Clustering of disease features within 512 multicase rheumatoid arthritis families

Does persistence to methotrexate treatment in early rheumatoid arthritis have a familial component?

Objectives

To assess whether persistence to treatment with methotrexate (MTX) in early rheumatoid arthritis (RA) is shared among first-degree relatives with RA and to estimate any underlying heritability.

Methods

First-degree relative pairs diagnosed with RA 1999–2018 and starting MTX (in monotherapy) as their first disease-modifying anti-rheumatic drug (DMARD) treatment were identified by linking the Swedish Rheumatology Quality Register to national registers. Short- and long-term persistence to MTX was defined as remaining on treatment at 1 and 3 years, respectively, with no additional DMARDs added. We assessed familial aggregation through relative risks (RR) using log-binomial regression with robust standard errors and estimated heritability using tetrachoric correlations. We also explored the familial aggregation of EULAR treatment response after 3 and 6 months. To mimic the clinical setting, we also tested the association between having a family history of MTX persistence and persistence within the index patient.

Results

Familial persistence was not associated with persistence at 1 (RR=1.02, 95% CI 0.87–1.20), only at 3 (RR=1.41, 95% CI 1.14–1.74) years. Heritability at 1 and 3 years was estimated to be 0.08 (95% CI 0–0.43) and 0.58 (95% CI 0.27–0.89), respectively. No significant associations were found between family history and EULAR response at 3 and 6 months, neither overall nor in the clinical setting analysis.

Conclusions

Our findings imply a familial component, including a possible genetic element, within the long-term persistence to MTX following RA diagnosis. Whether this component is reflective of characteristics of the underlying RA disease or determinants for sustained response to MTX in itself will require further investigation.

Family History of Rheumatic, Autoimmune, and Nonautoimmune Diseases and Risk of Rheumatoid Arthritis

OBJECTIVE

Since comorbidities such as autoimmune diseases may be associated with rheumatoid arthritis (RA) risk, we hypothesized that a family history of these other conditions might also predict RA. Therefore, we aimed to determine the association between family history of 79 comorbidities and RA.

METHODS

This case-control study identified 821 cases of RA in the Mayo Clinic Biobank (positive predictive value 95%) and matched 3 controls to each case based on age, sex, recruitment year, and location. Patients self reported family history and characteristics (adjusted). Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for RA risk according to the presence of family history for each comorbidity, adjusted for body mass index, race, and smoking.

RESULTS

Family history of several conditions was associated with developing RA, including rheumatic autoimmune diseases (ORadj 1.89 [95% CI 1.41-2.52]), pulmonary fibrosis (ORadj 2.12 [95% CI 1.16-3.80]), inflammatory bowel disease (ORadj 1.45 [95% CI 1.05-1.98]), hyper/hypothyroidism (ORadj 1.34 [95% CI 1.10-1.63]), and obstructive sleep apnea (ORadj 1.28 [95% CI 1.05-1.55]). Parkinson's disease and type 2 diabetes mellitus were associated with a statistically decreased risk of RA that did not reach the prespecified significance threshold of P < 0.01 (ORadj 0.70 [95% CI 0.49-0.98] and ORadj 0.81 [95% CI 0.67-0.97], respectively). Analyses among 143 cases of incident RA were similar and also suggested an association with a family history of autism (OR 10.5 [95% CI 2.51-71.3]).

CONCLUSION

Family history of several autoimmune and nonautoimmune comorbidities was associated with increased risk of RA, providing an opportunity to identify novel populations at risk for RA.

The family history of rheumatoid arthritis in anti-cyclic citrullinated peptide antibody-positive patient is not a predictor of poor clinical presentation and treatment response with modern classification criteria and treatment strategy: the ANSWER cohort study

A family history of rheumatoid arthritis (RA) is a strong risk factor for developing RA, affecting both genetically and environmentally. However, whether family history provides clinically relevant information in the modern classification and treatment remains largely unknown. This study aimed to determine whether a family history of RA is associated with a different clinical presentation of RA and treatment response. We retrospectively evaluated the demographic data and disease activity of newly diagnosed RA patients at baseline, 1 year, and 2 years after onset, using the ANSWER (Kansai consortium for the well-being of rheumatic disease patients) cohort data. Thirty-one patients (11.9%) among 260 newly diagnosed RA patients had a family history of RA up to second degree. There was no significant difference in the age at onset, time from onset to first visit, sex, positivity or value of rheumatoid factor or anti-cyclic citrullinated peptide antibody (ACPA), or disease activity between patients with and without a family history of RA. However, patients who had a family history of RA and were ACPA positive showed significantly lower erythrocyte sedimentation rate, and C-reactive protein. Disease activity in patients with a family history was not worse at baseline, after 1 year or 2 years of treatment. The Larsen score 2 years after onset was equivalent between the patients with and without a family history of RA in ACPA-positive patients. Family history of RA in ACPA-positive patients is not associated with high disease activity at baseline and is not a predictor of poor outcome 2 years after onset.

Systematic approach demonstrates enrichment of multiple interactions between non-HLA risk variants and HLA-DRB1 risk alleles in rheumatoid arthritis

OBJECTIVE

In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), a particular subset of HLA-DRB1 alleles, called shared epitope (SE) alleles, is a highly influential genetic risk factor. Here, we investigated whether non-HLA single nucleotide polymorphisms (SNP), conferring low disease risk on their own, interact with SE alleles more frequently than expected by chance and if such genetic interactions influence the HLA-DRB1 SE effect concerning risk to ACPA-positive RA.

METHODS

We computed the attributable proportion (AP) due to additive interaction at genome-wide level for two independent ACPA-positive RA cohorts: the Swedish epidemiological investigation of rheumatoid arthritis (EIRA) and the North American rheumatoid arthritis consortium (NARAC). Then, we tested for differences in the AP p value distributions observed for two groups of SNPs, non-associated and associated with disease. We also evaluated whether the SNPs in interaction with HLA-DRB1 were cis-eQTLs in the SE alleles context in peripheral blood mononuclear cells from patients with ACPA-positive RA (SE-eQTLs).

