Genome-wide association studies (GWAS) have identified common variants of modest-effect size at hundreds of loci for common autoimmune diseases; however, a substantial fraction of heritability remains unexplained, to which rare variants may contribute1,2. To discover rare variants and test them for association with a phenotype, most studies re-sequence a small initial sample size and then genotype the discovered variants in a larger sample set3,4,5. This approach fails to analyse a large fraction of the rare variants present in the entire sample set. Here we perform simultaneous amplicon-sequencing-based variant discovery and genotyping for coding exons of 25 GWAS risk genes in 41,911 UK residents of white European origin, comprising 24,892 subjects with six autoimmune disease phenotypes and 17,019 controls, and show that rare coding-region variants at known loci have a negligible role in common autoimmune disease susceptibility. These results do not support the rare-variant synthetic genome-wide-association hypothesis6 (in which unobserved rare causal variants lead to association detected at common tag variants). Many known autoimmune disease risk loci contain multiple, independently associated, common and low-frequency variants, and so genes at these loci are a priori stronger candidates for harbouring rare coding-region variants than other genes. Our data indicate that the missing heritability for common autoimmune diseases may not be attributable to the rare coding-region variant portion of the allelic spectrum, but perhaps, as others have proposed, may be a result of many common-variant loci of weak effect7,8,9,10.

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Data deposits

Genome data has been deposited at the European Genome–phenome Archive (http://www.ebi.ac.uk/ega/), which is hosted at the EBI, under accession number EGAS00001000476.


  1. 1.

    et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009)

  2. 2.

    Rare and common variants: twenty arguments. Nature Rev. Genet. 13, 135–145 (2012)

  3. 3.

    , , , & Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes. Science 324, 387–389 (2009)

  4. 4.

    et al. Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease. Nature Genet. 43, 1066–1073 (2011)

  5. 5.

    et al. Resequencing of positional candidates identifies low frequency IL23R coding variants protecting against inflammatory bowel disease. Nature Genet. 43, 43–47 (2011)

  6. 6.

    , , , & Rare variants create synthetic genome-wide associations. PLoS Biol. 8, e1000294 (2010)

  7. 7.

    , , , & Finding the sources of missing heritability in a yeast cross. Nature 494, 234–237 (2013)

  8. 8.

    et al. Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis. Nature Genet. 44, 483–489 (2012)

  9. 9.

    et al. Estimation of effect size distribution from genome-wide association studies and implications for future discoveries. Nature Genet. 42, 570–575 (2010)

  10. 10.

    et al. Common SNPs explain a large proportion of the heritability for human height. Nature Genet. 42, 565–569 (2010)

  11. 11.

    et al. Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nature Commun. 1, 131 (2010)

  12. 12.

    et al. An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people. Science 337, 100–104 (2012)

  13. 13.

    et al. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science 337, 64–69 (2012)

  14. 14.

    et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 493, 216–220 (2013)

  15. 15.

    et al. A genome-wide association study identifies new psoriasis susceptibility loci and an interaction between HLA-C and ERAP1. Nature Genet. 42, 985–990 (2010)

  16. 16.

    et al. Rare and common variants in CARD14, encoding an epidermal regulator of NF-kappaB, in psoriasis. Am. J. Hum. Genet. 90, 796–808 (2012)

  17. 17.

    et al. Rare, low-frequency, and common variants in the protein-coding sequence of biological candidate genes from GWASs contribute to risk of rheumatoid arthritis. Am. J. Hum. Genet. 92, 15–27 (2013)

  18. 18.

    et al. CARD15/NOD2 mutational analysis and genotype-phenotype correlation in 612 patients with inflammatory bowel disease. Am. J. Hum. Genet. 70, 845–857 (2002)

  19. 19.

    et al. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease. Nature Genet. 43, 1193–1201 (2011)

  20. 20.

    et al. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature Genet. 41, 703–707 (2009)

  21. 21.

    et al. Lupus-associated causal mutation in neutrophil cytosolic factor 2 (NCF2) brings unique insights to the structure and function of NADPH oxidase. Proc. Natl Acad. Sci. USA 109, E59–E67 (2012)

  22. 22.

    & Neutrophil recruitment and function in health and inflammation. Nature Rev. Immunol. 13, 159–175 (2013)

  23. 23.

    & Estimating genetic effects and quantifying missing heritability explained by identified rare-variant associations. Am. J. Hum. Genet. 91, 585–596 (2012)

  24. 24.

    et al. Seven newly identified loci for autoimmune thyroid disease. Hum Mol Genet 21, 5202–5208 (2012)

  25. 25.

    et al. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012)

  26. 26.

    et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature 476, 214–219 (2011)

  27. 27.

    et al. Identification of 15 new psoriasis susceptibility loci highlights the role of innate immunity. Nat Genet 44, 1341–1348 (2012)

  28. 28.

    et al. Cell-specific protein phenotypes for the autoimmune locus IL2RA using a genotype-selectable human bioresource. Nat Genet 41, 1011–1015 (2009)

  29. 29.

