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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Single-nucleotide variations in cardiac arrhythmias: prospects for genomics and proteomics based biomarker discovery
Ayman Abunimer1, Krista Smith2, Tsung-Jung Wu3
1Department of Biochemistry and Molecular Medicine, George Washington University, Washington, DC 20037, USA. aabunimer115@gmail.com.
Insights
Researchers identified 75 genetic variations linked to cardiac arrhythmias, including 10 that alter proteins. Further analysis revealed how these genetic changes affect S-nitrosylation, impacting pathways like blood coagulation and muscle contraction, aiding arrhythmia susceptibility prediction.
Area of Science:
- Genetics and Cardiovascular Research
- Proteomics and Molecular Biology
Background:
- Cardiovascular diseases are a leading cause of premature death globally.
- Cardiac arrhythmias, like sudden cardiac death and atrial fibrillation, arise from abnormal heart electrical activity.
- Genome-wide association studies (GWAS) identify genetic variations (SNVs) linked to acquired arrhythmias.
Purpose of the Study:
- To compile a comprehensive list of SNVs associated with cardiac arrhythmias.
- To investigate the impact of non-synonymous SNVs on protein function, specifically S-nitrosylation.
- To identify novel genetic and proteomic factors contributing to arrhythmia susceptibility.
Main Methods:
- Manual curation of published GWAS data to identify 75 arrhythmia-associated SNVs.
- Analysis of S-nitrosylation sites affected by non-synonymous SNVs (nsSNVs).
- Bioinformatic analysis (pathway and Gene Ontology analysis) of predicted S-nitrosylation sites.
Main Results:
- A curated list of 75 SNVs associated with cardiac arrhythmias was established.
- Ten SNVs were found to cause amino acid changes, enabling proteomic detection.
- Analysis revealed loss of 7 known S-nitrosylation sites and modification of 1429 proteins due to nsSNVs.
- Over-representation of blood coagulation, muscle contraction, and cytoskeletal activity pathways was observed.
Conclusions:
- This study provides a valuable resource of SNVs and their proteomic context for arrhythmia research.
- Understanding the interplay between genetic variation, S-nitrosylation, and cardiac function can improve arrhythmia susceptibility prediction.
- Elucidating these mechanisms offers a new parameter for predicting predisposition to cardiac diseases.
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.
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