RESULTS

We found a strong enrichment of significant interactions (AP p<0.05) between the HLA-DRB1 SE alleles and the group of SNPs associated with ACPA-positive RA in both cohorts (Kolmogorov-Smirnov test D=0.35 for EIRA and D=0.25 for NARAC, p<2.2e-16 for both). Interestingly, 564 out of 1492 SNPs in consistent interaction for both cohorts were significant SE-eQTLs. Finally, we observed that the effect size of HLA-DRB1 SE alleles for disease decreases from 5.2 to 2.5 after removal of the risk alleles of the two top interacting SNPs (rs2476601 and rs10739581).

CONCLUSION

Our data demonstrate that there are massive genetic interactions between the HLA-DRB1 SE alleles and non-HLA genetic variants in ACPA-positive RA.

Beyond disease susceptibility-Leveraging genome-wide association studies for new insights into complex disease biology

Genetic studies in complex diseases have been highly successful, but have also been largely one-dimensional: predominantly focusing on the genetic contribution to disease susceptibility. While this is undoubtedly important-indeed it is a pre-requisite for understanding the mechanisms underlying disease development-there are many other important aspects of disease biology that have received comparatively little attention. In this review, I will discuss how existing genetic data can be leveraged to provide new insights into other aspects of disease biology, why such insights could change the way we think about complex disease, and how this could provide opportunities for better therapies and/or facilitate personalised medicine. To do this, I will use the example of Crohn's disease-a chronic form of inflammatory bowel disease that has been one of the main success stories in complex disease genetics. Indeed, thanks to genetic studies, we now have a much more detailed understanding of the processes involved in Crohn's disease development, but still know relatively little about what determines the subsequent disease course (prognosis) and why this differs so considerably between individuals. I will discuss how we came to realise that genetic variation plays an important role in determining disease prognosis and how this has changed the way we think about Crohn's disease genetics. This will illustrate how phenotypic data can be used to leverage new insights from genetic data and will provide a broadly applicable framework that could yield new insights into the biology of multiple diseases.

Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease

For most immune-mediated diseases, the main determinant of patient well-being is not the diagnosis itself but instead the course that the disease takes over time (prognosis). Prognosis may vary substantially between patients for reasons that are poorly understood. Familial studies support a genetic contribution to prognosis, but little evidence has been found for a proposed association between prognosis and the burden of susceptibility variants. To better characterize how genetic variation influences disease prognosis, we performed a within-cases genome-wide association study in two cohorts of patients with Crohn's disease. We identified four genome-wide significant loci, none of which showed any association with disease susceptibility. Conversely, the aggregated effect of all 170 disease susceptibility loci was not associated with disease prognosis. Together, these data suggest that the genetic contribution to prognosis in Crohn's disease is largely independent of the contribution to disease susceptibility and point to a biology of prognosis that could provide new therapeutic opportunities.

Family history of rheumatoid arthritis: an old concept with new developments

Family history of rheumatoid arthritis (RA) is a proxy for an individual's genetic and, in part, environmental risk of developing RA, and is a well-recognized predictor of disease onset. Although family history of RA is an old concept, the degree of familial aggregation of RA, whether it differs by age, sex, or serology, and what value it has for clinical decisions once a diagnosis of RA has been made remain unclear. New data have been emerging in parallel to substantial progress made in genetic association studies. In this Review, we describe the various ways that familial aggregation has been measured, and how the findings from these studies, whether they are based on twins, cohorts of first-degree relatives, or genetic data, correspond to each other and aid understanding of the aetiology of RA. In addition, we review the potential usefulness of family history of RA from a clinical point of view, demonstrating that, in the era of big data and genomics, family history still has a role in directing clinical decision-making and research.

Genetic vectors as a tool in association studies: definitions and application for study of rheumatoid arthritis

To identify putative relations between different genetic factors in the human genome in the development of common complex disease, we mapped the genetic data to an ensemble of spin chains and analysed the data as a quantum system. Each SNP is considered as a spin with three states corresponding to possible genotypes. The combined genotype represents a multispin state, described by the product of individual-spin states. Each person is characterized by a single genetic vector (GV) and individuals with identical GVs comprise the GV group. This consolidation of genotypes into GVs provides integration of multiple genetic variants for a single statistical test and excludes ambiguity of biological interpretation known for allele and haplotype associations. We analyzed two independent cohorts, with 2633 rheumatoid arthritis cases and 2108 healthy controls, and data for 6 SNPs from the HTR2A locus plus shared epitope allele. We found that GVs based on selected markers are highly informative and overlap for 98.3% of the healthy population between two cohorts. Interestingly, some of the GV groups contain either only controls or only cases, thus demonstrating extreme susceptibility or protection features. By using this new approach we confirmed previously detected univariate associations and demonstrated the most efficient selection of SNPs for combined analyses for functional studies.

Copy number variation in Y chromosome multicopy genes is linked to a paternal parent-of-origin effect on CNS autoimmune disease in female offspring

Background

The prevalence of some autoimmune diseases is greater in females compared with males, although disease severity is often greater in males. The reason for this sexual dimorphism is unknown, but it may reflect negative selection of Y chromosome-bearing sperm during spermatogenesis or male fetuses early in the course of conception/pregnancy. Previously, we showed that the sexual dimorphism in experimental autoimmune encephalomyelitis (EAE) is associated with copy number variation (CNV) in Y chromosome multicopy genes. Here, we test the hypothesis that CNV in Y chromosome multicopy genes influences the paternal parent-of-origin effect on EAE susceptibility in female mice.

Results

We show that C57BL/6 J consomic strains of mice possessing an identical X chromosome and CNV in Y chromosome multicopy genes exhibit sperm head abnormalities and female-biased sex ratio. This is consistent with X-Y intragenomic conflict arising from an imbalance in CNV between homologous X:Y chromosome multicopy genes. These males also display paternal transmission of EAE to female offspring and differential loading of microRNAs within the sperm nucleus. Furthermore, in humans, families of probands with multiple sclerosis similarly exhibit a female-biased sex ratio, whereas families of probands affected with non-sexually dimorphic autoimmune diseases exhibit unbiased sex ratios.

Conclusions

These findings provide evidence for a mechanism at the level of the male gamete that contributes to the sexual dimorphism in EAE and paternal parent-of-origin effects in female mice, raising the possibility that a similar mechanism may contribute to the sexual dimorphism in multiple sclerosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0591-7) contains supplementary material, which is available to authorized users.

