{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T19:35:29Z","timestamp":1789328129769,"version":"build-2803163510"},"reference-count":44,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T00:00:00Z","timestamp":1782345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ruth and Robert Wershkoff Multiple Sclerosis Research Fund"},{"name":"UIC Chancellor\u2019s Fund"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background\/Objectives: Our prior epigenome-wide association study (EWAS) on multiple sclerosis (MS) identified myeloid-associated methylation signatures and an association with enhancer regions. Here we compared differential DNA methylation across three central nervous system inflammatory disorders: MS, neuromyelitis optica (NMO), and neurologic post-acute sequelae of COVID-19 (neuro-PASC). Methods: Whole-blood DNA was profiled on Infinium MethylationEPIC arrays. Analyses included EWAS at the CpG level, differentially methylation region (DMR) analysis, and gene regulatory-element enrichment using Locus Overlap Analysis (LOLA). Limma linear models were adjusted for race, EPIC array version, age, sex, disease-modifying treatment class, and blood cell composition. Results: All three diseases were associated with broad CpG-level differential methylation. The most robust findings were disease-specific DMR signatures in gene regulatory regions. All three diseases shared Lamin B1-anchored chromatin states as an architectural genomic feature but differed in immune regulatory transcription factor binding sites (TFBS), RNA polymerase (Pol II) occupancy, and DNase accessibility. MS was enriched for TFBS in myeloid CEBPB and SPI1\/PU.1 and lymphocyte-associated RUNX3, EBF1, and BATF. MS hypomethylated DMRs were concentrated at active enhancers and myeloid TFBS, suggestive of chronic myeloid activation. NMO showed the clearest promoter and B lymphocyte associated profile. Neuro-PASC was associated with hematopoietic DNase accessibility and TFBS for BATF and EBF1. Conclusions: These results suggest that DNA methylation in MS, NMO, and neuro-PASC differ meaningfully in regulatory architecture rather than conforming to a single shared disease-associated methylation model. A long-term goal is to develop immune therapies for newly recognized diseases such as neuro-PASC.<\/jats:p>","DOI":"10.3390\/jcm15134968","type":"journal-article","created":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:49:23Z","timestamp":1782434963000},"page":"4968","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Distinct Regulatory DNA Methylation Signatures Across Multiple Sclerosis, Neuromyelitis Optica, and Neurological Post-Acute Sequelae of COVID-19"],"prefix":"10.3390","volume":"15","author":[{"given":"Syed Ilyas","family":"Munzir","sequence":"first","affiliation":[{"name":"Department of Neurology and Rehabilitation, University of Illinois College of Medicine at Chicago, Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6179-0793","authenticated-orcid":false,"given":"Daniel B.","family":"Hier","sequence":"additional","affiliation":[{"name":"Department of Neurology and Rehabilitation, University of Illinois College of Medicine at Chicago, Chicago, IL 60616, USA"},{"name":"Center for Artificial Intelligence and Autonomous Systems, Kummer Institute, Missouri University of Science and Technology, Rolla, MO 65409, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael D.","family":"Carrithers","sequence":"additional","affiliation":[{"name":"Department of Neurology and Rehabilitation, University of Illinois College of Medicine at Chicago, Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.jaut.2009.09.008","article-title":"Recent Insights in the Epidemiology of Autoimmune Diseases: Improved Prevalence Estimates and Understanding of Clustering of Diseases","volume":"33","author":"Cooper","year":"2009","journal-title":"J. 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