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

Exploring the Genetic Etiology of Pediatric Epilepsy: Insights from Targeted Next-Generation Sequence Analysis

Introduction

Epilepsy is a group of neurologic disorders with clinical and genetic heterogeneity. Epilepsy often affects children; thus, early diagnosis and precise treatment are vital to protecting the standard of life of a child. Progress in epilepsy-related gene discovery has caused enormous novelty in specific epilepsy diagnoses. Genetic testing using next-generation sequencing is now reachable, leading to higher diagnosis ratios and understanding of the disease's underlying mechanisms. The study's primary aim was to identify the genetic etiology based on targeted next-generation sequence analysis data and to calculate the diagnostic value of the epilepsy gene panel in the 0-17 age-group diagnosed with epilepsy. The secondary aim was to demonstrate the significance of periodic reinterpretation of variant of uncertain significance (VUS) variants and genotype-phenotype correlation.

Methods

This retrospective study comprised 107 patients with epilepsy aged 8 months to 17 years, for whom a targeted gene panel covered 110 genes. VUS variants were reanalyzed, and genotype-phenotype correlation was performed.

Results

In the initial evaluation, causal variants were described in 23 patients (21.5%). After reinterpretation of VUS, we detected causal variants in 30 out of 107 patients (28%). By reinterpreting the VUS and evaluating genotype-phenotype correlations, we enhanced our diagnostic value by 30.32%. After reinterpretation of VUS variants, the ACMG classification of 36 variants, including 15 benign (31%), 15 likely benign (31%), 5 likely pathogenic (10%), and 1 pathogenic (2%), were redefined. We most frequently detected causal variants in TSC2 (n = 5), GRIN2A (n = 4), and ALDH7A1 (n = 4) genes.

Conclusion

The predictive value for epilepsy panel testing was 28% in the cohort. Our study revealed the importance of reanalysis of VUS variants and contributed to enriching the mutation spectrum in epilepsy.

A labeled medical records corpus for the timely detection of rare diseases using machine learning approaches

Rare diseases (RDs) are a group of pathologies that individually affect less than 1 in 2000 people but collectively impact around 7% of the world's population. Most of them affect children, are chronic and progressive, and have no specific treatment. RD patients face diagnostic challenges, with an average diagnosis time of 5 years, multiple specialist visits, and invasive procedures. This 'diagnostic odyssey' can be detrimental to their health. Machine learning (ML) has the potential to improve healthcare by providing more personalized and accurate patient management, diagnoses, and in some cases, treatments. Leveraging the MIMIC-III database and additional medical notes from different sources such as in-house data, PubMed and chatGPT, we propose a labeled dataset for early RD detection in hospital settings. Applying various supervised ML methods, including logistic regression, decision trees, support vector machine (SVM), deep learning methods (LSTM and CNN), and Transformers (BERT), we validated the use of the proposed resource, achieving 92.7% F-measure and a 96% AUC using SVM. These findings highlight the potential of ML in redirecting RD patients towards more accurate diagnostic pathways and presents a corpus that can be used for future development and refinements.

Astrocyte-derived SerpinA3N promotes neuroinflammation and epileptic seizures by activating the NF-κB signaling pathway in mice with temporal lobe epilepsy

Impaired activation and regulation of the extinction of inflammatory cells and molecules in injured neuronal tissues are key factors in the development of epilepsy. SerpinA3N is mainly associated with the acute phase response and inflammatory response. In our current study, transcriptomics analysis, proteomics analysis, and Western blotting showed that the expression level of Serpin clade A member 3N (SerpinA3N) is significantly increased in the hippocampus of mice with kainic acid (KA)-induced temporal lobe epilepsy, and this molecule is mainly expressed in astrocytes. Notably, in vivo studies using gain- and loss-of-function approaches revealed that SerpinA3N in astrocytes promoted the release of proinflammatory factors and aggravated seizures. Mechanistically, RNA sequencing and Western blotting showed that SerpinA3N promoted KA-induced neuroinflammation by activating the NF-κB signaling pathway. In addition, co-immunoprecipitation revealed that SerpinA3N interacts with ryanodine receptor type 2 (RYR2) and promotes RYR2 phosphorylation. Overall, our study reveals a novel SerpinA3N-mediated mechanism in seizure-induced neuroinflammation and provides a new target for developing neuroinflammation-based strategies to reduce seizure-induced brain injury.

