A genome-wide functional genomics approach uncovers genetic determinants of immune phenotypes in type 1 diabetes

  1. Xiaojing Chu
  2. Anna WM Janssen
  3. Hans Koenen
  4. Linzhung Chang
  5. Xuehui He
  6. Irma Joosten
  7. Rinke Stienstra
  8. Yunus Kuijpers
  9. Cisca Wijmenga
  10. Cheng-Jian Xu
  11. Mihai G Netea
  12. Cees J Tack  Is a corresponding author
  13. Yang Li  Is a corresponding author
  1. University Medical Center Groningen, Netherlands
  2. Radboud University Nijmegen Medical Centre, Netherlands
  3. Helmholtz Centre for Infection Research, Germany
  4. University of Groningen, Netherlands

Abstract

Background: The large inter-individual variability in immune-cell cell composition and function determines immune responses in general and susceptibility to immune-mediated diseases in particular. While much has been learned about the genetic variants relevant for type 1 diabetes (T1D), the pathophysiological mechanisms through which these variations exert their effects remain unknown.

Methods: Blood samples were collected from 243 patients with T1D of Dutch descent. We applied genetic association analysis on > 200 immune cell traits and >100 cytokine production profiles in response to stimuli measured to identify genetic determinants of immune function, and compared the results obtained in T1D to healthy controls.

Results: Genetic variants that determine susceptibility to T1D significantly affect T cell composition. Specifically, the CCR5+ regulatory T cells associate with T1D through the CCR region, suggesting a shared genetic regulation. Genome-wide quantitative trait loci (QTL) mapping analysis of immune traits revealed 15 genetic loci that influence immune responses in T1D, including 12 that have never been reported in healthy population studies, implying a disease-specific genetic regulation.

Conclusion: This study provides new insights into the genetic factors that affect immunological responses in T1D.

Funding: This work was supported by an ERC starting grant (no. 948207) and a Radboud University Medical Centre Hypatia grant (2018) to Y.L. and an ERC advanced grant (no. 833247) and a Spinoza grant of the Netherlands Association for Scientific Research to M.G.N. C.T received funding from the Perspectief Biomarker Development Center Research Programme, which is (partly) financed by the Netherlands Organisation for Scientific Research (NWO). AJ was funded by a grant from the European Foundation for the Study of Diabetes (EFSD/AZ Macrovascular Programme 2015). X.C was supported by the China Scholarship Council (201706040081).

Data availability

All the raw data on immune phenotypes and summary statistics generated directly from genetic data needed to precisely reproduce published results are deposited in Dryad (https://doi.org/10.5061/dryad.4f4qrfjd0). Custom scripts for generating summary statistics and all results are deposited in GitHub (https://github.com/Chuxj/Gf_of_ip_in_T1D). Individual genetic data and other privacy-sensitive individual information are not publicly available because they contain information that could compromise research participant privacy. For data access, please contact Prof. Cees Tack (Cees.Tack@radboudumc.nl). This original data is available for qualified researchers, i.e. senior investigators employed or legitimately affiliated with an academic, non-profit or government institution who have a track record in the field. We would ask the researcher to sign a data access agreement that needs to be signed by applicants and legal representatives of their universities. In addition, we would require a research proposal, to ensure that 'Applications for access to Data must be Specific, Measurable, Attainable, Resourced and Timely.' The applicant must implement the proposed research within the designed time frame and the data must be deleted after finishing the proposal.

The following data sets were generated

Article and author information

Author details

  1. Xiaojing Chu

    Department of Genetics, University Medical Center Groningen, Groningen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  2. Anna WM Janssen

    Department of Internal Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  3. Hans Koenen

    Department of Laboratory Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  4. Linzhung Chang

    Department of Genetics, University Medical Center Groningen, Groningen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  5. Xuehui He

    Department of Laboratory Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  6. Irma Joosten

    Department of Laboratory Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  7. Rinke Stienstra

    Department of Internal Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  8. Yunus Kuijpers

    Department of Computational Biology for Individualised Infection Medicine, Helmholtz Centre for Infection Research, Hannover, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5075-3970
  9. Cisca Wijmenga

    Department of Genetics, University of Groningen, Groningen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5635-1614
  10. Cheng-Jian Xu

    Department of Computational Biology for Individualised Infection Medicine, Helmholtz Centre for Infection Research, Hannover, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1586-4672
  11. Mihai G Netea

    Department of Internal Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2421-6052
  12. Cees J Tack

    Department of Internal Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
    For correspondence
    Cees.Tack@radboudumc.nl
    Competing interests
    The authors declare that no competing interests exist.
  13. Yang Li

    Department of Computational Biology for Individualised Infection Medicine, Helmholtz Centre for Infection Research, Hannover, Germany
    For correspondence
    yang.li@helmholtz-hzi.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4022-7341

Funding

ERC Starting grant (948207)

  • Yang Li

Radboud Universitair Medisch Centrum (Hypatia Grant 2018)

  • Yang Li

ERC advanced grant (833247)

  • Mihai G Netea

the Netherlands Association of Scientific Reasearch (Spinoza grant)

  • Mihai G Netea

the Netherlands Organisation for Scientific Research (Perspectief Biomarker Development Center Research Programme)

  • Cees J Tack

European Foundation for the Study of Diabetes (AZ Macrovascular Programme 2015)

  • Anna WM Janssen

China Scholarship Council (201706040081)

  • Anna WM Janssen

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: The 500FG-DM study was approved by the ethical committee of Radboud University Nijmegen (NL-number: 54214.091.15). Experiments were conducted according to the principles expressed in the Declaration of Helsinki. Written informed consent was obtained from all participants.

Reviewing Editor

  1. Christoph Buettner, Rutgers Robert Wood Johnson Medical School, United States

Version history

  1. Received: September 8, 2021
  2. Preprint posted: December 7, 2021 (view preprint)
  3. Accepted: May 16, 2022
  4. Accepted Manuscript published: May 31, 2022 (version 1)
  5. Version of Record published: June 17, 2022 (version 2)

Copyright

© 2022, Chu et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Xiaojing Chu
  2. Anna WM Janssen
  3. Hans Koenen
  4. Linzhung Chang
  5. Xuehui He
  6. Irma Joosten
  7. Rinke Stienstra
  8. Yunus Kuijpers
  9. Cisca Wijmenga
  10. Cheng-Jian Xu
  11. Mihai G Netea
  12. Cees J Tack
  13. Yang Li
(2022)
A genome-wide functional genomics approach uncovers genetic determinants of immune phenotypes in type 1 diabetes
eLife 11:e73709.
https://doi.org/10.7554/eLife.73709

Share this article

https://doi.org/10.7554/eLife.73709

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