Dataset Information

Diagnostic Yield From 339 Epilepsy Patients Screened on a Clinical Gene Panel.

ABSTRACT: BACKGROUND:The contribution of genetic factors to epilepsy has long been recognized and has been estimated to play a role in 70% to 80% of cases. Identification of a pathogenic variant can help families to better cope with the disorder, allows for genetic counseling to determine recurrence risk, and in some cases, can directly influence treatment options. In this study, we determined the diagnostic yield of a clinical gene panel applied to an unselected cohort of epilepsy patients. METHODS:Variant reports from 339 clinically referred epilepsy patients screened using a 110-gene panel were retrospectively reviewed. Variants were classified using the American College of Medical Genetics and Genomics guidelines. RESULTS:Pathogenic or likely pathogenic variants were identified in 62 individuals (18%) and potentially causative variants were identified in an additional 21 individuals (6%). Causative and potentially causative variants were most frequently identified in SCN1A (n = 15) and KCNQ2 (n = 10). Other genes in which disease-causing variants were identified in multiple individuals included CDKL5, SCN2A, SCN8A, SCN1B, STXBP1, TPP1, PCDH19, CACNA1A, GABRA1, GRIN2A, SLC2A1, and TSC2. Sixteen additional genes had variants identified in single individuals. CONCLUSIONS:We identified 87 variants in 30 different genes that could explain disease, of which 54% were not previously reported. This study confirms the utility of targeted gene panel analysis in epilepsy and highlights several factors to improve the yield of diagnostic genetic testing, including the critical need for clinical phenotype information and parental samples, microarray analysis for whole exon deletions and duplications, and frequent update of panels to incorporate new disease genes.

SUBMITTER: Butler KM

PROVIDER: S-EPMC6885003 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Diagnostic Yield From 339 Epilepsy Patients Screened on a Clinical Gene Panel.

Butler Kameryn M KM da Silva Cristina C Alexander John J JJ Hegde Madhuri M Escayg Andrew A

Pediatric neurology 20170906

<h4>Background</h4>The contribution of genetic factors to epilepsy has long been recognized and has been estimated to play a role in 70% to 80% of cases. Identification of a pathogenic variant can help families to better cope with the disorder, allows for genetic counseling to determine recurrence risk, and in some cases, can directly influence treatment options. In this study, we determined the diagnostic yield of a clinical gene panel applied to an unselected cohort of epilepsy patients.<h4>Me ...[more]

PMID: 29056246

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Project description:BackgroundIn a considerable number of patients with a suspected hereditary tumor syndrome (HTS), no underlying germline mutation is detected in the most likely affected genes. The present study aimed to establish and validate a large gene panel for HTS, and determine its diagnostic yield and clinical utility.MethodsThe study cohort comprised 173 patients with suspected, but unexplained, HTS (group U) and 64 HTS patients with a broad spectrum of known germline mutations (group K). All patients in group U presented with early age at onset, multiple tumors, and/or a familial clustering of various tumor types; no germline mutation had been identified during routine diagnostics. Sequencing of leukocyte DNA was performed for the 94 HTS genes of the Illumina TruSight™Cancer Panel and 54 additional HTS genes.ResultsThe sensitivity of the panel to identify known germline variants was 99.6%. In addition to known mutations, a total of 192 rare, potentially pathogenic germline variants in 86 genes were identified. Neither the proportion of rare variants per patient (group K: 0.9 variants; group U: 0.8 variants) nor the proportion of variants in the most frequently mutated, moderately penetrant genes CHEK2 and ATM showed significant inter-group difference. Four of the five patients from group U with a truncating CHEK2 mutation had thyroid cancer, pointing to a broader tumor spectrum in patients with pathogenic CHEK2 variants. In 22% of patients from group K, a further potential causative variant was identified. Here, the most interesting finding was an NF1 nonsense mutation in a child with a known TP53 frameshift mutation. In 17% of patients from group U, potential causative variants were identified. In three of these patients (2%), mutations in PMS2, PTEN, or POLD1 were considered to be causative. In both groups, incidental findings with presumptive predictive value were generated.ConclusionsThe gene panel identified the genetic cause in some prescreened, unexplained HTS patients and generated incidental findings. Some patients harbored predicted pathogenic mutations in more than one established HTS gene, rendering interpretation of the respective alterations challenging. Established moderate risk genes showed an almost equal distribution among patients with known and unexplained disease.

Project description:Exome sequencing (ES) has been used in a variety of clinical settings but there are limited data on its utility for diagnosis and/or prediction of monogenic liver diseases. We developed a curated list of 502 genes for monogenic disorders associated with liver phenotypes and analyzed ES data for these genes in 758 patients with chronic liver diseases (CLD). For comparison, we examined ES data in 7856 self-declared healthy controls (HC), and 2187 patients with chronic kidney disease (CKD). Candidate pathogenic (P) or likely pathogenic (LP) variants were initially identified in 19.9% of participants, most of which were attributable to previously reported pathogenic variants with implausibly high allele frequencies. After variant annotation and filtering based on population minor allele frequency (MAF ≤ 10-4 for dominant disorders and MAF ≤ 10-3 for recessive disorders), we detected a significant enrichment of P/LP variants in the CLD cohort compared to the HC cohort (X2 test OR 5.00, 95% CI 3.06-8.18, p value = 4.5e-12). A second-level manual annotation was necessary to capture true pathogenic variants that were removed by stringent allele frequency and quality filters. After these sequential steps, the diagnostic rate of monogenic disorders was 5.7% in the CLD cohort, attributable to P/LP variants in 25 genes. We also identified concordant liver disease phenotypes for 15/22 kidney disease patients with P/LP variants in liver genes, mostly associated with cystic liver disease phenotypes. Sequencing results had many implications for clinical management, including familial testing for early diagnosis and management, preventative screening for associated comorbidities, and in some cases for therapy. Exome sequencing provided a 5.7% diagnostic rate in CLD patients and required multiple rounds of review to reduce both false positive and false negative findings. The identification of concordant phenotypes in many patients with P/LP variants and no known liver disease also indicates a potential for predictive testing for selected monogenic liver disorders.

Dataset Information

Diagnostic Yield From 339 Epilepsy Patients Screened on a Clinical Gene Panel.

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Diagnostic Yield From 339 Epilepsy Patients Screened on a Clinical Gene Panel.

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