ArticlePloS one2012
Protein-protein interaction analysis highlights additional loci of interest for multiple sclerosis.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- Upregulation of MTOR, RPS6KB1, and EIF4EBP1 in the whole blood samples of Iranian patients with multiple sclerosis compared to healthy controls.Metabolic brain disease · 2020Article
- Protein-Protein interactions uncover candidate 'core genes' within omnigenic disease networks.PLoS genetics · 2020Article
- Molecular signature of different lesion types in the brain white matter of patients with progressive multiple sclerosis.Acta neuropathologica communications · 2019Article
- Network analysis of common genes related to esophageal, gastric, and colon cancers.Gastroenterology and hepatology from bed to bench · 2017Article
- Systematic protein-protein interaction and pathway analyses in the idiopathic inflammatory myopathies.Arthritis research & therapy · 2016Article
- Network.assisted analysis to prioritize GWAS results: principles, methods and perspectives.Human genetics · 2014Review
- Protein-protein interaction networks (PPI) and complex diseases.Gastroenterology and hepatology from bed to bench · 2014Review
- What is the Real Fate of Vitamin D in Multiple Sclerosis?International journal of preventive medicine · 2013Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
Abstract
Genetic factors play an important role in determining the risk of multiple sclerosis (MS). The strongest genetic association in MS is located within the major histocompatibility complex class II region (MHC), but more than 50 MS loci of modest effect located outside the MHC have now been identified. However, the relative candidate genes that underlie these associations and their functions are largely unknown. We conducted a protein-protein interaction (PPI) analysis of gene products coded in loci recently reported to be MS associated at the genome-wide significance level and in loci suggestive of MS association. Our aim was to identify which suggestive regions are more likely to be truly associated, which genes are mostly implicated in the PPI network and their expression profile. From three recent independent association studies, SNPs were considered and divided into significant and suggestive depending on the strength of the statistical association. Using the Disease Association Protein-Protein Link Evaluator tool we found that direct interactions among genetic products were significantly higher than expected by chance when considering both significant regions alone (p<0.0002) and significant plus suggestive (p<0.007). The number of genes involved in the network was 43. Of these, 23 were located within suggestive regions and many of them directly interacted with proteins coded within significant regions. These included genes such as SYK, IL-6, CSF2RB, FCLR3, EIF4EBP2 and CHST12. Using the gene portal BioGPS, we tested the expression of these genes in 24 different tissues and found the highest values among immune-related cells as compared to non-immune tissues (p<0.001). A gene ontology analysis confirmed the immune-related functions of these genes. In conclusion, loci currently suggestive of MS association interact with and have similar expression profiles and function as those significantly associated, highlighting the fact that more common variants remain to be found to be associated to MS.
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