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Variation at HLA-DRB1 is associated with resistance to enteric fever

Nature Genetics volume 46, pages 1333–1336 (2014)Cite this article

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Abstract

Enteric fever affects more than 25 million people annually and results from systemic infection with Salmonella enterica serovar Typhi or Paratyphi pathovars A, B or C1. We conducted a genome-wide association study of 432 individuals with blood culture–confirmed enteric fever and 2,011 controls from Vietnam. We observed strong association at rs7765379 (odds ratio (OR) for the minor allele = 0.18, P = 4.5 × 10−10), a marker mapping to the HLA class II region, in proximity to HLA-DQB1 and HLA-DRB1. We replicated this association in 595 enteric fever cases and 386 controls from Nepal and also in a second independent collection of 151 cases and 668 controls from Vietnam. Imputation-based fine-mapping across the extended MHC region showed that the classical HLA-DRB1*04:05 allele (OR = 0.14, P = 2.60 × 10−11) could entirely explain the association at rs7765379, thus implicating HLA-DRB1 as a major contributor to resistance against enteric fever, presumably through antigen presentation.

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Figure 1: Association results for enteric fever within the broad HLA region.

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Acknowledgements

This work was supported by the Wellcome Trust, UK as part of their Major Overseas Program in Viet Nam (089276/Z/09/Z) and by the Biomedical Research Council, Agency for Science, Technology and Research, Singapore. S.B. is a Sir Henry Dale Fellow, jointly funded by the Wellcome Trust and the Royal Society (100087/Z/12/Z). P.I.W.d.B. acknowledges support from the Netherlands Organization for Scientific Research (Vernieuwingsimpuls VIDI Award NWO project number 016.126.354).

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Authors and Affiliations

  1. Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam

    Sarah J Dunstan, Nguyen Thi Hue, Trinh Thi Bich Tram, Christopher M Parry, Nga Tran Vu Thieu, Phat Voong Vinh, Christiane Dolecek, Katherine L Anders, Cameron P Simmons, Stephen Baker, Tran Tinh Hien & Jeremy J Farrar

  2. Nuffield Department of Clinical Medicine, Centre for Tropical Medicine, Oxford University, Oxford, UK

    Sarah J Dunstan, Christiane Dolecek, Katherine L Anders, Cameron P Simmons, Stephen Baker & Jeremy J Farrar

  3. Nossal Institute of Global Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia

    Sarah J Dunstan

  4. Faculty of Biology, University of Science, Vietnam National University, Ho Chi Minh City, Vietnam

    Nguyen Thi Hue

  5. Asan Institute for Life Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea

    Buhm Han

  6. Department of Medicine, Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA

    Buhm Han & Soumya Raychaudhuri

  7. Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA

    Buhm Han & Soumya Raychaudhuri

  8. Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA

    Buhm Han & Soumya Raychaudhuri

  9. Genome Institute of Singapore, Singapore

    Zheng Li, Kar Seng Sim, Jia Nee Foo, Martin L Hibberd & Chiea Chuen Khor

  10. Liverpool School of Tropical Medicine, Liverpool, UK

    Christopher M Parry

  11. Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam

    Nguyen Tran Chinh, Ha Vinh & Nguyen Phu Huong Lan

  12. Oxford University Clinical Research Unit–Nepal, Patan Academy of Health Sciences, Patan Hospital, Patan, Nepal

    Samir Koirala, Sabina Dongol, Amit Arjyal, Abhilasha Karkey, Olita Shilpakar & Buddha Basnyat

  13. Dong Thap Provincial Hospital, Cao Lanh, Vietnam

    Le Thi Phuong & Mai Ngoc Lanh

  14. Vietnam National Institute of Ophthalmology, Hanoi, Vietnam

    Tan Do & Do Nu Hon

  15. Singapore Eye Research Institute, Singapore

    Tin Aung & Chiea Chuen Khor

  16. Department of Statistics and Applied Probability, National University of Singapore, Singapore

    Yik Ying Teo

  17. Saw Swee Hock School of Public Health, National University of Singapore, Singapore

    Yik Ying Teo & Chiea Chuen Khor

  18. London School of Tropical Medicine and Hygiene, London, UK

    Martin L Hibberd & Stephen Baker

  19. Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan

    Yukinori Okada

  20. Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Yukinori Okada

  21. Department of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Soumya Raychaudhuri

  22. Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK

    Soumya Raychaudhuri

  23. Department of Microbiology and Immunology, The University of Melbourne, Melbourne, Victoria, Australia

    Cameron P Simmons

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

    Paul I W de Bakker

  25. Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands

    Paul I W de Bakker

  26. Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

    Chiea Chuen Khor

  27. Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

    Chiea Chuen Khor

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  1. Sarah J Dunstan
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  2. Nguyen Thi Hue
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Contributions

