Derivation and validation of a clinical-molecular signature to predict fibrotic progression and treatment response in patients with autoimmune interstitial lung disease

推导和验证临床分子特征以预测自身免疫性间质性肺病患者的纤维化进展和治疗反应

• 批准号: 10275747
• 负责人: Justin M Oldham
• 金额: $ 39.97万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-20 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10275747
• 关键词: Address; Applications Grants; Autoimmune; Autoimmune Diseases; Biological Markers; Cause of Death; Cessation of life; Clinical; Clinical Trials; Data; Derivation procedure; Diagnosis; Disease Progression; Future; Goals; Immunosuppressive Agents; Individual; Inflammation; International; Interstitial Lung Diseases; Investigation; Logistic Regressions; Modeling; Modification; Molecular; Molecular Profiling; Natural History; Nature; Outcome; Patients; Phenotype; Plasma; Population; Prevalence; Process; Progression-Free Survivals; Pulmonary Fibrosis; Research; Research Personnel; Resistance; Sampling; Therapeutic; Therapeutic Intervention; Transplantation; Validation; Vital capacity; Work; antifibrotic treatment; biomarker-driven; clinical biomarkers; clinical decision support; clinical decision-making; clinical practice; clinical predictors; clinically relevant; cohort; disease natural history; disease phenotype; disorder risk; fibrogenesis; functional decline; high risk; idiopathic pulmonary fibrosis; molecular diagnostics; mortality; optimal treatments; outcome prediction; performance tests; precision medicine; predictive marker; primary endpoint; prospective; pulmonary function decline; response; tool; treatment response

Project Summary Progressive fibrosing interstitial lung disease (PF-ILD) is a devastating condition characterized by parenchymal destruction, lung function decline and ultimately death. Autoimmune ILD (aILD) is a leading cause of PF-ILD, but the natural history of PF-ILD in those with aILD has yet to be characterized. Immunosuppressant (IS) therapy is generally used to treat aILD, as parenchymal inflammation often precedes pulmonary fibrosis. Of those aILD patients treated with IS, some will respond favorably, while others will develop PF-ILD. Because pulmonary fibrosis is an irreversible process, there exists a critical need to better understand PF-ILD, identify those most likely to develop this phenotype and establish an optimal treatment approach for this group. We recently identified a number of circulating plasma biomarkers of PF-ILD and have now generated exciting preliminary data that show a clinical-molecular signature (CMS) comprised of aggregated clinical and plasma biomarker data predicts differential PF-ILD risk and IS response in those with aILD. Optimization and validation of these findings would advance our understanding of PF-ILD and have profound treatment implications for the field. The objective of this application to optimize and validate our preliminary CMS of PF- ILD and IS response in a large, multi-center, international aILD cohort. My co-investigators and I have expertise in translational ILD research, including plasma biomarker investigation. All plasma samples needed for this proposal have been collected, underscoring the feasibility of our approach. We will first characterize the natural history of PF-ILD in a well-phenotyped, multi-center aILD cohort (n=2000). We will determine the prevalence of short-term forced vital capacity decline and long-term mortality. Will identify clinical predictors of these endpoints and validate our findings in an independent aILD cohort. Next, we will derive and validate a CMS of PF-ILD. A quantitative, multiplex platform will be used to determine plasma concentration for 64 relevant biomarkers of inflammation and fibrogenesis. Using one-year progression-free survival as the primary endpoint, logistic regression will be performed to identify independent clinical and biomarker predictors of outcome. A CMS of PF-ILD will be derived using regression point estimates and then validated in three independent aILD cohorts. Finally, we will derive and validate a CMS of IS response. Using Interaction modeling will be performed to identify independent clinical and molecular predictors of IS effect modification. A CMS of IS response will be derived using regression point estimates and then validated in three independent aILD cohorts, including two prospectively collected IS clinical trial cohorts. Successful completion of this proposal will lead to prospective CMS validation with the goal of developing the first molecular diagnostic tool to support clinical decision making in aILD. This work will allow for rapid identification of patients at high-risk of short-term disease progression and guide therapeutic selection.

项目摘要 进行性纤维化间质性肺病（PF-ILD）是一种破坏性疾病，其特征在于： 肺实质破坏，肺功能下降，最终死亡。自身免疫性ILD（aILD）是导致 的PF-ILD，但PF-ILD在aILD患者中的自然史尚未得到表征。免疫抑制 (IS)由于实质性炎症通常先于肺纤维化，因此通常使用该疗法来治疗aILD。的 在接受IS治疗的aILD患者中，有些患者的反应良好，而另一些患者则会发展为PF-ILD。因为 肺纤维化是一个不可逆的过程，迫切需要更好地了解PF-ILD， 最有可能发展这种表型的人，并为这一群体建立最佳治疗方法。 我们最近发现了许多PF-ILD的循环血浆生物标志物， 令人兴奋的初步数据显示，临床分子特征（CMS）由聚集的临床和 血浆生物标志物数据可预测aILD患者的不同PF-ILD风险和IS应答。优化和 这些发现的验证将促进我们对PF-ILD的理解， 对该领域的影响。本申请的目的是优化和验证我们初步的PF CMS- 一个大型、多中心、国际aILD队列中的ILD和IS缓解。我和我的同事 转化性ILD研究，包括血浆生物标志物研究。所需的所有血浆样本 我们已收集了大量的建议，强调了我们的方法的可行性。 我们将首先在一个表型良好的多中心aILD队列中描述PF-ILD的自然史 （n=2000）。我们将确定短期强迫肺活量下降和长期死亡率的患病率。 将确定这些终点的临床预测因素，并在一个独立的aILD队列中验证我们的发现。接下来， 我们将推导并验证PF-ILD的CMS。将使用定量、多重平台测定血浆 针对炎症和纤维化的64种相关生物标志物的浓度。使用一年无进展 生存率作为主要终点，将进行逻辑回归以确定独立的临床和 生物标志物预测结果。将使用回归点估计值推导PF-ILD的CMS，然后 在三个独立的aILD队列中得到验证。最后，我们将推导并验证IS响应的CMS。使用 将进行相互作用建模，以确定IS效应的独立临床和分子预测因子 改性将使用回归点估计值推导IS响应的CMS，然后在三个模型中进行验证 独立aILD队列，包括两个前瞻性收集的IS临床试验队列。 成功完成此提案将导致未来CMS验证，目标是开发 第一个支持aILD临床决策的分子诊断工具。这项工作将允许快速 识别短期疾病进展的高风险患者并指导治疗选择。