Elucidating the genomic determinants of outcomes in idiopathic pulmonary fibrosis

阐明特发性肺纤维化结果的基因组决定因素

• 批准号: 9369287
• 负责人: Justin M Oldham
• 金额: $ 18.27万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9369287
• 关键词: Adverse effects; Advisory Committees; Award; Bioinformatics; Biological; Biology; Biometry; Center Core Grants; Center for Translational Science Activities; Cessation of life; Clinical; Clinical Data; Clinical Sciences; Clinical Treatment; Clinical Trials; Clinical Trials Design; Code; Conduct Clinical Trials; Country; Coupled; Custom; DNA; Data; Data Set; Development; Development Plans; Diagnosis; Disease; Disease Outcome; Disease Progression; Drug Kinetics; Early treatment; Educational workshop; Enrollment; Environment; Environmental Health; Event; Foundations; Funding; Genes; Genetic; Genetic Markers; Genetic Polymorphism; Genetic Predisposition to Disease; Genetic Risk; Genomics; Genotype; Goals; Grant; Hamman-Rich syndrome; Hospitalization; Individual; Institutional Review Boards; Interstitial Lung Diseases; Investigation; Laboratories; Leadership; Link; Medicine; Mentored Patient-Oriented Research Career Development Award; Mentorship; Minority; Modeling; National Institute of Environmental Health Sciences; Outcome; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacodynamics; Pharmacogenetics; Phenotype; Pirfenidone; Predisposition; Progressive Disease; Publishing; Pulmonary Fibrosis; Registries; Research; Research Personnel; Resources; Respiratory physiology; Risk; Risk stratification; Sampling; Single Nucleotide Polymorphism; Survival Analysis; TOLLIP gene; Technology; Testing; Therapeutic; Time; Training; United States National Institutes of Health; Writing; adverse outcome; antioxidant therapy; base; biobank; career; career development; clinical decision-making; clinical predictors; clinically relevant; cohort; comparative; design; experience; gene interaction; genetic epidemiology; genome wide association study; genome-wide; improved; laboratory experience; mortality; novel; outcome forecast; patient oriented research; patient population; personalized medicine; pharmacogenetic testing; precision medicine; programs; prospective; pulmonary function decline; respiratory; response; skills; stem; success; therapeutic target; tool; treatment response

PROJECT SUMMARY/ABSTRACT Idiopathic pulmonary fibrosis (IPF) is a rare, but devastating interstitial lung disease characterized by a progressive decline in lung function and a median survival of 3-5 years after diagnosis. Despite the poor prognosis, IPF follows a highly variable clinical course, whereby most patients experience gradual disease progression, some demonstrate relative stability and a small group dies from rapidly progressive disease. Anti- fibrotic therapies were recently approved for the treatment of IPF, but it remains unclear which IPF phenotypes derive the most benefit. Recent advances in genomic technology provide an excellent opportunity to improve our understanding of IPF progression and treatment response. In this proposal, I aim to take advantage of these genomic advances to identify single nucleotide polymorphisms (SNPs) linked to relevant IPF outcomes. I will do this using DNA samples collected from patients enrolled in past and current IPF clinical trials, along with two large IPF registries. My central hypothesis is that patients genetically predisposed to death, disease progression and treatment response can be prospectively identified using SNPs linked to these endpoints. I will first conduct a genome-wide survival analysis to identify SNPs linked to early IPF mortality. I will then genotype relevant susceptibility and outcome-associated SNPs in several clinical trial datasets to determine whether they predict relevant trial endpoints, including pulmonary function decline and hospitalization. Finally, I will genotype SNPs at potential pharmacogenetic loci to determine whether such SNPs modulate the response to anti-fibrotic therapy. Successful completion of this proposal will lead to the development of customized SNP chips that inform the design of IPF clinical trials and has a high potential to identify novel genes that may one day serve as therapeutic targets. My long-term career goal is to incorporate genetics into clinical decision-making in patients with IPF, specifically clinical trial enrollment and therapeutic selection. To make progress towards this goal, the relevant genetic markers with which to stratify IPF cohorts for risk-stratification and pharmacogenetic testing must first be identified. To do this, a career development has been devised that will provide outstanding mentorship, hands-on laboratory experience and additional training in genetic epidemiology, statistical genetics and bioinformatics. I will draw mentorship from leaders in the field of genomics, interstitial lung disease and clinical and translational investigation. An advisory committee composed of individuals with diverse backgrounds has been assembled to provide specific guidance with regard to clinical registry and biorepository management, laboratory training, statistical genetics and outcomes modeling. This K23 award is vital to successful completion of this proposal and timely execution of my career development plan, as it will provide the time necessary to meet the realistic milestones that have set in conjunction with my advisory committee. Ultimately this award will allow me to successfully compete for R01 funding aimed at advancing my long-term goal above. The research environment at UC Davis is among the best in the country and includes the NIH-funded Clinical and Translational Science Center (CTSC), the Career Development Core funded by the NIEHS P30 program in Environmental Health Sciences (ESH), the Center for Comparative Respiratory Biology and Medicine (CCRBM) and the Integrative Genetics and Genomics Graduate Group (IGG). The UC Davis CTSC was one of the original 12 NIH-supported Centers nationally and provides resources in bioinformatics, IRB submission and the conduct of investigator-initiated clinical trials. The EHS career development core provides vital assistance to junior investigators launching research careers including mentorship workshops, grant writing assistance and laboratory leadership-focused seminars. The CCRBM, which includes many collaborative investigators focused on pulmonary fibrosis, also offers graduate classes in clinical and advanced biostatistics. The IGG provides additional coursework in genetic epidemiology, statistical genetics and bioinformatics. Coupled with a large and well-established ILD program, UC-Davis has an established track record of excellence in patient- oriented research and provides the ideal environment in which to conduct this proposal. !

