Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets

CVgenes@target consortium, Harri Lempiäinen, Ingrid Brænne, Tom Michoel, Vinicius Tragante, Baiba Vilne, Tom R Webb, Theodosios Kyriakou, Johannes Eichner, Lingyao Zeng, Christina Willenborg, Oscar Franzen, Arno Ruusalepp, Anuj Goel, Sander W. Van Der Laan, Claudia Biegert, Stephen E. Hamby, Husain A. Talukdar, Hassan Foroughi Asl, Gerard PasterkampHugh Watkins, Nilesh J Samani, Timo Wittenberger, Jeanette Erdmann, Heribert Schunkert, Folkert W. Asselbergs, Johan L M Björkegren

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Genome-wide association studies (GWAS) have identified over two hundred chromosomal loci that modulate risk of coronary artery disease (CAD). The genes affected by variants at these loci are largely unknown and an untapped resource to improve our understanding of CAD pathophysiology and identify potential therapeutic targets. Here, we prioritized 68 genes as the most likely causal genes at genome-wide significant loci identified by GWAS of CAD and examined their regulatory roles in 286 metabolic and vascular tissue gene-protein sub-networks ("modules"). The modules and genes within were scored for CAD druggability potential. The scoring enriched for targets of cardiometabolic drugs currently in clinical use and in-depth analysis of the top-scoring modules validated established and revealed novel target tissues, biological processes, and druggable targets. This study provides an unprecedented resource of tissue-defined gene-protein interactions directly affected by genetic variance in CAD risk loci.

Original languageEnglish
Pages (from-to)3434
JournalScientific Reports
Volume8
Issue number1
DOIs
Publication statusPublished - 21 Feb 2018

Keywords / Materials (for Non-textual outputs)

  • Journal Article

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