ArticleGenes and immunity2014
A gene pathway analysis highlights the role of cellular adhesion molecules in multiple sclerosis susceptibility.
Article in Genes and immunity, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Identification of Key Genes and Regulatory Pathways in Multiple Sclerosis Brain Samples: A Meta-Analysis of Micro-Array Datasets.International journal of molecular sciences · 2023Pooled it
- Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans.Brain : a journal of neurology · 2023Article
- Brain Barriers and Multiple Sclerosis: Novel Treatment Approaches from a Brain Barriers Perspective.Handbook of experimental pharmacology · 2022Article
- Reworking GWAS Data to Understand the Role of Nongenetic Factors in MS Etiopathogenesis.Genes · 2020Review
- B and T Cells Driving Multiple Sclerosis: Identity, Mechanisms and Potential Triggers.Frontiers in immunology · 2020Review
- A Loss-of-Function Mutation in the Integrin Alpha L (Infection and immunity · 2019Article
- Pleiotropic Roles of P2X7 in the Central Nervous System.Frontiers in cellular neuroscience · 2019Review
- Five-Year Longitudinal Study of Neck Vessel Cross-Sectional Area in Multiple Sclerosis.AJNR. American journal of neuroradiology · 2018Article
- Genetic Variants and Multiple Sclerosis Risk Gene SLC9A9 Expression in Distinct Human Brain Regions.Molecular neurobiology · 2017Article
- LRCH1 interferes with DOCK8-Cdc42-induced T cell migration and ameliorates experimental autoimmune encephalomyelitis.The Journal of experimental medicine · 2017Article
- GWAS analysis implicates NF-κB-mediated induction of inflammatory T cells in multiple sclerosis.Genes and immunity · 2016Article
- Seeking balance: Potentiation and inhibition of multiple sclerosis autoimmune responses by IL-6 and IL-10.Cytokine · 2015Review
- Article
Corrections and comments
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Authors and funding
11 authors at 8 institutions in 4 countries.
Funding
Abstract
Genome-wide association studies (GWASs) perform per-SNP association tests to identify variants involved in disease or trait susceptibility. However, such an approach is not powerful enough to unravel genes that are not individually contributing to the disease/trait, but that may have a role in interaction with other genes as a group. Pathway analysis is an alternative way to highlight such group of genes. Using SNP association P-values from eight multiple sclerosis (MS) GWAS data sets, we performed a candidate pathway analysis for MS susceptibility by considering genes interacting in the cell adhesion molecule (CAMs) biological pathway using Cytoscape software. This network is a strong candidate, as it is involved in the crossing of the blood-brain barrier by the T cells, an early event in MS pathophysiology, and is used as an efficient therapeutic target. We drew up a list of 76 genes belonging to the CAM network. We highlighted 64 networks enriched with CAM genes with low P-values. Filtering by a percentage of CAM genes up to 50% and rejecting enriched signals mainly driven by transcription factors, we highlighted five networks associated with MS susceptibility. One of them, constituted of ITGAL, ICAM1 and ICAM3 genes, could be of interest to develop novel therapeutic targets.
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Registered trials
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.