PURPOSE: We evaluated the diagnostic yield in pediatric dilated cardiomyopathy (DCM) of combining exome sequencing (ES)-based targeted analysis and genome-wide copy-number variation (CNV) analysis. Based on our findings, we retrospectively designed an effective approach for genetic testing in pediatric DCM. METHODS: We identified 95 patients (in 85 families) with pediatric onset of DCM. We initially excluded 13 of these families because they already had a genetic diagnosis, leaving a total of 31 probands for single-nucleotide polymorphism (SNP) array and trio-ES. We used Human Phenotype Ontology (HPO)-based filtering for our data analysis. RESULTS: We reached a genetic diagnosis in 15/31 (48.4%) families. ES yielded a diagnosis in 13 probands (13/15; 86.7%), with most variants being found in genes encoding structural cardiomyocyte components. Two large deletions were identified using SNP array. If we had included the 13 excluded families, our estimated yield would have been 54%. CONCLUSION: We propose a standardized, stepwise analysis of (i) well-known cardiomyopathy genes, (ii) CNVs, (iii) all genes assigned to HPO cardiomyopathy, and (iv) if appropriate, genes assigned to other HPO terms. This diagnostic approach yields the highest increase at each subsequent step and reduces analytic effort, cost, the number of variants of unknown clinical significance, and the chance of incidental findings.
PURPOSE: We evaluated the diagnostic yield in pediatric dilated cardiomyopathy (DCM) of combining exome sequencing (ES)-based targeted analysis and genome-wide copy-number variation (CNV) analysis. Based on our findings, we retrospectively designed an effective approach for genetic testing in pediatric DCM. METHODS: We identified 95 patients (in 85 families) with pediatric onset of DCM. We initially excluded 13 of these families because they already had a genetic diagnosis, leaving a total of 31 probands for single-nucleotide polymorphism (SNP) array and trio-ES. We used Human Phenotype Ontology (HPO)-based filtering for our data analysis. RESULTS: We reached a genetic diagnosis in 15/31 (48.4%) families. ES yielded a diagnosis in 13 probands (13/15; 86.7%), with most variants being found in genes encoding structural cardiomyocyte components. Two large deletions were identified using SNP array. If we had included the 13 excluded families, our estimated yield would have been 54%. CONCLUSION: We propose a standardized, stepwise analysis of (i) well-known cardiomyopathy genes, (ii) CNVs, (iii) all genes assigned to HPO cardiomyopathy, and (iv) if appropriate, genes assigned to other HPO terms. This diagnostic approach yields the highest increase at each subsequent step and reduces analytic effort, cost, the number of variants of unknown clinical significance, and the chance of incidental findings.
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Authors: Jay Ramchand; Mathew Wallis; Ivan Macciocca; Elly Lynch; Omar Farouque; Melissa Martyn; Dean Phelan; Belinda Chong; Siobhan Lockwood; Robert Weintraub; Tina Thompson; Alison Trainer; Dominica Zentner; Jitendra Vohra; Michael Chetrit; David L Hare; Paul James Journal: J Am Heart Assoc Date: 2020-01-14 Impact factor: 5.501
Authors: Elena Valeryevna Feofanova; Guo-Qiang Zhang; Samden Lhatoo; Ginger A Metcalf; Eric Boerwinkle; Eric Venner Journal: JMIR Res Protoc Date: 2021-03-26
Authors: Kim Elsink; Manon M H Huibers; Iris H I M Hollink; Annet Simons; Evelien Zonneveld-Huijssoon; Lars T van der Veken; Helen L Leavis; Stefanie S V Henriet; Marcel van Deuren; Frank L van de Veerdonk; Judith Potjewijd; Dagmar Berghuis; Virgil A S H Dalm; Clementien L Vermont; Annick A J M van de Ven; Annechien J A Lambeck; Kristin M Abbott; P Martin van Hagen; Godelieve J de Bree; Taco W Kuijpers; Geert W J Frederix; Mariëlle E van Gijn; Joris M van Montfrans Journal: Front Immunol Date: 2021-12-21 Impact factor: 7.561