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Review
. 2016 Jul 1;8(7):688-701.
doi: 10.15252/emmm.201506174. Print 2016 Jul.

The impact of genome-wide association studies on the pathophysiology and therapy of cardiovascular disease

Thorsten Kessler  1 , Baiba Vilne  1 , Heribert Schunkert  2
Affiliations
Review

The impact of genome-wide association studies on the pathophysiology and therapy of cardiovascular disease

Thorsten Kessler et al. EMBO Mol Med. .

Abstract

Cardiovascular diseases are leading causes for death worldwide. Genetic disposition jointly with traditional risk factors precipitates their manifestation. Whereas the implications of a positive family history for individual risk have been known for a long time, only in the past few years have genome-wide association studies (GWAS) shed light on the underlying genetic variations. Here, we review these studies designed to increase our understanding of the pathophysiology of cardiovascular diseases, particularly coronary artery disease and myocardial infarction. We focus on the newly established pathways to exemplify the translation from the identification of risk-related genetic variants to new preventive and therapeutic strategies for cardiovascular disease.

Keywords: atherosclerosis; coronary artery disease; genome‐wide association studies; myocardial infarction.

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Figures

Figure 1
Figure 1. Numbers of individuals and SNPs investigated by GWAS influence the power for the detection of associated loci
The number of investigated individuals in the discovery phases of the relative GWAS/meta‐analyses was plotted against the number of variants reaching genome‐wide level of significance in the overall analysis of the studies. Association between individuals in the discovery phase and the number of hits was evaluated by linear regression. P < 0.05 was considered as statistically significant. GraphPad Prism version 6.0c for Mac OS X (GraphPad Software, La Jolla, CA, USA) was used. (A) The number of SNPs detected at genome‐wide significant level for coronary artery disease in consecutive studies. (B) The number of SNPs detected with genome‐wide significance after replication correlates with the number of individuals included in the discovery studies. Symbols denote the numbers of genotyped SNPs [dots: ≤ 500,000 SNPs (Samani et al, 2007; McPherson et al, 2007; Helgadottir et al, 2007; Myocardial Infarction Genetics Consortium, 2009; Erdmann et al, 2009; Tregouet et al, 2009; IBC 50K CAD Consortium, 2011; Lu et al, 2012); asterisks: 2,500,000 SNPs (Coronary Artery Disease C4D Genetics Consortium, 2011; Schunkert et al, 2011; CARDIoGRAMplusC4D Consortium et al, 2013); arrow: 940,000 SNPs (Nikpay et al, 2015)].
Figure 2
Figure 2. Genetic variation and pathophysiological pathways in atherosclerosis
Figure 3
Figure 3. Genes involved in different pathophysiological pathways extracted from the 56 loci listed in Table 2
Functional annotations were collected from (i) the ConsensusPathDB database (http://consensuspathdb.org; Kamburov et al, 2013), (ii) the AmiGO 2 Gene Ontology (GO) browser (http://amigo.geneontology.org/amigo; Carbon et al, 2009), as well from (iii) the biomedical literature. Known and predicted associations among the genes within each functional category/pathway were retrieved from the STRING database (http://string-db.org; Franceschini et al, 2013) using default parameters. (A) Lipid metabolism. (B) Blood pressure. (C) NO‐cGMP signalling/platelet aggregation. (D) Vascular remodelling. (E) Inflammation.
Figure 4
Figure 4. Novel insights into the genetic variation in LDL cholesterol metabolism and therapeutic modulation
In low‐density lipoprotein (LDL) metabolism, sortilin 1 (SORT1), LDL cholesterol receptor (LDLR) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are exemplarily shown (green, favourable effect regarding LDL cholesterol/triglycerides; red, unfavourable effect regarding LDL cholesterol/triglycerides; ↑, variants increase the risk of CAD; ↓, variants decrease the risk of CAD).
See this image and copyright information in PMC

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