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Common variants in the HLA-DQ region confer susceptibility to idiopathic achalasia

Nature Genetics volume 46, pages 901–904 (2014)Cite this article

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Abstract

Idiopathic achalasia is characterized by a failure of the lower esophageal sphincter to relax due to a loss of neurons in the myenteric plexus1,2. This ultimately leads to massive dilatation and an irreversibly impaired megaesophagus. We performed a genetic association study in 1,068 achalasia cases and 4,242 controls and fine-mapped a strong MHC association signal by imputing classical HLA haplotypes and amino acid polymorphisms. An eight-residue insertion at position 227–234 in the cytoplasmic tail of HLA-DQβ1 (encoded by HLA-DQB1*05:03 and HLA-DQB1*06:01) confers the strongest risk for achalasia (P = 1.73 × 10−19). In addition, two amino acid substitutions in the extracellular domain of HLA-DQα1 at position 41 (lysine encoded by HLA-DQA1*01:03; P = 5.60 × 10−10) and of HLA-DQβ1 at position 45 (glutamic acid encoded by HLA-DQB1*03:01 and HLA-DQB1*03:04; P = 1.20 × 10−9) independently confer achalasia risk. Our study implies that immune-mediated processes are involved in the pathophysiology of achalasia.

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Figure 1: Immunochip association analysis across 1,068 achalasia cases and 4,242 controls.
Figure 2: Structural model of the extracellular part of HLA-DQ.

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References

  1. Gockel, H.R. et al. Achalasia: will genetic studies provide insights? Hum. Genet. 128, 353–364 (2010).

    Article  CAS  Google Scholar 

  2. Park, W. & Vaezi, M.F. Etiology and pathogenesis of achalasia: the current understanding. Am. J. Gastroenterol. 100, 1404–1414 (2005).

    Article  Google Scholar 

  3. de Bakker, P.I. et al. A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC. Nat. Genet. 38, 1166–1172 (2006).

    Article  CAS  Google Scholar 

  4. Jia, X. et al. Imputing amino acid polymorphisms in human leukocyte antigens. PLoS ONE 8, e64683 (2013).

    Article  CAS  Google Scholar 

  5. Senju, S. et al. Allele-specific expression of the cytoplasmic exon of HLA-DQB1 gene. Immunogenetics 36, 319–325 (1992).

    Article  CAS  Google Scholar 

  6. Raychaudhuri, S. et al. Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis. Nat. Genet. 44, 291–296 (2012).

    Article  CAS  Google Scholar 

  7. Pos, W. et al. Crystal structure of the HLA-DM–HLA-DR1 complex defines mechanisms for rapid peptide selection. Cell 151, 1557–1568 (2012).

    Article  CAS  Google Scholar 

  8. Khalil, H. et al. The MHC class II β chain cytoplasmic tail overcomes the invariant chain p35-encoded endoplasmic reticulum retention signal. Int. Immunol. 15, 1249–1263 (2003).

    Article  CAS  Google Scholar 

  9. Parkes, M., Cortes, A., van Heel, D.A. & Brown, M.A. Genetic insights into common pathways and complex relationships among immune-mediated diseases. Nat. Rev. Genet. 14, 661–673 (2013).

    Article  CAS  Google Scholar 

  10. Tollefsen, S. et al. Structural and functional studies of trans-encoded HLA-DQ2.3 (DQA1*03:01/DQB1*02:01) protein molecule. J. Biol. Chem. 287, 13611–13619 (2012).

    Article  CAS  Google Scholar 

  11. Robinson, J. et al. The IMGT/HLA database. Nucleic Acids Res. 39, D1171–D1176 (2011).

    Article  CAS  Google Scholar 

  12. Schmermund, A. et al. Assessment of clinically silent atherosclerotic disease and established and novel risk factors for predicting myocardial infarction and cardiac death in healthy middle-aged subjects: rationale and design of the Heinz Nixdorf RECALL Study. Risk Factors, Evaluation of Coronary Calcium and Lifestyle. Am. Heart J. 144, 212–218 (2002).

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  14. Manichaikul, A. et al. Robust relationship inference in genome-wide association studies. Bioinformatics 26, 2867–2873 (2010).

    Article  CAS  Google Scholar 

  15. Browning, B.L. & Browning, S.R. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am. J. Hum. Genet. 84, 210–223 (2009).

