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. 2020 Feb;61(2):249-258.
doi: 10.1111/epi.16427. Epub 2020 Jan 19.

Genetic diagnoses in epilepsy: The impact of dynamic exome analysis in a pediatric cohort

Affiliations

Genetic diagnoses in epilepsy: The impact of dynamic exome analysis in a pediatric cohort

Anne Rochtus et al. Epilepsia. 2020 Feb.

Abstract

Objective: We evaluated the yield of systematic analysis and/or reanalysis of whole exome sequencing (WES) data from a cohort of well-phenotyped pediatric patients with epilepsy and suspected but previously undetermined genetic etiology.

Methods: We identified and phenotyped 125 participants with pediatric epilepsy. Etiology was unexplained at the time of enrollment despite clinical testing, which included chromosomal microarray (57 patients), epilepsy gene panel (n = 48), both (n = 28), or WES (n = 8). Clinical epilepsy diagnoses included developmental and epileptic encephalopathy (DEE), febrile infection-related epilepsy syndrome, Rasmussen encephalitis, and other focal and generalized epilepsies. We analyzed WES data and compared the yield in participants with and without prior clinical genetic testing.

Results: Overall, we identified pathogenic or likely pathogenic variants in 40% (50/125) of our study participants. Nine patients with DEE had genetic variants in recently published genes that had not been recognized as epilepsy-related at the time of clinical testing (FGF12, GABBR1, GABBR2, ITPA, KAT6A, PTPN23, RHOBTB2, SATB2), and eight patients had genetic variants in candidate epilepsy genes (CAMTA1, FAT3, GABRA6, HUWE1, PTCHD1). Ninety participants had concomitant or subsequent clinical genetic testing, which was ultimately explanatory for 26% (23/90). Of the 67 participants whose molecular diagnoses were "unsolved" through clinical genetic testing, we identified pathogenic or likely pathogenic variants in 17 (25%).

Significance: Our data argue for early consideration of WES with iterative reanalysis for patients with epilepsy, particularly those with DEE or epilepsy with intellectual disability. Rigorous analysis of WES data of well-phenotyped patients with epilepsy leads to a broader understanding of gene-specific phenotypic spectra as well as candidate disease gene identification. We illustrate the dynamic nature of genetic diagnosis over time, with analysis and in some cases reanalysis of exome data leading to the identification of disease-associated variants among participants with previously nondiagnostic results from a variety of clinical testing strategies.

Keywords: epilepsy; genetics; phenotype; reanalysis; whole exome sequencing.

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Conflict of interest statement

Conflicts of Interest

Nothing to report. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

Figures

Figure 1:
Figure 1:. Diagnostic yield of research WES
Diagnostic yield of research WES compared with diagnostic yield of prior/concomitant clinical genetic testing. CMA = chromosomal microarray; WES = whole exome sequencing. Blue represents the diagnostic yield from clinical testing and orange the diagnostic yield from research WES. Overall, 90 participants had at least one clinical genetic test. Since the type of clinical genetic testing that each participant had was variable and some participants had more than one genetic test, the total n represented by the categories in the figure does not add up to 90.

References

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