SBIR-STTR Award

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.

Public Health Relevance Statement:


Public Health Relevance:
Diagnosis of autoimmune diseases, including multiple sclerosis (MS), can be a difficult, long and costly process and mis-diagnosis of MS is not uncommon. Long non-coding RNAs (lncRNA) are a new class of regulatory RNA molecules that exhibit high degrees of cell-type specific expression. The hypothesis we will test in this application is that measurement of expression of disease-specific lncRNAs in MS will have greater utility to provide meaningful clinical information to health-care providers than faced with these diagnostic dilemmas than measurement of disease-specific mRNAs.

Project Terms:
Address; Autoimmune Diseases; base; Biological Markers; Biological Process; Categories; cell type; Cerebrospinal Fluid; Clinical; Code; Complex; cost; Data; Demyelinations; Detection; Diagnosis; Diagnostic; Diagnostic tests; differential expression; Disease; Event; Evoked Potentials; Exhibits; experience; Fibromyalgia; Gene Expression Profile; Genes; Health Personnel; Healthcare; Healthcare Systems; Hour; Human; human disease; infancy; Inflammation; Invertebrates; Irritable Bowel Syndrome; Laboratories; Magnetic Resonance Imaging; Measurement; Messenger RNA; Multiple Sclerosis; nervous system disorder; Neurologic; novel; Oligoclonal Bands; Organism; Pattern; Persons; Process; Proteins; public health relevance; Research; Research Subjects; Rest; RNA; Symptoms; Syndrome; Systemic Scleroderma; Testing; Time; United States; Untranslated RNA; Vertebrates; Whole Blood

Diagnosis of relapsing remitting multiple sclerosis (MS) rests on clinical symptoms and examinations as outlined in the revised McDonald’s criteria supported by appropriate magnetic resonance imaging findings and other laboratory tests. The need for early diagnosis is clearly emphasized in a position paper produced in 2015 by MS Brain Health organization called “Brain health, Time matters in multiple sclerosis’ which is endorsed by the major organizations and foundations that advocate for MS research, providers and patients including Accelerated Cure Project (ACP), Americans Committed for Treatment and Research in Multiple Sclerosis (ACTRIMS), The Consortium of Multiple Sclerosis Centers (CMSC), European Brain Council (EBC), European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), European Multiple Sclerosis Platform (EMSP), International Society of Neuroimmunology (ISNI), International Organization of Multiple Sclerosis Nurses (IOMSN), National Multiple Sclerosis Society (NMSS), and Multiple Sclerosis Trust (MS). To cite from their executive summary page: (1) “A therapeutic strategy that offers the best chance of preserving brain and spinal cord tissue early in the disease course needs to be widely accepted – and urgently adopted.” (2) “Significant delays often occur before a person with symptoms suggestive of MS sees a neurologist for diagnosis and treatment.” (3) “Early intervention is vital.” (bold type face is theirs, not ours). 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 MS as a disease category and have identified and validated 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 to determine expression levels of target lncRNAs in blood obtained from larger cohorts of subjects that include 1) subjects with RRMS, 2) healthy controls, 3) neurologic disease controls including both inflammatory and non- inflammatory disorders, and 4) 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 the MS cohorts from healthy and disease control cohorts with greatest overall accuracy.

Public Health Relevance Statement:
Diagnosis of relapsing remitting multiple sclerosis (MS) is a subjective diagnosis based largely on clinical symptoms and MRI findings disseminated in time and space. Biomarkers to aid and accelerate this diagnosis is an area of active investigation. Long non-coding RNAs (lncRNAs) are newly discovered classes of RNAs with an array of regulatory functions. Our hypothesis to test, and supported by our phase 1 studies, is that classifiers can be built based upon differential expression of lncRNAs in blood. These classifiers will possess greater accuracy to identify presence of MS in a subject earlier than is currently available leading to preservation of ‘brain health’.

Project Terms:
Address; Adopted; Advocate; American; Area; Asians; Autoimmune Diseases; base; Biological Markers; Biological Preservation; Biological Process; Blood; Brain; brain health; Categories; cell type; Clinical; Code; cohort; Complex; cost; Data; Demyelinations; Diagnosis; Diagnostic tests; differential expression; Disease; disorder control; Early Diagnosis; Early Intervention; Europe; European; Event; Exhibits; experience; Face; Fibromyalgia; Foundations; Gene Expression Profile; Genes; Geographic Distribution; health organization; Healthcare; Healthcare Systems; Hour; Human; human disease; infancy; Inflammation; Inflammatory; International; Invertebrates; Investigation; Irritable Bowel Syndrome; Laboratories; Latin American; Machine Learning; Magnetic Resonance Imaging; Messenger RNA; Middle East; Multiple Sclerosis; nervous system disorder; neuroimmunology; Neurologic; Neurologist; Northern Africa; Nurses; Organism; Paper; Patients; Pattern; Peripheral; Persons; Phase; phase 1 study; Positioning Attribute; Proteins; Provider; Relapsing-Remitting Multiple Sclerosis; Research; Research Subjects; Rest; RNA; Site; Societies; Spinal Cord; Suggestion; Symptoms; Syndrome; Systemic Scleroderma; Testing; Therapeutic; Time; Tissues; Trust; United States; Untranslated RNA; Vertebrates; Whole Blood; Work