Long non-coding RNA signatures to distinguish fibromyalgia syndrome from rheumatic diseases

长非编码 RNA 特征可区分纤维肌痛综合征和风湿性疾病

• 批准号: 9555179
• 负责人: Thomas M. Aune
• 金额: $ 49.83万
• 依托单位: IQUITY LABS, INC
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-02 至 2020-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9555179
• 关键词: Address; Affect; Area; Autoimmune Diseases; Biological Markers; Biological Process; Blood; Blood specimen; Body Weight Changes; Cartilage; Categories; Clinical; Code; Complex; Data; Deformity; Diagnosis; Diagnostic; Differential Diagnosis; Disease; Early Diagnosis; Etiology; Europe; Exclusion; Exhibits; Fatigue; Fever; Fibromyalgia; Functional disorder; Gene Expression Profile; Genes; Geographic Distribution; Health Personnel; Healthcare; Human; Individual; Inflammatory; Invertebrates; Investigation; Joints; Judgment; Kidney; Laboratories; Life; Ligaments; Machine Learning; Measurement; Messenger RNA; Mixed Connective Tissue Disease; Muscle; Musculoskeletal Pain; Myalgia; Neuraxis; Organ; Organism; Outcome; Patient-Focused Outcomes; Patients; Pattern; Peripheral; Phase; Physicians; Polyarthritides; Population; Procedures; Process; Proteins; RNA; Research; Research Subjects; Rheumatism; Rheumatoid Arthritis; Sensitivity and Specificity; Site; Sjogren' s Syndrome; Specificity; System; Systemic Lupus Erythematosus; Tendon structure; Testing; Time; Untranslated RNA; Vertebrates; Whole Blood; Work; base; body system; bone erosion; care providers; cell type; cohort; cost; diagnostic biomarker; differential expression; disease diagnosis; disorder control; human disease; improved outcome; infancy; phase 1 study; rheumatologist; tool; virtual; Address; Affect; Area; Autoimmune Diseases; Biological Markers; Biological Process; Blood; Blood specimen; Body Weight Changes; Cartilage; Categories; Clinical; Code; Complex; Data; Deformity; Diagnosis; Diagnostic; Differential Diagnosis; Disease; Early Diagnosis; Etiology; Europe; Exclusion; Exhibits; Fatigue; Fever; Fibromyalgia; Functional disorder; Gene Expression Profile; Genes; Geographic Distribution; Health Personnel; Healthcare; Human; Individual; Inflammatory; Invertebrates; Investigation; Joints; Judgment; Kidney; Laboratories; Life; Ligaments; Machine Learning; Measurement; Messenger RNA; Mixed Connective Tissue Disease; Muscle; Musculoskeletal Pain; Myalgia; Neuraxis; Organ; Organism; Outcome; Patient-Focused Outcomes; Patients; Pattern; Peripheral; Phase; Physicians; Polyarthritides; Population; Procedures; Process; Proteins; RNA; Research; Research Subjects; Rheumatism; Rheumatoid Arthritis; Sensitivity and Specificity; Site; Sjogren' s Syndrome; Specificity; System; Systemic Lupus Erythematosus; Tendon structure; Testing; Time; Untranslated RNA; Vertebrates; Whole Blood; Work; base; body system; bone erosion; care providers; cell type; cohort; cost; diagnostic biomarker; differential expression; disease diagnosis; disorder control; human disease; improved outcome; infancy; phase 1 study; rheumatologist; tool; virtual

No other group of diseases encompasses a greater pathophysiology than do the rheumatic diseases. Spanning multiple organ systems, clinical decisions often rely on coordinated efforts from primary care providers and rheumatologists to rule in or rule out differential diagnoses when treating inflammatory conditions such as rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). RA is a symmetric, inflammatory, peripheral polyarthritis leading to deformity of joints via erosion of bone and surrounding cartilage. SLE can affect virtually any organ leading to fatigue, fever, myalgia, weight change and complications associated with renal, central nervous system, and hematologic systems can be life-threatening. RA and SLE are diagnosed through clinical judgment after excluding alternative diagnoses. In the case of both diseases, individual laboratory tests are effective only in a portion of the disease population. Across these analyses, the sensitivity and specificity for these laboratory measurements may have high specificity to rule in SLE but lack sensitivity as these diagnostic markers can be found in other disorders. As a physician colleague pointed out, “it is difficult to diagnose a negative”. Diagnostic approaches for both RA and SLE often rely on multiple, independent laboratory tests combined with clinical observation. Distinguishing between these diseases is important since treatment procedures for these diseases are different. Time is a factor in diagnosis of these diseases and tools are required to facilitate earlier diagnosis as treatment for autoimmune diseases are highly effective and early initiation of therapy leads to the best outcomes. Misdiagnosis of these conditions is not uncommon. Another common disease seen by rheumatologists is fibromyalgia syndrome (FMS). FMS is a common cause of widespread musculoskeletal pain that affects tendons, ligaments, and muscle. FMS is difficult to diagnose and treat and a critical clinical point is that FMS is not explained by another rheumatic or systemic disorder. Thus, FMS is a diagnosis of exclusion once other etiologies have been considered and excluded. RA and SLE are two diseases that must be eliminated from the differential diagnosis. Given the complicated diagnostic process these patients are often forced to endure, recent studies have also suggested that healthcare dollars are saved post-diagnosis and patient outcomes improve. To date, there is no laboratory test that can determine presence or absence of these three conditions from a single blood sample. The question of whether or not disease classifiers capable of providing clinically useful information could be built based upon disease-specific expression levels of mRNAs in whole blood has been a subject of research for several years. Long non-coding RNAs (lncRNA) are recently discovered regulatory RNA molecules that do not code for proteins but influence a vast array of biological processes. It is also thought that lncRNAs drive biologic complexity observed in vertebrates that may also be reflected by the greater array of complex idiopathic diseases that humans develop. As such, our data obtained in the phase 1 portion of this work, support the notion that disease-associated lncRNAs exhibit far greater differences in expression than disease-associated mRNAs. In this application, we propose to explore the hypothesis that lncRNAs are better biomarkers of human disease than mRNAs. Here, we will focus on FMS and the rheumatic diseases as disease categories and have identified and validated FMS and rheumatic disease-associated associated differentially expressed lncRNAs. Study of lncRNAs in human autoimmune disease is in its infancy and exploration of lncRNAs as biomarkers of autoimmune disease has not been previously addressed. We propose to determine expression levels of target lncRNAs in blood obtained from larger cohorts of subjects that include 1) subjects with fibromyalgia syndrome, 2) healthy controls, 3) rheumatoid arthritis, 4) systemic lupus erythematosus, and 5) peripheral autoimmune disease controls obtained from various sites in the U.S. and Europe to establish a wide geographic distribution and to identify optimum machine learning classifiers to distinguish fibromyalgia syndrome and rheumatic diseases from healthy and disease control cohorts with greatest overall accuracy.

