Extracellular RNA Expression Biomarkers in Osteoarthritis Disease and Progression

骨关节炎疾病和进展中的细胞外 RNA 表达生物标志物

• 批准号: 10593308
• 负责人: Thomas Michael Best
• 金额: $ 20.05万
• 依托单位: UNIVERSITY OF MIAMI 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: 2023-02-22 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10593308
• 关键词: Address; Affect; Age; American; Architecture; Biochemical; Bioinformatics; Biological; Biological Assay; Biological Markers; Biological Specimen Banks; Body mass index; Categories; Chronic Disease; Classification; Clinical; Clinical Data; Cohort Studies; Complex; Data; Degenerative polyarthritis; Development; Diagnosis; Diagnostic; Disease; Disease Progression; Failure; Gene Expression Profile; Genes; Genetic; Genetic Markers; Genetic Techniques; Genetic Transcription; Genomics; Heart Diseases; Heterogeneity; High-Throughput RNA Sequencing; Image; Incidence; Individual; Knee Osteoarthritis; Magnetic Resonance Imaging; Malignant Neoplasms; Measures; Methodology; Methods; MicroRNAs; Molecular; Molecular Genetics; Molecular Profiling; Multiple Sclerosis; Pain; Pathway interactions; Patients; Pattern; Phenotype; Physiological Processes; Plasma; Population; Prevalence; Public Health; Questionnaires; RNA; Resources; Risk Factors; Roentgen Rays; Role; Sampling; Signaling Molecule; Statistical Data Interpretation; Stress; Symptoms; Therapeutic; Therapeutic Intervention; Time; Tissues; aging population; arthropathies; biomarker identification; clinical data repository; clinical phenotype; clinical subtypes; cohort; disease heterogeneity; disorder risk; disorder subtype; effusion; experimental study; extracellular; functional genomics; genomic signature; insight; joint destruction; molecular marker; muscle strength; novel; pain symptom; precision medicine; prevent; prognostic; progression marker; prospective; radiological imaging; risk stratification; sex; specific biomarkers; targeted treatment; treatment strategy

PROJECT SUMMARY Osteoarthritis (OA) is a progressive and degenerative joint disease with an increasing prevalence in the aging population for which existing treatments targeting the primary symptom of pain are only minimally successful. The manifestation of OA is heterogeneous with symptomology differing across individuals. This disease heterogeneity has made identification of reliable and consistent molecular biomarkers elusive. This has in part hindered the progress toward development of specific therapeutic treatments. Therefore, the identification of specific biomarkers of OA clinical phenotypes and longitudinal changes over disease progression is required. To begin addressing this issue, here we propose an initiative for the discovery of plasma extracellular RNA (exRNA) expression signatures genomic signatures of OA among diverse clinical and progressive phenotypes. exRNA has been demonstrated in a variety of complex diseases to have prognostic and biological value. The experiments will utilize the Osteoarthritis Initiative (OAI) which is a prospective, longitudinal multicenter cohort study of nearly 5000 subjects diagnosed with radiographic knee OA or at risk for the disease. We will first cluster the entire OAI cohort into distinct clinical phenotypes based on biochemical assays, imaging data, and clinical symptom questionnaires and identify exRNA signatures associated with those phenotypes using high throughput RNA sequencing (SA1). Furthermore, we will identify individuals with progressive OA defined as progression by radiograph changes over time as well as increasing pain over time. We will then generate longitudinal time- course profiles of exRNA expression to deduce biological mechanisms of that progression (SA2). By generating specific phenotype definitions, this study has increased power to identify molecular signatures of these OA groups. This will be an important step toward harnessing the value of functional genomics as a biomarker in the precision medicine of OA.

项目概要 骨关节炎（OA）是一种进行性和退行性关节疾病，随着年龄的增长患病率不断增加 现有针对疼痛主要症状的治疗方法收效甚微的人群。 OA 的表现具有异质性，个体之间的症状也不同。这种病 异质性使得可靠且一致的分子生物标志物的鉴定变得难以实现。这有部分 阻碍了特定治疗方法的开发进展。因此，识别 需要 OA 临床表型和疾病进展纵向变化的特定生物标志物。 为了开始解决这个问题，我们在此提出一项发现血浆细胞外 RNA 的倡议 (exRNA) 表达特征是不同临床和进展表型中 OA 的基因组特征。 exRNA 已被证明在多种复杂疾病中具有预后和生物学价值。这 实验将利用骨关节炎倡议 (OAI)，这是一个前瞻性、纵向多中心队列 对近 5000 名被诊断患有膝关节 OA 或有患病风险的受试者进行的研究。我们首先要聚类 根据生化分析、影像数据和临床数据，将整个 OAI 队列分为不同的临床表型 症状调查问卷并使用高通量识别与这些表型相关的 exRNA 特征 RNA 测序 (SA1)。此外，我们将识别患有进行性 OA 的个体，定义为通过以下方法进行进展： X 光片随着时间的推移而变化，疼痛也随着时间的推移而增加。然后我们将生成纵向时间- exRNA 表达的过程概况，以推断该进展的生物学机制 (SA2)。 通过生成特定的表型定义，这项研究增强了识别分子特征的能力 这些 OA 组。这将是发挥功能基因组学价值的重要一步。 OA 精准医学中的生物标志物。