139 research outputs found

    The cytokine language of monocytes and macrophages in systemic sclerosis

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    Many important observations suggest monocyte/macrophage involvement in systemic sclerosis (SSc). A high concentration of immune mediators, such as IL-6, IL-10 and IL-13, the infiltration of mononuclear cells in affected organs and the production of autoantibodies suggest that immune system dysfunction drives SSc pathogenesis. The recently reported study by Higashi-Kuwata and colleagues, in light of other observations, provides further insight into activation of macrophages/monocytes in SSc patients, suggesting that these cells undergo distinct activation pathways. These results emphasize the need for more detailed analyses of the several markers now defined in SSc peripheral blood mononuclear cells and tissues to better define the cytokine language speaking to monocytes/macrophages in SSc that promote vascular injury and tissue fibrosis

    Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

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    Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype-phenotype associations, 26 represented phenotypes closely related to previously known genotype-phenotype associations, and 33 represented potentially novel genotype-phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits

    MultiPhen: Joint Model of Multiple Phenotypes Can Increase Discovery in GWAS

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    The genome-wide association study (GWAS) approach has discovered hundreds of genetic variants associated with diseases and quantitative traits. However, despite clinical overlap and statistical correlation between many phenotypes, GWAS are generally performed one-phenotype-at-a-time. Here we compare the performance of modelling multiple phenotypes jointly with that of the standard univariate approach. We introduce a new method and software, MultiPhen, that models multiple phenotypes simultaneously in a fast and interpretable way. By performing ordinal regression, MultiPhen tests the linear combination of phenotypes most associated with the genotypes at each SNP, and thus potentially captures effects hidden to single phenotype GWAS. We demonstrate via simulation that this approach provides a dramatic increase in power in many scenarios. There is a boost in power for variants that affect multiple phenotypes and for those that affect only one phenotype. While other multivariate methods have similar power gains, we describe several benefits of MultiPhen over these. In particular, we demonstrate that other multivariate methods that assume the genotypes are normally distributed, such as canonical correlation analysis (CCA) and MANOVA, can have highly inflated type-1 error rates when testing case-control or non-normal continuous phenotypes, while MultiPhen produces no such inflation. To test the performance of MultiPhen on real data we applied it to lipid traits in the Northern Finland Birth Cohort 1966 (NFBC1966). In these data MultiPhen discovers 21% more independent SNPs with known associations than the standard univariate GWAS approach, while applying MultiPhen in addition to the standard approach provides 37% increased discovery. The most associated linear combinations of the lipids estimated by MultiPhen at the leading SNPs accurately reflect the Friedewald Formula, suggesting that MultiPhen could be used to refine the definition of existing phenotypes or uncover novel heritable phenotypes

    Cell Invasion by Neisseria meningitidis Requires a Functional Interplay between the Focal Adhesion Kinase, Src and Cortactin

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    Entry of Neisseria meningitidis (the meningococcus) into human brain microvascular endothelial cells (HBMEC) is mediated by fibronectin or vitronectin bound to the surface protein Opc forming a bridge to the respective integrins. This interaction leads to cytoskeletal rearrangement and uptake of meningococci. In this study, we determined that the focal adhesion kinase (FAK), which directly associates with integrins, is involved in integrin-mediated internalization of N. meningitidis in HBMEC. Inhibition of FAK activity by the specific FAK inhibitor PF 573882 reduced Opc-mediated invasion of HBMEC more than 90%. Moreover, overexpression of FAK mutants that were either impaired in the kinase activity or were not capable of autophosphorylation or overexpression of the dominant-negative version of FAK (FRNK) blocked integrin-mediated internalization of N. meningitidis. Importantly, FAK-deficient fibroblasts were significantly less invaded by N. meningitidis. Furthermore, N. meningitidis induced tyrosine phosphorylation of several host proteins including the FAK/Src complex substrate cortactin. Inhibition of cortactin expression by siRNA silencing and mutation of critical amino acid residues within cortactin, that encompass Arp2/3 association and dynamin binding, significantly reduced meningococcal invasion into eukaryotic cells suggesting that both domains are critical for efficient uptake of N. meningitidis into eukaryotic cells. Together, these results indicate that N. meningitidis exploits the integrin signal pathway for its entry and that FAK mediates the transfer of signals from activated integrins to the cytoskeleton. A cooperative interplay between FAK, Src and cortactin then enables endocytosis of N. meningitidis into host cells
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