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Common variants in the HLA-DRB1–HLA-DQA1 HLA class II region are associated with susceptibility to visceral leishmaniasis

Nature Genetics volume 45, pages 208–213 (2013)Cite this article

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Abstract

To identify susceptibility loci for visceral leishmaniasis, we undertook genome-wide association studies in two populations: 989 cases and 1,089 controls from India and 357 cases in 308 Brazilian families (1,970 individuals). The HLA-DRB1–HLA-DQA1 locus was the only region to show strong evidence of association in both populations. Replication at this region was undertaken in a second Indian population comprising 941 cases and 990 controls, and combined analysis across the three cohorts for rs9271858 at this locus showed Pcombined = 2.76 × 10−17 and odds ratio (OR) = 1.41, 95% confidence interval (CI) = 1.30–1.52. A conditional analysis provided evidence for multiple associations within the HLA-DRB1–HLA-DQA1 region, and a model in which risk differed between three groups of haplotypes better explained the signal and was significant in the Indian discovery and replication cohorts. In conclusion, the HLA-DRB1–HLA-DQA1 HLA class II region contributes to visceral leishmaniasis susceptibility in India and Brazil, suggesting shared genetic risk factors for visceral leishmaniasis that cross the epidemiological divides of geography and parasite species.

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Figure 1: Plot of genome-wide association results for the separate and combined discovery GWAS using a variance components method.
Figure 2: Regional association plots of the signal at the MHC region.
Figure 3: Schematic of the HLA and SNP phased Indian discovery haplotypes in the MHC region.

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References

  1. Alvar, J. et al. Leishmaniasis worldwide and global estimates of its incidence. PLoS ONE 7, e35671 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Bucheton, B. et al. The interplay between environmental and host factors during an outbreak of visceral leishmaniasis in eastern Sudan. Microbes Infect. 4, 1449–1457 (2002).

    Article  PubMed  Google Scholar 

  3. Sacks, D.L., Lal, S.L., Shrivastava, S.N., Blackwell, J.M. & Neva, F.A. An analysis of T cell responsiveness in Indian Kala-azar. J. Immunol. 138, 908–913 (1987).

    CAS  PubMed  Google Scholar 

  4. Ho, M., Siongok, T.K., Lyerly, W.H. & Smith, D.H. Prevalence and disease spectrum in a new focus of visceral leishmaniasis in Kenya. Trans. R. Soc. Trop. Med. Hyg. 76, 741–746 (1982).

    Article  CAS  PubMed  Google Scholar 

  5. Cabello, P.H., Lima, A.M., Azevedo, E.S. & Kriger, H. Familial aggregation of Leishmnaia chagasi infection in northeastern Brazil. Am. J. Trop. Med. Hyg. 52, 364–365 (1995).

    Article  CAS  PubMed  Google Scholar 

  6. Peacock, C.S. et al. Genetic epidemiology of visceral leishmaniasis in northeastern Brazil. Genet. Epidemiol. 20, 383–396 (2001).

    Article  CAS  PubMed  Google Scholar 

  7. Burgner, D., Jamieson, S.E. & Blackwell, J.M. Genetic susceptibility to infectious diseases: big is beautiful, but will bigger be even better? Lancet Infect. Dis. 6, 653–663 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Blackwell, J.M. et al. Genetics and visceral leishmaniasis: of mice and man. Parasite Immunol. 31, 254–266 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Blackwell, J.M., Jamieson, S.E. & Burgner, D. HLA and infectious diseases. Clin. Microbiol. Rev. 22, 370–385 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Jeronimo, S.M. et al. Genetic predisposition to self-curing infection with the protozoan Leishmania chagasi: a genomewide scan. J. Infect. Dis. 196, 1261–1269 (2007).

