Jane Worthington

Harvard Medical School, Boston, Massachusetts, United States

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Publications (275)2153.96 Total impact

  • Stephen Eyre, Jane Worthington
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    ABSTRACT: Many of the hits identified through genome-wide association studies are located outside protein-coding regions, making it difficult to define mechanism. In Nature, Farh et al., (2014) describe an approach to identify causal variants in autoimmune disease as first step to assigning function. Copyright © 2014 Elsevier Inc. All rights reserved.
    Immunity 12/2014; · 19.75 Impact Factor
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    ABSTRACT: A large portion of common variant loci associated with genetic risk for schizophrenia reside within noncoding sequence of unknown function. Here, we demonstrate promoter and enhancer enrichment in schizophrenia variants associated with expression quantitative trait loci (eQTL). The enrichment is greater when functional annotations derived from the human brain are used relative to peripheral tissues. Regulatory trait concordance analysis ranked genes within schizophrenia genome-wide significant loci for a potential functional role, based on colocalization of a risk SNP, eQTL, and regulatory element sequence. We identified potential physical interactions of noncontiguous proximal and distal regulatory elements. This was verified in prefrontal cortex and -induced pluripotent stem cell–derived neurons for the L-type calciumchannel (CACNA1C) risk locus. Our findings point to a functional link between schizophrenia-associated noncoding SNPs and 3D genome architecture associated with chromosomal loopings and transcriptional regulation in the brain.
    Cell Reports 11/2014; 9:1-13. · 7.21 Impact Factor
  • Annie Yarwood, Tom W J Huizinga, Jane Worthington
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    ABSTRACT: There is now a general consensus that RA has a spectrum of disease stages that can begin many years before the onset of clinical symptoms. It is widely thought that understanding the complex interplay between genetics and environment, and their role in pathogenesis, is essential in gaining further insight into the mechanisms that drive disease development and progression. More than 100 genetic susceptibility loci have now been identified for RA through studies that have focused on patients with established RA compared with healthy controls. Studying the early preclinical phases of disease will provide valuable insights into the biological events that precede disease and could potentially identify biomarkers to predict disease onset and future therapeutic targets. In this review we will cover recent advances in the knowledge of genetic and environmental risk factors and speculate on how these factors may influence the transition from one stage of disease to another.
    Rheumatology (Oxford, England) 09/2014; · 4.44 Impact Factor
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    Arthritis & Rheumatology. 09/2014;
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    ABSTRACT: Despite progress in defining human leukocyte antigen (HLA) alleles for anti-citrullinated-protein-autoantibody-positive (ACPA(+)) rheumatoid arthritis (RA), identifying HLA alleles for ACPA-negative (ACPA(-)) RA has been challenging because of clinical heterogeneity within clinical cohorts. We imputed 8,961 classical HLA alleles, amino acids, and SNPs from Immunochip data in a discovery set of 2,406 ACPA(-) RA case and 13,930 control individuals. We developed a statistical approach to identify and adjust for clinical heterogeneity within ACPA(-) RA and observed independent associations for serine and leucine at position 11 in HLA-DRβ1 (p = 1.4 × 10(-13), odds ratio [OR] = 1.30) and for aspartate at position 9 in HLA-B (p = 2.7 × 10(-12), OR = 1.39) within the peptide binding grooves. These amino acid positions induced associations at HLA-DRB1(∗)03 (encoding serine at 11) and HLA-B(∗)08 (encoding aspartate at 9). We validated these findings in an independent set of 427 ACPA(-) case subjects, carefully phenotyped with a highly sensitive ACPA assay, and 1,691 control subjects (HLA-DRβ1 Ser11+Leu11: p = 5.8 × 10(-4), OR = 1.28; HLA-B Asp9: p = 2.6 × 10(-3), OR = 1.34). Although both amino acid sites drove risk of ACPA(+) and ACPA(-) disease, the effects of individual residues at HLA-DRβ1 position 11 were distinct (p < 2.9 × 10(-107)). We also identified an association with ACPA(+) RA at HLA-A position 77 (p = 2.7 × 10(-8), OR = 0.85) in 7,279 ACPA(+) RA case and 15,870 control subjects. These results contribute to mounting evidence that ACPA(+) and ACPA(-) RA are genetically distinct and potentially have separate autoantigens contributing to pathogenesis. We expect that our approach might have broad applications in analyzing clinical conditions with heterogeneity at both major histocompatibility complex (MHC) and non-MHC regions.
