{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T16:13:39Z","timestamp":1769184819238,"version":"3.49.0"},"reference-count":31,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T00:00:00Z","timestamp":1642636800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012905","name":"Department of Science and Technology of Shandong Province","doi-asserted-by":"publisher","award":["2018103"],"award-info":[{"award-number":["2018103"]}],"id":[{"id":"10.13039\/100012905","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Multiple sclerosis is an immune-mediated demyelinating disorder of the central nervous system. Because of the complexity of etiology, pathology, clinical manifestations, and the diversity of classification, the diagnosis of MS is very difficult. We found that McDonald Criteria is very strict and relies heavily on the evidence for DIS and DIT. Therefore, we hope to find a new method to supplement the evidence and improve the accuracy of MS diagnosis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We finally selected GSE61240, GSE18781, and GSE185047 based on the GPL570 platform to build a diagnosis model. We initially selected 54 MS susceptibility locus genes identified by IMSGC and WTCCC2 as predictors for the model. After Random Forests and other series of screening, the logistic regression model was established with 4 genes as the final predictors. In external validation, the model showed high accuracy with an AUC of 0.96 and an accuracy of 86.30%. Finally, we established a nomogram and an online prediction tool to better display the diagnosis model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The diagnosis model based on microarray data in this study has a high degree of discrimination and calibration in the validation set, which is helpful for diagnosis in the absence of evidence for DIS and DIT. Only one SLE case was misdiagnosed as MS, indicating that the model has a high specificity (93.93%), which is useful for differential diagnosis. The significance of the study lies in proving that it is feasible to identify MS by peripheral blood RNA, and the further application of the model and be used as a supplement to McDonald Criteria still need to be trained with larger sample size.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fneur.2021.721788","type":"journal-article","created":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T15:04:16Z","timestamp":1642691056000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Constructing a Multiple Sclerosis Diagnosis Model Based on Microarray"],"prefix":"10.3389","volume":"12","author":[{"given":"Haoran","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyun","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiying","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiapei","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2022,1,20]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1016\/j.ncl.2016.06.016","article-title":"Epidemiology of multiple sclerosis","volume":"34","author":"Howard","year":"2016","journal-title":"Neurol Clin."},{"key":"B2","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1001\/jama.2020.26858","article-title":"Diagnosis and treatment of multiple sclerosis: a review","volume":"325","author":"McGinley","year":"2021","journal-title":"JAMA."},{"key":"B3","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/S1474-4422(14)70231-5","article-title":"Treatment of progressive multiple sclerosis: what works, what does not, and what is needed","volume":"14","author":"Feinstein","year":"2015","journal-title":"Lancet Neurol."},{"key":"B4","doi-asserted-by":"publisher","first-page":"1336","DOI":"10.1016\/S0140-6736(16)30959-X","article-title":"Diagnosis of multiple sclerosis: progress and challenges","volume":"389","author":"Brownlee","year":"2017","journal-title":"Lancet."},{"key":"B5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/00207454.2020.1812601","article-title":"Toll-like receptors 2 and 4 expression on peripheral blood lymphocytes and neutrophils of Egyptian multiple sclerosis patients","volume":"26","author":"Labib","year":"2020","journal-title":"Int J Neurosci"},{"key":"B6","doi-asserted-by":"publisher","first-page":"835","DOI":"10.3389\/fimmu.2019.00835","article-title":"Blood levels of co-inhibitory-receptors: a biomarker of disease prognosis in multiple sclerosis","volume":"10","author":"Lavon","year":"2019","journal-title":"Front Immunol."},{"key":"B7","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1038\/nature10251","article-title":"Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis","volume":"476","author":"Sawcer","year":"2011","journal-title":"Nature."},{"key":"B8","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1007\/s10888-011-9188-x","article-title":"The origins of the Gini index: extracts from Variabilit\u00e0 e Mutabilit\u00e0 (1912) by Corrado Gini","volume":"10","author":"Ceriani","year":"2012","journal-title":"J Econ Inequal."},{"key":"B9","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-62008-0_35","article-title":"RFRSF: employee turnover prediction based on random forests and survival analysis","volume-title":"Web Information Systems Engineering \u2013 WISE 2020.","author":"Jin","year":"2020"},{"key":"B10","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1080\/09720502.2010.10700699","article-title":"Collinearity diagnostics of binary logistic regression model","volume":"13","author":"Midi","year":"2010","journal-title":"J Interdiscip Math."},{"key":"B11","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/S0167-7152(01)00031-1","article-title":"Cook's distance in local polynomial regression","volume":"54","author":"Kim","year":"2001","journal-title":"Stat Probab Lett."},{"key":"B12","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/S1474-4422(17)30470-2","article-title":"Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria","volume":"17","author":"Thompson","year":"2018","journal-title":"Lancet Neurol."