项目摘要/摘要 特发性肺纤维化（IPF）是一种罕见但具有毁灭性的间质性肺疾病，其特征是 肺功能的逐渐下降和诊断后3 - 5年的中位生存期。尽管贫穷 预后，IPF遵循高度可变的临床过程，大多数患者都会逐渐疾病 进展，有些表明相对稳定性，而一小组死于快速进行性疾病。反对- 纤维化疗法最近被批准用于治疗IPF，但尚不清楚哪种IPF表型 获得最大的好处。基因组技术的最新进展为改善 我们对IPF进展和治疗反应的理解。在此提案中，我的目标是利用 这些基因组进步确定与相关IPF结果相关的单核苷酸多态性（SNP）。我 将使用从过去和当前IPF临床试验中的患者收集的DNA样本以及 两个大型IPF注册表。我的核心假设是，遗传上易于死亡的患者，疾病 可以使用与这些终点链接的SNP前瞻性地识别进展和治疗反应。我会 首先进行全基因组生存分析，以识别与早期IPF死亡率相关的SNP。然后我将基因型 在几个临床试验数据集中，相关的敏感性和与结果相关的SNP 他们预测相关的试验终点，包括肺功能下降和住院。最后，我会的 潜在药物基因座的基因型SNP，以确定这种SNP是否调节对 抗纤维化疗法。成功完成该提案将导致定制SNP的发展 为IPF临床试验设计的芯片，并且具有识别可能的新基因的潜力很高 白天是治疗靶标。 我的长期职业目标是将遗传学纳入IPF患者的临床决策中 特别是临床试验入学和治疗选择。为了朝这个目标取得进步，相关的 将IPF队列分层以进行风险分层和药物遗传学测试的遗传标记必须首先 被识别。为此，已经设计了一个职业发展，该发展将提供出色的指导， 动手实验室经验和遗传流行病学，统计遗传学和 生物信息学。我将从基因组学领域，间质性肺部疾病和临床领域的领导者那里汲取指导 和翻译调查。由具有不同背景的个人组成的咨询委员会 组装以提供有关临床注册中心和生物座席管理的具体指导， 实验室培训，统计遗传学和结果建模。这个K23奖对于成功至关重要 完成此建议的完成以及我的职业发展计划的及时执行，因为它将提供时间 与我的咨询委员会结合结合的现实里程碑所必需的。最终 该奖项将使我能够成功竞争R01资金，以促进上面的长期目标。 加州大学戴维斯分校的研究环境是该国最好的，包括NIH资助的临床 和转化科学中心（CTSC），由NIEHS P30计划资助的职业发展核心 比较呼吸生物学与医学中心环境卫生科学（ESH） （CCRBM）以及综合遗传学和基因组学研究生组（IgG）。 UC Davis CTSC是之一 全国最初的12个NIH支持中心，并提供生物信息学，IRB提交和 研究人员发起的临床试验的进行。 EHS职业发展核心提供了重要的帮助 向初级调查人员发起包括指导研讨会在内的研究职业，赠款写作协助 和以实验室领导为重点的研讨会。 CCRBM，其中包括许多合作调查员 专注于肺纤维化，还提供临床和晚期生物统计学的研究生课程。 IgG 提供遗传流行病学，统计遗传学和生物信息学的其他课程。加上一个 加州大学戴维斯（UC-Davis 定向研究，并提供了进行该建议的理想环境。 呢