    Btrim: a fast, lightweight adapter and quality trimming program for next-generation sequencing technologies. Genomics 98, 152–153 (2011)

  30. 30.

    et al. A systematic survey of loss-of-function variants in human protein-coding genes. Science 335, 823–828 (2012)

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The study was primarily funded by the Medical Research Council (MRC G1001158 to D.A.v.H and V.P.), with further funding from Coeliac UK (to D.A.v.H). We thank C. Wijmenga and G. Trynka for sharing ImmunoChip data, and the International Multiple Sclerosis Genomics Consortium for ImmunoChip data and samples. J.N.B. and R.C.T. are supported by MRC grant G0601387. This research was supported by the National Institutes for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The study was supported by the Cambridge NIHR Biomedical Research Centre. We thank E. Gray and D. Jones (Wellcome Trust Sanger Institute) for sample preparation. We acknowledge use of DNA from The UK Blood Services collection of Common Controls (UKBS-CC collection), funded by the Wellcome Trust grant 076113/C/04/Z and by NIHR programme grant to NHS Blood and Transplant (RP-PG-0310-1002). The collection was established as part of the Wellcome Trust Case Control Consortium (WTCCC). We acknowledge use of DNA from the British 1958 Birth Cohort collection, funded by the UK MRC grant G0000934 and the Wellcome Trust grant 068545/Z/02. We thank nurses and doctors for recruiting autoimmune thyroid disease (AITD) subjects into the AITD National Collection, funded by the Wellcome Trust grant 068181. We acknowledge use of DNA from the Cambridge BioResource. We acknowledge use of DNA from the Juvenile Diabetes Research Foundation (JDRF)/Wellcome Trust Case-Series (GRID), funded by JDRF and the Wellcome Trust (grant references JDRF 4-2001-1008 and WT061858). The subjects were recruited in the UK by D. Dunger and his team with support from the British Society for Paediatric Endocrinology and Diabetes. The samples were prepared and provided by the JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, University of Cambridge, UK. Psoriasis samples used were based on the WTCCC2 GWAS clinical panel, for which we thank D. Burden, C. Griffiths, M. Cork and R. McManus. Finally, we would like to thank all autoimmune disease and control subjects for participating in this study.

Author information


  1. Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK

    • Karen A. Hunt
    • , Vanisha Mistry
    • , Nicholas A. Bockett
    •  & David A. van Heel
  2. Peninsula College of Medicine and Dentistry, Barrack Road, Exeter EX2 5DW, UK

    • Tariq Ahmad
  3. University of Cambridge, Department of Clinical Neurosciences, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK

    • Maria Ban
    • , Alastair Compston
    •  & Steven Sawcer
  4. Division of Genetics and Molecular Medicine, King’s College London School of Medicine, 8th Floor Tower Wing, Guy’s Hospital, London SE1 9RT, UK

    • Jonathan N. Barker
    • , Francesca Capon
    • , Christopher G. Mathew
    • , Muddassar Mirza
    • , Efterpi Papouli
    •  & Michael A. Simpson
  5. Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK

    • Jeffrey C. Barrett
    •  & Hannah Blackburn
  6. Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK

    • Oliver Brand
    • , Stephen C. L. Gough
    •  & Matthew J. Simmonds
  7. Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, UK

    • Oliver Burren
    • , Sarah Nutland
    • , Neil M. Walker
    •  & John A. Todd
  8. Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, UK

    • Luke Jostins
  9. Department of Molecular Biophysics and Biochemistry, W.M. Keck Foundation Biotechnology Resource Laboratory, Yale University, New Haven, Connecticut 06510, USA

    • Yong Kong
  10. Department of Medicine, University of Cambridge School of Clinical Medicine, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK

    • James C. Lee
    •  & Miles Parkes
  11. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA

    • Monkol Lek
    •  & Daniel G. MacArthur
  12. Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne NE1 3BZ, UK

    • John C. Mansfield
  13. Genome Centre, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London EC1M 6BQ, UK

    • Charles A. Mein
    •  & Eva Wozniak
  14. Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia 22908-0717, USA

    • Suna Onengut-Gumuscu
    •  & Stephen S. Rich
  15. Gastrointestinal Unit, Molecular Medicine Centre, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK

    • Jack Satsangi
  16. Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK

    • Richard C. Trembath
  17. University College London Genetics Institute, Gower Street, London WC1E 6BT, UK

    • Vincent Plagnol


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D.A.v.H. designed and led the study. K.A.H. coordinated wet laboratory work, with K.A.H., V.M., N.A.B. and E.W. performing DNA sample preparation, Fluidigm PCR amplification, sample barcoding, MiSeq library validation and Sanger sequencing preparation. HiSeq sequencing was performed by M.M. and E.P. D.A.v.H., V.P. and M.S. performed bioinformatics and statistical analyses. All other authors contributed to diverse aspects of sample collection, phenotyping, DNA preparation, ImmunoChip data production or specific analyses. D.A.v.H. and V.P drafted the manuscript, which all authors reviewed.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Vincent Plagnol or David A. van Heel.

Supplementary information

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    Supplementary Information

    This file contains Supplementary Tables 1-4 and Supplementary Figures 1-3.

Excel files

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    Supplementary Data

    This file contains full results (for all tested phenotypes, all MAF, all single variants or pooled gene tests) for the data shown in Supplementary Table 4 and Figure 1.

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