ExomeChip Identifies 10 Novel QT Loci

ExomeChip Identifies 10 Novel QT Loci


– [Narrator] This is an
overview of an article entitled ExomeChip-Wide Analysis
of 95,626 Individuals Identifies 10 novel Loci Associated with QT and JT intervals, published in the January 2018 issue of Circulation: Genomic
and Precision Medicine. The electrocardiographic QT interval spans from the beginning of the QRS complex to the end of the T-wave, as shown in the schematic here. The QT interval is
measured in order to assess the length of duration of
ventricular repolarization. Abnormality of the QT
interval in either direction, too long or too short, predisposes to arrhythmias
and sudden cardiac death. The JT interval, as shown here, is a more precise measure of
ventricular repolarization since it subtracts the QRS interval, which is when ventricular
depolarization occurs, from the QT interval. To assess for genetic
factors that contribute to clinical traits, genetic association studies are performed. The most commonly done association study has been the genome-wide
association study, or GWAS, which assesses common DNA
variants throughout the genome for strength of association
with the phenotype of interest. These common variants
are, for the most part, non-coding variants. More recently, exome
chips that can directly interrogate coding variants in genes have become available. While the exome chips do cover
some non-coding variants, they are very comprehensive with respect to coding variants,
covering all coding variants that were found in at
least three individuals out of 12,000 individuals
who had undergone exome sequencing. This comprises almost
200,000 coding variants in more than 17,000 genes. The authors of the paper under discussion performed an exome chip
genotyping association study in more than 95,000 individuals, most of whom were of European descent, although several other ethnicities were represented in smaller numbers. The rationale for using the exome chip is that GWASes tended to
identify non-coding variants that often do not pinpoint specific genes, since non-coding variants can affect genes at a large distance, meaning that each GWAS hit might implicate numerous candidate snips in
the vicinity of the locus. In contrast, exome chip studies tend to identify coding
variants within genes, which implicate those specific genes as the causal genes. Here are the results of
the exome chip analysis with the QT interval. In this graph the X axis is
the position in the genome split into different chromosomes, and the Y axis is the
strength of association. The green line indicates
a stringent threshold for statistical significance, taking into account the
hundreds of thousands of variants tested in the study. Many known loci implicated by
previous association studies were validated in this
study, indicated in yellow. In red are genes or loci being linked to the QT interval for the
first time in this study. Here are the genes or loci associated with the JT interval
but not the QT interval. There were no prior loci
linked only to the JT interval. This study found four novel
genes or loci, indicated in red. There were several key
findings in this study. First, the exome chip analysis identified coding variants in two notable genes as being linked to the QT interval, SCN10A and KCNQ1. Both have previously been linked to cardiac repolarization, SCN10A to Brugada syndrome by GWAS. KCNQ1 is the well established causal gene for long QT syndrome type one. Second, the study found
four hits associated only with the JT interval. Third, functional
annotation of the various exome chip hits identified
several known pathways, potassium, sodium, or
calcium ion regulation, and autonomic control, and new pathways, the physical force of
contraction of cardiomyocytes, as well as conduction
of the electrical signal between cardiomyocytes. In conclusion, this study identified
a total of 10 new loci associated with the QT and/or JT interval. The exome chip analysis
pinpointed variants in 17 genes, seven of which are new loci. These findings validated
previously identified molecular pathways involved
in cardiac repolarization and nominated new pathways. Finally, by identifying hits
linked to the JT interval but not the QT interval, the study suggests that
different genetic factors might influence the
depolarization and repolarization phases of the ventricles. Together, these findings shed new light on normal cardiac electrophysiology, diseases with repolarization
abnormalities, and potential treatments for the diseases.

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