How do autoimmune diseases cluster in families? A systematic review and meta-analysis

BACKGROUND

A primary characteristic of complex genetic diseases is that affected individuals tend to cluster in families (that is, familial aggregation). Aggregation of the same autoimmune condition, also referred to as familial autoimmune disease, has been extensively evaluated. However, aggregation of diverse autoimmune diseases, also known as familial autoimmunity, has been overlooked. Therefore, a systematic review and meta-analysis were performed aimed at gathering evidence about this topic.

METHODS

Familial autoimmunity was investigated in five major autoimmune diseases, namely, rheumatoid arthritis, systemic lupus erythematosus, autoimmune thyroid disease, multiple sclerosis and type 1 diabetes mellitus. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed. Articles were searched in Pubmed and Embase databases.

RESULTS

Out of a total of 61 articles, 44 were selected for final analysis. Familial autoimmunity was found in all the autoimmune diseases investigated. Aggregation of autoimmune thyroid disease, followed by systemic lupus erythematosus and rheumatoid arthritis, was the most encountered.

CONCLUSIONS

Familial autoimmunity is a frequently seen condition. Further study of familial autoimmunity will help to decipher the common mechanisms of autoimmunity.

A towards-multidimensional screening approach to predict candidate genes of rheumatoid arthritis based on SNP, structural and functional annotations

Background

According to the Genetic Analysis Workshops (GAW), hundreds of thousands of SNPs have been tested for association with rheumatoid arthritis. Traditional genome-wide association studies (GWAS) have been developed to identify susceptibility genes using a "most significant SNPs/genes" model. However, many minor- or modest-risk genes are likely to be missed after adjustment of multiple testing. This screening process uses a strict selection of statistical thresholds that aim to identify susceptibility genes based only on statistical model, without considering multi-dimensional biological similarities in sequence arrangement, crystal structure, or functional categories/biological pathways between candidate and known disease genes.

Methods

Multidimensional screening approaches combined with traditional statistical genetics methods can consider multiple biological backgrounds of genetic mutation, structural, and functional annotations. Here we introduce a newly developed multidimensional screening approach for rheumatoid arthritis candidate genes that considers all SNPs with nominal evidence of Bayesian association (BFLn > 0), and structural and functional similarities of corresponding genes or proteins.

Results

Our multidimensional screening approach extracted all risk genes (BFLn > 0) by odd ratios of hypothesis H₁ to H₀, and determined whether a particular group of genes shared underlying biological similarities with known disease genes. Using this method, we found 6614 risk SNPs in our Bayesian screen result set. Finally, we identified 146 likely causal genes for rheumatoid arthritis, including CD4, FGFR1, and KDR, which have been reported as high risk factors by recent studies. We must denote that 790 (96.1%) of genes identified by GWAS could not easily be classified into related functional categories or biological processes associated with the disease, while our candidate genes shared underlying biological similarities (e.g. were in the same pathway or GO term) and contributed to disease etiology, but where common variations in each of these genes make modest contributions to disease risk. We also found 6141 risk SNPs that were too minor to be detected by conventional approaches, and associations between 58 candidate genes and rheumatoid arthritis were verified by literature retrieved from the NCBI PubMed module.

Conclusions

Our proposed approach to the analysis of GAW16 data for rheumatoid arthritis was based on an underlying biological similarities-based method applied to candidate and known disease genes. Application of our method could identify likely causal candidate disease genes of rheumatoid arthritis, and could yield biological insights that not detected when focusing only on genes that give the strongest evidence by multiple testing. We hope that our proposed method complements the "most significant SNPs/genes" model, and provides additional insights into the pathogenesis of rheumatoid arthritis and other diseases, when searching datasets for hundreds of genetic variances.

Association analysis of TNFR2, VDR, A2M, GSTT1, GSTM1, and ACE genes with rheumatoid arthritis in South Asians and Caucasians of East Midlands in the United Kingdom

Genetic associations of TNFR2, VDR (Bsm I and Fok I), A2M, GSTT(1), GSTM(1) and ACE in South Asian and Caucasian patients with rheumatoid arthritis (RA) were assessed in this study. DNA samples from South Asians (134 cases, 149 controls) and Caucasians (137 cases, 150 controls) from the East Midlands of the United Kingdom were genotyped for seven polymorphisms. All cases were rheumatoid-factor positive. Significant genetic associations were observed with TNFR2 R-R (OR = 3.16, CI 1.20-9.26, P < 0.05), A2M 1-1 (OR = 2.09, CI 1.21-3.64, P < 0.05) and GST T(1)null (OR = 1.97, CI 1.07-3.68, P < 0.05) among Caucasian patients. In South Asians, VDR Bsm I B-B genotype (OR = 2.08, CI 1.23-3.52, P < 0.05), A2M 2-2 genotype (OR = 3.99, CI 1.19-17.18, P < 0.05), and GST T(1)null genotype (OR = 2.81, CI 1.40-5.77, P < 0.002) genotypes were associated with RA. In the majority of cases, recessive and multiplicative modes of inheritance explained the observed associations. This study demonstrates that ethnicity affects the genetic associations in RA.

Evidence for interaction between 5-hydroxytryptamine (serotonin) receptor 2A and MHC type II molecules in the development of rheumatoid arthritis

It has repeatedly been suggested that the development of complex diseases can be elucidated by gene-gene interactions. Recently, we found that HTR2A, a member of the serotonin receptor family, is associated with rheumatoid arthritis (RA). This study was aimed to investigate the possibility of a gene-gene interaction between HTR2A and the major genetic risk factor for RA, HLA-DRB1 shared epitope (SE) alleles. We studied 4095 RA cases and 3223 controls from three different populations - from Sweden, the United States and the Netherlands - to test for interaction between the protective HTR2A haplotype and HLA-DRB1 SE alleles. Further, we analyzed mRNA and/or protein expression of HTR2A and HLA-DR in biopsy samples and in synovial fibroblasts from RA patients. The interaction was defined as departure from additivity of effects using attributable proportion due to interaction. First, we could demonstrate and further replicate an interaction between a protective haplotype in HTR2A and HLA-DRB1 SE alleles regarding risk of developing autoantibody-positive RA. Second, we could show that both genes are constitutively expressed in fibroblasts from synovial tissue of RA patients, and, by double immunofluorescence staining, we demonstrated that these two proteins are colocalized in these cells. In conclusion, our data demonstrate a statistical interaction between HTR2A and HLA-DRB1 SE alleles and colocalization of the product of these two genes in inflamed synovial tissue, which suggest a possible biological relationship between these two proteins. This finding may lead to the development of treatment based on enhancing the protective features of 5-HT2A in individuals with a certain HLA genotype.

