{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T09:28:18Z","timestamp":1789810098526,"version":"4.0.1"},"reference-count":87,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:00:00Z","timestamp":1755907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institutes of Health","award":["P20GM103436"],"award-info":[{"award-number":["P20GM103436"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease affecting approximately 1 million people in the United States. Despite extensive research into the mechanisms of disease development, many aspects of the biological changes during MS progression and the varying symptoms among patients remain unclear. In the era of high-throughput sequencing, transcriptome databases are flooded with data. However, bulk RNA sequencing (RNA-seq) data are typically used only for differential gene expression analysis. Alternative splicing, a key process that alters the transcriptome, can also be identified from bulk data. Here, we accessed 11 studies with bulk RNA-seq data of postmortem MS patients\u2019 brain samples via NCBI\u2019s Gene Expression Omnibus (GEO). We extracted additional information from these data by identifying exclusively alternatively spliced genes via replicate multivariate analysis of transcript splicing (rMATS) analysis. Our analyses revealed that changes in RNA splicing mediate distinct biological signals compared to those driven by differential gene expression. Gene ontology and protein do-main analyses of genes exclusively regulated by alternative splicing revealed distinct molecular differences between progressive and relapsing\u2013remitting MS as well as among lesions from different brain regions and between white and gray matter. These findings highlight the critical role of alternative splicing and its associated pathways in MS disease development and progression.<\/jats:p>","DOI":"10.3390\/ijms26178195","type":"journal-article","created":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T00:10:36Z","timestamp":1756080636000},"page":"8195","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Systematic Analysis of Alternative Splicing in Transcriptomes of Multiple Sclerosis Patient Brain Samples"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7000-9914","authenticated-orcid":false,"given":"M\u00fcge","family":"Sak","sequence":"first","affiliation":[{"name":"Kentucky IDeA Networks of Biomedical Research Excellence Data Science Core, Department of Neuroscience Training, University of Louisville, Louisville, KY 40292, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia H.","family":"Chariker","sequence":"additional","affiliation":[{"name":"Kentucky IDeA Networks of Biomedical Research Excellence Data Science Core, Department of Neuroscience Training, University of Louisville, Louisville, KY 40292, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3487-6572","authenticated-orcid":false,"given":"Eric C.","family":"Rouchka","sequence":"additional","affiliation":[{"name":"Kentucky IDeA Networks of Biomedical Research Excellence Data Science Core, Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY 40292, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"152","DOI":"10.3892\/br.2014.407","article-title":"Mechanism of Alternative Splicing and Its Regulation","volume":"3","author":"Wang","year":"2015","journal-title":"Biomed. 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