    Article  CAS  PubMed  Google Scholar 

  11. Ettinger, N.A. et al. Genetic admixture in Brazilians exposed to infection with Leishmania chagasi. Ann. Hum. Genet. 73, 304–313 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Bellenguez, C., Strange, A., Freeman, C., Donnelly, P. & Spencer, C.C. A robust clustering algorithm for identifying problematic samples in genome-wide association studies. Bioinformatics 28, 134–135 (2012).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Astle, W. & Balding, D.J. Population structure and cryptic relatedness in genetic association studies. Stat. Sci. 24, 451–471 (2009).

    Article  Google Scholar 

  15. Lippert, C. et al. FaST linear mixed models for genome-wide association studies. Nat. Methods 8, 833–835 (2011).

    Article  CAS  PubMed  Google Scholar 

  16. Zhang, Z. et al. Mixed linear model approach adapted for genome-wide association studies. Nat. Genet. 42, 355–360 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kang, H.M. et al. Variance component model to account for sample structure in genome-wide association studies. Nat. Genet. 42, 348–354 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Amin, N., van Duijn, C.M. & Aulchenko, Y.S. A genomic background based method for association analysis in related individuals. PLoS ONE 2, e1274 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Mehrotra, S. et al. Genetic and functional evaluation of the role of CXCR1 and CXCR2 in susceptibility to visceral leishmaniasis in north-east India. BMC Med. Genet. 12, 162 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Bucheton, B. et al. Identification of a novel G245R polymorphism in the IL-2 receptor β membrane proximal domain associated with human visceral leishmaniasis. Genes Immun. 8, 79–83 (2007).

    Article  CAS  PubMed  Google Scholar 

  21. Jamieson, S.E. et al. Genome-wide scan for visceral leishmaniasis susceptibility genes in Brazil. Genes Immun. 8, 84–90 (2007).

    Article  CAS  PubMed  Google Scholar 

  22. Fakiola, M. et al. Genetic and functional evidence implicating DLL1 as the gene that influences susceptibility to visceral leishmaniasis at chromosome 6q27. J. Infect. Dis. 204, 467–477 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mohamed, H.S. et al. SLC11A1 (formerly NRAMP1) and susceptibility to visceral leishmaniasis in The Sudan. Eur. J. Hum. Genet. 12, 66–74 (2004).

    Article  CAS  PubMed  Google Scholar 

  24. Cortes, A. & Brown, M.A. Promise and pitfalls of the Immunochip. Arthritis Res. Ther. 13, 101 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  25. 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  PubMed  PubMed Central  Google Scholar 

  26. Sundar, S., Reed, S.G., Sharma, S., Mehrotra, A. & Murray, H.W. Circulating T helper 1 (Th1) cell– and Th2 cell–associated cytokines in Indian patients with visceral leishmaniasis. Am. J. Trop. Med. Hyg. 56, 522–525 (1997).

    Article  CAS  PubMed  Google Scholar 

  27. Carvalho, E.M. et al. Immunologic markers of clinical evolution in children recently infected with Leishmania donovani chagasi. J. Infect. Dis. 165, 535–540 (1992).

    Article  CAS  PubMed  Google Scholar 

  28. Meddeb-Garnaoui, A. et al. Association analysis of HLA-class II and class III gene polymorphisms in the susceptibility to mediterranean visceral leishmaniasis. Hum. Immunol. 62, 509–517 (2001).

    Article  CAS  PubMed  Google Scholar 

  29. Kuhls, K. et al. Comparative microsatellite typing of new world leishmania infantum reveals low heterogeneity among populations and its recent old world origin. PLoS Negl. Trop. Dis. 5, e1155 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Olivo-Díaz, A. et al. Role of HLA class II alleles in susceptibility to and protection from localized cutaneous leishmaniasis. Hum. Immunol. 65, 255–261 (2004).

    Article  PubMed  CAS  Google Scholar 

  31. Cabrera, M. et al. Polymorphism in TNF genes associated with mucocutaneous leishmaniasis. J. Exp. Med. 182, 1259–1264 (1995).