More powerful haplotype sharing by accounting for the mode of inheritance

The concept of haplotype sharing (HS) has received considerable attention recently, and several haplotype association methods have been proposed. Here, we extend the work of Beckmann and colleagues [2005 Hum. Hered. 59:67-78] who derived an HS statistic (BHS) as special case of Mantel's space-time clustering approach. The Mantel-type HS statistic correlates genetic similarity with phenotypic similarity across pairs of individuals. While phenotypic similarity is measured as the mean-corrected cross product of phenotypes, we propose to incorporate information of the underlying genetic model in the measurement of the genetic similarity. Specifically, for the recessive and dominant modes of inheritance we suggest the use of the minimum and maximum of shared length of haplotypes around a marker locus for pairs of individuals. If the underlying genetic model is unknown, we propose a model-free HS Mantel statistic using the max-test approach. We compare our novel HS statistics to BHS using simulated case-control data and illustrate its use by re-analyzing data from a candidate region of chromosome 18q from the Rheumatoid Arthritis (RA) Consortium. We demonstrate that our approach is point-wise valid and superior to BHS. In the re-analysis of the RA data, we identified three regions with point-wise P-values<0.005 containing six known genes (PMIP1, MC4R, PIGN, KIAA1468, TNFRSF11A and ZCCHC2) which might be worth follow-up.

Association of the 6q23 region with the rate of joint destruction in rheumatoid arthritis

Background

Two novel genetic polymorphisms on chromosome 6q23 are associated with susceptibility to rheumatoid arthritis (RA). Both polymorphisms (rs6920220 and rs10499194) reside in a region close to the gene encoding tumour necrosis factor α-induced protein 3 (TNFAIP3). TNFAIP3 is a negative regulator of NF-κB and is involved in inhibiting TNF-receptor-mediated signalling effects. Interestingly, the initial associations were detected in patients with longstanding RA. However, no association was found for rs10499194 in a Swedish cohort with early arthritis. This might be caused by over-representation of patients with severe disease in cohorts with longstanding RA.

Objective

To analyse the effect of the 6q23 region on the rate of joint destruction.

Methods

Five single nucleotide polymorphisms in 6q23 were genotyped in 324 Dutch patients with early RA. Genotypes were correlated with progression of radiographic joint damage for a follow-up time of 5 years.

Results

Two polymorphisms (rs675520 and rs9376293) were associated with severity of radiographic joint damage in patients positive for anti-citrullinated protein/peptide antibodies (ACPA). Importantly, the effects were present after correction for confounding factors such as secular trends in treatment.

Conclusions

These data associate the 6q23 region with the rate of joint destruction in ACPA+ RA.

Several regions in the major histocompatibility complex confer risk for anti-CCP-antibody positive rheumatoid arthritis, independent of the DRB1 locus

Recent evidence suggests that additional risk loci for RA are present in the major histocompatibility complex (MHC), independent of the class II HLA-DRB1 locus. We have now tested a total of 1,769 SNPs across 7.5Mb of the MHC located from 6p22.2 (26.03 Mb) to 6p21.32 (33.59 Mb) derived from the Illumina 550K Beadchip (Illumina, San Diego, CA, USA). For an initial analysis in the whole dataset (869 RA CCP + cases, 1,193 controls), the strongest association signal was observed in markers near the HLA-DRB1 locus, with additional evidence for association extending out into the Class I HLA region. To avoid confounding that may arise due to linkage disequilibrium with DRB1 alleles, we analyzed a subset of the data by matching cases and controls by DRB1 genotype (both alleles matched 1:1), yielding a set of 372 cases with 372 controls. This analysis revealed the presence of at least two regions of association with RA in the Class I region, independent of DRB1 genotype. SNP alleles found on the conserved A1-B8-DR3 (8.1) haplotype show the strongest evidence of positive association (P ~ 0.00005) clustered in the region around the HLA-C locus. In addition, we identified risk alleles that are not present on the 8.1 haplotype, with maximal association signals (P ~ 0.001-0.0027) located near the ZNF311 locus. This latter association is enriched in DRB1*0404 individuals. Finally, several additional association signals were found in the extreme centromeric portion of the MHC, in regions containing the DOB1, TAP2, DPB1, and COL11A2 genes. These data emphasize that further analysis of the MHC is likely to reveal genetic risk factors for rheumatoid arthritis that are independent of the DRB1 shared epitope alleles.

A large-scale rheumatoid arthritis genetic study identifies association at chromosome 9q33.2

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease affecting both joints and extra-articular tissues. Although some genetic risk factors for RA are well-established, most notably HLA-DRB1 and PTPN22, these markers do not fully account for the observed heritability. To identify additional susceptibility loci, we carried out a multi-tiered, case-control association study, genotyping 25,966 putative functional SNPs in 475 white North American RA patients and 475 matched controls. Significant markers were genotyped in two additional, independent, white case-control sample sets (661 cases/1322 controls from North America and 596 cases/705 controls from The Netherlands) identifying a SNP, rs1953126, on chromosome 9q33.2 that was significantly associated with RA (OR(common) = 1.28, trend P(comb) = 1.45E-06). Through a comprehensive fine-scale-mapping SNP-selection procedure, 137 additional SNPs in a 668 kb region from MEGF9 to STOM on 9q33.2 were chosen for follow-up genotyping in a staged-approach. Significant single marker results (P(comb)<0.01) spanned a large 525 kb region from FBXW2 to GSN. However, a variety of analyses identified SNPs in a 70 kb region extending from the third intron of PHF19 across TRAF1 into the TRAF1-C5 intergenic region, but excluding the C5 coding region, as the most interesting (trend P(comb): 1.45E-06 --> 5.41E-09). The observed association patterns for these SNPs had heightened statistical significance and a higher degree of consistency across sample sets. In addition, the allele frequencies for these SNPs displayed reduced variability between control groups when compared to other SNPs. Lastly, in combination with the other two known genetic risk factors, HLA-DRB1 and PTPN22, the variants reported here generate more than a 45-fold RA-risk differential.

