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Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies

Authors :
Alexandra S. Shadrina
Dmitry G. Alexeev
Lucija Klaric
Peter K. Joshi
Eugene D Pakhomov
Sodbo Zh Sharapov
Yurii S. Aulchenko
Yakov A. Tsepilov
James F. Wilson
Anna A. Torgasheva
Tatiana I. Shashkova
Source :
Scientific Reports, Scientific Reports, Vol 10, Iss 1, Pp 1-15 (2020), Shadrina, A S, Shashkova, T I, Torgasheva, A A, Sharapov, S Z, Klaric, L, Pakhomov, E D, Alexeev, D G, Wilson, J, Tsepilov, Y A, Joshi, P K & Aulchenko, Y S 2020, ' Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies ', Scientific Reports, vol. 10, no. 1, pp. 10486 . https://doi.org/10.1038/s41598-020-67001-w
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

Genome-wide association studies have led to a significant progress in identification of genomic loci affecting coronary artery disease (CAD) risk. However, revealing the causal genes responsible for the observed associations is challenging. In the present study, we aimed to prioritize CAD-relevant genes based on cumulative evidence from the published studies and our own study of colocalization between eQTLs and loci associated with CAD using SMR/HEIDI approach. Prior knowledge of candidate genes was extracted from both experimental and in silico studies, employing different prioritization algorithms. Our review systematized information for a total of 51 CAD-associated loci. We pinpointed 37 genes in 36 loci. For 27 genes we infer they are causal for CAD, and for 10 further genes we judge them most likely causal. Colocalization analysis showed that for 18 out of these loci, association with CAD can be explained by changes in gene expression in one or more CAD-relevant tissues. Furthermore, for 8 out of 36 loci, existing evidence suggested additional CAD-associated genes. For the remaining 15 loci, we concluded that evidence for gene prioritization remains inconsistent, insufficient, or absent. Our results provide deeper insights into the genetic etiology of CAD and demonstrate knowledge gaps where further research is warranted.

Details

ISSN :
20452322
Volume :
10
Database :
OpenAIRE
Journal :
Scientific Reports
Accession number :
edsair.doi.dedup.....fa2ad26ee42275e37050b5d860687c02
Full Text :
https://doi.org/10.1038/s41598-020-67001-w