    Article  CAS  PubMed  Google Scholar 

  32. Petzl-Erler, M.L., Belich, M.P. & Queiroz-Telles, F. Association of mucosal leishmaniasis with HLA. Hum. Immunol. 32, 254–260 (1991).

    Article  CAS  PubMed  Google Scholar 

  33. Jallow, M. et al. Genome-wide and fine-resolution association analysis of malaria in West Africa. Nat. Genet. 41, 657–665 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Thye, T. et al. Genome-wide association analyses identifies a susceptibility locus for tuberculosis on chromosome 18q11.2. Nat. Genet. 42, 739–741 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Khor, C.C. et al. Genome-wide association study identifies susceptibility loci for dengue shock syndrome at MICB and PLCE1. Nat. Genet. 43, 1139–1141 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Zhang, F.R. et al. Genomewide association study of leprosy. N. Engl. J. Med. 361, 2609–2618 (2009).

    Article  CAS  PubMed  Google Scholar 

  37. Singh, S.P., Reddy, D.C., Mishra, R.N. & Sundar, S. Knowledge, attitude, and practices related to Kala-azar in a rural area of Bihar state, India. Am. J. Trop. Med. Hyg. 75, 505–508 (2006).

    Article  PubMed  Google Scholar 

  38. Manna, M., Majumder, H.K., Sundar, S. & Bhaduri, A.N. The molecular characterization of clinical isolates from Indian Kala-azar patients by MLEE and RAPD-PCR. Med. Sci. Monit. 11, BR220–BR227 (2005).

    CAS  PubMed  Google Scholar 

  39. Chatterjee, M., Manna, M., Bhaduri, A.N. & Sarkar, D. Recent kala-azar cases in India: isozyme profiles of Leishmania parasites. Indian J. Med. Res. 102, 165–172 (1995).

    CAS  PubMed  Google Scholar 

  40. Thakur, C.P., Dedet, J.P., Narain, S. & Pratlong, F. Leishmania species, drug unresponsiveness and visceral leishmaniasis in Bihar, India. Trans. R. Soc. Trop. Med. Hyg. 95, 187–189 (2001).

    Article  CAS  PubMed  Google Scholar 

  41. Sundar, S. et al. Resistance to treatment in Kala-azar: speciation of isolates from northeast India. Am. J. Trop. Med. Hyg. 65, 193–196 (2001).

    Article  CAS  PubMed  Google Scholar 

  42. Blackwell, J.M. et al. Immunogenetics of leishmanial and mycobacterial infections: the Belem Family Study. Phil. Trans. R. Soc. Lond. B 352, 1331–1345 (1997).

    Article  CAS  Google Scholar 

  43. Jeronimo, S.M. et al. An emerging peri-urban pattern of infection with Leishmania chagasi, the protozoan causing visceral leishmaniasis in northeast Brazil. Scand. J. Infect. Dis. 36, 443–449 (2004).

    Article  PubMed  Google Scholar 

  44. Khalil, E.A., Zijlstra, E.E., Kager, P.A. & El Hassan, A.M. Epidemiology and clinical manifestations of Leishmania donovani infection in two villages in an endemic area in eastern Sudan. Trop. Med. Int. Health 7, 35–44 (2002).

    Article  CAS  PubMed  Google Scholar 

  45. Fakiola, M. et al. Classification and regression tree and spatial analyses reveal geographic heterogeneity in genome wide linkage study of Indian visceral leishmaniasis. PLoS ONE 5, e15807 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Zijlstra, E.E., el-Hassan, A.M., Ismael, A. & Ghalib, H.W. Endemic kala-azar in eastern Sudan: a longitudinal study on the incidence of clinical and subclinical infection and post-kala-azar dermal leishmaniasis. Am. J. Trop. Med. Hyg. 51, 826–836 (1994).

    Article  CAS  PubMed  Google Scholar 

  47. Conrad, D.F. et al. Origins and functional impact of copy number variation in the human genome. Nature 464, 704–712 (2010).