    The American Journal of Human Genetics 03/2014; · 11.20 Impact Factor
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    ABSTRACT: A highly polygenic aetiology and high degree of allele-sharing between ancestries have been well elucidated in genetic studies of rheumatoid arthritis. Recently, the high-density genotyping array Immunochip for immune disease loci identified 14 new rheumatoid arthritis risk loci among individuals of European ancestry. Here, we aimed to identify new rheumatoid arthritis risk loci using Korean-specific Immunochip data. We analysed Korean rheumatoid arthritis case-control samples using the Immunochip and genome-wide association studies (GWAS) array to search for new risk alleles of rheumatoid arthritis with anticitrullinated peptide antibodies. To increase power, we performed a meta-analysis of Korean data with previously published European Immunochip and GWAS data for a total sample size of 9299 Korean and 45 790 European case-control samples. We identified eight new rheumatoid arthritis susceptibility loci (TNFSF4, LBH, EOMES, ETS1-FLI1, COG6, RAD51B, UBASH3A and SYNGR1) that passed a genome-wide significance threshold (p<5×10(-8)), with evidence for three independent risk alleles at 1q25/TNFSF4. The risk alleles from the seven new loci except for the TNFSF4 locus (monomorphic in Koreans), together with risk alleles from previously established RA risk loci, exhibited a high correlation of effect sizes between ancestries. Further, we refined the number of single nucleotide polymorphisms (SNPs) that represent potentially causal variants through a trans-ethnic comparison of densely genotyped SNPs. This study demonstrates the advantage of dense-mapping and trans-ancestral analysis for identification of potentially causal SNPs. In addition, our findings support the importance of T cells in the pathogenesis and the fact of frequent overlap of risk loci among diverse autoimmune diseases.
    Annals of the rheumatic diseases 02/2014; · 9.27 Impact Factor
  • Annals of the Rheumatic Diseases 01/2014; 72(Suppl 3):A67-A67. · 9.27 Impact Factor
  • Annals of the Rheumatic Diseases 01/2014; 71(Suppl 3):154-154. · 9.27 Impact Factor
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    ABSTRACT: A recent genome-wide association study (GWAS) comprising a French cohort of systemic sclerosis (SSc) reported several non-HLA single-nucleotide polymorphisms (SNPs) showing a nominal association in the discovery phase. We aimed to identify previously overlooked susceptibility variants using a follow-up strategy. Sixty six non-HLA SNPs showing a P-value < 10-4 in the discovery phase of the French SSc GWAS were analyzed in the first step of this study performing a meta-analysis which combined data from the two published SSc GWASs. A total of 2,921 SSc patients and 6,963 healthy controls were included in this first phase. Two SNPs, PPARG rs310746 and CHRNA9 rs6832151, were selected for genotyping in the replication cohort (1,068 SSc patients and 6,762 healthy controls) based on the results of the first step. Genotyping was performed using TaqMan SNP genotyping assays. We observed nominal associations for both PPARG rs310746 (PMH = 1.90 x 10-6, OR = 1.28) and CHRNA9 rs6832151 (PMH = 4.30 x 10-6, OR = 1.17) genetic variants with SSc in the first step of our study. In the replication phase, we observed a trend of association for PPARG rs310746 (P-value = 0.066, OR = 1.17). The combined overall Mantel-Haenszel meta-analysis of all the cohorts included in the present study revealed that PPARG rs310746 remained associated with SSc with a nominal non-genome wide significant P-value (PMH = 5.00 x 10-7, OR = 1.25). No evidence of association was observed for CHRNA9 rs6832151 either in the replication phase or in the overall pooled-analysis. Our results suggest a role of PPARG gene in the development of SSc.
