ArticleScientific reports2018
Integrative analysis of Multiple Sclerosis using a systems biology approach.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies.BMC bioinformatics · 2019Pooled it
- Integrative Transcriptomics Uncovers IFN-β Signature and IFITM3 as Putative Molecular Mediator in MS.International journal of molecular sciences · 2026Article
- The multifaceted role of SMAD4 in immune cell function.Biochemistry and biophysics reports · 2025Review
- Gene network revealsFrontiers in neurology · 2023Article
- Multiple sclerosis and computational biology (Review).Biomedical reports · 2022Review
- Modelling liver cancer microenvironment using a novel 3D culture system.Scientific reports · 2022Article
- Subtypes of relapsing-remitting multiple sclerosis identified by network analysis.Frontiers in digital health · 2022Article
- A Final Frontier in Environment-Genome Interactions? Integrated, Multi-Omic Approaches to Predictions of Non-Communicable Disease Risk.Frontiers in genetics · 2022Review
- Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach.Frontiers in genetics · 2022Article
- Identification of viral-mediated pathogenic mechanisms in neurodegenerative diseases using network-based approaches.Briefings in bioinformatics · 2021Article
- Analysis of association between MALAT1 haplotype and the severity of normal-tension glaucoma (NTG).Journal of cellular and molecular medicine · 2021Article
- The Role of Hemoglobin Subunit Delta in the Immunopathy of Multiple Sclerosis: Mitochondria Matters.Frontiers in immunology · 2021Article
- Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis.Cellular immunology · 2020Review
- Gene Regulatory Networks in Peripheral Mononuclear Cells Reveals Critical Regulatory Modules and Regulators of Multiple Sclerosis.Scientific reports · 2019Article
- Emerging small-molecule treatments for multiple sclerosis: focus on B cells.F1000Research · 2019Review
- A potential association between IL-3 and type I and III interferons in systemic lupus erythematosus.Clinical & translational immunology · 2019Article
- Observational
- Blood platelet RNA enables the detection of multiple sclerosis.Multiple sclerosis journal - experimental, translational and clinicalArticle
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammatory-demyelinating events in the central nervous system. Despite more than 40 years of MS research its aetiology remains unknown. This study aims to identify the most frequently reported and consistently regulated molecules in MS in order to generate molecular interaction networks and thereby leading to the identification of deregulated processes and pathways which could give an insight of the underlying molecular mechanisms of MS. Driven by an integrative systems biology approach, gene-expression profiling datasets were combined and stratified into "Non-treated" and "Treated" groups and additionally compared to other disease patterns. Molecular identifiers from dataset comparisons were matched to our Multiple Sclerosis database (MuScle; www.padb.org/muscle ). From 5079 statistically significant molecules, correlation analysis within groups identified a panel of 16 high-confidence genes unique to the naïve MS phenotype, whereas the "Treated" group reflected a common pattern associated with autoimmune disease. Pathway and gene-ontology clustering identified the Interferon gamma signalling pathway as the most relevant amongst all significant molecules, and viral infections as the most likely cause of all down-stream events observed. This hypothesis-free approach revealed the most significant molecular events amongst different MS phenotypes which can be used for further detailed studies.
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