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Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes

Nature Genetics volume 50, pages 1366–1374 (2018)Cite this article

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Abstract

To define potentially causal variants for autoimmune disease, we fine-mapped1,2 76 rheumatoid arthritis (11,475 cases, 15,870 controls)3 and type 1 diabetes loci (9,334 cases, 11,111 controls)4. After sequencing 799 1-kilobase regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We defined credible sets of ≤5 causal variants at 5 rheumatoid arthritis and 10 type 1 diabetes loci. We identified potentially causal missense variants at DNASE1L3, PTPN22, SH2B3, and TYK2, and noncoding variants at MEG3, CD28–CTLA4, and IL2RA. We also identified potential candidate causal variants at SIRPG and TNFAIP3. Using functional assays, we confirmed allele-specific protein binding and differential enhancer activity for three variants: the CD28–CTLA4 rs117701653 SNP, MEG3 rs34552516 indel, and TNFAIP3 rs35926684 indel.

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Fig. 1: Imputation accuracy and quality of datasets.
Fig. 2: Variants in the 95% credible sets of significant loci determined by the Bayesian factor.
Fig. 3: Analysis of the CD28–CTLA4 locus.
Fig. 4: Analysis of the MEG3 locus.
Fig. 5: Analysis of the TNFAIP3 locus.

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Data availability

Summary statistics for all variants are available through the following GitHub repository: https://github.com/immunogenomics/harmjan/tree/master/RA-T1D-Finemap-SummaryStats. Genotype data have been previously published3,4 and are available from Rheumatoid Arthritis Consortium International and the Type 1 Diabetes Genetics Consortium upon request. The ATAC-Seq data discussed in this publication have been deposited in the Gene Expression Omnibus under accession number GSE116497.

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Acknowledgements

This work is supported in part by funding from the National Institutes of Health (U01GM092691, UH2AR067677, 1U01HG009088, and 1R01AR063759 to S.R.), and Doris Duke Charitable Foundation Grant number 2013097. This work is part of the research program Rubicon ALW with project number 825.14.019 (H.-J.W.), which is partly financed by the Netherlands Organization for Scientific Research. Further support was provided by Wellcome (107212/Z/15/Z) and the Juvenile Diabetes Research Foundation (5-SRA-2015-130-A-N) to the Diabetes and Inflammation Laboratory, and by Wellcome (203141/Z/16/Z) to the Wellcome Centre for Human Genetics (J.A.T.). P.K.G. was supported in part by the Feinstein Institute and a generous gift from E. L. Greenland. P.A.N. is supported by a Rheumatology Research Foundation Disease Targeted Research Grant, NIH P30 AR070253 and R01 AR065538, and the Fundación Bechara. S.S.R., W.-M.C. and S.O. were supported in part by funding from the National Institutes of Health (R01DK096926). This research makes use of resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Allergy and Infectious Diseases, National Human Genome Research Institute, National Institute of Child Health and Human Development and Juvenile Diabetes Research Foundation International, and is supported by grant U01DK062418 (S.S.R.).

Author information

Author notes

  1. These authors contributed equally: Harm-Jan Westra, Marta Martínez-Bonet.

Authors and Affiliations

  1. Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Harm-Jan Westra, Yang Luo, Nikola Teslovich & Soumya Raychaudhuri

  2. Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Harm-Jan Westra, Yang Luo, Nikola Teslovich & Soumya Raychaudhuri

  3. Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA

    Harm-Jan Westra, Yang Luo, Nikola Teslovich & Soumya Raychaudhuri

  4. Division of Rheumatology, Immunology, and Allergy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Harm-Jan Westra, Marta Martínez-Bonet, Yang Luo, Nikola Teslovich, Peter A. Nigrovic & Soumya Raychaudhuri

  5. Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

    Harm-Jan Westra

  6. Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA

    Suna Onengut-Gumuscu, Wei-Min Chen, Aaron Quinlan & Stephen S. Rich

  7. Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA

    Suna Onengut-Gumuscu, Wei-Min Chen & Stephen S. Rich

  8. The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, USA

    Annette Lee & Peter K. Gregersen

  9. Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK

    Jane Worthington, Steve Eyre & Soumya Raychaudhuri

  10. NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK

    Jane Worthington & Steve Eyre

  11. Instituto de Parasitología y Biomedicina López-Neyra, Consejo Superior de Investigaciones Científicas, Granada, Spain

    Javier Martin

  12. Department of Rheumatology, Leiden University Medical Centre, Leiden, The Netherlands

    Tom Huizinga

  13. Rheumatology Unit, Department of Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden

    Lars Klareskog

  14. Department of Public Health and Clinical Medicine, Division of Rheumatology, Umeå University, Umeå, Sweden

    Solbritt Rantapaa-Dahlqvist

  15. Department of Human Genetics, University of Utah, Salt Lake City, UT, USA

    Aaron Quinlan

  16. Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA

    Aaron Quinlan

  17. JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK

    John A. Todd

  18. Division of Immunology, Boston Children’s Hospital, Boston, MA, USA

    Peter A. Nigrovic

  19. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    Soumya Raychaudhuri

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  1. Harm-Jan Westra
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Contributions

H.-J.W., Y.L. and S.R. performed the analyses. M.M.-B. and P.A.N. performed the functional assays. H.-J.W., M.M.-B., P.A.N. and S.R. designed the study. S.O., A.L., N.T., J.W., J.M., T.H., L.K., S.R.-D., W.-M.C., A.Q., J.A.T., S.E., P.K.G., S.S.R. and S.R. acquired the data. H.-J.W., M.M.-B., Y.L., J.A.T., P.A.N., P.K.G., S.S.R. and S.R. wrote and edited the manuscript.

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Correspondence to Soumya Raychaudhuri.

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Westra, HJ., Martínez-Bonet, M., Onengut-Gumuscu, S. et al. Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes. Nat Genet 50, 1366–1374 (2018). https://doi.org/10.1038/s41588-018-0216-7

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