Genetic Testing in Children with Developmental and Epileptic Encephalopathies: A Review of Advances in Epilepsy Genomics

Advances in disease-related gene discovery have led to tremendous innovations in the field of epilepsy genetics. Identification of genetic mutations that cause epileptic encephalopathies has opened new avenues for the development of targeted therapies. Clinical testing using extensive gene panels, exomes, and genomes is currently accessible and has resulted in higher rates of diagnosis and better comprehension of the disease mechanisms underlying the condition. Children with developmental disabilities have a higher risk of developing epilepsy. As our understanding of the mechanisms underlying encephalopathies and epilepsies improves, there may be greater potential to develop innovative therapies tailored to an individual’s genotype. This article provides an overview of the significant progress in epilepsy genomics in recent years, with a focus on developmental and epileptic encephalopathies in children. The aim of this review is to enhance comprehension of the clinical utilization of genetic testing in this particular patient population. The development of effective and precise therapeutic strategies for epileptic encephalopathies may be facilitated by a comprehensive understanding of their molecular pathogenesis.

Challenging Occam’s Razor: Dual Molecular Diagnoses Explain Entangled Clinical Pictures

Dual molecular diagnoses are defined as the presence of pathogenic variants at two distinct and independently segregating loci that cause two different Mendelian conditions. In this study, we report the identification of double genetic disorders in a series of patients with complex clinical features. In the last 24 months, 342 syndromic patients have been recruited and clinically characterised. Whole Exome Sequencing analysis has been performed on the proband and on both parents and identified seven patients affected by a dual molecular diagnosis. Upon a detailed evaluation of both their clinical and molecular features, subjects are able to be divided into two groups: (A) five patients who present distinct phenotypes, due to each of the two different underlying genetic diseases; (B) two patients with overlapping clinical features that may be underpinned by both the identified genetic variations. Notably, only in one case a multilocus genomic variation was already suspected during the clinical evaluation. Overall, our findings highlight how dual molecular diagnoses represent a challenging model of complex inheritance that should always be considered whenever a patient shows atypical clinical features. Indeed, an accurate genetic characterisation is of the utmost importance to provide patients with a personalised and safe clinical management.

Phenotypic Spectrum and Prognosis of Epilepsy Patients With GABRG2 Variants

OBJECTIVE

This study aimed to obtain a comprehensive understanding of the genetic and phenotypic aspects of GABRG2-related epilepsy and its prognosis and to explore the potential prospects for personalized medicine.

METHODS

Through a multicenter collaboration in China, we analyzed the genotype-phenotype correlation and antiseizure medication (ASM) of patients with GABRG2-related epilepsy. The three-dimensional protein structure of the GABRG2 variant was modeled to predict the effect of GABRG2 missense variants using PyMOL 2.3 software.

RESULTS

In 35 patients with GABRG2 variants, 22 variants were de novo, and 18 variants were novel. The seizure onset age was ranged from 2 days after birth to 34 months (median age: 9 months). The seizure onset age was less than 1 year old in 22 patients (22/35, 62.9%). Seizure types included focal seizures (68.6%), generalized tonic-clonic seizures (60%), myoclonic seizures (14.3%), and absence seizures (11.4%). Other clinical features included fever-sensitive seizures (91.4%), cluster seizures (57.1%), and developmental delay (45.7%). Neuroimaging was abnormal in 2 patients, including dysplasia of the frontotemporal cortex and delayed myelination of white matter. Twelve patients were diagnosed with febrile seizures plus, eleven with epilepsy and developmental delay, two with Dravet syndrome, two with developmental and epileptic encephalopathy, two with focal epilepsy, two with febrile seizures, and four with unclassified epilepsy. The proportions of patients with missense variants in the extracellular region and the transmembrane region exhibiting developmental delay were 40% and 63.2%, respectively. The last follow-up age ranged from 11 months to 17 years. Seizures were controlled in 71.4% of patients, and 92% of their seizures were controlled by valproate and/or levetiracetam.

CONCLUSION

The clinical features of GABRG2-related epilepsy included seizure onset, usually in infancy, and seizures were fever-sensitive. More than half of the patients had cluster seizures. Phenotypes of GABRG2-related epilepsy were ranged from mild febrile seizures to severe epileptic encephalopathies. Most patients with GABRG2 variants who experienced seizures had a good prognosis. Valproate and levetiracetam were effective treatments for most patients.

Next-generation sequencing in childhood-onset epilepsies: Diagnostic yield and impact on neuronal ceroid lipofuscinosis type 2 (CLN2) disease diagnosis