One- and two-locus models for mapping rheumatoid arthritis-susceptibility genes on chromosome 6

To evaluate whether there is evidence for two rheumatoid arthritis (RA) susceptibility genes on chromosome 6, we applied new robust methods for two-locus multipoint identical-by-descent mapping to the rheumatoid arthritis data of the Genetic Analysis Workshop 15. The software GEEARP was used to estimate the locations and the corresponding genetic effects for one locus or two linked loci in a region on chromosome 6, on the basis of affected relative pairs. These methods were applied to the data sets from the North American Rheumatoid Arthritis Consortium, Canada, France, and the first screen of United Kingdom. From the resultant 95% confidence intervals given by a robust variance estimator, a linked region, other than the well-known HLA region, was at 54.7–69.6 cM, providing evidence for a second rheumatoid arthritis susceptibility locus on chromosome 6.

Detecting haplotype effects in genomewide association studies

The analysis of genomewide association studies requires methods that are both computationally feasible and statistically powerful. Given the large-scale collection of single nucleotide polymorphisms (SNPs), it is desirable to explore the information contained in their interrelationships. In particular, utilizing haplotypes rather than individual SNPs and accounting for correlations of polymorphisms in adjustment for multiple testing can lead to increased power. We present a statistically powerful and numerically efficient method based on sliding windows of adjacent SNPs to detect haplotype-disease association in genomewide studies. This method consists of an efficient algorithm to calculate a proper likelihood-ratio statistic for any given window of SNPs, along with an accurate and efficient Monte Carlo procedure to adjust for multiple testing. Simulation studies using the HapMap data showed that the proposed method performs well in realistic situations. We applied the new method to a case-control study on rheumatoid arthritis and identified several loci worthy of further investigations.

Evidence of linkage to chromosome 1 for early age of onset of rheumatoid arthritis and HLA marker DRB1 genotype in NARAC data

Focusing on chromosome 1, a recursive partitioning linkage algorithm (RP) was applied to perform linkage analysis on the rheumatoid arthritis NARAC data, incorporating covariates such as HLA-DRB1 genotype, age at onset, severity, anti-cyclic citrullinated peptide (anti-CCP), and life time smoking. All 617 affected sib pairs from the ascertained families were used, and an RP linkage model was used to identify linkage possibly influenced by covariates. This algorithm includes a likelihood ratio (LR)-based splitting rule, a pruning algorithm to identify optimal tree size, and a bootstrap method for final tree selection.

The strength of the linkage signals was evaluated by empirical p-values, obtained by simulating marker data under null hypothesis of no linkage. Two suggestive linkage regions on chromosome 1 were detected by the RP linkage model, with identified associated covariates HLA-DRB1 genotype and age at onset. These results suggest possible gene × gene and gene × environment interactions at chromosome 1 loci and provide directions for further gene mapping.

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.

Identifying single-nucleotide polymorphisms responsible for the linkage signal of rheumatoid arthritis on chromosome 6 by joint modeling of linkage and association

This study evaluated the utility of unrelated controls and flanking markers when performing joint modeling of linkage and association by the LAMP software (version 0.0.6) [Am J Hum Genet 2005, 76:934–949; Am J Hum Genet 2006, 78:778–792]. Analyses were conducted on the simulated rheumatoid arthritis (RA) data in Genetic Analysis Workshop 15 (GAW15), using single-nucleotide polymorphisms (SNPs) on chromosome 6 over the 100 simulated replicates. We found that the LOD score for testing association in the presence of linkage dramatically increased when unrelated controls were added to affected sib pairs (ASPs), and that choosing a sufficient number of flanking markers is critical in order to distinguish between perfect linkage disequilibrium (which leads to the conclusion of a measured SNP explaining a linkage signal) and incomplete linkage disequilibrium (which leads to the conclusion of other undetected causal variants in a linkage region).

A two-dimensional genome scan for rheumatoid arthritis susceptibility loci

We performed a genome-wide search for pairs of susceptibility loci that jointly contribute to rheumatoid arthritis in families recruited by the North American Rheumatoid Arthritis Consortium. A complete two-dimensional (2D) non-parametric linkage scan was carried out using 380 autosomal microsatellite markers in 511 families. At each 2D peak we obtained the most likely underlying genetic model explaining the two-locus effects, defining epistasis as a departure from an additive or a multiplicative two-locus penetrance function. The highest peak in the surface identified an epistatic interaction between loci 6p21 and 16p12 (two-locus lod score = 18.02, epistasis P < 0.012). Significant and suggestive two-locus effects were also obtained for region 6p21 in combination with loci 18q21, 8p23, 1q41, and 6p22, while the highest 2D peaks excluding region 6p21 were observed at locus pairs 8p23-18q21 and 1p21-18q21. The 2D peaks were further examined using combined microsatellite and single-nucleotide polymorphism (SNP) marker genotypes in 744 families. The two-locus evidence for linkage increased for region pairs 6p21-18q12, 6p21-16p12, 6p21-8p23, 1q41-6p21, and 6p21-6p22, but decreased for pairs of regions that did not include locus 6p21. In conclusion, we obtained evidence for multi-locus interactions in rheumatoid arthritis that are mediated by the major susceptibility locus at 6p21.

