Integrative analysis of 3604 GWAS reveals multiple novel cell type-specific regulatory associations

Charles E. Breeze*, Eric Haugen, Alex Reynolds, Andrew Teschendorff, Jenny van Dongen, Qing Lan, Nathaniel Rothman, Guillaume Bourque, Ian Dunham, Stephan Beck, John Stamatoyannopoulos, Nora Franceschini, Sonja I. Berndt

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Background: Genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) are known to preferentially co-locate to active regulatory elements in tissues and cell types relevant to disease aetiology. Further characterisation of associated cell type-specific regulation can broaden our understanding of how GWAS signals may contribute to disease risk. Results: To gain insight into potential functional mechanisms underlying GWAS associations, we developed FORGE2 (https://forge2.altiusinstitute.org/), which is an updated version of the FORGE web tool. FORGE2 uses an expanded atlas of cell type-specific regulatory element annotations, including DNase I hotspots, five histone mark categories and 15 hidden Markov model (HMM) chromatin states, to identify tissue- and cell type-specific signals. An analysis of 3,604 GWAS from the NHGRI-EBI GWAS catalogue yielded at least one significant disease/trait-tissue association for 2,057 GWAS, including > 400 associations specific to epigenomic marks in immune tissues and cell types, > 30 associations specific to heart tissue, and > 60 associations specific to brain tissue, highlighting the key potential of tissue- and cell type-specific regulatory elements. Importantly, we demonstrate that FORGE2 analysis can separate previously observed accessible chromatin enrichments into different chromatin states, such as enhancers or active transcription start sites, providing a greater understanding of underlying regulatory mechanisms. Interestingly, tissue-specific enrichments for repressive chromatin states and histone marks were also detected, suggesting a role for tissue-specific repressed regions in GWAS-mediated disease aetiology. Conclusion: In summary, we demonstrate that FORGE2 has the potential to uncover previously unreported disease-tissue associations and identify new candidate mechanisms. FORGE2 is a transparent, user-friendly web tool for the integrative analysis of loci discovered from GWAS.

Original languageEnglish
Article number13
Pages (from-to)1-22
Number of pages22
JournalGenome Biology
Volume23
Issue number1
DOIs
Publication statusPublished - 7 Jan 2022

Bibliographical note

Funding Information:
We would like to acknowledge the International Human Epigenome Consortium (IHEC) integrative analysis project for supporting this research.

Funding Information:
This study was supported in part by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH. SB acknowledges funding from the Wellcome Trust (218274/Z/19/Z).

Publisher Copyright:
© 2021, The Author(s).

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