Genomic and Imaging Markers to Understand and Predict Progression of Joint Damage After Injury

基因组和成像标记物可了解和预测受伤后关节损伤的进展

• 批准号: 10605787
• 负责人: THORSTEN KIRSCH
• 金额: $ 74.58万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-08 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10605787
• 关键词: Acute; Address; Age Years; Biological; Biological Markers; Biological Testing; Cartilage; Cells; Clinical; Clinical Research; Clinical assessments; Complex; Complication; Development; Diffusion Magnetic Resonance Imaging; Disease; Early Diagnosis; Environment; Event; Failure; Fatty acid glycerol esters; Gene Expression; Gene Expression Profiling; Genes; Genetic Transcription; Genomics; Goals; Homeostasis; Image; Inflammation; Injury; Intervention; Joints; Link; Lipid Bilayers; Lipids; Magnetic Resonance Imaging; Measures; Meniscus structure of joint; Methods; Molecular; Operative Surgical Procedures; Orthopedic Surgery; Outcome; Parents; Pathology; Patients; Phase; Play; Population; Positioning Attribute; Prevalence; Proteins; RNA; Research; Risk Factors; Role; Sampling; Severities; Symptoms; Synovial Fluid; Testing; Time; Tissue-Specific Gene Expression; Tissues; Traumatic Arthropathy; Untranslated RNA; Validation; anterior cruciate ligament injury; anterior cruciate ligament rupture; articular cartilage; biobank; biomarker panel; candidate marker; cell type; clinical application; cohort; cost effective; diagnostic tool; disability; extracellular vesicles; follow-up; genomic biomarker; genomic profiles; healing; imaging biomarker; imaging modality; joint destruction; joint injury; magnetic resonance imaging biomarker; novel diagnostics; older patient; outcome prediction; participant enrollment; particle; posttranscriptional; predictive marker; predictive panel; predictive tools; prevent; prospective; recruit; response; response to injury; tissue degeneration; tool

PROJECT SUMMARY Posttraumatic osteoarthritis (PTOA) is a major complication that follows an episode anterior cruciate ligament (ACL) rupture. In the US, there are over 100,000 ACL ruptures per year, from which 70% occur in physically active subjects under 40 years of age. At 10 to 20 years after ACL rupture the prevalence of PTOA is estimated to be 50–70%, regardless of surgical or non-surgical interventions. The failure of surgery to prevent PTOA leads to the hypothesis that the acute changes in the joint following directly after injury triggers a cascade of events leading to PTOA. However, little is known about how biological response to injury links to the subsequent joint damage. Therefore, it is important to have tools available that provide comprehensive assessment of response to injury and predict who will develop PTOA after ACL injury. Even though candidate biomarkers have been investigated, their practical use is still very limited. The goal of this proposal is to investigate if biological response to injury by measuring soluble biomarkers in synovial fluid (SF) and analyzing the genomic profile of extracellular vesicles (EVs) isolated from SF obtained during the acute and sub-acute phases of ACL injuries of 18- to 40- years old patients has the potential to predict joint degradation at 3-4 and 6-7 years after injury. Differences between patients in the biological responses to ACL injury involve the presence of different cell types and different cellular responses. EVs, which are being released by all cell types, are attractive candidates as all-in- one, complex biomarkers able to provide a multi-faceted, integrated, snapshot “omics” joint profile of the entire joint environment. In addition, given that these lipid bilayer–delimited particles carry cargos of proteins, different types of RNA, and lipids derived from their parent cells, and that EVs can modulate target cells, make these particles even more attractive as biomarkers. To measure progression of joint damage we will use advanced MRI biomarkers developed in our labs that can detect early tissue degeneration, especially of articular cartilage, a tissue, which is key in the early diagnosis of PTOA. Even more importantly, our MRI markers have shown ability to predict progression. We aim to test our hypothesis that early response to injury captured by the cargo of EVs will provide a new window into early biological changes directly after joint injury is associated with progression of joint damage leading to PTOA. To achieve our goal to establish a biomarker profile that predicts the biological response to the injury and ultimately the development of PTOA, we propose two aims. Aim 1 will provide a panel of biomarkers directly after injury (2 to 3 weeks after injury) and at time of surgery (8 to 12 weeks after injury) establishing the biological response to injury, and determine the relation of these biomarkers to baseline MRI measures of joint damage. In Aim 2, we will test whether these biomarkers can predict changes in the clinical and imaging outcomes determined 3-4 years and 6-7 years after injury. Finally, we will establish a panel of predictive biomarkers for joint degradation validated by cost-effective methods employed in the clinical setting.

项目摘要 创伤后骨关节炎（PTOA）是一个主要的并发症，遵循前交叉韧带发作 （ACL）破裂。在美国，每年有超过100,000个ACL破裂，从那里发生70％ 40岁以下的活跃受试者。 ACL破裂后的10到20年，PTOA的患病率估计 无论手术或非手术干预措施如何，为50–70％。手术未能防止PTOA引线 假设损伤后直接在关节发生的急性变化会触发一系列事件 导致PTOA。但是，关于对损伤的生物反应如何与随后的关节联系的知之甚少 损害。因此，重要的是要有可用的工具来提供全面评估响应 受伤并预测ACL受伤后谁将出现PTOA。即使候选生物标志物已经 调查，他们的实际使用仍然非常有限。该提议的目的是研究生物学反应是否 通过测量滑液（SF）中的固体生物标志物来损伤并分析细胞外基因组谱 从ACL损伤的急性和亚急性阶段中获得的SF分离出的蔬菜（EV）18至40- 年龄的患者有可能在受伤后3 - 4年和6 - 7年预测关节降解。差异 在生物学反应中，患者对ACL损伤的反应涉及不同细胞类型的存在和 不同的细胞反应。所有细胞类型都释放的电动汽车是有吸引力的候选者 一个复杂的生物标志物可以提供整个多面的，集成的，快照的“ OMICS”联合轮廓 联合环境。另外，鉴于这些脂质双层脱落的颗粒携带蛋白质的cargos， RNA的类型和源自其母细胞的脂质，EV可以调节靶细胞，使这些细胞使这些细胞 作为生物标志物，颗粒更具吸引力。为了衡量关节损害的进展，我们将使用高级 MRI生物标志物在我们的实验室中开发，可以检测早期组织变性，尤其是关节软骨， 组织，这是PTOA早期诊断的关键。更重要的是，我们的MRI标记已显示 预测进展的能力。我们旨在检验我们的假设，即货物捕获的伤害的早期反应 电动汽车将在关节损伤后直接提供一个新的窗口，以进行早期生物学变化 导致PTOA的关节损伤的进展。实现我们的目标，建立一个预测的生物标志物概况 我们提出了两个目标，对损伤的生物反应以及最终的PTOA发展。目标1意志 受伤后直接提供一组生物标志物（受伤后2至3周）和手术时（8至12周） 受伤后）建立生物学对损伤的反应，并确定这些生物标志物与 基线MRI的关节损伤指标。在AIM 2中，我们将测试这些生物标志物是否可以预测变化 在受伤后3 - 4年零6 - 7年的临床和成像结果中。最后，我们将建立一个 通过在临床上进行的成本效益方法验证的关节降解的预测生物标志物面板 环境。