    Article  CAS  PubMed  Google Scholar 

  48. Barrett, J.C. et al. Genome-wide association study of ulcerative colitis identifies three new susceptibility loci, including the HNF4A region. Nat. Genet. 41, 1330–1334 (2009).

    Article  CAS  PubMed  Google Scholar 

  49. 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  PubMed  PubMed Central  Google Scholar 

  50. Fisher, R.A. The correlation between relatives on the supposition of Mendelian inheritance. Trans. R. Soc. Edinb. 52, 399–433 (1918).

    Article  Google Scholar 

  51. Henderson, C.R. Estimation of variance and covariance components. Biometrics 9, 226–252 (1953).

    Article  Google Scholar 

  52. Boerwinkle, E., Chakraborty, R. & Sing, C.F. The use of measured genotype information in the analysis of quantitative phenotypes in man. I. Models and analytical methods. Am. Hum. Genet. 50, 181–194 (1986).

    Article  CAS  Google Scholar 

  53. Chen, W.M. & Abecasis, G.R. Family-based association tests for genomewide association scans. Am. J. Hum. Genet. 81, 913–926 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Yu, J. et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 38, 203–208 (2006).

    Article  CAS  PubMed  Google Scholar 

  55. Aulchenko, Y.S., de Koning, D.J. & Haley, C. Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis. Genetics 177, 577–585 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Svishcheva, G.R., Axenovich, T.I., Belonogova, N.M., van Duijn, C.M. & Aulchenko, Y.S. Rapid variance components–based method for whole-genome association analysis. Nat. Genet. 44, 1166–1170 (2012).

    Article  CAS  PubMed  Google Scholar 

  57. Zhou, X. & Stephens, M. Genome-wide efficient mixed-model analysis for association studies. Nat. Genet. 44, 821–824 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Horvath, S., Wei, E., Xu, X., Palmer, L.J. & Baur, M. Family-based association test method: age of onset traits and covariates. Genet. Epidemiol. 21 (suppl. 1), S403–S408 (2001).

    PubMed  Google Scholar 

  59. Thornton, T. & McPeek, M.S. ROADTRIPS: case-control association testing with partially or completely unknown population and pedigree structure. Am. J. Hum. Genet. 86, 172–184 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Sayer, D. et al. HLA-DRB1 DNA sequencing based typing: an approach suitable for high throughput typing including unrelated bone marrow registry donors. Tissue Antigens 57, 46–54 (2001).

    Article  CAS  PubMed  Google Scholar 

  61. Barrett, J.C., Fry, B., Maller, J. & Daly, M.J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265 (2005).

    Article  CAS  PubMed  Google Scholar 

  62. Scheet, P. & Stephens, M. A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am. J. Hum. Genet. 78, 629–644 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Marsh, S.G. et al. Nomenclature for factors of the HLA system, 2010. Tissue Antigens 75, 291–455 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Howie, B.N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Stephens, M., Smith, N.J. & Donnelly, P. A new statistical method for haplotype reconstruction from population data. Am. J. Hum. Genet. 68, 978–989 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Su, Z., Cardin, N., Donnelly, P. & Marchini, J. A Bayesian method for detecting and characterizing allelic heterogeneity and boosting signals in genome-wide association studies. Stat. Sci. 24, 430–450 (2009).

