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

No other group of diseases encompasses a greater pathophysiology than do the rheumatic diseasesSpanning multiple organ systemsclinical 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 arthritisRAand systemic lupus erythematosusSLERA is a symmetricinflammatoryperipheral polyarthritis leading to deformity of joints via erosion of bone and surrounding cartilageSLE can affect virtually any organ leading to fatiguefevermyalgiaweight change and complications associated with renalcentral nervous systemand hematologic systems can be life threateningRA and SLE are diagnosed through clinical judgment after excluding alternative diagnosesIn the case of both diseasesindividual laboratory tests are effective only in a portion of the disease populationAcross these analysesthe 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 disordersAs a physician colleague pointed outit is difficult to diagnose a negativeDiagnostic approaches for both RA and SLE often rely on multipleindependent laboratory tests combined with clinical observationDistinguishing between these diseases is important since treatment procedures for these diseases are differentTime 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 outcomesMisdiagnosis of these conditions is not uncommonAnother common disease seen by rheumatologists is fibromyalgia syndromeFMSFMS is a common cause of widespread musculoskeletal pain that affects tendonsligamentsand muscleFMS is difficult to diagnose and treat and a critical clinical point is that FMS is not explained by another rheumatic or systemic disorderThusFMS is a diagnosis of exclusion once other etiologies have been considered and excludedRA and SLE are two diseases that must be eliminated from the differential diagnosisGiven the complicated diagnostic process these patients are often forced to endurerecent studies have also suggested that healthcare dollars are saved post diagnosis and patient outcomes improveTo datethere is no laboratory test that can determine presence or absence of these three conditions from a single blood sampleThe 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 yearsLong non coding RNAslncRNAare recently discovered regulatory RNA molecules that do not code for proteins but influence a vast array of biological processesIt 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 developAs suchour data obtained in the phaseportion of this worksupport the notion that disease associated lncRNAs exhibit far greater differences in expression than disease associated mRNAsIn this applicationwe propose to explore the hypothesis that lncRNAs are better biomarkers of human disease than mRNAsHerewe will focus on FMS and the rheumatic diseases as disease categories and have identified and validated FMS and rheumatic disease associated associated differentially expressed lncRNAsStudy of lncRNAs in human autoimmune disease is in its infancy and exploration of lncRNAs as biomarkers of autoimmune disease has not been previously addressedWe propose to determine expression levels of target lncRNAs in blood obtained from larger cohorts of subjects that includesubjects with fibromyalgia syndromehealthy controlsrheumatoid arthritissystemic lupus erythematosusandperipheral autoimmune disease controls obtained from various sites in the U Sand 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 Diagnosis of fibromyalgia syndrome and other rheumatic diseases can be a difficultlong and costly process and misdiagnosis of these diseases is not uncommonBiomarkers to aid and accelerate diagnosis is an area of active investigationLong non coding RNAslncRNAsare newly discovered classes of RNAs with an array of regulatory functionsOur hypothesis to testand supported by our phasestudiesis that classifiers can be built based upon differential expression of lncRNAs in bloodThese classifiers will possess greater accuracy to identify fibromyalgia syndrome and rheumatic disease and provide meaningful clinical information to healthcare providers faced with these diagnostic dilemmas