C.C.K. and S.J.D. are the principal investigators for the study who conceived and obtained funding for the project. C.C.K. organized and supervised the GWAS and replication genotyping pipeline, devised the overall analysis plan and wrote the first draft of the manuscript with input from S.J.D. S.J.D. established the enteric fever cohorts for the discovery and replication stages of this genetics study by working with J.J.F., T.T.H., N.P.H.L., N.T.H., T.T.B.T., C.M.P., N.T.C., H.V., L.T.P., M.N.L., N.T.V.T. and P.V.V. in Vietnam and with B.B., S.K., S.D., A.A., A.K., O.S., C.D. and S.B. in Nepal to coordinate the collection of clinical samples and phenotype data. K.L.A. and C.P.S. coordinated and collected the Vietnamese control cohorts. T.D., D.N.H. and T.A. contributed data from Vietnamese replication cohorts with other diseases. Z.L., K.S.S. and J.N.F. performed genotyping and DNA quality checks on all samples. C.C.K., Y.Y.T., P.I.W.d.B., B.H., Y.O., M.L.H. and S.R. analyzed the data and performed imputation. All authors critically reviewed manuscript revisions and contributed intellectual input to the final submission.

Corresponding authors

Correspondence to Sarah J Dunstan or Chiea Chuen Khor.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Quantile-quantile plot of the association P values obtained in the discovery sample collection.

The two clear outlying SNPs indicated for follow-up assessment are rs6841458 and rs7765379.

Supplementary Figure 2 Principal-component analysis of the discovery sample collection comprising 432 patients with enteric fever and 2,011 controls from Vietnam.

Shown here are plots between the first and second principal components (top panel) and between the first and third principal components (bottom panel). Patients with enteric fever are labeled as cases in red. Controls are labeled in yellow.

Supplementary Figure 3 Principal-component analysis of the Vietnamese enteric fever cases and controls in the context of Asian populations, some of which are from the Asian 1000 Genomes Project.

CDX refers to Chinese Dai individuals from Xishuangbanna, China. CHB refers to Chinese Han in Beijing. CHD refers to Chinese in metropolitan Denver city. CHS refers to Southern Han Chinese. JPT refers to Japanese individuals. KHV refers to Vietnamese Kinh from Ho Chi Minh City. SIMES refers to Singaporean Malays, and SINDI refers to South Indians in Singapore. The upper panel shows all populations so analyzed, whereas the lower panel shows the ancestral matching of the enteric fever cases and controls with more clarity.

Supplementary Figure 4 Manhattan plot of the association P values obtained in the discovery sample collection.

The horizontal red line denotes P = 5 × 10–8, the threshold for genome-wide significance, and the horizontal dotted blue line denotes P = 1 × 10–6. SNPs surpassing genome-wide significance in the discovery collection are labeled.

Supplementary Figure 5 Manhattan plot of the association P values obtained in the discovery sample collection after genome-wide imputation using the 1000 Genomes Project Asian reference panel.

Supplementary Figure 6 Genotyping clouds for SNP rs7765379 across different batches.

Top, Illumina Human Exome BeadChip; bottom, Illumina 660W BeadChip. The genotypes for wild type, heterozygous carrier and homozygous minor allele are clearly distinguished.

Supplementary Figure 7 Genotyping clouds for SNP rs6841458 across different batches.

Top, Salmonella cases, Illumina OmniExpress. Bottom, controls, Illumina 660W BeadChip. The genotypes for wild type, heterozygous carrier and homozygous minor allele are clearly distinguished.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7, Supplementary Tables 1–5 and 7, and Supplementary Note. (PDF 1050 kb)

Supplementary Table 6

List of all 5,422 binary markers within the broad HLA region and the accompanying association results. (XLSX 636 kb)

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Dunstan, S., Hue, N., Han, B. et al. Variation at HLA-DRB1 is associated with resistance to enteric fever. Nat Genet 46, 1333–1336 (2014). https://doi.org/10.1038/ng.3143

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