    Arthritis research & therapy 01/2014; 16(1):R6. · 4.12 Impact Factor
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    ABSTRACT: In this study, 1,833 systemic sclerosis (SSc) cases and 3,466 controls were genotyped with the Immunochip array. Classical alleles, amino acid residues, and SNPs across the human leukocyte antigen (HLA) region were imputed and tested. These analyses resulted in a model composed of six polymorphic amino acid positions and seven SNPs that explained the observed significant associations in the region. In addition, a replication step comprising 4,017 SSc cases and 5,935 controls was carried out for several selected non-HLA variants, reaching a total of 5,850 cases and 9,401 controls of European ancestry. Following this strategy, we identified and validated three SSc risk loci, including DNASE1L3 at 3p14, the SCHIP1-IL12A locus at 3q25, and ATG5 at 6q21, as well as a suggested association of the TREH-DDX6 locus at 11q23. The associations of several previously reported SSc risk loci were validated and further refined, and the observed peak of association in PXK was related to DNASE1L3. Our study has increased the number of known genetic associations with SSc, pro- vided further insight into the pleiotropic effects of shared autoimmune risk factors, and highlighted the power of dense mapping for detecting previously overlooked susceptibility loci.
    The American Journal of Human Genetics 01/2014; 94:47-61. · 10.99 Impact Factor
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    ABSTRACT: 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.
    PLoS ONE 01/2014; 9(2):e87645. · 3.53 Impact Factor
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    ABSTRACT: A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses-as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes-to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
    Nature 12/2013; · 42.35 Impact Factor
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    ABSTRACT: Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain [Formula: see text] more heritability than GWAS-associated SNPs on average ([Formula: see text]). For some diseases, this increase was individually significant: [Formula: see text] for Multiple Sclerosis (MS) ([Formula: see text]) and [Formula: see text] for Crohn's Disease (CD) ([Formula: see text]); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained [Formula: see text] more MS heritability than known MS SNPs ([Formula: see text]) and [Formula: see text] more CD heritability than known CD SNPs ([Formula: see text]), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of [Formula: see text] Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with [Formula: see text] more heritability from all SNPs at GWAS loci ([Formula: see text]) and [Formula: see text] more heritability from all autoimmune disease loci ([Formula: see text]) compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.
    PLoS Genetics 12/2013; 9(12):e1003993. · 8.17 Impact Factor
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    ABSTRACT: ObjectiveA recent high-density fine-mapping (ImmunoChip) study of genetic associations in rheumatoid arthritis (RA) identified 14 risk loci with validated genome-wide significance, as well as a number of loci showing associations suggestive of significance (P = 5 × 10−5 < 5 × 10−8), but these have yet to be replicated. The aim of this study was to determine whether these potentially significant loci are involved in the pathogenesis of RA, and to explore whether any of the loci are associated with a specific RA serotype. MethodsA total of 16 single-nucleotide polymorphisms (SNPs) were selected for genotyping and association analyses in 2 independent validation cohorts, comprising 6,106 RA cases and 4,290 controls. A meta-analysis of the data from the original ImmunoChip discovery cohort and from both validation cohorts was carried out, for a combined total of 17,581 RA cases and 20,160 controls. In addition, stratified analysis of patient subsets, defined according to their anti–cyclic citrullinated peptide (anti-CCP) antibody status, was performed. ResultsA significant association with RA risk (P < 0.05) was replicated for 6 of the SNPs assessed in the validation cohorts. All SNPs in the validation study had odds ratios (ORs) for RA susceptibility in the same direction as those in the ImmunoChip discovery study. One SNP, rs72928038, mapping to an intron of BACH2, achieved genome-wide significance in the meta-analysis (P = 1.2 × 10−8, OR 1.12), and a second SNP, rs911263, mapping to an intron of RAD51B, was significantly associated in the anti-CCP–positive RA subgroup (P = 4 × 10−8, OR 0.89), confirming that both are RA susceptibility loci. Conclusion This study provides robust evidence for an association of RA susceptibility with genes involved in B cell differentiation (BACH2) and DNA repair (RAD51B). The finding that the RAD51B gene exhibited different associations based on serologic subtype adds to the expanding knowledge base in defining subgroups of RA.
