Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Jan 8;118(1):83-94.
doi: 10.1161/CIRCRESAHA.115.306629. Epub 2015 Oct 20.

Identifying Novel Gene Variants in Coronary Artery Disease and Shared Genes With Several Cardiovascular Risk Factors

Affiliations

Identifying Novel Gene Variants in Coronary Artery Disease and Shared Genes With Several Cardiovascular Risk Factors

Marissa LeBlanc et al. Circ Res. .

Abstract

Rationale: Coronary artery disease (CAD) is a critical determinant of morbidity and mortality. Previous studies have identified several cardiovascular disease risk factors, which may partly arise from a shared genetic basis with CAD, and thus be useful for discovery of CAD genes.

Objective: We aimed to improve discovery of CAD genes and inform the pathogenic relationship between CAD and several cardiovascular disease risk factors using a shared polygenic signal-informed statistical framework.

Methods and results: Using genome-wide association studies summary statistics and shared polygenic pleiotropy-informed conditional and conjunctional false discovery rate methodology, we systematically investigated genetic overlap between CAD and 8 traits related to cardiovascular disease risk factors: low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, type 2 diabetes mellitus, C-reactive protein, body mass index, systolic blood pressure, and type 1 diabetes mellitus. We found significant enrichment of single-nucleotide polymorphisms associated with CAD as a function of their association with low-density lipoprotein, high-density lipoprotein, triglycerides, type 2 diabetes mellitus, C-reactive protein, body mass index, systolic blood pressure, and type 1 diabetes mellitus. Applying the conditional false discovery rate method to the enriched phenotypes, we identified 67 novel loci associated with CAD (overall conditional false discovery rate <0.01). Furthermore, we identified 53 loci with significant effects in both CAD and at least 1 of low-density lipoprotein, high-density lipoprotein, triglycerides, type 2 diabetes mellitus, C-reactive protein, systolic blood pressure, and type 1 diabetes mellitus.

Conclusions: The observed polygenic overlap between CAD and cardiometabolic risk factors indicates a pathogenic relation that warrants further investigation. The new gene loci identified implicate novel genetic mechanisms related to CAD.

Keywords: Women’s Genome Health Study; coronary artery disease; coronary heart disease; genetic pleiotropy; genome-wide association study; lipids; molecular epidemiology; myocardial infarction.

PubMed Disclaimer

Figures

Figure 1
Figure 1. Shared Polygenic Enrichment
Conditional quantile-quantile plot of nominal versus empirical −log10 p-values in Coronary Artery Disease (CAD) as a function of significance of association with A) low density lipoprotein cholesterol (LDL), B) C-reactive protein (CRP), C) type 1 diabetes (T1D) and D) type 2 diabetes (T2D), at the level of −log10(p) > 0, −log10(p) > 1, −log10(p) > 2, −log10(p) > 3 corresponding to p < 1, p < 0.1, p < 0.01, p < 0.001, respectively. Due to the linkage disequilibrium structure on the Metabochip, a linkage disequilibrium-pruned set of SNPs was used for the quantile-quantile plots. Input p-values were adjusted for shared subjects, if present. Dotted lines indicate the null-hypothesis.
Figure 2
Figure 2
Conditional FDR Manhattan plot’ of −log10 (FDR)* values for Coronary Artery Disease (CAD) alone (black), and −log10 (conditional FDR) for CAD given type 2 diabetes (T2D; CAD|T2D; navy blue), CAD given type 1 diabetes (T1D; CAD|T1D; light green), CAD given low density lipoprotein (LDL; CAD|LDL; aqua). CAD given high density lipoprotein (HDL; CAD|HDL; dark green), CAD given triglycerides (TG; CAD|TG; fuchsia), CAD given body mass index (BMI; CAD|BMI; mustard yellow). CAD given C-reactive protein (CRP; CAD|CRP; royal blue) and CAD given systolic blood pressure (SBP; CAD|SBP; maroon). SNPs with −log10 (conditional FDR) > 2.9 (i.e. overall FDR < 0.01 after Bonferroni correction for eight traits) are shown with large points. A black circle around the large points indicates the most significant SNP in each linkage disequilibrium block and this SNP was annotated with the closest gene which is listed above the symbols in each locus, except for the HLA region on chromosome 6, which was excluded from the analysis. Details for the novel loci with −log10 (conditional FDR) > 2.9 are given in Table 1.* For the –log10 (FDR) for CAD alone the maximum value displayed in this figure is 6.5. This is done purely for display purposes and as such should be interpreted as >6.5.

Comment in

Similar articles

Cited by

References

    1. Peden JF, Farrall M. Thirty-five common variants for coronary artery disease: The fruits of much collaborative labour. Hum Mol Genet. 2011;20:R198–205. - PMC - PubMed
    1. CAD Consortium. Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR, Ingelsson E, Saleheen D, Erdmann J, Goldstein BA, Stirrups K, Konig IR, et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet. 2013;45:25–33. - PMC - PubMed
    1. Eichler EE, Flint J, Gibson G, Kong A, Leal SM, Moore JH, Nadeau JH. Missing heritability and strategies for finding the underlying causes of complex disease. Nat Rev Genet. 2010;11:446–450. - PMC - PubMed
    1. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, Cho JH, Guttmacher AE, Kong A, et al. Finding the missing heritability of complex diseases. Nature. 2009;461:747–753. - PMC - PubMed
    1. Li C, Yang C, Gelernter J, Zhao H. Improving genetic risk prediction by leveraging pleiotropy. Hum Genet. 2014;133:639–650. - PMC - PubMed

Publication types

MeSH terms