Protective effect of noninherited maternal HLA-DR antigens on rheumatoid arthritis development

Rheumatoid arthritis (RA) is a complex genetic disorder in which the HLA-region contributes most to the genetic risk. HLA-DRB1-molecules containing the amino acid sequence DERAA (i.e., HLA-DRB1*0103, *0402, *1102, *1103, *1301, *1302, and *1304) are associated with protection from RA. It has been proposed that not only inherited but also noninherited HLA-antigens from the mother (NIMA) can influence RA-susceptibility. Up to now, no protective NIMAs were described. Here, we studied whether DERAA-containing HLA-DRB1-alleles as NIMA are associated with a protective effect. One hundred seventy-nine families were studied, 88 from the Netherlands and 91 from the United Kingdom. The frequency of DERAA-containing HLA-DRB1-alleles of the Dutch mothers (16.1%), but not of the fathers (26.2%), was lower compared with the general Dutch population (29.3%; P = 0.02). This was replicated in the English set of patients and controls (P = 0.01). Further, of all families, 45 contained at least one DERAA-negative child with RA and at least one DERAA-positive parent. The odds for the DERAA-negative RA patients of having a DERAA-positive mother was significantly lower compared with having a DERAA-positive father (OR 0.25; P = 0.003). These data show a protective NIMA-effect in a human autoimmune disease and indicate that a DERAA-positive mother can transfer protection against RA to her DERAA-negative child.

Two independent alleles at 6q23 associated with risk of rheumatoid arthritis

To identify susceptibility alleles associated with rheumatoid arthritis, we genotyped 397 individuals with rheumatoid arthritis for 116,204 SNPs and carried out an association analysis in comparison to publicly available genotype data for 1,211 related individuals from the Framingham Heart Study. After evaluating and adjusting for technical and population biases, we identified a SNP at 6q23 (rs10499194, approximately 150 kb from TNFAIP3 and OLIG3) that was reproducibly associated with rheumatoid arthritis both in the genome-wide association (GWA) scan and in 5,541 additional case-control samples (P = 10(-3), GWA scan; P < 10(-6), replication; P = 10(-9), combined). In a concurrent study, the Wellcome Trust Case Control Consortium (WTCCC) has reported strong association of rheumatoid arthritis susceptibility to a different SNP located 3.8 kb from rs10499194 (rs6920220; P = 5 x 10(-6) in WTCCC). We show that these two SNP associations are statistically independent, are each reproducible in the comparison of our data and WTCCC data, and define risk and protective haplotypes for rheumatoid arthritis at 6q23.

The MHC2TA -168A/G polymorphism and risk for rheumatoid arthritis: a meta-analysis of 6861 patients and 9270 controls reveals no evidence for association

BACKGROUND

An association between major histocompatibility complex (MHC) genes, particularly those within the class II HLA region, and rheumatoid arthritis (RA) is well established, and accounts for an estimated 30% of the genetic component in RA. The MHC class II transactivator gene (MHC2TA) on chromosome 16p13 has recently emerged as the most important transcription factor regulating genes required for class II MHC-restricted antigen presentation. Previous studies of a promoter region polymorphism (-168A/G, rs3087456) in the MHC2TA gene and RA have yielded conflicting results.

OBJECTIVE

To assess the association of the MHC2TA -168A/G polymorphism (rs3087456) and risk for RA by meta-analysis.

METHODS

Meta-analysis was performed for 6861 patients with RA and 9270 controls from 10 case-control studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each study. Summary ORs and 95% CIs were calculated for random effects models.

RESULTS

No effect was observed for the G risk allele (OR 1.02, 95% CI 0.93 to 1.12, p = 0.70) or the GG risk genotype (OR 1.14, 95% CI 0.95 to 1.36, p = 0.16).

CONCLUSIONS

Our results indicate that the MHC2TA -168A/G polymorphism (rs3087456) is not associated with RA yet underscore the importance of including shared epitope allele carrier status, secondary phenotypes and more complete characterisation of MHC2TA variation in future studies.

Interaction between smoking, the shared epitope, and anti-cyclic citrullinated peptide: a mixed picture in three large North American rheumatoid arthritis cohorts

OBJECTIVE

Recently, Swedish members of the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) provided evidence that smoking may trigger RA-specific immune reactions to citrullinated protein in carriers of HLA-DR shared epitope alleles. In an effort to confirm this interaction between smoking and shared epitope alleles, we performed a case-only analysis of 3 North American RA cohorts.

METHODS

A total of 2,476 white patients with RA were studied, 1,105 from the North American Rheumatoid Arthritis Consortium (NARAC) family collection, 753 from the National Inception Cohort of Rheumatoid Arthritis Patients (Inception Cohort), and 618 from the Study of New Onset Rheumatoid Arthritis (SONORA). All patients were HLA-DRB1 typed, and tested for anti-cyclic citrullinated peptide (anti-CCP) and rheumatoid factor. Information about smoking history was obtained by questionnaire.

RESULTS

A significant association was found between smoking and the presence of anti-CCP in the NARAC and the Inception Cohort, but not in the SONORA. The shared epitope alleles consistently correlated with anti-CCP in all 3 populations. Using multiple logistic regression analyses, shared epitope alleles were still the most significant risk factor for anti-CCP positivity. Weak evidence of gene-environment interaction between smoking and shared epitope alleles for anti-CCP formation was found only in the NARAC.

CONCLUSION

Unlike the EIRA data, we could not confirm a major gene-environment interaction for anti-CCP formation between shared epitope alleles and smoking in 3 North American RA cohorts. Our data indicate a need for further studies to address the full range of environmental factors other than smoking that may be associated with citrullination and RA.

Gene-gene and gene-environment interactions involving HLA-DRB1, PTPN22, and smoking in two subsets of rheumatoid arthritis

Gene-gene and gene-environment interactions are key features in the development of rheumatoid arthritis (RA) and other complex diseases. The aim of this study was to use and compare three different definitions of interaction between the two major genetic risk factors of RA--the HLA-DRB1 shared epitope (SE) alleles and the PTPN22 R620W allele--in three large case-control studies: the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study, the North American RA Consortium (NARAC) study, and the Dutch Leiden Early Arthritis Clinic study (in total, 1,977 cases and 2,405 controls). The EIRA study was also used to analyze interactions between smoking and the two genes. "Interaction" was defined either as a departure from additivity, as interaction in a multiplicative model, or in terms of linkage disequilibrium--for example, deviation from independence of penetrance of two unlinked loci. Consistent interaction, defined as departure from additivity, between HLA-DRB1 SE alleles and the A allele of PTPN22 R620W was seen in all three studies regarding anti-CCP-positive RA. Testing for multiplicative interactions demonstrated an interaction between the two genes only when the three studies were pooled. The linkage disequilibrium approach indicated a gene-gene interaction in EIRA and NARAC, as well as in the pooled analysis. No interaction was seen between smoking and PTPN22 R620W. A new pattern of interactions is described between the two major known genetic risk factors and the major environmental risk factor concerning the risk of developing anti-CCP-positive RA. The data extend the basis for a pathogenetic hypothesis for RA involving genetic and environmental factors. The study also raises and illustrates principal questions concerning ways to define interactions in complex diseases.

