Convergence of coronary artery disease genes onto endothelial cell programs

Gavin R Schnitzler; Helen Kang; Shi Fang; Ramcharan S Angom; Vivian S Lee-Kim; X Rosa Ma; Ronghao Zhou; Tony Zeng; Katherine Guo; Martin S Taylor; Shamsudheen K Vellarikkal; Aurelie E Barry; Oscar Sias-Garcia; Alex Bloemendal; Glen Munson; Philine Guckelberger; Tung H Nguyen; Drew T Bergman; Stephen Hinshaw; Nathan Cheng; Brian Cleary; Krishna Aragam; Eric S Lander; Hilary K Finucane; Debabrata Mukhopadhyay; Rajat M Gupta; Jesse M Engreitz

doi:10.1038/s41586-024-07022-x

Convergence of coronary artery disease genes onto endothelial cell programs

Nature. 2024 Feb;626(8000):799-807. doi: 10.1038/s41586-024-07022-x. Epub 2024 Feb 7.

Authors

Gavin R Schnitzler^#^{1

2

3}, Helen Kang^#^{4

5}, Shi Fang^{1

3}, Ramcharan S Angom⁶, Vivian S Lee-Kim^{1

3}, X Rosa Ma^{4

5}, Ronghao Zhou^{4

5}, Tony Zeng^{4

5}, Katherine Guo^{4

5}, Martin S Taylor⁷, Shamsudheen K Vellarikkal^{1

3}, Aurelie E Barry^{1

3}, Oscar Sias-Garcia^{1

3}, Alex Bloemendal^{1

2}, Glen Munson¹, Philine Guckelberger¹, Tung H Nguyen¹, Drew T Bergman^{1

8}, Stephen Hinshaw⁹, Nathan Cheng¹, Brian Cleary^{1

10}, Krishna Aragam^{1

11}, Eric S Lander^{1

12

13}, Hilary K Finucane^{1

14

15

16}, Debabrata Mukhopadhyay⁶, Rajat M Gupta^{17

18

19}, Jesse M Engreitz^{20

21

22

23

24}

Affiliations

¹ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
² The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA.
³ Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
⁴ Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
⁵ Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA.
⁶ Department of Biochemistry and Molecular Biology, Mayo Clinic College of Medicine and Science, Jacksonville, FL, USA.
⁷ Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁸ Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
⁹ Department of Chemical and Systems Biology, ChEM-H, and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
¹⁰ Faculty of Computing and Data Sciences, Departments of Biology and Biomedical Engineering, Biological Design Center, and Program in Bioinformatics, Boston University, Boston, MA, USA.
¹¹ Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
¹² Department of Biology, MIT, Cambridge, MA, USA.
¹³ Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
¹⁴ Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
¹⁵ Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
¹⁶ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA. rgupta@bwh.harvard.edu.
¹⁸ The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA. rgupta@bwh.harvard.edu.
¹⁹ Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. rgupta@bwh.harvard.edu.
²⁰ Broad Institute of MIT and Harvard, Cambridge, MA, USA. engreitz@stanford.edu.
²¹ The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA. engreitz@stanford.edu.
²² Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA. engreitz@stanford.edu.
²³ Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA. engreitz@stanford.edu.
²⁴ Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA. engreitz@stanford.edu.

^# Contributed equally.

Abstract

Linking variants from genome-wide association studies (GWAS) to underlying mechanisms of disease remains a challenge^1-3. For some diseases, a successful strategy has been to look for cases in which multiple GWAS loci contain genes that act in the same biological pathway^1-6. However, our knowledge of which genes act in which pathways is incomplete, particularly for cell-type-specific pathways or understudied genes. Here we introduce a method to connect GWAS variants to functions. This method links variants to genes using epigenomics data, links genes to pathways de novo using Perturb-seq and integrates these data to identify convergence of GWAS loci onto pathways. We apply this approach to study the role of endothelial cells in genetic risk for coronary artery disease (CAD), and discover 43 CAD GWAS signals that converge on the cerebral cavernous malformation (CCM) signalling pathway. Two regulators of this pathway, CCM2 and TLNRD1, are each linked to a CAD risk variant, regulate other CAD risk genes and affect atheroprotective processes in endothelial cells. These results suggest a model whereby CAD risk is driven in part by the convergence of causal genes onto a particular transcriptional pathway in endothelial cells. They highlight shared genes between common and rare vascular diseases (CAD and CCM), and identify TLNRD1 as a new, previously uncharacterized member of the CCM signalling pathway. This approach will be widely useful for linking variants to functions for other common polygenic diseases.

MeSH terms

Coronary Artery Disease* / genetics
Coronary Artery Disease* / pathology
Endothelial Cells* / metabolism
Endothelial Cells* / pathology
Epigenomics
Genetic Predisposition to Disease / genetics
Genome-Wide Association Study*
Hemangioma, Cavernous, Central Nervous System* / genetics
Hemangioma, Cavernous, Central Nervous System* / pathology
Humans
Multifactorial Inheritance
Polymorphism, Single Nucleotide
Signal Transduction / genetics

Substances

CCM2 protein, human
TLNRD1 protein, human

Abstract

MeSH terms

Substances

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