    Article  CAS  Google Scholar 

  16. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  Google Scholar 

  17. SAS Institute, Inc. SAS/STAT 9.2 User's Guide (SAS Institute, Inc., Cary, NC, 2008).

Download references

Acknowledgements

We thank all subjects for participating to this study. We acknowledge our collaborating clinical partners, all colleagues who contributed to patient recruitment, and our laboratory technicians and colleagues responsible for database management (for a complete list of all individuals, see the Supplementary Note). I.G., M.K. and J.S. received support for this work from the Deutsche Forschungsgemeinschaft (DFG), individual grants GO 1795/1-1, KN 378/2-1 and SCHU 1596/5-1. M.M.N. received support for this work from the Alfried Krupp von Bohlen und Halbach-Stiftung. M.M.N. is a member of the DFG-funded Excellence Cluster ImmunoSensation. The Heinz Nixdorf Recall cohort was established with the generous support of the Heinz Nixdorf Foundation, Germany. We thank B. Pötzsch (University of Bonn) for help with collecting DNA samples from anonymous blood donors. In addition, we thank the Type I Diabetes Genetics Consortium (T1DGC) for data access and J. Sauter (German Bone Marrow Donor Center (DKMS), Tübingen) for help differentiating HLA-DQA1 alleles. P.I.W.d.B. is the recipient of a Vernieuwingsimpuls VIDI Award from the Netherlands Organization for Scientific Research (NWO project 016.126.354). M.M.W. is supported by a postdoctoral fellowship of the Fund for Scientific Research (FWO) Flanders, Belgium. G.E.B. is supported by a grant from the Research Foundation–Flanders (FWO) (Odysseus program). K.-P.H. is supported by DFG SFB 684 and the Center for Integrated Protein Sciences Munich.

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Author notes

  1. Ines Gockel and Jessica Becker: These authors contributed equally to this work.

  2. Michael Knapp and Johannes Schumacher: These authors jointly directed this work.

Authors and Affiliations

  1. Department of General, Visceral and Transplant Surgery, University Medical Center, University of Mainz, Mainz, Germany

    Ines Gockel, Stefan Niebisch, Henning R Gockel, Daniel Drescher, Werner Kneist & Hauke Lang

  2. Institute of Human Genetics, University of Bonn, Bonn, Germany

    Jessica Becker, Timo Hess, Per Hoffmann, Stefan Herms, Elisabeth Mangold, Stefanie Heilmann, Markus M Nöthen & Johannes Schumacher

  3. Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany

    Jessica Becker, Timo Hess, Per Hoffmann, Stefan Herms, Elisabeth Mangold, Stefanie Heilmann, Markus M Nöthen & Johannes Schumacher

  4. Translational Research Center for Gastrointestinal Disorders, Catholic University of Leuven, Leuven, Belgium

    Mira M Wouters, Jan Tack & Guy E Boeckxstaens

  5. Department of Neurology, Division of Clinical Neurosciences, University of Bonn, Bonn, Germany

    David Ramonet, Julian Zimmermann & Michael T Heneka

  6. Department of Immunology, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain

    Ana González Vigo & Elena Urcelay

  7. Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

    Gosia Trynka, Vinod Kumar, Lude Franke, Harm-Jan Westra & Cisca Wijmenga

  8. Department of Gastroenterology, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain

    Antonio Ruiz de León & Julio Pérez de la Serna

  9. First Department of Internal Medicine, University Medical Center, University of Mainz, Mainz, Germany

    Jens U Marquardt & Peter R Galle

  10. Department of Biomedicine, Aarhus University, Aarhus, Denmark

    Manuel Mattheisen

  11. Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark

    Manuel Mattheisen

  12. Department of Gastroenterology, Careggi Hospital, University of Florence, Florence, Italy

    Vito Annese

  13. Division of Gastroenterology, Istituto di Ricovero e Cura a Carattere Scientifico, Casa Sollievo della Sofferenza Hospital, San Giovanni Rotondo, Italy

    Anna Latiano

  14. Department of Surgery, Istituto Clinico Humanitas, Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy

    Uberto Fumagalli

  15. Department of Gastroenterology, Istituto Clinico Humanitas, Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy

    Luigi Laghi

  16. Department of Clinical Medicine and Surgery, Division of Gastroenterology, Federico II University Hospital School of Medicine, Naples, Italy

