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      Does gamma-aminobutyric acid (GABA) influence the development of chronic inflammation in rheumatoid arthritis?

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      Author(s): 1 , 1 , 1 ,
      Publication date (Electronic):
      Journal: Journal of Neuroinflammation
      Publisher: BioMed Central

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          Abstract

          Background

          Recent studies have demonstrated a role for spinal p38 MAP kinase (MAPK) in the development of chronic inflammation and peripheral arthritis and a role for GABA in the inhibition of p38 MAPK mediated effects. Integrating these data suggests that GABA may play a role in downregulating mechanisms that lead to the production of proinflammatory agents such as interleukin-1, interleukin-6, and matrix metalloproteinase 3 – agents implicated in the pathogenesis of rheumatoid arthritis (RA). Genetic studies have also associated RA with members of the p38 MAPK pathway.

          Hypothesis

          We propose a hypothesis for an inefficient GABA signaling system that results in unchecked proinflammatory cytokine production via the p38 MAPK pathway. This model also supports the need for increasing research in the integration of immunology and neuroscience.

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          Gene map of the extended human MHC.

          Roger Horton, Laurens Wilming, Vikki Rand … (2004)
          The major histocompatibility complex (MHC) is the most important region in the vertebrate genome with respect to infection and autoimmunity, and is crucial in adaptive and innate immunity. Decades of biomedical research have revealed many MHC genes that are duplicated, polymorphic and associated with more diseases than any other region of the human genome. The recent completion of several large-scale studies offers the opportunity to assimilate the latest data into an integrated gene map of the extended human MHC. Here, we present this map and review its content in relation to paralogy, polymorphism, immune function and disease.
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            STAT4 and the risk of rheumatoid arthritis and systemic lupus erythematosus.

            Elaine Remmers, Robert Plenge, Annette T. Lee … (2007)
            Rheumatoid arthritis is a chronic inflammatory disease with a substantial genetic component. Susceptibility to disease has been linked with a region on chromosome 2q. We tested single-nucleotide polymorphisms (SNPs) in and around 13 candidate genes within the previously linked chromosome 2q region for association with rheumatoid arthritis. We then performed fine mapping of the STAT1-STAT4 region in a total of 1620 case patients with established rheumatoid arthritis and 2635 controls, all from North America. Implicated SNPs were further tested in an independent case-control series of 1529 patients with early rheumatoid arthritis and 881 controls, all from Sweden, and in a total of 1039 case patients and 1248 controls from three series of patients with systemic lupus erythematosus. A SNP haplotype in the third intron of STAT4 was associated with susceptibility to both rheumatoid arthritis and systemic lupus erythematosus. The minor alleles of the haplotype-defining SNPs were present in 27% of chromosomes of patients with established rheumatoid arthritis, as compared with 22% of those of controls (for the SNP rs7574865, P=2.81x10(-7); odds ratio for having the risk allele in chromosomes of patients vs. those of controls, 1.32). The association was replicated in Swedish patients with recent-onset rheumatoid arthritis (P=0.02) and matched controls. The haplotype marked by rs7574865 was strongly associated with lupus, being present on 31% of chromosomes of case patients and 22% of those of controls (P=1.87x10(-9); odds ratio for having the risk allele in chromosomes of patients vs. those of controls, 1.55). Homozygosity of the risk allele, as compared with absence of the allele, was associated with a more than doubled risk for lupus and a 60% increased risk for rheumatoid arthritis. A haplotype of STAT4 is associated with increased risk for both rheumatoid arthritis and systemic lupus erythematosus, suggesting a shared pathway for these illnesses. Copyright 2007 Massachusetts Medical Society.
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              Accounting for human polymorphisms predicted to affect protein function.

              Pauline C. Ng, Steven Henikoff (2002)
              A major interest in human genetics is to determine whether a nonsynonymous single-base nucleotide polymorphism (nsSNP) in a gene affects its protein product and, consequently, impacts the carrier's health. We used the SIFT (Sorting Intolerant From Tolerant) program to predict that 25% of 3084 nsSNPs from dbSNP, a public SNP database, would affect protein function. Some of the nsSNPs predicted to affect function were variants known to be associated with disease. Others were artifacts of SNP discovery. Two reports have indicated that there are thousands of damaging nsSNPs in an individual's human genome; we find the number is likely to be much lower.
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                Author and article information

                Journal
                Journal ID (nlm-ta): J Neuroinflammation
                Title: Journal of Neuroinflammation
                Publisher: BioMed Central
                ISSN (Electronic): 1742-2094
                Publication date Collection: 2008
                Publication date (Electronic): 3 January 2008
                Volume: 5
                Page: 1
                Affiliations
                [1 ]Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
                Article
                Publisher ID: 1742-2094-5-1
                DOI: 10.1186/1742-2094-5-1
                PMC ID: 2235846
                PubMed ID: 18171484
                SO-VID: 0eeb06d5-c3d2-4d90-9b4c-fa7fbb13f9b9
                Copyright © Copyright © 2008 Kelley et al; licensee BioMed Central Ltd.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 28 October 2007
                Date accepted : 3 January 2008
                Categories
                Subject: Hypothesis

                ScienceOpen disciplines: Neurosciences
                Data availability:
                ScienceOpen disciplines: Neurosciences

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