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Genome-Wide Association Analysis for Severity of Coronary Artery Disease Using the Gensini Scoring System

Authors :
Tanja Zeller
Moritz Seiffert
Christian Müller
Markus Scholz
Anna Schäffer
Francisco Ojeda
Heinz Drexel
Axel Mündlein
Marcus E. Kleber
Winfried März
Christoph Sinning
Fabian J. Brunner
Christoph Waldeyer
Till Keller
Christoph H. Saely
Karsten Sydow
Joachim Thiery
Daniel Teupser
Stefan Blankenberg
Renate Schnabel
Source :
Frontiers in Cardiovascular Medicine, Vol 4 (2017)
Publication Year :
2017
Publisher :
Frontiers Media S.A., 2017.

Abstract

Coronary artery disease (CAD) has a complex etiology involving numerous environmental and genetic factors of disease risk. To date, the genetic 9p21 locus represents the most robust genetic finding for prevalent and incident CAD. However, limited information is available on the genetic background of the severity and distribution of CAD. CAD manifests itself as stable CAD or acute coronary syndrome. The Gensini score quantifies the extent CAD but requires coronary angiography. Here, we aimed to identify novel genetic variants associated with Gensini score severity and distribution of CAD. A two-stage approach including a discovery and a replication stage was used to assess genetic variants. In the discovery phase, a meta-analysis of genome-wide association data of 4,930 CAD-subjects assessed by the Gensini score was performed. Selected single nucleotide polymorphisms (SNPs) were replicated in 2,283 CAD-subjects by de novo genotyping. We identified genetic loci located on chromosome 2 and 9 to be associated with Gensini score severity and distribution of CAD in the discovery stage. Although the loci on chromosome 2 could not be replicated in the second stage, the known CAD-locus on chromosome 9p21, represented by rs133349, was identified and, thus, was confirmed as risk locus for CAD severity.

Details

Language :
English
ISSN :
2297055X
Volume :
4
Database :
Directory of Open Access Journals
Journal :
Frontiers in Cardiovascular Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.f2d37eda8ca4d25819ae2c5f5b796c1
Document Type :
article
Full Text :
https://doi.org/10.3389/fcvm.2017.00057