    Rosario Cuomo & Giovanni Sarnelli

  17. Department of Gastroenterology, German Diagnostic Clinic, Wiesbaden, Germany

    Michaela Müller & Alexander J Eckardt

  18. Division of Medical Genetics, University Hospital, Basel, Switzerland

    Per Hoffmann & Stefan Herms

  19. Department of Biomedicine, Human Genetics Research Group, University of Basel, Basel, Switzerland

    Per Hoffmann & Stefan Herms

  20. Department of Internal Medicine, Hospital St. Marien, Frankfurt, Germany

    Ralf Kiesslich

  21. Department of General, Visceral, Vascular and Pediatric Surgery, University of Würzburg, Würzburg, Germany

    Burkhard H A von Rahden

  22. Center of Internal Medicine, Hospital Garmisch-Partenkirchen, Garmisch-Partenkirchen, Germany

    Hans-Dieter Allescher

  23. Department of General and Abdominal Surgery, Protestant Hospital Castrop-Rauxel, Castrop-Rauxel, Germany

    Henning G Schulz

  24. Department of Biochemistry, Gene Center, Ludwig Maximilians University, Munich, Germany

    Karl-Peter Hopfner

  25. Center for Integrated Protein Sciences, Munich, Germany

    Karl-Peter Hopfner

  26. Department of Epidemiology, University Medical Center Utrecht, Utrecht, the Netherlands

    Paul I W de Bakker

  27. Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, the Netherlands

    Paul I W de Bakker

  28. Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany

    Michael Knapp

Authors
  1. Ines Gockel
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  2. Jessica Becker
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  3. Mira M Wouters
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  47. Johannes Schumacher
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Contributions

H.L., I.G., J.B., J.S., M.M.N. and M.T.H. initiated the study. J.B., J.S., K.-P.H., M.K. and P.I.W.d.B. analyzed and interpreted the data. D.R., J.B., J.T., J.Z., M.M.W. and T.H. prepared the DNA and performed the molecular genetic experiments. A.G.V., A.J.E., A.L., A.R.d.L., B.H.A.v.R., D.D., E.M., E.U., G.E.B., G.S., H.-D.A., H.R.G., H.G.S., I.G., J.P.d.l.S., J.U.M., L.L., M. Müller, P.R.G., R.C., R.K., S. Heilmann, S.N., U.F., V.A. and W.K. clinically characterized the achalasia cases and/or collected blood samples from cases and/or controls. C.W., G.T., H.-J.W., L.F. and V.K. provided genotype data from the Dutch, Italian and Spanish controls. M. Mattheisen, P.H. and S. Herms provided database management. I.G., J.B., J.S., M.K. and M.M.N. prepared the manuscript, with feedback from the other authors.

Corresponding author

Correspondence to Johannes Schumacher.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Association results within the MHC region.

(a) The strongest genetic determinant of achalasia risk represents an 8-residue insertion at position 227–234 in HLA-DQβ1. (b) Subsequent conditional analysis controlling for this insertion as well as for amino acid changes at position 41/130 in HLA-DQα1 and position 45 in HLA-DQβ1 revealed no further independent association within the MHC region (P > 1 × 10−6).

Supplementary Figure 2 Comparison of disease risk predicted by two different models.

This figure shows the comparison of the disease risk predicted by a full logistic regression model in which each HLA-DQ allele confers its own unique risk (y axis) with the disease risk predicted by a simpler logistic regression model in which risk is defined by HLA-DQβ1 positions 227–234 and 45 as well as HLA-DQα1 position 41/130 (x axis). Patients are represented in red, and controls are represented in blue.

Supplementary Figure 3 Multidimensional scaling (MDS) analysis.

Representation of our study sample and HapMap individuals for the first two dimensions obtained by multidimensional scaling analysis of a matrix of pairwise IBS (identical-by-state) distance values between samples.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3, Supplementary Tables 1–9 and Supplementary Note. (PDF 1032 kb)

Supplementary Table 10

Imputation of classical HLA haplotypes. (XLSX 44 kb)

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Gockel, I., Becker, J., Wouters, M. et al. Common variants in the HLA-DQ region confer susceptibility to idiopathic achalasia. Nat Genet 46, 901–904 (2014). https://doi.org/10.1038/ng.3029

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