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Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements

Author

Listed:
  • Fiona Allum

    (McGill University
    McGill University and Genome Quebec Innovation Centre)

  • Åsa K. Hedman

    (Karolinska Institute)

  • Xiaojian Shao

    (McGill University
    McGill University and Genome Quebec Innovation Centre)

  • Warren A. Cheung

    (McGill University
    McGill University and Genome Quebec Innovation Centre
    Children’s Mercy Hospitals and Clinics)

  • Jinchu Vijay

    (McGill University
    McGill University and Genome Quebec Innovation Centre)

  • Frédéric Guénard

    (Université Laval)

  • Tony Kwan

    (McGill University
    McGill University and Genome Quebec Innovation Centre)

  • Marie-Michelle Simon

    (McGill University
    McGill University and Genome Quebec Innovation Centre)

  • Bing Ge

    (McGill University
    McGill University and Genome Quebec Innovation Centre)

  • Cristiano Moura

    (McGill University)

  • Elodie Boulier

    (McGill University
    McGill University and Genome Quebec Innovation Centre)

  • Lars Rönnblom

    (Uppsala University)

  • Sasha Bernatsky

    (McGill University)

  • Mark Lathrop

    (McGill University
    McGill University and Genome Quebec Innovation Centre)

  • Mark I. McCarthy

    (University of Oxford
    University of Oxford
    John Radcliffe Hospital)

  • Panos Deloukas

    (Queen Mary University of London)

  • André Tchernof

    (Université Laval)

  • Tomi Pastinen

    (McGill University
    McGill University and Genome Quebec Innovation Centre
    Children’s Mercy Hospitals and Clinics)

  • Marie-Claude Vohl

    (Université Laval)

  • Elin Grundberg

    (McGill University
    McGill University and Genome Quebec Innovation Centre
    Children’s Mercy Hospitals and Clinics)

Abstract

Sparse profiling of CpG methylation in blood by microarrays has identified epigenetic links to common diseases. Here we apply methylC-capture sequencing (MCC-Seq) in a clinical population of ~200 adipose tissue and matched blood samples (Ntotal~400), providing high-resolution methylation profiling (>1.3 M CpGs) at regulatory elements. We link methylation to cardiometabolic risk through associations to circulating plasma lipid levels and identify lipid-associated CpGs with unique localization patterns in regulatory elements. We show distinct features of tissue-specific versus tissue-independent lipid-linked regulatory regions by contrasting with parallel assessments in ~800 independent adipose tissue and blood samples from the general population. We follow-up on adipose-specific regulatory regions under (1) genetic and (2) epigenetic (environmental) regulation via integrational studies. Overall, the comprehensive sequencing of regulatory element methylomes reveals a rich landscape of functional variants linked genetically as well as epigenetically to plasma lipid traits.

Suggested Citation

  • Fiona Allum & Åsa K. Hedman & Xiaojian Shao & Warren A. Cheung & Jinchu Vijay & Frédéric Guénard & Tony Kwan & Marie-Michelle Simon & Bing Ge & Cristiano Moura & Elodie Boulier & Lars Rönnblom & Sasha, 2019. "Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09184-z
    DOI: 10.1038/s41467-019-09184-z
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