Improving molecular diagnosis in epilepsy by a dedicated high-throughput sequencing platform

Mina, Erika Della; Ciccone, Roberto; Brustia, Francesca; Bayindir, Baran; Limongelli, Ivan; Vetro, Annalisa; Iascone, Maria; Pezzoli, Laura; Bellazzi, Riccardo; Perotti, Gianfranco; Giorgis, Valentina De; Lunghi, Simona; Coppola, Giangennaro; Orcesi, Simona; Merli, Pietro; Savasta, Salvatore; Veggiotti, Pierangelo; Zuffardi, Orsetta

doi:10.1038/ejhg.2014.92

Cited by 52 publications

(33 citation statements)

References 42 publications

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“…The overall diagnostic yield for patients with EEs was 32%, compared to 16% in patients with focal or multifocal epilepsy. These diagnostic yields are similar to published studies on other targeted NGS panels [Lemke et al, 2012;Carvill et al, 2013a;Kodera et al, 2013;Wang et al, 2014;Della Mina et al, 2015;Mercimek-Mahmutoglu et al, 2015].…”

Section: Discussionsupporting

confidence: 76%

“…A presumed disease-causing variant was found in 23%, and a VUS was found in additional 3%. Targeted epilepsy gene panels are increasingly being used in research, and diagnostic laboratories and several studies using gene panels consisting of 35-265 genes have been published with diagnostic yields ranging between 10 and 48.5% [Lemke et al, 2012;Carvill et al, 2013a;Kodera et al, 2013;Wang et al, 2014;Della Mina et al, 2015;Mercimek-Mahmutoglu et al, 2015]. In these studies, there was a clear tendency towards higher positive rates in patients with early-onset epilepsies as well as in cases with severe phenotypes, and as expected, the observed de novo rate was high [Epi4K Consortium et al, 2013].…”

Section: Discussionmentioning

confidence: 99%

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Gene Panel Testing in Epileptic Encephalopathies and Familial Epilepsies

Larsen²,

et al. 2016

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In recent years, several genes have been causally associated with epilepsy. However, making a genetic diagnosis in a patient can still be difficult, since extensive phenotypic and genetic heterogeneity has been observed in many monogenic epilepsies. This study aimed to analyze the genetic basis of a wide spectrum of epilepsies with age of onset spanning from the neonatal period to adulthood. A gene panel targeting 46 epilepsy genes was used on a cohort of 216 patients consecutively referred for panel testing. The patients had a range of different epilepsies from benign neonatal seizures to epileptic encephalopathies (EEs). Potentially causative variants were evaluated by literature and database searches, submitted to bioinformatic prediction algorithms, and validated by Sanger sequencing. If possible, parents were included for segregation analysis. We identified a presumed disease-causing variant in 49 (23%) of the 216 patients. The variants were found in 19 different genes including SCN1A, STXBP1, CDKL5, SCN2A, SCN8A, GABRA1, KCNA2, and STX1B. Patients with neonatal-onset epilepsies had the highest rate of positive findings (57%). The overall yield for patients with EEs was 32%, compared to 17% among patients with generalized epilepsies and 16% in patients with focal or multifocal epilepsies. By the use of a gene panel consisting of 46 epilepsy genes, we were able to find a disease-causing genetic variation in 23% of the analyzed patients. The highest yield was found among patients with neonatal-onset epilepsies and EEs.

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Section: Discussionsupporting

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Gene Panel Testing in Epileptic Encephalopathies and Familial Epilepsies

Larsen²,

et al. 2016

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“…genes), are taken into account, and targets of association discovery are broadened. Finally, the ROIs that resulted more important for patients classification are significantly more mutated in cases than in controls, matching previous findings [37–40]. …”

Section: Introductionsupporting

confidence: 87%

A Data Fusion Approach to Enhance Association Study in Epilepsy

et al. 2016

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Among the scientific challenges posed by complex diseases with a strong genetic component, two stand out. One is unveiling the role of rare and common genetic variants; the other is the design of classification models to improve clinical diagnosis and predictive models for prognosis and personalized therapies. In this paper, we present a data fusion framework merging gene, domain, pathway and protein-protein interaction data related to a next generation sequencing epilepsy gene panel. Our method allows integrating association information from multiple genomic sources and aims at highlighting the set of common and rare variants that are capable to trigger the occurrence of a complex disease. When compared to other approaches, our method shows better performances in classifying patients affected by epilepsy.

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“…[2][3][4] It is also considered to be time-effective compared with sequential Sanger screening of multiple genes. Such a strategy was recently successfully applied to patients with early-onset dementia, 5 where a good sensitivity and a good specificity were found.…”

Section: Introductionmentioning

confidence: 99%

Screening of dementia genes by whole-exome sequencing in early-onset Alzheimer disease: input and lessons

Nicolas¹,

Wallon²,

Charbonnier³

et al. 2015

Eur J Hum Genet

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Causative variants in APP, PSEN1 or PSEN2 account for a majority of cases of autosomal dominant early-onset Alzheimer disease (ADEOAD, onset before 65 years). Variant detection rates in other EOAD patients, that is, with family history of lateonset AD (LOAD) (and no incidence of EOAD) and sporadic cases might be much lower. We analyzed the genomes from 264 patients using whole-exome sequencing (WES) with high depth of coverage: 90 EOAD patients with family history of LOAD and no incidence of EOAD in the family and 174 patients with sporadic AD starting between 51 and 65 years. We found three PSEN1 and one PSEN2 causative, probably or possibly causative variants in four patients (1.5%). Given the absence of PSEN1, PSEN2 and APP causative variants, we investigated whether these 260 patients might be burdened with protein-modifying variants in 20 genes that were previously shown to cause other types of dementia when mutated. For this analysis, we included an additional set of 160 patients who were previously shown to be free of causative variants in PSEN1, PSEN2 and APP: 107 ADEOAD patients and 53 sporadic EOAD patients with an age of onset before 51 years. In these 420 patients, we detected no variant that might modify the function of the 20 dementia-causing genes. We conclude that EOAD patients with family history of LOAD and no incidence of EOAD in the family or patients with sporadic AD starting between 51 and 65 years have a low variant-detection rate in AD genes.

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Improving molecular diagnosis in epilepsy by a dedicated high-throughput sequencing platform

Cited by 52 publications

References 42 publications

Gene Panel Testing in Epileptic Encephalopathies and Familial Epilepsies

Gene Panel Testing in Epileptic Encephalopathies and Familial Epilepsies

A Data Fusion Approach to Enhance Association Study in Epilepsy

Screening of dementia genes by whole-exome sequencing in early-onset Alzheimer disease: input and lessons

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