Fyn and PTP-PEST–mediated Regulation of Wiskott-Aldrich Syndrome Protein (WASp) Tyrosine Phosphorylation Is Required for Coupling T Cell Antigen Receptor Engagement to WASp Effector Function and T Cell Activation

Involvement of the Wiskott-Aldrich syndrome protein (WASp) in promoting cell activation requires its release from autoinhibitory structural constraints and has been attributed to WASp association with activated cdc42. Here, however, we show that T cell development and T cell receptor (TCR)-induced proliferation and actin polymerization proceed normally in WASp−/− mice expressing a WASp transgene lacking the cdc42 binding domain. By contrast, mutation of tyrosine residue Y291, identified here as the major site of TCR-induced WASp tyrosine phosphorylation, abrogated induction of WASp tyrosine phosphorylation and its effector activities, including nuclear factor of activated T cell transcriptional activity, actin polymerization, and immunological synapse formation. TCR-induced WASp tyrosine phosphorylation was also disrupted in T cells lacking Fyn, a kinase shown here to bind, colocalize with, and phosphorylate WASp. By contrast, WASp was tyrosine dephosphorylated by protein tyrosine phosphatase (PTP)-PEST, a tyrosine phosphatase shown here to interact with WASp via proline, serine, threonine phosphatase interacting protein (PSTPIP)1 binding. Although Fyn enhanced WASp-mediated Arp2/3 activation and was required for synapse formation, PTP-PEST combined with PSTPIP1 inhibited WASp-driven actin polymerization and synapse formation. These observations identify key roles for Fyn and PTP-PEST in regulating WASp and imply that inducible WASp tyrosine phosphorylation can occur independently of cdc42 binding, but unlike the cdc42 interaction, is absolutely required for WASp contributions to T cell activation

Identification of the NF-κB activating protein-like locus as a risk locus for rheumatoid arthritis

Objective: To fine-map the NF-κB activating protein-like (NKAPL) locus identified in a prior genome-wide study as a possible rheumatoid arthritis (RA) risk locus and thereby delineate additional variants with stronger and/or independent disease association. Methods: Genotypes for 101 SNPs across the NKAPL locus on chromosome 6p22.1 were obtained on 1368 Canadian RA cases and 1471 controls. Single marker associations were examined using logistic regression and the most strongly associated NKAPL locus SNPs then typed in another Canadian and a US-based RA case/control cohort. Results: Fine-mapping analyses identified six NKAPL locus variants in a single haplotype block showing association with p≤5.6×10−8 in the combined Canadian cohort. Among these SNPs, rs35656932 in the zinc finger 193 gene and rs13208096 in the NKAPL gene remained significant after conditional logistic regression, contributed independently to risk for disease, and were replicated in the US cohort (Pcomb=4.24×10−10 and 2.44×10−9, respectively). These associations remained significant after conditioning on SNPs tagging the HLA-shared epitope (SE) DRB1*0401 allele and were significantly stronger in the HLA-SE negative versus positive subgroup, with a significant negative interaction apparent between HLA-DRB1 SE and NKAPL risk alleles. Conclusions: By illuminating additional NKAPL variants with highly significant effects on risk that are distinct from, but interactive with those arising from the HLA-DRB1 locus, our data conclusively identify NKAPL as an RA susceptibility locus

Data for Genetic Analysis Workshop (GAW) 15 Problem 2, Genetic Causes of Rheumatoid Arthritis and Associated Traits

For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North American Rheumatoid Arthritis Consortium (NARAC), collaboration among Canadian researchers, the European Consortium on Rheumatoid Arthritis Families (ECRAF), and investigators from Manchester, England. All groups used a common standard for defining rheumatoid arthritis, but NARAC also further selected for a more severe phenotype in the probands. Genotyping and family structures for microsatellite-based linkage analysis were provided from all centers. In addition, all centers but ECRAF have genotyped families for linkage analysis using SNPs and these data were additionally provided. NARAC also had additional data from a dense genotyping analysis of a region of chromosome 18 and results from candidate gene studies, which were provided. Finally, smoking influences risk for rheumatoid arthritis, and data were provided from the NARAC study on this behavior as well as some additional phenotypes measuring severity. Several questions could be evaluated using the data that were provided. These include comparing linkage analysis using single-nucleotide polymorphisms versus microsatellites and identifying credible regions of linkage outside the HLA region on chromosome 6p13, which has been extensively documented; evaluating the joint effects of smoking with genetic factors; and identifying more homogenous subsets of families for whom genetic susceptibility might be stronger, so that linkage and association studies may be more efficiently conducted

Data for Genetic Analysis Workshop (GAW) 15 Problem 2, genetic causes of rheumatoid arthritis and associated traits

For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North American Rheumatoid Arthritis Consortium (NARAC), collaboration among Canadian researchers, the European Consortium on Rheumatoid Arthritis Families (ECRAF), and investigators from Manchester, England. All groups used a common standard for defining rheumatoid arthritis, but NARAC also further selected for a more severe phenotype in the probands. Genotyping and family structures for microsatellite-based linkage analysis were provided from all centers. In addition, all centers but ECRAF have genotyped families for linkage analysis using SNPs and these data were additionally provided. NARAC also had additional data from a dense genotyping analysis of a region of chromosome 18 and results from candidate gene studies, which were provided. Finally, smoking influences risk for rheumatoid arthritis, and data were provided from the NARAC study on this behavior as well as some additional phenotypes measuring severity. Several questions could be evaluated using the data that were provided. These include comparing linkage analysis using single-nucleotide polymorphisms versus microsatellites and identifying credible regions of linkage outside the HLA region on chromosome 6p13, which has been extensively documented; evaluating the joint effects of smoking with genetic factors; and identifying more homogenous subsets of families for whom genetic susceptibility might be stronger, so that linkage and association studies may be more efficiently conducted