    Arthritis & Rheumatology 12/2013; 65(12). · 7.48 Impact Factor
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    ABSTRACT: There is currently great interest in the incorporation of genetic susceptibility loci into screening models to identify individuals at high risk of disease. Here, we present the first risk prediction model including all 46 known genetic loci associated with rheumatoid arthritis (RA). A weighted genetic risk score (wGRS) was created using 45 RA non-human leucocyte antigen (HLA) susceptibility loci, imputed amino acids at HLA-DRB1 (11, 71 and 74), HLA-DPB1 (position 9) HLA-B (position 9) and gender. The wGRS was tested in 11 366 RA cases and 15 489 healthy controls. The risk of developing RA was estimated using logistic regression by dividing the wGRS into quintiles. The ability of the wGRS to discriminate between cases and controls was assessed by receiver operator characteristic analysis and discrimination improvement tests. Individuals in the highest risk group showed significantly increased odds of developing anti-cyclic citrullinated peptide-positive RA compared to the lowest risk group (OR 27.13, 95% CI 23.70 to 31.05). The wGRS was validated in an independent cohort that showed similar results (area under the curve 0.78, OR 18.00, 95% CI 13.67 to 23.71). Comparison of the full wGRS with a wGRS in which HLA amino acids were replaced by a HLA tag single-nucleotide polymorphism showed a significant loss of sensitivity and specificity. Our study suggests that in RA, even when using all known genetic susceptibility variants, prediction performance remains modest; while this is insufficiently accurate for general population screening, it may prove of more use in targeted studies. Our study has also highlighted the importance of including HLA variation in risk prediction models.
    Annals of the Rheumatic Diseases 10/2013; · 9.27 Impact Factor
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    ABSTRACT: Objective: The number of confirmed rheumatoid arthritis (RA) loci currently stands at 32, but many lines of evidence indicate that expansion of existing genome wide association studies (GWAS) enhances the power to detect additional loci. The objective of this study was to extend our previous UK RA GWAS adding more independent cases and control samples, with the aim of detecting novel association signals for susceptibility to RA in a homogeneous UK cohort. Methods: We had available 3,223 UK RA cases and 5,272 UK controls, which adds 1,361 cases and 2,334 controls to the original GWAS. The genotype data for all cases was imputed using IMPUTE2. After a stringent QC was applied, 3,034 cases, 5,271 controls and 1,831,729 SNPs were available for analysis. Association testing was performed using PLINK. Results: We found suggestive association to 6 novel RA loci (P<10(-4) ) that have previously been associated with other autoimmune diseases and these SNPs were genotyped in independent samples. We validated association with two loci, one of which was associated at genome wide levels of significance in the combined analysis, identifying a novel RA locus at 22q12 (P = 6.9 x 10(-9) ). In addition, we confirmed association to most of the previously known RA susceptibility loci and found increased evidence of association for 16 loci. Conclusions: A new RA locus mapping to 22q12 has been identified. This study supports the evidence that increasing the power of GWAS enhances novel gene discovery. © 2013 American College of Rheumatology.
    Arthritis & Rheumatology 09/2013; · 7.48 Impact Factor
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    ABSTRACT: The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively.
    PLoS Genetics 09/2013; 9(9):e1003808. · 8.17 Impact Factor
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    ABSTRACT: Genome-wide association studies have facilitated the identification of over 30 susceptibility loci for rheumatoid arthritis (RA). However, evidence for a number of potential susceptibility genes have not so far reached genome-wide significance in studies of Caucasian RA. A cohort of 4286 RA patients from across Europe and 5642 population matched controls were genotyped for 25 SNPs, then combined in a meta-analysis with previously published data. Significant evidence of association was detected for nine SNPs within the European samples. When meta-analysed with previously published data, 21 SNPs were associated with RA susceptibility. Although SNPs in the PTPN2 gene were previously reported to be associated with RA in both Japanese and European populations, we show genome-wide evidence for a different SNP within this gene associated with RA susceptibility in an independent European population (rs7234029, P = 4.4×10(-9)). This study provides further genome-wide evidence for the association of the PTPN2 locus (encoding the T cell protein tyrosine phosphastase) with Caucasian RA susceptibility. This finding adds to the growing evidence for PTPN2 being a pan-autoimmune susceptibility gene.
