ArticleBMC medical genomics2020
Dense module searching for gene networks associated with multiple sclerosis.
Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 18 citations in OpenAlex.
- The Effects and Mechanisms of Ti-Fu-Kang Decoction in Alleviating Central Fatigue: Insights from Network Pharmacology and Metabolomics.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Pharmacogenomics of clinical response to Natalizumab in multiple sclerosis: a genome-wide multi-centric association study.Journal of neurology · 2024Article
- A gene regulatory network approach harmonizes genetic and epigenetic signals and reveals repurposable drug candidates for multiple sclerosis.Human molecular genetics · 2023Article
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- Gene network revealsFrontiers in neurology · 2023Article
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- Prioritization of risk genes in multiple sclerosis by a refined Bayesian framework followed by tissue-specificity and cell type feature assessment.BMC genomics · 2022Article
- Article
- Distinct effect of prenatal and postnatal brain expression across 20 brain disorders and anthropometric social traits: a systematic study of spatiotemporal modularity.Briefings in bioinformatics · 2021Article
- An integrative study of genetic variants with brain tissue expression identifies viral etiology and potential drug targets of multiple sclerosis.Molecular and cellular neurosciences · 2021Article
- Characterization of genome-wide association study data reveals spatiotemporal heterogeneity of mental disorders.BMC medical genomics · 2020Article
- The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): computational methods and applications in medical genomics.BMC medical genomics · 2020Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMultiple sclerosis (MS) is a complex disease in which the immune system attacks the central nervous system. The molecular mechanisms contributing to the etiology of MS remain poorly understood. Genome-wide association studies (GWAS) of MS have identified a small number of genetic loci significant at the genome level, but they are mainly non-coding variants. Network-assisted analysis may help better interpret the functional roles of the variants with association signals and potential translational medicine application. The Dense Module Searching of GWAS tool (dmGWAS version 2.4) developed in our team is applied to 2 MS GWAS datasets (GeneMSA and IMSGC GWAS) using the human protein interactome as the reference network. A dual evaluation strategy is used to generate results with reproducibility.
resultsApproximately 7500 significant network modules were identified for each independent GWAS dataset, and 20 significant modules were identified from the dual evaluation. The top modules included GRB2, HDAC1, JAK2, MAPK1, and STAT3 as central genes. Top module genes were enriched with functional terms such as "regulation of glial cell differentiation" (adjusted p-value = 2.58 × 10
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.