Long non-coding RNA signatures to classify multiple sclerosis

用于对多发性硬化症进行分类的长非编码 RNA 特征

• 批准号: 9136402
• 负责人: Thomas M. Aune
• 金额: $ 15.98万
• 依托单位: IQUITY LABS, INC
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9136402
• 关键词: Address; Autoimmune Diseases; Biological Markers; Biological Process; Categories; Cerebrospinal Fluid; Clinical; Code; Complex; Data; Demyelinations; Detection; Diagnosis; Diagnostic; Diagnostic tests; Disease; Event; Evoked Potentials; Exhibits; Fibromyalgia; Gene Expression Profile; Genes; Health Personnel; Healthcare; Healthcare Systems; Hour; Human; Inflammation; Invertebrates; Irritable Bowel Syndrome; Laboratories; Magnetic Resonance Imaging; Measurement; Messenger RNA; Multiple Sclerosis; Neurologic; Oligoclonal Bands; Organism; Pattern; Persons; Process; Proteins; RNA; Research; Research Subjects; Rest; Symptoms; Syndrome; Systemic Scleroderma; Testing; Time; United States; Untranslated RNA; Vertebrates; Whole Blood; base; cell type; cost; differential expression; experience; human disease; infancy; nervous system disorder; novel; public health relevance

 DESCRIPTION (provided by applicant): Diagnosis of multiple sclerosis [MS] rests on clinical symptoms and examinations supported by appropriate magnetic resonance imaging findings or other laboratory tests such as oligoclonal bands in cerebrospinal fluid and evoked potential testing. Clinically isolated syndrome (CIS) is a first neurologic episode lasting at least 24 hours possibly caused by focal inflammation or demyelination. Approximately 10,000-15,000 new diagnoses of MS are made in the United States each year. Approximately 2-3 times that number experience a CIS each year indicating that a far greater number of subjects experience a CIS than develop MS. Costs to healthcare of determining if a subject with a CIS will develop MS are significant. Furthermore, misdiagnosis of MS produces a huge cost burden on our healthcare system as it is a frequent event and with the rising cost of newer as well as older therapies, the cost of managing a person with MS can exceed $50,000 per year. Thus, even a simple confirmatory test would be of significant financial benefit to the healthcare system. 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 greater than ten years. Many disease-specific gene expression signatures have been identified in the research lab. A few of these have even progressed into commercially viable diagnostic tests, notably for irritable bowel syndrome, fibromyalgia, and systemic sclerosis. 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. In vertebrates, the number of lncRNA genes greatly exceeds the number of protein-coding genes. It is also thought that lncRNAs drive greater biologic complexity between vertebrates and invertebrates. These lncRNAs also show much greater cell-type specific expression patterns than mRNAs. Humans also develop many more complex diseases than other organisms. As such, our data presented in preliminary studies, 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 MS as a disease category and have identified MS 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 the following specific aim: To identify annotated and novel lncRNAs differentially expressed in MS and assess their function as biomarkers to distinguish MS subjects from healthy subjects and subjects with other neurologic disorders.

 描述（由申请人提供）：多发性硬化症[MS]的诊断依赖于临床症状和检查，并由适当的磁共振成像结果或其他实验室检查（如脑脊液中的寡克隆带和诱发电位测试）支持。临床孤立综合征（CIS）是一种持续至少24小时的首次神经系统发作 可能由局部炎症或脱髓鞘引起。在美国，每年大约有10，000 - 15，000例MS的新诊断。每年经历CIS的人数约为该人数的2-3倍，表明经历CIS的受试者人数远多于发展MS的人数。确定患有CIS的受试者是否会发展MS的医疗保健成本是显著的。此外，MS的误诊对我们的医疗保健系统产生了巨大的成本负担，因为它是一种常见的事件，并且随着更新和旧疗法的成本不断上升，管理MS患者的成本每年可能超过50，000美元。因此，即使是一个简单的验证性测试也会对医疗保健系统产生重大的经济效益。 是否能够基于全血中mRNA的疾病特异性表达水平来构建能够提供临床有用信息的疾病分类器的问题已经是超过十年的研究主题。许多疾病特异性基因表达特征已在研究实验室中被鉴定。其中一些甚至已经发展成为商业上可行的诊断测试，特别是肠易激综合征，纤维肌痛和系统性硬化症。 长链非编码RNA（lncRNA）是近年来发现的一类不编码蛋白质但影响多种生物过程的调控RNA分子。在脊椎动物中，lncRNA基因的数量大大超过了蛋白质编码基因的数量。人们还认为lncRNA驱动脊椎动物和无脊椎动物之间更大的生物复杂性。这些lncRNA也显示出比mRNA大得多的细胞类型特异性表达模式。人类也会患上比其他生物更复杂的疾病。因此，我们在初步研究中提供的数据支持疾病相关lncRNA比疾病相关mRNA表现出更大的表达差异的观点。在本申请中，我们提出探索lncRNA是比mRNA更好的人类疾病生物标志物的假设。在这里，我们将集中在MS作为一种疾病类别，并确定MS相关的差异表达的lncRNA。lncRNA在人类自身免疫性疾病中的研究尚处于起步阶段，并且以前尚未解决lncRNA作为自身免疫性疾病的生物标志物的探索。我们提出了以下具体目标：鉴定MS中差异表达的注释的和新的lncRNA，并评估它们作为生物标志物的功能，以区分MS受试者与健康受试者和患有其他神经系统疾病的受试者。

项目成果

Predictive modeling of COVID-19 case growth highlights evolving racial and ethnic risk factors in Tennessee and Georgia.

• DOI: 10.1136/bmjhci-2021-100349
• 发表时间: 2021-08
• 期刊: BMJ health & care informatics
• 影响因子: 4.1
• 作者: Gray JD;Harris CR;Wylezinski LS;Spurlock Iii CF
• 通讯作者: Spurlock Iii CF

Predictive Modeling of COVID-19 Case Growth Highlights Evolving Demographic Risk Factors in Tennessee and Georgia.

COVID-19 病例增长的预测模型凸显了田纳西州和佐治亚州不断变化的人口风险因素。

• DOI: 10.1101/2021.02.09.21251106
• 发表时间: 2021
• 期刊: medRxiv : the preprint server for health sciences
• 作者: Gray,JamiesonD;Harris,ColemanR;Wylezinski,LukaszS;Spurlock3rd,CharlesF
• 通讯作者: Spurlock3rd,CharlesF

Longitudinal assessment and stability of long non-coding RNA gene expression profiles measured in human peripheral whole blood collected into PAXgene blood RNA tubes.

• DOI: 10.1186/s13104-020-05360-3
• 发表时间: 2020-11-12
• 期刊: BMC research notes
• 影响因子: 1.8
• 作者: Wylezinski LS;Shaginurova GI;Spurlock Iii CF
• 通讯作者: Spurlock Iii CF