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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Targeted next-generation sequencing identifies pathogenic variants in familial congenital heart disease
Gillian M Blue1, Edwin P Kirk2, Eleni Giannoulatou3
1Kids Heart Research, The Children's Hospital at Westmead, Sydney, Australia; The Heart Centre for Children, The Children's Hospital at Westmead, Sydney, Australia; Sydney Medical School, University of Sydney, Sydney, Australia.
Background:
Many genes have been implicated in the development of congenital heart disease (CHD). Next-generation sequencing offers opportunities for genetic testing but is often complicated by logistic and interpretative hurdles.
Objectives:
This study sought to apply next-generation sequencing technology to CHD families with multiple affected members using a purpose-designed gene panel to assess diagnostic potential for future clinical applications.
Methods:
We designed a targeted next-generation sequencing gene panel for 57 genes previously implicated in CHD. Probands were screened in 16 families with strong CHD histories and in 15 control subjects. Variants affecting protein-coding regions were classified in silico using prediction programs and filtered according to predicted mode of inheritance, minor allele frequencies, and presence in databases such as dbSNP (Single Nucleotide Polymorphism Database) and ESP (Exome Sequencing Project). Disease segregation studies were conducted in variants identified in CHD cases predicted to be deleterious and with minor allele frequencies <0.1%.
Results:
Thirteen potential disease-causing variants were identified in 9 families. Of these, 5 variants segregated with disease phenotype, revealing a likely molecular diagnosis in 31% of this cohort. Significant increases in the number of "indels, nonsense, and splice" variants, as well as variants classified as "probably damaging" were identified in CHD cases but not in control subjects. Also, there was a significant increase in the total number of "rare" and "low" frequency variants (minor allele frequencies <0.05) in the CHD cases.
Conclusions:
When multiple relatives are affected by CHD, a gene panel-based approach may identify its cause in up to 31% of families. Identifying causal variants has implications for clinical care and future family planning.
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