Convergence of coronary artery disease genes onto endothelial cell programs,Nature

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Convergence of coronary artery disease genes onto endothelial cell programs
Nature ( IF 50.5 ) Pub Date : 2024-02-07 , DOI: 10.1038/s41586-024-07022-x
Gavin R Schnitzler _{1,

2,

3} , Helen Kang _{4,

5} , Shi Fang _{1,

3} , Ramcharan S Angom ₆ , 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 Taylor ₇ , Shamsudheen K Vellarikkal _{1,

3} , Aurelie E Barry _{1,

3} , Oscar Sias-Garcia _{1,

3} , Alex Bloemendal _{1,

2} , Glen Munson ₁ , Philine Guckelberger ₁ , Tung H Nguyen ₁ , Drew T Bergman _{1,

8} , Stephen Hinshaw ₉ , Nathan Cheng ₁ , Brian Cleary _{1,

10} , Krishna Aragam _{1,

11} , Eric S Lander _{1,

12,

13} , Hilary K Finucane _{1,

14,

15,

16} , Debabrata Mukhopadhyay ₆ , Rajat M Gupta _{1,

2,

3} , Jesse M Engreitz _{1,

2,

4,

5,

17}

Affiliation

Broad Institute of MIT and Harvard, Cambridge, MA, USA.
The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA.
Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA.
Department of Biochemistry and Molecular Biology, Mayo Clinic College of Medicine and Science, Jacksonville, FL, USA.
Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
Department of Chemical and Systems Biology, ChEM-H, and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
Faculty of Computing and Data Sciences, Departments of Biology and Biomedical Engineering, Biological Design Center, and Program in Bioinformatics, Boston University, Boston, MA, USA.
Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
Department of Biology, MIT, Cambridge, MA, USA.
Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.

Linking variants from genome-wide association studies (GWAS) to underlying mechanisms of disease remains a challenge^1,2,3. 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^1,2,3,4,5,6. 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.

中文翻译：

冠状动脉疾病基因向内皮细胞程序的收敛

将全基因组关联研究（GWAS）的变异与疾病的潜在机制联系起来仍然是一个挑战^1,2,3。对于某些疾病，一种成功的策略是寻找多个 GWAS 基因座包含在同一生物途径中起作用的基因的情况^1,2,3,4,5,6。然而，我们对哪些基因在哪些途径中起作用的了解并不完整，特别是对于细胞类型特异性途径或研究不足的基因。在这里，我们介绍了一种将 GWAS 变体连接到函数的方法。该方法使用表观基因组学数据将变异与基因联系起来，使用 Perturb-seq 将基因与通路从头联系起来，并整合这些数据以识别 GWAS 基因座与通路的收敛。我们应用这种方法来研究内皮细胞在冠状动脉疾病（CAD）遗传风险中的作用，并发现了 43 个 CAD GWAS 信号，这些信号汇聚在脑海绵状血管畸形（CCM）信号通路上。该通路的两个调节因子 CCM2 和 TLNRD1 分别与 CAD 风险变异有关，调节其他 CAD 风险基因并影响内皮细胞中的动脉粥样硬化保护过程。这些结果表明，CAD 风险部分是由致病基因收敛到内皮细胞中特定转录途径驱动的。他们强调了常见和罕见血管疾病（CAD 和 CCM）之间的共享基因，并将 TLNRD1 确定为 CCM 信号通路中一个新的、以前未表征的成员。这种方法将广泛用于将变异与其他常见多基因疾病的功能联系起来。

更新日期：2024-02-07

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