Dissecting the heterogeneity of rheumatoid arthritis through linkage analysis of quantitative traits

OBJECTIVE

To dissect the heterogeneity of rheumatoid arthritis (RA) through linkage analysis of quantitative traits, specifically, IgM rheumatoid factor (IgM-RF) and anti-cyclic citrullinated peptide (anti-CCP) autoantibody titers.

METHODS

Subjects, 1,002 RA patients from 491 multiplex families recruited by the North American RA Consortium, were typed for 379 microsatellite markers. Anti-CCP titers were determined based on a second-generation enzyme-linked immunosorbent assay, and IgM-RF levels were quantified by immunonephelometry. We used the Merlin statistical package to perform nonparametric quantitative trait linkage analysis.

RESULTS

For each of the quantitative traits, evidence of linkage, with logarithm of odds (LOD) scores of >1.0, was found in 9 regions. For both traits, the strongest evidence of linkage was for marker D6S1629 on chromosome 6p (LOD 14.02 for anti-CCP and LOD 12.09 for RF). Six other regions with LOD scores of >1.0 overlapped between the 2 traits, on chromosomes 1p21.1, 5q15, 8p23.1, 16p12.1, 16q23.1, and 18q21.31. Evidence of linkage to anti-CCP titer but not to RF titer was found in 2 regions (chromosomes 9p21.3 and 10q21.1), and evidence of linkage to RF titer but not to anti-CCP titer was found in 2 regions (chromosomes 5p15.2 and 1q42.3). Several covariates were significantly associated with 1 or both traits, and linkage analysis exploring the covariate effects revealed striking effects of sex in modulating linkage signals for several chromosomal regions. For example, sex had a striking impact on the linkage results for both quantitative traits on chromosome 6p (P = 0.0007 for anti-CCP titer and P = 0.0012 for RF titer), suggesting a sex-HLA region interaction.

CONCLUSION

Analysis of quantitative components of RA is a promising approach for dissecting the genetic heterogeneity of this complex disorder. These results highlight the potential importance of sex or other covariates that may modulate some of the genetic effects that influence the risk of specific disease manifestations.

Influence of male sex on disease phenotype in familial rheumatoid arthritis

OBJECTIVE

To examine sex differences in clinical, demographic, and genetic characteristics among a large cohort of patients with familial rheumatoid arthritis (RA).

METHODS

We studied 1,004 affected members of 467 Caucasian multicase RA families recruited from the North American Rheumatoid Arthritis Consortium. Standardized information about demographic and clinical characteristics was collected from all patients. Affected individuals also underwent radiography of the hands and were genotyped for markers in the HLA region. Sex differences were assessed using contingency table analysis (for categorical variables) and Student's t-tests for (continuous variables), and by multivariate logistic and linear regression analysis.

RESULTS

Male patients had a significantly later onset of RA, were more likely to be seropositive for RF, and had significantly higher titers of anti-cyclic citrullinated peptide (anti-CCP) antibodies compared with female patients, even after adjustment for covariates in multivariate analyses. Male patients were also significantly more likely to have a history of smoking and to be HLA-DRB1 shared epitope (SE) positive. Interestingly, female patients with an affected male sibling had significantly higher titers of anti-CCP antibodies and were more likely to be SE positive compared with female patients without affected male siblings. Multivariate analyses indicated that the presence of the SE did not fully explain the increased anti-CCP antibody titers observed in these families.

CONCLUSION

Sex has an important influence on the disease phenotype in RA, including the age at disease onset and autoantibody production. Furthermore, families with affected male members are characterized by higher titers of autoantibodies, particularly anti-CCP antibodies. Our results indicate that these findings are not fully explained by differences in exposure to tobacco smoke, presence of the HLA-DRB1 SE, or other HLA region genetic variation. Thus, other genetic or nongenetic factors also contribute to sex differences in the RA phenotype.

High-density SNP analysis of 642 Caucasian families with rheumatoid arthritis identifies two new linkage regions on 11p12 and 2q33

We have completed a genome wide linkage scan using >5700 informative single-nucleotide polymorphism (SNP) markers (Illumina IV SNP linkage panel) in 642 Caucasian families containing affected sibling pairs with rheumatoid arthritis (RA), ascertained by the North American Rheumatoid Arthritis Consortium. The results show striking new evidence of linkage at chromosomes 2q33 and 11p12 with logarithm of odds (LOD) scores of 3.52 and 3.09, respectively. In addition to a strong and broad linkage interval surrounding the major histocompatibility complex (LOD>16), regions with LOD>2.5 were observed on chromosomes 5 and 10. Additional linkage evidence (LOD scores between 1.46 and 2.35) was also observed on chromosomes 4, 7, 12, 16 and 18. This new evidence for multiple regions of genetic linkage is partly explained by the significantly increased information content of the Illumina IV SNP linkage panel (75.6%) compared with a standard microsatellite linkage panel utilized previously (mean 52.6%). Stratified analyses according to whether or not the sibling pair members showed elevated anticyclic citrullinated peptide titers indicates significant variation in evidence for linkage among strata on chromosomes 4, 5, 6 and 7. Overall, these new linkage data should reinvigorate efforts to utilize positional information to identify susceptibility genes for RA.

Regulation of anti-cyclic citrullinated peptide antibodies in rheumatoid arthritis: contrasting effects of HLA-DR3 and the shared epitope alleles

OBJECTIVE

To examine the association between HLA-DRB1 alleles and the production of anti-cyclic citrullinated peptide (anti-CCP) and rheumatoid factor (RF) autoantibodies in patients with rheumatoid arthritis (RA).

