Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci

  1. Reza K Hammond
  2. Matthew C Pahl
  3. Chun Su
  4. Diana L Cousminer
  5. Michelle E Leonard
  6. Sumei Lu
  7. Claudia A Doege
  8. Yadav Wagley
  9. Kenyaita M Hodge
  10. Chiara Lasconi
  11. Matthew E Johnson
  12. James A Pippin
  13. Kurt D Hankenson
  14. Rudolph L Leibel
  15. Alessandra Chesi
  16. Andrew D Wells
  17. Struan FA Grant  Is a corresponding author
  1. Children's Hospital of Philadelphia, United States
  2. Columbia University Vagelos College of Physicians and Surgeons, United States
  3. University of Michigan Medical School, United States

Abstract

To uncover novel significant association signals (P<5x10-8), GWAS requires increasingly larger sample sizes to overcome statistical correction for multiple testing. As an alternative, we aimed to identify associations among suggestive signals (5x10-8P < 5x10-4) in increasingly powered GWAS efforts using chromatin accessibility and direct contact with gene promoters as biological constraints. We conducted retrospective analyses of three GIANT BMI GWAS efforts using ATAC-seq and promoter-focused Capture C data from human adipocytes and ESC-derived hypothalamic-like neurons. This approach, with its extremely low false positive rate, identified 15 loci at P<5x10-5 in the 2010 GWAS, 13 of which achieved genome-wide significance by 2018, including at NAV1, MTIF3 and ADCY3. 80% of constrained 2015 loci achieved genome-wide significance in 2018. We observed similar results in waist-to-hip ratio analyses. In conclusion, biological constraints on sub-significant GWAS signals can reveal potentially true-positive loci for further investigation in existing datasets without increasing sample size.

Data availability

Adipose ATAC-seq and promoter-focused capture C data is available in GEO under accession number GSE164912Hypothalamic Neuron ATAC-eq and promoter-focused capture C data is the subject of another atlas-based manuscript currently under peer review and through that process that dataset will be made available once the paper is published- the corresponding hypothalamus preprint can be found at: https://www.biorxiv.org/content/10.1101/2020.07.06.146951v1.full

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Reza K Hammond

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Matthew C Pahl

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Chun Su

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Diana L Cousminer

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Michelle E Leonard

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Sumei Lu

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Claudia A Doege

    Division of Molecular Genetics (Pediatrics) and the Naomi Berrie Diabetes Center, Columbia University Vagelos College of Physicians and Surgeons, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Yadav Wagley

    Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Kenyaita M Hodge

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Chiara Lasconi

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4684-704X
  11. Matthew E Johnson

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. James A Pippin

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Kurt D Hankenson

    Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Rudolph L Leibel

    Division of Molecular Genetics (Pediatrics) and the Naomi Berrie Diabetes Center, Columbia University Vagelos College of Physicians and Surgeons, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Alessandra Chesi

    Center for Spatial and Functional Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Andrew D Wells

    Center for Spatial and Functional Genomics, Department of Pathology, Children's Hospital of Philadelphia, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  17. Struan FA Grant

    Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, United States
    For correspondence
    grants@email.chop.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2025-5302

Funding

Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01-HD056465)

  • Struan FA Grant

National Human Genome Research Institute (R01-HG010067)

  • Struan FA Grant

Children's Hospital of Philadelphia (Daniel B. Burke Endowed Chair for Diabetes Research)

  • Struan FA Grant

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

Reviewing Editor

  1. Mone Zaidi, Icahn School of Medicine at Mount Sinai, United States

Publication history

  1. Received: August 18, 2020
  2. Accepted: January 8, 2021
  3. Accepted Manuscript published: January 18, 2021 (version 1)
  4. Version of Record published: January 18, 2021 (version 2)

Copyright

© 2021, Hammond 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. Reza K Hammond
  2. Matthew C Pahl
  3. Chun Su
  4. Diana L Cousminer
  5. Michelle E Leonard
  6. Sumei Lu
  7. Claudia A Doege
  8. Yadav Wagley
  9. Kenyaita M Hodge
  10. Chiara Lasconi
  11. Matthew E Johnson
  12. James A Pippin
  13. Kurt D Hankenson
  14. Rudolph L Leibel
  15. Alessandra Chesi
  16. Andrew D Wells
  17. Struan FA Grant
(2021)
Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
eLife 10:e62206.
https://doi.org/10.7554/eLife.62206

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