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Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics

Gianmarco Abbadessa Orcid Logo, Ai Nagano, Simon Hametner, Owain Howell Orcid Logo, David Owen, Artemis Papadaki Orcid Logo, Prashant Srivastava, Simona Bonavita, Roberta Magliozzi Orcid Logo, Richard Reynolds, Mie Rizig, Richard Nicholas Orcid Logo

Annals of Neurology

Swansea University Author: Owain Howell Orcid Logo

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DOI (Published version): 10.1002/ana.27216

Abstract

ObjectivesRapid advances in transcriptomics have driven efforts to identify deregulated pathways in multiple sclerosis (MS) tissues, though many detected differentially expressed genes are likely false positives, with only a small fraction reflecting actual pathological events. Robust, integrative m...

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Published in: Annals of Neurology
ISSN: 0364-5134 1531-8249
Published: Wiley 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa68903
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Robust, integrative methods are essential for accurately understanding the molecular mechanisms underlying MS pathology.MethodsWe conducted a gene prioritization analysis of MS white matter pathology transcriptomic studies. Articles were sought in Scopus and PubMed up to July 31, 2024. Potentially eligible publications were those that provided either transcriptomics datasets (deposited in GEO) or lists of differentially expressed genes comparing MS white matter to control white matter.ResultsApplying a vote-count strategy to search for the intersection of genes reported in multiple independent studies with a consistent fold-change direction, followed by a Monte Carlo simulation, we identified 528 highly significant differentially expressed multi-study genes (p&#x2009;&lt;&#x2009;0.0001; 10,000 simulations). Functional enrichment analysis revealed deregulation of the folate pathway in MS normal-appearing white matter, and tumor necrosis factor (TNF) -related and complement-related pathways in active and chronic active lesions, respectively. Network analysis identified 6 key signaling hubs: PTPRC, HLA-B, MYC, MMP2, COL11A2, MAG. The major nodes identified revealed mechanistic concordance with published in vivo MS models, supporting their value as potential therapeutic targets.InterpretationOur strategy provides a robust framework for integrating gene expression data, effectively identifying the intricate pathways altered in human diseased tissues. This method holds potential for translating findings into drug development strategies. 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spelling 2025-03-25T15:04:35.2052539 v2 68903 2025-02-17 Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics 58c995486fc93a242b987640b692db8c 0000-0003-2157-9157 Owain Howell Owain Howell true false 2025-02-17 MEDS ObjectivesRapid advances in transcriptomics have driven efforts to identify deregulated pathways in multiple sclerosis (MS) tissues, though many detected differentially expressed genes are likely false positives, with only a small fraction reflecting actual pathological events. Robust, integrative methods are essential for accurately understanding the molecular mechanisms underlying MS pathology.MethodsWe conducted a gene prioritization analysis of MS white matter pathology transcriptomic studies. Articles were sought in Scopus and PubMed up to July 31, 2024. Potentially eligible publications were those that provided either transcriptomics datasets (deposited in GEO) or lists of differentially expressed genes comparing MS white matter to control white matter.ResultsApplying a vote-count strategy to search for the intersection of genes reported in multiple independent studies with a consistent fold-change direction, followed by a Monte Carlo simulation, we identified 528 highly significant differentially expressed multi-study genes (p < 0.0001; 10,000 simulations). Functional enrichment analysis revealed deregulation of the folate pathway in MS normal-appearing white matter, and tumor necrosis factor (TNF) -related and complement-related pathways in active and chronic active lesions, respectively. Network analysis identified 6 key signaling hubs: PTPRC, HLA-B, MYC, MMP2, COL11A2, MAG. The major nodes identified revealed mechanistic concordance with published in vivo MS models, supporting their value as potential therapeutic targets.InterpretationOur strategy provides a robust framework for integrating gene expression data, effectively identifying the intricate pathways altered in human diseased tissues. This method holds potential for translating findings into drug development strategies. ANN NEUROL 2025 Journal Article Annals of Neurology 0 Wiley 0364-5134 1531-8249 14 2 2025 2025-02-14 10.1002/ana.27216 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee G.A. was supported by the European Academy of Neurology (EAN) Research Fellowship 2024. 2025-03-25T15:04:35.2052539 2025-02-17T14:35:23.0692934 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Biomedical Science Gianmarco Abbadessa 0000-0001-8912-3055 1 Ai Nagano 2 Simon Hametner 3 Owain Howell 0000-0003-2157-9157 4 David Owen 5 Artemis Papadaki 0000-0002-2295-3713 6 Prashant Srivastava 7 Simona Bonavita 8 Roberta Magliozzi 0000-0001-8284-7763 9 Richard Reynolds 10 Mie Rizig 11 Richard Nicholas 0000-0003-0414-1225 12 68903__33880__0addfaf66253435a8024f85da14e565a.pdf 68903.VoR.pdf 2025-03-25T14:19:00.1279967 Output 8190050 application/pdf Version of Record true © 2025 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics
spellingShingle Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics
Owain Howell
title_short Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics
title_full Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics
title_fullStr Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics
title_full_unstemmed Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics
title_sort Mapping Molecular Pathways of Multiple Sclerosis: A Gene Prioritization and Network Analysis of White Matter Pathology Transcriptomics
author_id_str_mv 58c995486fc93a242b987640b692db8c
author_id_fullname_str_mv 58c995486fc93a242b987640b692db8c_***_Owain Howell
author Owain Howell
author2 Gianmarco Abbadessa
Ai Nagano
Simon Hametner
Owain Howell
David Owen
Artemis Papadaki
Prashant Srivastava
Simona Bonavita
Roberta Magliozzi
Richard Reynolds
Mie Rizig
Richard Nicholas
format Journal article
container_title Annals of Neurology
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publishDate 2025
institution Swansea University
issn 0364-5134
1531-8249
doi_str_mv 10.1002/ana.27216
publisher Wiley
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Biomedical Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Biomedical Science
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description ObjectivesRapid advances in transcriptomics have driven efforts to identify deregulated pathways in multiple sclerosis (MS) tissues, though many detected differentially expressed genes are likely false positives, with only a small fraction reflecting actual pathological events. Robust, integrative methods are essential for accurately understanding the molecular mechanisms underlying MS pathology.MethodsWe conducted a gene prioritization analysis of MS white matter pathology transcriptomic studies. Articles were sought in Scopus and PubMed up to July 31, 2024. Potentially eligible publications were those that provided either transcriptomics datasets (deposited in GEO) or lists of differentially expressed genes comparing MS white matter to control white matter.ResultsApplying a vote-count strategy to search for the intersection of genes reported in multiple independent studies with a consistent fold-change direction, followed by a Monte Carlo simulation, we identified 528 highly significant differentially expressed multi-study genes (p < 0.0001; 10,000 simulations). Functional enrichment analysis revealed deregulation of the folate pathway in MS normal-appearing white matter, and tumor necrosis factor (TNF) -related and complement-related pathways in active and chronic active lesions, respectively. Network analysis identified 6 key signaling hubs: PTPRC, HLA-B, MYC, MMP2, COL11A2, MAG. The major nodes identified revealed mechanistic concordance with published in vivo MS models, supporting their value as potential therapeutic targets.InterpretationOur strategy provides a robust framework for integrating gene expression data, effectively identifying the intricate pathways altered in human diseased tissues. This method holds potential for translating findings into drug development strategies. ANN NEUROL 2025
published_date 2025-02-14T07:32:41Z
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