Integration of Sequence Data from a Consanguineous Family with Genetic Data from an Outbred Population Identifies PLB1 as a Candidate Rheumatoid Arthritis Risk Gene

Integrating genetic data from families with highly penetrant forms of disease together with genetic data from outbred populations represents a promising strategy to uncover the complete frequency spectrum of risk alleles for complex traits such as rheumatoid arthritis (RA). Here, we demonstrate that rare, low-frequency and common alleles at one gene locus, phospholipase B1 (PLB1), might contribute to risk of RA in a 4-generation consanguineous pedigree (Middle Eastern ancestry) and also in unrelated individuals from the general population (European ancestry). Through identity-by-descent (IBD) mapping and whole-exome sequencing, we identified a non-synonymous c.2263G>C (p.G755R) mutation at the PLB1 gene on 2q23, which significantly co-segregated with RA in family members with a dominant mode of inheritance (P = 0.009). We further evaluated PLB1 variants and risk of RA using a GWAS meta-analysis of 8,875 RA cases and 29,367 controls of European ancestry. We identified significant contributions of two independent non-coding variants near PLB1 with risk of RA (rs116018341 [MAF = 0.042] and rs116541814 [MAF = 0.021], combined P = 3.2×10−6). Finally, we performed deep exon sequencing of PLB1 in 1,088 RA cases and 1,088 controls (European ancestry), and identified suggestive dispersion of rare protein-coding variant frequencies between cases and controls (P = 0.049 for C-alpha test and P = 0.055 for SKAT). Together, these data suggest that PLB1 is a candidate risk gene for RA. Future studies to characterize the full spectrum of genetic risk in the PLB1 genetic locus are warranted

Genetic Variants in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: A Bayesian Approach and Systematic Review.

A number of genome-wide association studies (GWASs) and meta-analyses of genetic variants have been performed in antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis. We reinterpreted previous studies using false-positive report probability (FPRP) and Bayesian false discovery probability (BFDP). This study searched publications in PubMed and Excerpta Medica Database (EMBASE) up to February 2018. Identification of noteworthy associations were analyzed using FPRP and BFDP, and data (i.e., odds ratio (OR), 95% confidence interval (CI), p-value) related to significant associations were separately extracted. Using filtered gene variants, gene ontology (GO) enrichment analysis and protein⁻protein interaction (PPI) networks were performed. Overall, 241 articles were identified, and 7 were selected for analysis. Single nucleotide polymorphisms (SNPs) discovered by GWASs were shown to be noteworthy, whereas only 27% of significant results from meta-analyses of observational studies were noteworthy. Eighty-five percent of SNPs with borderline p-values (5.0 × 10-8 < p < 0.05) in GWASs were found to be noteworthy. No overlapping SNPs were found between PR3-ANCA and MPO-ANCA vasculitis. GO analysis revealed immune-related GO terms, including "antigen processing and presentation of peptide or polysaccharide antigen via major histocompatibility complex (MHC) class II", "interferon-gamma-mediated (IFN-γ) signaling pathway". By using FPRP and BFDP, network analysis of noteworthy genetic variants discovered genetic risk factors associated with the IFN-γ pathway as novel mechanisms potentially implicated in the complex pathogenesis of ANCA-associated vasculitis

Meta-Analysis of Genome-Wide Association Studies in Celiac Disease and Rheumatoid Arthritis Identifies Fourteen Non-HLA Shared Loci

Epidemiology and candidate gene studies indicate a shared genetic basis for celiac disease (CD) and rheumatoid arthritis (RA), but the extent of this sharing has not been systematically explored. Previous studies demonstrate that 6 of the established non-HLA CD and RA risk loci (out of 26 loci for each disease) are shared between both diseases. We hypothesized that there are additional shared risk alleles and that combining genome-wide association study (GWAS) data from each disease would increase power to identify these shared risk alleles. We performed a meta-analysis of two published GWAS on CD (4,533 cases and 10,750 controls) and RA (5,539 cases and 17,231 controls). After genotyping the top associated SNPs in 2,169 CD cases and 2,255 controls, and 2,845 RA cases and 4,944 controls, 8 additional SNPs demonstrated P<5×10−8 in a combined analysis of all 50,266 samples, including four SNPs that have not been previously confirmed in either disease: rs10892279 near the DDX6 gene (Pcombined = 1.2×10−12), rs864537 near CD247 (Pcombined = 2.2×10−11), rs2298428 near UBE2L3 (Pcombined = 2.5×10−10), and rs11203203 near UBASH3A (Pcombined = 1.1×10−8). We also confirmed that 4 gene loci previously established in either CD or RA are associated with the other autoimmune disease at combined P<5×10−8 (SH2B3, 8q24, STAT4, and TRAF1-C5). From the 14 shared gene loci, 7 SNPs showed a genome-wide significant effect on expression of one or more transcripts in the linkage disequilibrium (LD) block around the SNP. These associations implicate antigen presentation and T-cell activation as a shared mechanism of disease pathogenesis and underscore the utility of cross-disease meta-analysis for identification of genetic risk factors with pleiotropic effects between two clinically distinct diseases

Pervasive Sharing of Genetic Effects in Autoimmune Disease

Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases—as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple—but not all—immune-mediated diseases (SNP-wise PCPMA<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis