: 10225430
• 负责人: Cecilia Pilar Chung
• 金额: $ 42.43万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10225430
• 关键词: Adverse effects; Adverse event; Affect; Asians; Azathioprine; Bone Marrow Suppression; Candidate Disease Gene; Clinical; Clinical Data; Databases; Development; Dose; Drug Kinetics; Drug toxicity; Effectiveness; Enrollment; Enzymes; Essential Drugs; Face; Frequencies; GSTP1 gene; Gene Expression; Gene Expression Profiling; Gene Expression Regulation; Genes; Genetic; Genetic Determinism; Genetic Models; Genetic Polymorphism; Genetic Risk; Genetic Variation; Genome Scan; Genotype; Goals; HLA-DQA1; HLA-DRB1; Haplotypes; Hematologic Neoplasms; Immunologics; Immunosuppressive Agents; Inflammatory; Inflammatory Bowel Diseases; Link; Mediating; Medical; Medical Genetics; Modeling; Myelosuppression; Organ Transplantation; Other Genetics; Pancreatitis; Pathway interactions; Patient Care; Patient Rights; Patient risk; Patients; Pharmaceutical Preparations; Pharmacogenetics; Phase; Phenotype; Phospholipase C; Play; Population Sizes; Precision Medicine Initiative; Program Development; Records; Reporting; Reproducibility; Research; Resources; Rheumatism; Risk; Role; Signal Transduction; TPMT gene; Techniques; Testing; Therapeutic Index; Tissue-Specific Gene Expression; Tissues; Toxic effect; Validation; Variant; Veterans; World Health Organization; adverse drug reaction; base; biobank; clinical practice; clinically significant; cohort; genetic association; genetic predictors; genetic variant; genome wide association study; high risk; improved; inter-individual variation; novel; personalized medicine; programs; response; side effect; thiopurine; thiopurine methyltransferase

Abstract Azathioprine is an immunosuppressive drug widely used for the treatment of rheumatic and other inflammatory conditions. However, it has a narrow therapeutic index, and the frequency of clinically significant side effects associated with its use is approximately 50%. Based on clinical importance and differences in mechanisms, this project focuses on two of the most serious adverse effects of AZA: myelosuppression and pancreatitis. Currently, clinicians are limited to thiopurine methyltransferase (TPMT) testing to predict patients' risk for azathioprine toxicity. Despite their usefulness, TPMT polymorphisms explain only one in four cases of myelosuppression associated with azathioprine, and they do not predict pancreatitis. Recent evidence suggests other genetic variants have important roles in azathioprine-related side effects. For example, NUDT15 and the HLA- DQA1*02:01–HLA-DRB1*07:01 haplotype are genetic determinants of myelosuppression and pancreatitis, respectively. Nevertheless, their usefulness in routine clinical practice and their combined ability to predict side effects of AZA remains unclear. The overarching hypothesis of this proposal is that genetic risk scores can identify patients who develop azathioprine toxicity. Using state of the art and novel techniques and resources, we will conduct genetic and gene expression association analyses, leveraging two large practice- based biobanks: (1) Vanderbilt's BioVU, one of the largest practice-based biobanks in the U.S., and (2) the Million Veteran Program (MVP), currently enrolling, collecting clinical data from, and genotyping U.S. Veterans. In Aim 1, we will conduct genetic association analyses to discover novel genetic predictors of myelosuppression and pancreatitis in patients taking azathioprine. In Aim 2, we will test the hypothesis that novel genetic variants, identified by gene expression association analyses, predict AZA-related myelosuppression and pancreatitis. We will predict gene expression by utilizing the Genotype Tissue-Expression (GTEx) database. In Aim 3, we will combine all variants identified from Aims 1 and 2 to generate two genetic risk scores (i.e., myelosuppression risk and pancreatitis risk) for patients in the BioVU cohort. We will further validate the genetic risk scores in the independent MVP cohort. This project aims to further the goals of the Precision Medicine Initiative by constructing two genetic models that will predict serious and frequent side effects of azathioprine. Better prediction capacity will offer better treatment options for patients and advance personalized medicine, which seeks to deliver “the right drug, at the right dose, to the right patient.”

摘要 硫唑嘌呤是一种免疫抑制药物，广泛用于治疗风湿性和其他炎症 条件然而，它具有狭窄的治疗指数，并且临床显著副作用的频率 与其使用相关的风险约为50%。基于临床重要性和机制的差异， 该项目的重点是AZA的两个最严重的副作用：骨髓抑制和胰腺炎。目前， 临床医生仅限于通过硫嘌呤甲基转移酶（TPMT）检测来预测患者使用硫唑嘌呤的风险 毒性尽管TPMT多态性很有用，但它们只能解释四分之一的骨髓抑制病例 与硫唑嘌呤相关，但不能预测胰腺炎。最近的证据表明， 变体在硫唑嘌呤相关的副作用中具有重要作用。例如，NUDT 15和HLA-1。 DQA 1 *02：01-HLA-DRB 1 *07：01单倍型是骨髓抑制和胰腺炎的遗传决定因素， 分别然而，它们在常规临床实践中的有用性和它们预测副作用的联合能力， AZA的影响尚不清楚。这项建议的首要假设是，遗传风险评分 可以鉴别出硫唑嘌呤中毒的病人使用最先进的技术和新的技术， 资源，我们将进行遗传和基因表达关联分析，利用两个大的实践- （1）范德比尔特的BioVU，美国最大的基于实践的生物库之一，（2） 百万退伍军人计划（MVP），目前正在招募，收集临床数据，并对美国退伍军人进行基因分型。 在目标1中，我们将进行遗传关联分析，以发现骨髓抑制的新遗传预测因子 以及服用硫唑嘌呤的患者的胰腺炎。在目标2中，我们将检验新的遗传变异， 通过基因表达关联分析鉴定，预测AZA相关的骨髓抑制和胰腺炎。我们 将利用基因型组织表达（GTEx）数据库预测基因表达。在目标3中，我们 联合收割机组合从目的1和2鉴定的所有变体以产生两个遗传风险评分（即，骨髓抑制风险 和胰腺炎风险）。我们将进一步验证遗传风险评分， 独立MVP队列。 该项目旨在通过构建两个遗传模型， 将预示硫唑嘌呤严重且频繁的副作用。更好的预测能力将提供更好的治疗 为患者提供选择和先进的个性化医疗，旨在提供“正确的药物，以正确的剂量， 正确的病人”。