没有其他疾病比风湿病更大的病理生理学。 跨越多器官系统，临床决策通常依赖于初级保健提供者的协调努力 以及风湿病学家在治疗炎症状况（例如 类风湿关节炎（RA）和全身性红斑狼疮（SLE）。 RA是对称，炎症，周围的 通过骨骼和周围软骨侵蚀导致关节畸形的多关节炎。 SLE实际上会影响 任何导致疲劳，发烧，肌痛，体重变化和与肾脏中心相关的并发症的器官 神经系统和血液系统可能会威胁生命。 RA和SLE是通过临床诊断的 排除替代诊断后的判断。在这两种疾病的情况下，单个实验室检查是 仅在一部分疾病人群中有效。在这些分析中，对 这些实验室测量可能具有很高的特异性来统治SLE，但由于这些诊断而缺乏灵敏度 标记可以在其他疾病中找到。正如身体同事指出的那样，“很难诊断 RA和SLE的负面诊断方法通常依赖于多个独立的实验室测试 结合临床观察。区分这些疾病很重要，因为治疗 这些疾病的程序不同。时间是诊断这些疾病的一个因素，需要工具 为了促进早期诊断，作为自身免疫性疾病的治疗是非常有效的，并且早期开始 治疗可带来最好的结果。这些疾病的误诊并不少见。另一个常见 风湿病学家看到的疾病是纤维肌痛综合征（FMS）。 FMS是宽度的常见原因 影响肌腱，韧带和肌肉的肌肉骨骼疼痛。 FMS很难诊断和治疗，并且 关键的临床点是，FMS并未通过另一种风湿性或全身性疾病来解释。那是一个FMS 一旦考虑并排除了其他病因，排除的诊断。 RA和SLE是两种疾病 这必须从差异诊断中消除。考虑到复杂的诊断过程这些患者 通常被迫忍受，最近的研究还表明，诊断后保存保健资金 患者的结果得到改善。迄今为止，还没有实验室测试可以确定 这三个条件来自单个血液样本。 疾病分类器是否能够提供临床有用信息的问题可能是 基于全血中mRNA的特异性表达水平建立，一直是研究的主题 几年。最近发现的不编码RNA（lncRNA）是未发现的调节RNA分子 蛋白质代码，但会影响大量的生物过程。还认为lncrnas驱动生物学 在脊椎动物中观察到的复杂性也可能被较大的复杂特发性疾病反映 人类的发展。因此，我们在本工作的第1阶段中获得的数据，支持这样的观念 与疾病相关的mRNA相比，与疾病相关的LNCRNA在表达上暴露了更大的差异。在 我们建议探索LNCRNA是人类疾病更好的生物标志物的假设 比mrnas。在这里，我们将专注于FMS和风湿性疾病作为疾病类别，并已确定 并验证了FMS和风湿性疾病相关的相关相关的LNCRNA。研究 人类自身免疫性疾病中的LNCRNA仍处于起步阶段，并将LNCRNA作为生物标志物的探索 自身免疫性疾病以前尚未解决。我们建议确定目标的表达水平 从较大的受试者获得的血液中的LNCRNA，包括1）患有纤维肌痛综合征的受试者， 2）健康对照，3）类风湿关节炎，4）全身性红斑狼疮和5）外周自身免疫 从美国和欧洲的各个地点获得的疾病控制以建立广泛的地理分布 并确定最佳机器学习分类器以区分纤维肌痛综合征和风湿性 健康和疾病控制队列的疾病总体准确性最高。