},{"key":"B13","doi-asserted-by":"publisher","first-page":"1419","DOI":"10.1093\/brain\/112.6.1419","article-title":"The natural history of multiple sclerosis: a geographically based study. 2. Predictive value of the early clinical course","volume":"112","author":"Weinshenker","year":"1989","journal-title":"Brain."},{"key":"B14","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1093\/brain\/112.1.133","article-title":"The natural history of multiple sclerosis: a geographically based study. I. Clinical course and disability","volume":"112","author":"Weinshenker","year":"1989","journal-title":"Brain."},{"key":"B15","doi-asserted-by":"publisher","first-page":"1001","DOI":"10.3174\/ajnr.A6547","article-title":"Value of 3T susceptibility-weighted imaging in the diagnosis of multiple sclerosis","volume":"41","author":"Clarke","year":"2020","journal-title":"AJNR Am J Neuroradiol."},{"key":"B16","doi-asserted-by":"publisher","first-page":"934","DOI":"10.1002\/ana.25461","article-title":"The \u201ccentral vein sign\u201d in inflammatory demyelination: the role of fibrillar collagen type I","volume":"85","author":"Absinta","year":"2019","journal-title":"Ann Neurol."},{"key":"B17","doi-asserted-by":"publisher","first-page":"1446","DOI":"10.1001\/jamaneurol.2019.2478","article-title":"Evaluation of the central vein sign as a diagnostic imaging biomarker in multiple sclerosis","volume":"76","author":"Sinnecker","year":"2019","journal-title":"JAMA Neurol."},{"key":"B18","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1016\/S1474-4422(21)00095-8","article-title":"2021 MAGNIMS\u2013CMSC\u2013NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis","volume":"20","author":"Wattjes","year":"2021","journal-title":"Lancet Neurol."},{"key":"B19","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1016\/S1474-4422(15)00393-2","article-title":"MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines","volume":"15","author":"Filippi","year":"2016","journal-title":"Lancet Neurol."},{"key":"B20","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.1016\/j.autrev.2015.07.014","article-title":"Peripheral blood biomarkers in multiple sclerosis","volume":"14","author":"D'Ambrosio","year":"2015","journal-title":"Autoimmun Rev."},{"key":"B21","doi-asserted-by":"publisher","first-page":"726","DOI":"10.3389\/fimmu.2019.00726","article-title":"The Cerebrospinal Fluid in Multiple Sclerosis","volume":"10","author":"Deisenhammer","year":"2019","journal-title":"Front Immunol."},{"key":"B22","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1002\/ana.22366","article-title":"Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria","volume":"69","author":"Polman","year":"2011","journal-title":"Ann Neurol."},{"key":"B23","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1186\/s40659-021-00334-6","article-title":"Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis","volume":"54","author":"Chen","year":"2021","journal-title":"Biol Res."},{"key":"B24","doi-asserted-by":"publisher","first-page":"882","DOI":"10.1093\/bioinformatics\/bts034","article-title":"The sva package for removing batch effects and other unwanted variation in high-throughput experiments","volume":"28","author":"Leek","year":"2012","journal-title":"Bioinformatics."},{"key":"B25","doi-asserted-by":"publisher","first-page":"58","DOI":"10.4049\/jimmunol.1200868","article-title":"Early growth response gene-2 controls IL-17 expression and Th17 differentiation by negatively regulating Batf","volume":"190","author":"Miao","year":"2013","journal-title":"J Immunol."},{"key":"B26","doi-asserted-by":"publisher","first-page":"7469","DOI":"10.1038\/sj.onc.1210054","article-title":"Function and biological roles of the Dickkopf family of Wnt modulators","volume":"25","author":"Niehrs","year":"2006","journal-title":"Oncogene."},{"key":"B27","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.brainres.2012.12.015","article-title":"Estrogen regulation of Dkk1 and Wnt\/\u03b2-Catenin signaling in neurodegenerative disease","volume":"1514","author":"Scott","year":"2013","journal-title":"Brain Res."},{"key":"B28","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.neulet.2012.12.040","article-title":"Region-specific expression of Dickkopf-like1 in the adult brain. Abbreviated title: Dkkl1 in the adult brain","volume":"535","author":"Sibbe","year":"2013","journal-title":"Neurosci Lett."},{"key":"B29","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1093\/bib\/bbr042","article-title":"Phylogenetic-based propagation of functional annotations within the Gene Ontology consortium","volume":"12","author":"Gaudet","year":"2011","journal-title":"Brief Bioinform."},{"key":"B30","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.jaut.2015.06.010","article-title":"The immunogenetics of multiple sclerosis: a comprehensive review","volume":"64","author":"Hollenbach","year":"2015","journal-title":"J Autoimmun."},{"key":"B31","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1002\/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4","article-title":"Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors","volume":"15","author":"Harrell","year":"1996","journal-title":"Stat Med."}],"container-title":["Frontiers in Neurology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fneur.2021.721788\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T15:04:19Z","timestamp":1642691059000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fneur.2021.721788\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,20]]},"references-count":31,"alternative-id":["10.3389\/fneur.2021.721788"],"URL":"https:\/\/doi.org\/10.3389\/fneur.2021.721788","relation":{},"ISSN":["1664-2295"],"issn-type":[{"value":"1664-2295","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,20]]},"article-number":"721788"}}