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A Combined Linkage and Exome Sequencing Analysis for Electrocardiogram Parameters in the Erasmus Rucphen Family Study. | LitMetric

AI Article Synopsis

  • ECG measurements are crucial for diagnosing heart rhythm problems and predicting sudden cardiac death, and while some genetic factors have been identified, many remain unknown.* -
  • This study aimed to find rare genetic variants linked to ECG measurements in a large family-based cohort, identifying five notable linkage regions for various ECG intervals.* -
  • A specific genetic variant associated with the QT interval was identified, suggesting it plays a role in heart function, though results weren't replicated in another study, indicating further investigation is needed.*

Article Abstract

Electrocardiogram (ECG) measurements play a key role in the diagnosis and prediction of cardiac arrhythmias and sudden cardiac death. ECG parameters, such as the PR, QRS, and QT intervals, are known to be heritable and genome-wide association studies of these phenotypes have been successful in identifying common variants; however, a large proportion of the genetic variability of these traits remains to be elucidated. The aim of this study was to discover loci potentially harboring rare variants utilizing variance component linkage analysis in 1547 individuals from a large family-based study, the Erasmus Rucphen Family Study (ERF). Linked regions were further explored using exome sequencing. Five suggestive linkage peaks were identified: two for QT interval (1q24, LOD = 2.63; 2q34, LOD = 2.05), one for QRS interval (1p35, LOD = 2.52) and two for PR interval (9p22, LOD = 2.20; 14q11, LOD = 2.29). Fine-mapping using exome sequence data identified a C > G missense variant (c.713C > G, p.Ser238Cys) in the gene associated with QT (rs74608430; = 2.8 × 10, minor allele frequency = 0.019). Heritability analysis demonstrated that the SNP explained 2.42% of the trait's genetic variability in ERF ( = 0.02). Pathway analysis suggested that the gene is involved in cytosolic Ca levels ( = 3.3 × 10) and AMPK stimulated fatty acid oxidation in muscle ( = 4.1 × 10). Look-ups in bioinformatics resources showed that expression of is associated with and expression. This finding was not replicated in the Rotterdam study. Combining the bioinformatics information with the association and linkage analyses, emerges as a strong candidate gene for QT interval.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5099142PMC
http://dx.doi.org/10.3389/fgene.2016.00190DOI Listing

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