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Utility and limitations of exome sequencing as a genetic diagnostic tool for conditions associated with pediatric sudden cardiac arrest/sudden cardiac death

Overview of attention for article published in Human Genomics, July 2015
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Title
Utility and limitations of exome sequencing as a genetic diagnostic tool for conditions associated with pediatric sudden cardiac arrest/sudden cardiac death
Published in
Human Genomics, July 2015
DOI 10.1186/s40246-015-0038-y
Pubmed ID
Authors

Mindy H. Li, Jenica L. Abrudan, Matthew C. Dulik, Ariella Sasson, Joshua Brunton, Vijayakumar Jayaraman, Noreen Dugan, Danielle Haley, Ramakrishnan Rajagopalan, Sawona Biswas, Mahdi Sarmady, Elizabeth T. DeChene, Matthew A. Deardorff, Alisha Wilkens, Sarah E. Noon, Maria I. Scarano, Avni B. Santani, Peter S. White, Jeffrey Pennington, Laura K. Conlin, Nancy B. Spinner, Ian D. Krantz, Victoria L. Vetter

Abstract

Conditions associated with sudden cardiac arrest/death (SCA/D) in youth often have a genetic etiology. While SCA/D is uncommon, a pro-active family screening approach may identify these inherited structural and electrical abnormalities prior to symptomatic events and allow appropriate surveillance and treatment. This study investigated the diagnostic utility of exome sequencing (ES) by evaluating the capture and coverage of genes related to SCA/D. Samples from 102 individuals (13 with known molecular etiologies for SCA/D, 30 individuals without known molecular etiologies for SCA/D and 59 with other conditions) were analyzed following exome capture and sequencing at an average read depth of 100X. Reads were mapped to human genome GRCh37 using Novoalign, and post-processing and analysis was done using Picard and GATK. A total of 103 genes (2,190 exons) related to SCA/D were used as a primary filter. An additional 100 random variants within the targeted genes associated with SCA/D were also selected and evaluated for depth of sequencing and coverage. Although the primary objective was to evaluate the adequacy of depth of sequencing and coverage of targeted SCA/D genes and not for primary diagnosis, all patients who had SCA/D (known or unknown molecular etiologies) were evaluated with the project's variant analysis pipeline to determine if the molecular etiologies could be successfully identified. The majority of exons (97.6 %) were captured and fully covered on average at minimum of 20x sequencing depth. The proportion of unique genomic positions reported within poorly covered exons remained small (4 %). Exonic regions with less coverage reflect the need to enrich these areas to improve coverage. Despite limitations in coverage, we identified 100 % of cases with a prior known molecular etiology for SCA/D, and analysis of an additional 30 individuals with SCA/D but no known molecular etiology revealed a diagnostic answer in 5/30 (17 %). We also demonstrated 95 % of 100 randomly selected reported variants within our targeted genes would have been picked up on ES based on our coverage analysis. ES is a helpful clinical diagnostic tool for SCA/D given its potential to successfully identify a molecular diagnosis, but clinicians should be aware of limitations of available platforms from technical and diagnostic perspectives.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
China 1 2%
Unknown 44 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 30%
Student > Bachelor 8 17%
Other 7 15%
Student > Ph. D. Student 3 7%
Professor > Associate Professor 3 7%
Other 7 15%
Unknown 4 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 37%
Medicine and Dentistry 9 20%
Agricultural and Biological Sciences 6 13%
Psychology 2 4%
Engineering 2 4%
Other 4 9%
Unknown 6 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 February 2020.
All research outputs
#6,572,065
of 25,374,647 outputs
Outputs from Human Genomics
#153
of 564 outputs
Outputs of similar age
#70,010
of 275,155 outputs
Outputs of similar age from Human Genomics
#7
of 14 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 275,155 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.