    Article  Google Scholar 

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Acknowledgements

The principal funding for this study was provided by the Wellcome Trust, as part of the WTCCC2 project (085475/B/08/Z and 085475/Z/08/Z). We thank S. Bertrand, J. Bryant, S.L. Clark, J.S. Conquer, T. Dibling, J.C. Eldred, S. Gamble, C. Hind, M.L. Perez, C.R. Stribling, S. Taylor and A. Wilk of the Wellcome Trust Sanger Institute's Sample and Genotyping Facilities for technical assistance. We thank D. Davison for making available his Shellfish program for calculating principal components in large genetic data sets. C.C.A.S. is supported by a Wellcome Trust Fellowship (097364/Z/11/Z). H.J.C. is supported by a Wellcome Senior Fellowship in Basic Biomedical Science (087436/Z/10/Z). P. Donnelly is supported in part by a Royal Society Wolfson Merit Award, and work was supported in part by Wellcome Trust Centre for Human Genetics core grants 090532/Z/09/Z and 075491/Z/04/B. Collection of samples and epidemiological data, sample preparation and sequence-based HLA typing were supported by grants from the Wellcome Trust (074196/Z/04/Z and 085475/Z/08/Z to J.M.B., S.S., S.M.B.J. and M.E.W.) and the US National Institutes of Health (Tropical Medicine Research Center award P50AI074321 to S.S. in India; Tropical Medicine Research Center award P50 AI-30639 to E.M. Carvalho and S.M.B.J. in Brazil; and R01 AI076233 to M.E.W. and J.M.B.; R01 AI048822 to M.E.W., S.M.B.J. and J.M.B.). We give special thanks to all subjects who contributed samples and to clinicians and field staff in India and Brazil who helped with the recruitment of study subjects.

Author information

Author notes

  1. E Nancy Miller and Leena Peltonen: Deceased.

  2. Michaela Fakiola and Amy Strange: These authors contributed equally to this work.

  3. Jenefer M Blackwell and Peter Donnelly: These authors jointly directed this work.

Authors and Affiliations

  1. Cambridge Institute for Medical Research, University of Cambridge School of Clinical Medicine, Addenbrooke's Hospital, Cambridge, UK

    Michaela Fakiola, E Nancy Miller & Jenefer M Blackwell

  2. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK

    Amy Strange, Matti Pirinen, Zhan Su, Gavin Band, Céline Bellenguez, Colin Freeman, Eleni Giannoulatou, Richard Pearson, Damjan Vukcevic, Anna Rautanen, Chris C A Spencer & Peter Donnelly

  3. Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK

    Heather J Cordell

  4. Institute of Medical Sciences, Banaras Hindu University, Varanasi, India

    Anshuman Mishra, Sanjana Mehrotra, Madhukar Rai, Shri P Singh & Shyam Sundar

  5. Department of Biochemistry, Center for Biosciences, Universidade Federal do Rio Grande do Norte, Natal, Brazil

    Gloria R Monteiro, Núbia N Pontes, Olivia Sousa & Selma M B Jeronimo

  6. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.,

    Serge Dronov, Sarah Edkins, Emma Gray, Sarah E Hunt, Cordelia Langford, Panos Deloukas & Leena Peltonen

  7. Department of Infectious Diseases, Universidade Federal do Rio Grande do Norte, Natal, Brazil

    Henio G Lacerda

  8. Department of Clinical Immunology, Royal Perth Hospital, Perth, Western Australia, Australia.,

    Linda Smith, Frank Christiansen & Campbell Witt

  9. National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health at the South London and Maudsley National Health Service (NHS) Foundation Trust and Institute of Psychiatry King's College London, London, UK

    Elvira Bramon

  10. University of Queensland Diamantina Institute, Princess Alexandra Hospital, University of Queensland, Brisbane, Queensland, Australia