METHODS

We studied 1,723 Caucasian RA patients enrolled in the North American Rheumatoid Arthritis Consortium (NARAC) family cohort and the Study of New Onset Rheumatoid Arthritis (SONORA) cohort. All patients were tested for anti-CCP antibodies (by enzyme-linked immunosorbent assay), RF (by nephelometry), and HLA-DR genotype (by polymerase chain reaction and sequence-specific oligonucleotide hybridization).

RESULTS

When controlled for the presence of RF, anti-CCP positivity was strongly associated with the HLA-DRB1 shared epitope (SE). In RF+ patients, the presence of the SE was very significantly associated with anti-CCP positivity, with an odds ratio (OR) of 5.8 and a 95% confidence interval (95% CI) of 4.1-8.3. This relationship was also seen in RF- patients (OR 3.1 [95% CI 1.8-5.3]). In contrast, RF positivity was not significantly associated with presence of the SE independently of anti-CCP antibodies. Strikingly, HLA-DRB1*03 was strongly associated with reduced anti-CCP titers, even after controlling for the presence of the SE and restricting the analysis to anti-CCP+ patients. HLA-DR3 was also associated with anti-CCP- RA in our population.

CONCLUSION

The HLA-DRB1 SE is strongly associated with the production of anti-CCP antibodies, but not RF. In contrast, HLA-DR3 alleles are associated with anti-CCP- disease and with lower levels of anti-CCP antibodies, even when controlling for the SE. These data emphasize the complexity of the genetic effects of the major histocompatibility complex on the RA phenotype.

Replication of putative candidate-gene associations with rheumatoid arthritis in >4,000 samples from North America and Sweden: association of susceptibility with PTPN22, CTLA4, and PADI4

Candidate-gene association studies in rheumatoid arthritis (RA) have lead to encouraging yet apparently inconsistent results. One explanation for the inconsistency is insufficient power to detect modest effects in the context of a low prior probability of a true effect. To overcome this limitation, we selected alleles with an increased probability of a disease association, on the basis of a review of the literature on RA and other autoimmune diseases, and tested them for association with RA susceptibility in a sample collection powered to detect modest genetic effects. We tested 17 alleles from 14 genes in 2,370 RA cases and 1,757 controls from the North American Rheumatoid Arthritis Consortium (NARAC) and the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) collections. We found strong evidence of an association of PTPN22 with the development of anti-citrulline antibody-positive RA (odds ratio [OR] 1.49; P=.00002), using previously untested EIRA samples. We provide support for an association of CTLA4 (CT60 allele, OR 1.23; P=.001) and PADI4 (PADI4_94, OR 1.24; P=.001) with the development of RA, but only in the NARAC cohort. The CTLA4 association is stronger in patients with RA from both cohorts who are seropositive for anti-citrulline antibodies (P=.0006). Exploration of our data set with clinically relevant subsets of RA reveals that PTPN22 is associated with an earlier age at disease onset (P=.004) and that PTPN22 has a stronger effect in males than in females (P=.03). A meta-analysis failed to demonstrate an association of the remaining alleles with RA susceptibility, suggesting that the previously published associations may represent false-positive results. Given the strong statistical power to replicate a true-positive association in this study, our results provide support for PTPN22, CTLA4, and PADI4 as RA susceptibility genes and demonstrate novel associations with clinically relevant subsets of RA.

PTPN22 genetic variation: evidence for multiple variants associated with rheumatoid arthritis

The minor allele of the R620W missense single-nucleotide polymorphism (SNP) (rs2476601) in the hematopoietic-specific protein tyrosine phosphatase gene, PTPN22, has been associated with multiple autoimmune diseases, including rheumatoid arthritis (RA). These genetic data, combined with biochemical evidence that this SNP affects PTPN22 function, suggest that this phosphatase is a key regulator of autoimmunity. To determine whether other genetic variants in PTPN22 contribute to the development of RA, we sequenced the coding regions of this gene in 48 white North American patients with RA and identified 15 previously unreported SNPs, including 2 coding SNPs in the catalytic domain. We then genotyped 37 SNPs in or near PTPN22 in 475 patients with RA and 475 individually matched controls (sample set 1) and selected a subset of markers for replication in an additional 661 patients with RA and 1,322 individually matched controls (sample set 2). Analyses of these results predict 10 common (frequency >1%) PTPN22 haplotypes in white North Americans. The sole haplotype found to carry the previously identified W620 risk allele was strongly associated with disease in both sample sets, whereas another haplotype, identical at all other SNPs but carrying the R620 allele, showed no association. R620W, however, does not fully explain the association between PTPN22 and RA, since significant differences between cases and controls persisted in both sample sets after the haplotype data were stratified by R620W. Additional analyses identified two SNPs on a single common haplotype that are associated with RA independent of R620W, suggesting that R620W and at least one additional variant in the PTPN22 gene region influence RA susceptibility.

Analysis of families in the multiple autoimmune disease genetics consortium (MADGC) collection: the PTPN22 620W allele associates with multiple autoimmune phenotypes

Autoimmune disorders constitute a diverse group of phenotypes with overlapping features and a tendency toward familial aggregation. It is likely that common underlying genes are involved in these disorders. Until very recently, no specific alleles--aside from a few common human leukocyte antigen class II genes--had been identified that clearly associate with multiple different autoimmune diseases. In this study, we describe a unique collection of 265 multiplex families assembled by the Multiple Autoimmune Disease Genetics Consortium (MADGC). At least two of nine "core" autoimmune diseases are present in each of these families. These core diseases include rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), multiple sclerosis (MS), autoimmune thyroid disease (Hashimoto thyroiditis or Graves disease), juvenile RA, inflammatory bowel disease (Crohn disease or ulcerative colitis), psoriasis, and primary Sjogren syndrome. We report that a recently described functional single-nucleotide polymorphism (rs2476601, encoding R620W) in the intracellular tyrosine phosphatase (PTPN22) confers risk of four separate autoimmune phenotypes in these families: T1D, RA, SLE, and Hashimoto thyroiditis. MS did not show association with the PTPN22 risk allele. These findings suggest a common underlying etiologic pathway for some, but not all, autoimmune disorders, and they suggest that MS may have a pathogenesis that is distinct from RA, SLE, and T1D. DNA and clinical data for the MADGC families are available to the scientific community; these data will provide a valuable resource for the dissection of the complex genetic factors that underlie the various autoimmune phenotypes.