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Determining the Likelihood of Disease Pathogenicity Among Incidentally Identified Genetic Variants in Rare Dilated Cardiomyopathy‐Associated Genes

BACKGROUND: As utilization of clinical exome sequencing (ES) has expanded, criteria for evaluating the diagnostic weight of incidentally identified variants are critical to guide clinicians and researchers. This is particularly important in genes associated with dilated cardiomyopathy (DCM), which c...

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Detalles Bibliográficos
Autores principales: Yang, Qixin, Berkman, Amy M., Ezekian, Jordan E., Rosamilia, Michael, Rosenfeld, Jill A., Liu, Pengfei, Landstrom, Andrew P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673717/
https://www.ncbi.nlm.nih.gov/pubmed/36129056
http://dx.doi.org/10.1161/JAHA.122.025257
Descripción
Sumario:BACKGROUND: As utilization of clinical exome sequencing (ES) has expanded, criteria for evaluating the diagnostic weight of incidentally identified variants are critical to guide clinicians and researchers. This is particularly important in genes associated with dilated cardiomyopathy (DCM), which can cause heart failure and sudden death. We sought to compare the frequency and distribution of incidentally identified variants in DCM‐associated genes between a clinical referral cohort with those in control and known case cohorts to determine the likelihood of pathogenicity among those undergoing genetic testing for non‐DCM indications. METHODS AND RESULTS: A total of 39 rare, non‐TTN DCM‐associated genes were identified and evaluated from a clinical ES testing referral cohort (n=14 005, Baylor Genetic Laboratories) and compared with a DCM case cohort (n=9442) as well as a control cohort of population variants (n=141 456) derived from the gnomAD database. Variant frequencies in each cohort were compared. Signal‐to‐noise ratios were calculated comparing the DCM and ES cohort with the gnomAD cohort. The likely pathogenic/pathogenic variant yield in the DCM cohort (8.2%) was significantly higher than in the ES cohort (1.9%). Based on signal‐to‐noise and correlation analysis, incidental variants found in FLNC, RBM20, MYH6, DSP, ABCC9, JPH2, and NEXN had the greatest chance of being DCM‐associated. CONCLUSIONS: The distribution of pathogenic variants between the ES cohort and the DCM case cohort was gene specific, and variants found in the ES cohort were similar to variants found in the control cohort. Incidentally identified variants in specific genes are more associated with DCM than others.