    Matthew A Brown

  11. Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK

    Juan P Casas

  12. Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland

    Aiden Corvin

  13. Molecular and Physiological Sciences, The Wellcome Trust, London, UK

    Audrey Duncanson

  14. Department of Oncology, University of Oxford, Oxford, UK

    Janusz Jankowski

  15. Stroke and Dementia Research Group, St George's University of London, London, UK

    Hugh S Markus

  16. Department of Medical and Molecular Genetics, King's College London School of Medicine, Guy's Hospital, London, UK

    Christopher G Mathew

  17. Medical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK

    Colin N A Palmer

  18. Social, Genetic and Developmental Psychiatry Centre, King's College London Institute of Psychiatry, London, UK

    Robert Plomin

  19. Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK

    Stephen J Sawcer

  20. Oxford Centre for Diabetes, Endocrinology and Metabolism (ICDEM), Churchill Hospital, Oxford, UK

    Richard C Trembath

  21. NIHR Biomedical Centre for Ophthalmology at Moorfields Eye Hospital NHS Foundation Trust, London, UK

    Ananth C Viswanathan

  22. University College London (UCL) Institute of Ophthalmology, London, UK

    Ananth C Viswanathan

  23. Department of Molecular Neuroscience, Institute of Neurology, London, UK

    Nicholas W Wood

  24. Department of Internal Medicine, University of Iowa, Iowa City, Iowa, USA

    Mary E Wilson

  25. Veterans Affairs (VA) Medical Center, Iowa City, Iowa, USA

    Mary E Wilson

  26. Telethon Institute for Child Health Research, Centre for Child Health Research, The University of Western Australia, Subiaco, Western Australia, Australia

    Jenefer M Blackwell

  27. Department of Statistics, University of Oxford, Oxford, UK

    Peter Donnelly

Authors
  1. Michaela Fakiola
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  2. Amy Strange
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  3. Heather J Cordell
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  4. E Nancy Miller
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  8. Sanjana Mehrotra
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  9. Gloria R Monteiro
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  18. Henio G Lacerda
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  20. Richard Pearson
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  22. Madhukar Rai
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  23. Shri P Singh
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  28. Matthew A Brown
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  33. Hugh S Markus
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  34. Christopher G Mathew
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  35. Colin N A Palmer
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  36. Robert Plomin
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  37. Anna Rautanen
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  38. Stephen J Sawcer
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  40. Ananth C Viswanathan
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  41. Nicholas W Wood
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  42. Mary E Wilson
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  43. Panos Deloukas
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  44. Leena Peltonen
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  45. Frank Christiansen
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  46. Campbell Witt
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  47. Selma M B Jeronimo
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  48. Shyam Sundar
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  49. Chris C A Spencer
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  50. Jenefer M Blackwell
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  51. Peter Donnelly
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Consortia

LeishGEN Consortium

Wellcome Trust Case Control Consortium 2

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M.F., E.N.M., A.M., S.M., G.R.M., H.G.L., N.N.P., M.R., S.P.S., O.S., M.E.W., S.M.B.J., S.S. and J.M.B. oversaw cohort collections for LeishGEN. The WTCCC2 DNA, genotyping, data quality control and informatics group (S.D., S.E., E. Gray, S.E.H. and C.L.) executed GWAS sample handling, genotyping and quality control. The WTCCC2 Management Committee (P. Donnelly, J.M.B., E.B., M.A.B., J.P.C., A.C., P. Deloukas, A.D., J.J., H.S.M., C.G.M., C.N.A.P., R. Plomin, A.R., S.J.S., R.C.T., A.C.V., L.P. and N.W.W.) monitored the execution of the GWAS. A.S., M.F., H.J.C., M.P., Z.S., G.B., C.B., C.F., E. Giannoulatou, R. Pearson, D.V. and C.C.A.S. performed statistical analyses. L.S., F.C. and C.W. oversaw HLA typing and interpretation. A.S., M.F., H.J.C., C.C.A.S., J.M.B. and P. Donnelly contributed to writing the manuscript. All authors reviewed the final manuscript.

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Correspondence to Jenefer M Blackwell or Peter Donnelly.

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The authors declare no competing financial interests.

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A full list of members and affiliations is provided in the Supplementary Note.

A full list of members and affiliations is provided in the Supplementary Note.

Supplementary information

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Supplementary Tables 1–5, Supplementary Figures 1–3 and Supplementary Note (PDF 815 kb)

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LeishGEN Consortium., Wellcome Trust Case Control Consortium 2., Fakiola, M. et al. Common variants in the HLA-DRB1–HLA-DQA1 HLA class II region are associated with susceptibility to visceral leishmaniasis. Nat Genet 45, 208–213 (2013). https://doi.org/10.1038/ng.2518

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