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
. 2014 Mar 27;5(2):254-69.
doi: 10.3390/genes5020254.

Single-nucleotide variations in cardiac arrhythmias: prospects for genomics and proteomics based biomarker discovery and diagnostics

Affiliations

Single-nucleotide variations in cardiac arrhythmias: prospects for genomics and proteomics based biomarker discovery and diagnostics

Ayman Abunimer et al. Genes (Basel). .

Abstract

Cardiovascular diseases are a large contributor to causes of early death in developed countries. Some of these conditions, such as sudden cardiac death and atrial fibrillation, stem from arrhythmias-a spectrum of conditions with abnormal electrical activity in the heart. Genome-wide association studies can identify single nucleotide variations (SNVs) that may predispose individuals to developing acquired forms of arrhythmias. Through manual curation of published genome-wide association studies, we have collected a comprehensive list of 75 SNVs associated with cardiac arrhythmias. Ten of the SNVs result in amino acid changes and can be used in proteomic-based detection methods. In an effort to identify additional non-synonymous mutations that affect the proteome, we analyzed the post-translational modification S-nitrosylation, which is known to affect cardiac arrhythmias. We identified loss of seven known S-nitrosylation sites due to non-synonymous single nucleotide variations (nsSNVs). For predicted nitrosylation sites we found 1429 proteins where the sites are modified due to nsSNV. Analysis of the predicted S-nitrosylation dataset for over- or under-representation (compared to the complete human proteome) of pathways and functional elements shows significant statistical over-representation of the blood coagulation pathway. Gene Ontology (GO) analysis displays statistically over-represented terms related to muscle contraction, receptor activity, motor activity, cystoskeleton components, and microtubule activity. Through the genomic and proteomic context of SNVs and S-nitrosylation sites presented in this study, researchers can look for variation that can predispose individuals to cardiac arrhythmias. Such attempts to elucidate mechanisms of arrhythmia thereby add yet another useful parameter in predicting susceptibility for cardiac diseases.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Percentage of predicted S-nitrosylated proteins and sites and the ones which are conserved across mouse, fly, plant or yeast and the nsSNVs mapped to these proteins and sites. Details are available in Table S2.
Figure 2
Figure 2
HIVE interface showing results obtained from SNV profiling of human exome reads mapped to FASTA sequence surrounding a SNV. (A) Overall coverage result with the 603 position showing variation. (B) Reads mapped to the reference with the yellow highlighting the column selected. (C) Only variations are shown in this panel.

References

    1. Darbar D. Genomics, heart failure and sudden cardiac death. Heart Fail. Rev. 2010;15:229–238. doi: 10.1007/s10741-008-9095-9. - DOI - PMC - PubMed
    1. Mahida S., Lubitz S.A., Rienstra M., Milan D.J., Ellinor P.T. Monogenic atrial fibrillation as pathophysiological paradigms. Cardiovasc. Res. 2011;89:692–700. doi: 10.1093/cvr/cvq381. - DOI - PMC - PubMed
    1. Parvez B., Darbar D. The “missing” link in atrial fibrillation heritability. J. Electrocardiol. 2011;44:641–644. doi: 10.1016/j.jelectrocard.2011.07.027. - DOI - PMC - PubMed
    1. Biesecker L.G. Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice: Lessons from the clinseq project. Genet. Med. 2012;14:393–398. doi: 10.1038/gim.2011.78. - DOI - PMC - PubMed
    1. Ng D., Johnston J.J., Teer J.K., Singh L.N., Peller L.C., Wynter J.S., Lewis K.L., Cooper D.N., Stenson P.D., Mullikin J.C., et al. Interpreting secondary cardiac disease variants in an exome cohort. Circ. Cardiovasc. Genet. 2013;6:337–346. doi: 10.1161/CIRCGENETICS.113.000039. - DOI - PMC - PubMed

LinkOut - more resources