Cargando…
Dense module searching for gene networks associated with multiple sclerosis
BACKGROUND: Multiple 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 si...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118851/ https://www.ncbi.nlm.nih.gov/pubmed/32241259 http://dx.doi.org/10.1186/s12920-020-0674-5 |
_version_ | 1783514648129044480 |
---|---|
author | Manuel, Astrid M. Dai, Yulin Freeman, Leorah A. Jia, Peilin Zhao, Zhongming |
author_facet | Manuel, Astrid M. Dai, Yulin Freeman, Leorah A. Jia, Peilin Zhao, Zhongming |
author_sort | Manuel, Astrid M. |
collection | PubMed |
description | BACKGROUND: Multiple 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. RESULTS: Approximately 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(− 3)), “T-cell costimulation” (adjusted p-value = 2.11 × 10(− 6)) and “virus receptor activity” (adjusted p-value = 1.67 × 10(− 3)). Interestingly, top gene networks included several MS FDA approved drug target genes HDAC1, IL2RA, KEAP1, and RELA, CONCLUSIONS: Our dmGWAS network analyses highlighted several genes (GRB2, HDAC1, IL2RA, JAK2, KEAP1, MAPK1, RELA and STAT3) in top modules that are promising to interpret GWAS signals and link to MS drug targets. The genes enriched with glial cell differentiation are important for understanding neurodegenerative processes in MS and for remyelination therapy investigation. Importantly, our identified genetic signals enriched in T cell costimulation and viral receptor activity supported the viral infection onset hypothesis for MS. |
format | Online Article Text |
id | pubmed-7118851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71188512020-04-07 Dense module searching for gene networks associated with multiple sclerosis Manuel, Astrid M. Dai, Yulin Freeman, Leorah A. Jia, Peilin Zhao, Zhongming BMC Med Genomics Research BACKGROUND: Multiple 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. RESULTS: Approximately 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(− 3)), “T-cell costimulation” (adjusted p-value = 2.11 × 10(− 6)) and “virus receptor activity” (adjusted p-value = 1.67 × 10(− 3)). Interestingly, top gene networks included several MS FDA approved drug target genes HDAC1, IL2RA, KEAP1, and RELA, CONCLUSIONS: Our dmGWAS network analyses highlighted several genes (GRB2, HDAC1, IL2RA, JAK2, KEAP1, MAPK1, RELA and STAT3) in top modules that are promising to interpret GWAS signals and link to MS drug targets. The genes enriched with glial cell differentiation are important for understanding neurodegenerative processes in MS and for remyelination therapy investigation. Importantly, our identified genetic signals enriched in T cell costimulation and viral receptor activity supported the viral infection onset hypothesis for MS. BioMed Central 2020-04-03 /pmc/articles/PMC7118851/ /pubmed/32241259 http://dx.doi.org/10.1186/s12920-020-0674-5 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Manuel, Astrid M. Dai, Yulin Freeman, Leorah A. Jia, Peilin Zhao, Zhongming Dense module searching for gene networks associated with multiple sclerosis |
title | Dense module searching for gene networks associated with multiple sclerosis |
title_full | Dense module searching for gene networks associated with multiple sclerosis |
title_fullStr | Dense module searching for gene networks associated with multiple sclerosis |
title_full_unstemmed | Dense module searching for gene networks associated with multiple sclerosis |
title_short | Dense module searching for gene networks associated with multiple sclerosis |
title_sort | dense module searching for gene networks associated with multiple sclerosis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118851/ https://www.ncbi.nlm.nih.gov/pubmed/32241259 http://dx.doi.org/10.1186/s12920-020-0674-5 |
work_keys_str_mv | AT manuelastridm densemodulesearchingforgenenetworksassociatedwithmultiplesclerosis AT daiyulin densemodulesearchingforgenenetworksassociatedwithmultiplesclerosis AT freemanleoraha densemodulesearchingforgenenetworksassociatedwithmultiplesclerosis AT jiapeilin densemodulesearchingforgenenetworksassociatedwithmultiplesclerosis AT zhaozhongming densemodulesearchingforgenenetworksassociatedwithmultiplesclerosis |