    PLoS ONE 06/2013; 8(6):e66456. · 3.53 Impact Factor
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    ABSTRACT: Objectives: Genome-wide association studies have facilitated the identification of over 30 susceptibility loci for rheumatoid arthritis (RA). However, evidence for a number of potential susceptibility genes have not so far reached genome-wide significance in studies of Caucasian RA. Methods: A cohort of 4286 RA patients from across Europe and 5642 population matched controls were genotyped for 25 SNPs, then combined in a meta-analysis with previously published data. Results: Significant evidence of association was detected for nine SNPs within the European samples. When meta-analysed with previously published data, 21 SNPs were associated with RA susceptibility. Although SNPs in the PTPN2 gene were previously reported to be associated with RA in both Japanese and European populations, we show genome-wide evidence for a different SNP within this gene associated with RA susceptibility in an independent European population (rs7234029, P = 4.4610 29). Conclusions: This study provides further genome-wide evidence for the association of the PTPN2 locus (encoding the T cell protein tyrosine phosphastase) with Caucasian RA susceptibility. This finding adds to the growing evidence for PTPN2 being a pan-autoimmune susceptibility gene. Copyright: ß 2013 Cobb et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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    ABSTRACT: Systemic sclerosis (SSc) and systemic lupus erythematosus (SLE) are two archetypal systemic autoimmune diseases which have been shown to share multiple genetic susceptibility loci. In order to gain insight into the genetic basis of these diseases we performed a pan-meta-analysis of two genome-wide association studies (GWAS) together with a replication stage including additional SSc and SLE cohorts. This increased the sample size to a total of 21,109 (6,835 cases and 14,274 controls). We selected for replication 19 SNPs from the GWAS data. We were able to validate KIAA0319 L (P=3.31x10−11, OR=1.49) as novel susceptibility loci for SSc and SLE. Furthermore, we also determined that the previously described SLE susceptibility loci PXK (P=3.27x10−11, OR=1.20) and JAZF1 (P=1.11x10−8, OR=1.13) are shared with SSc. Supporting these new discoveries, we observed that KIAA0319 L was overexpressed in peripheral blood cells of SSc and SLE patients compared to healthy controls. With these, we add three (KIAA0319 L, PXK and JAZF1) and one (KIAA0319 L) new susceptibility loci for SSc and SLE, respectively, increasing significantly the knowledge of the genetic basis of autoimmunity.
    Human Molecular Genetics 05/2013; 22(19):4021-4029. · 6.68 Impact Factor

Publication Stats

12k Citations
2,153.96 Total Impact Points

Institutions

  • 2014
    • Harvard Medical School
      Boston, Massachusetts, United States
  • 1992–2014
    • The University of Manchester
      • • Musculoskeletal Research Group
      • • Institute of Inflammation and Repair
      • • Centre for Integrated Genomic Medical Research (CIGMR)
      • • Manchester Medical School
      Manchester, England, United Kingdom
  • 2011–2013
    • Spanish National Research Council
      • Institute of Parasitology and Biomedicine "López-Neyra"
      Madrid, Madrid, Spain
    • Leiden University Medical Centre
      • Department of Rheumatology
      Leiden, South Holland, Netherlands
    • University of Texas MD Anderson Cancer Center
      • Department of Epidemiology
      Houston, TX, United States
  • 2012
    • Harvard University
      Cambridge, Massachusetts, United States
    • Concordia University–Ann Arbor
      Ann Arbor, Michigan, United States
    • Central Manchester University Hospitals NHS Foundation Trust
      • Arthritis Research UK Epidemiology Unit
      Manchester, England, United Kingdom
  • 2004–2012
    • The University of Sheffield
      • • Department of Biomedical Science
      • • Academic Unit of Rheumatology
      Sheffield, England, United Kingdom
  • 2010
    • Brigham and Women's Hospital
      • Division of Rheumatology, Immunology, and Allergy
      Boston, MA, United States
    • Wellcome Trust
      Londinium, England, United Kingdom
    • Salford Royal NHS Foundation Trust
      Salford, England, United Kingdom
  • 1991–2009
    • University of New Hampshire at Manchester
      Manchester, New Hampshire, United States
  • 2008
    • Broad Institute of MIT and Harvard
      • Program in Medical and Population Genetics
      Cambridge, MA, United States
  • 2002–2003
    • University of Wales
      • College of Medicine
      Cardiff, Wales, United Kingdom