IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v594y2021i7863d10.1038_s41586-021-03552-w.html
   My bibliography  Save this article

Interpreting type 1 diabetes risk with genetics and single-cell epigenomics

Author

Listed:
  • Joshua Chiou

    (University of California San Diego
    Pfizer Worldwide Research)

  • Ryan J. Geusz

    (University of California San Diego)

  • Mei-Lin Okino

    (University of California San Diego)

  • Jee Yun Han

    (University of California San Diego)

  • Michael Miller

    (University of California San Diego)

  • Rebecca Melton

    (University of California San Diego)

  • Elisha Beebe

    (University of California San Diego)

  • Paola Benaglio

    (University of California San Diego)

  • Serina Huang

    (University of California San Diego)

  • Katha Korgaonkar

    (University of California San Diego)

  • Sandra Heller

    (Ulm University)

  • Alexander Kleger

    (Ulm University)

  • Sebastian Preissl

    (University of California San Diego)

  • David U. Gorkin

    (University of California San Diego
    Emory University)

  • Maike Sander

    (University of California San Diego
    University of California San Diego
    University of California San Diego)

  • Kyle J. Gaulton

    (University of California San Diego
    University of California San Diego)

Abstract

Genetic risk variants that have been identified in genome-wide association studies of complex diseases are primarily non-coding1. Translating these risk variants into mechanistic insights requires detailed maps of gene regulation in disease-relevant cell types2. Here we combined two approaches: a genome-wide association study of type 1 diabetes (T1D) using 520,580 samples, and the identification of candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cells using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC–seq) of 131,554 nuclei. Risk variants for T1D were enriched in cCREs that were active in T cells and other cell types, including acinar and ductal cells of the exocrine pancreas. Risk variants at multiple T1D signals overlapped with exocrine-specific cCREs that were linked to genes with exocrine-specific expression. At the CFTR locus, the T1D risk variant rs7795896 mapped to a ductal-specific cCRE that regulated CFTR; the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in the pathogenesis of T1D and highlight the power of large-scale genome-wide association studies and single-cell epigenomics for understanding the cellular origins of complex disease.

Suggested Citation

  • Joshua Chiou & Ryan J. Geusz & Mei-Lin Okino & Jee Yun Han & Michael Miller & Rebecca Melton & Elisha Beebe & Paola Benaglio & Serina Huang & Katha Korgaonkar & Sandra Heller & Alexander Kleger & Seba, 2021. "Interpreting type 1 diabetes risk with genetics and single-cell epigenomics," Nature, Nature, vol. 594(7863), pages 398-402, June.
  • Handle: RePEc:nat:nature:v:594:y:2021:i:7863:d:10.1038_s41586-021-03552-w
    DOI: 10.1038/s41586-021-03552-w
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-021-03552-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-021-03552-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Parker C. Wilson & Yoshiharu Muto & Haojia Wu & Anil Karihaloo & Sushrut S. Waikar & Benjamin D. Humphreys, 2022. "Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression," Nature Communications, Nature, vol. 13(1), pages 1-20, December.
    2. Paul M. H. Tran & Fran Dong & Eileen Kim & Katherine P. Richardson & Lynn K. H. Tran & Kathleen Waugh & Diane Hopkins & Richard D. Cummings & Peng George Wang & Marian J. Rewers & Jin-Xiong She & Shar, 2022. "Use of a glycomics array to establish the anti-carbohydrate antibody repertoire in type 1 diabetes," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    3. Matthew T. Patrick & Qinmengge Li & Rachael Wasikowski & Nehal Mehta & Johann E. Gudjonsson & James T. Elder & Xiang Zhou & Lam C. Tsoi, 2022. "Shared genetic risk factors and causal association between psoriasis and coronary artery disease," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Clara Albiñana & Zhihong Zhu & Nis Borbye-Lorenzen & Sanne Grundvad Boelt & Arieh S. Cohen & Kristin Skogstrand & Naomi R. Wray & Joana A. Revez & Florian Privé & Liselotte V. Petersen & Cynthia M. Bu, 2023. "Genetic correlates of vitamin D-binding protein and 25-hydroxyvitamin D in neonatal dried blood spots," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    5. Chachrit Khunsriraksakul & Qinmengge Li & Havell Markus & Matthew T. Patrick & Renan Sauteraud & Daniel McGuire & Xingyan Wang & Chen Wang & Lida Wang & Siyuan Chen & Ganesh Shenoy & Bingshan Li & Xue, 2023. "Multi-ancestry and multi-trait genome-wide association meta-analyses inform clinical risk prediction for systemic lupus erythematosus," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    6. Pietro Demela & Nicola Pirastu & Blagoje Soskic, 2023. "Cross-disorder genetic analysis of immune diseases reveals distinct gene associations that converge on common pathways," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    7. Jennifer P. Nguyen & Timothy D. Arthur & Kyohei Fujita & Bianca M. Salgado & Margaret K. R. Donovan & Hiroko Matsui & Ji Hyun Kim & Agnieszka D’Antonio-Chronowska & Matteo D’Antonio & Kelly A. Frazer, 2023. "eQTL mapping in fetal-like pancreatic progenitor cells reveals early developmental insights into diabetes risk," Nature Communications, Nature, vol. 14(1), pages 1-22, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:594:y:2021:i:7863:d:10.1038_s41586-021-03552-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.