Epilepsy is one of the most common childhood-onset neurological conditions with a genetic etiology. Genetic diagnosis provides potential for etiologically-based management and treatment. Existing research has focused on early-onset (<24 months) epilepsies; data regarding later-onset epilepsies is limited. The goal of this study was to determine the diagnostic yield of a clinically available epilepsy panel in a selected pediatric epilepsy cohort with epilepsy onset between 24-60 months of life and evaluate whether this approach decreases the age of diagnosis of neuronal ceroid lipofuscinosis type 2 (CLN2). Next-generation sequencing (NGS)-based epilepsy panels, including genes associated with epileptic encephalopathies and inborn errors of metabolism (IEMs) that present with epilepsy, were used. Copy-number variant (CNV) detection from NGS data was included. Variant interpretation was performed per American College of Medical Genetics and Genomics (ACMG) guidelines. Results are reported from 211 consecutive patients with the following inclusion criteria: 24-60 months of age at the time of enrollment, first unprovoked seizure at/after 24 months, and at least one additional finding such as EEG/MRI abnormalities, speech delay, or motor symptoms. Median age was 42 months at testing and 30 months at first seizure onset; the mean delay from first seizure to comprehensive genetic testing was 10.3 months. A genetic diagnosis was established in 43 patients (20.4%). CNVs were reported in 25.6% diagnosed patients; 27.3% of CNVs identified were intragenic. Within the diagnosed cohort, 11 (25.6%) patients were diagnosed with an IEM. The predominant molecular diagnosis was CLN2 (14% of diagnosed patients). For these patients, diagnosis was achieved 12-24 months earlier than reported by natural history of the disease. This study supports comprehensive genetic testing for patients whose first seizure occurs ≥ 24 months of age. It also supports early application of testing in this age group, as the identified diagnoses can have significant impact on patient management and outcome.

CBG Montevideo: A Clinically Novel SERPINA6 Mutation Leading to Haploinsufficiency of Corticosteroid-binding Globulin

Corticosteroid-binding globulin (CBG) is the main transport protein for cortisol, binding up to 90% in a 1:1 ratio. CBG provides transport of cortisol within the circulation and targeted cortisol tissue delivery.

Here, we describe the clinically novel “CBG Montevideo” a SERPINA6 pathogenic variant that results in a 50% reduction in plasma CBG levels. This was associated with low serum total cortisol and clinical features of hypoglycemia, exercise intolerance, chronic fatigue, and hypotension in the proband, a 7-year-old boy, and his affected mother.

Previous reports of 9 human CBG genetic variants affecting either CBG concentrations or reduced CBG-cortisol binding properties have outlined symptoms consistent with attenuated features of hypocortisolism, fatigue, and hypotension. Here, however, the presence of hypoglycemia, despite normal circulating free cortisol, suggests a specific role for CBG in effecting glucocorticoid function, perhaps involving cortisol-mediated hepatic glucose homeostasis and cortisol-brain communication.

Genetic Diagnosis in Children with Epilepsy and Developmental Disorders by Targeted Gene Panel Analysis in a Developing Country

Background and Purpose

In childhood epilepsy, genetic etiology is increasingly recognized in recent years with the advent of next generation sequencing. This has broadened the scope of precision medicine in intractable epilepsy, particularly epileptic encephalopathy (EE). Developmental disorder (DD) is an integral part of childhood uncontrolled epilepsy. This study was performed to investigate the genetic etiology of childhood epilepsy and DD.

Methods

In this study, 40 children with epilepsy and DD with positive genetic mutation were included retrospectively. It was done in a tertiary care referral hospital of Bangladesh from January 2019 to December 2020. Genetic study was done by next generation sequencing. In all cases electroencephalography, neuroimaging was done and reviewed.

Results

In total, 40 children were enrolled and the average age was 41.4±35.850 months with a male predominance (67.5%). Generalized seizure was the predominant type of seizure. Regarding the association, intellectual disability and attention deficit hyperactivity disorder was common. Seventeen cases had genetically identified early infantile EE and common mutations observed were SCN1A (3), SCN8A (2), SLC1A2 (2), KCNT1 (2), and etc. Five patients of progressive myoclonic epilepsy were diagnosed and the mutations identified were in KCTD7, MFSD8, and CLN6 genes. Three cases had mitochondrial gene mutation (MT-ND5, MT-CYB). Some rare syndromes like Gibbs syndrome, Kohlschütter-Tönz syndrome, Cockayne syndrome, Pitt-Hopkins syndrome and cerebral creatine deficiency were diagnosed.

Conclusions

This is the first study from Bangladesh on genetics of epilepsy and DD. This will help to improve the understanding of genetics epilepsy of this region as well as contribute in administering precision medicine in these patients.

Whole genome sequencing reveals a frameshift mutation and a large deletion in YY1AP1 in a girl with a panvascular artery disease

Background

Rare diseases are pathologies that affect less than 1 in 2000 people. They are difficult to diagnose due to their low frequency and their often highly heterogeneous symptoms. Rare diseases have in general a high impact on the quality of life and life expectancy of patients, which are in general children or young people. The advent of high-throughput sequencing techniques has improved diagnosis in several different areas, from pediatrics, achieving a diagnostic rate of 41% with whole genome sequencing (WGS) and 36% with whole exome sequencing, to neurology, achieving a diagnostic rate between 47 and 48.5% with WGS. This evidence has encouraged our group to pursue a molecular diagnosis using WGS for this and several other patients with rare diseases.

Results

We used whole genome sequencing to achieve a molecular diagnosis of a 7-year-old girl with a severe panvascular artery disease that remained for several years undiagnosed. We found a frameshift variant in one copy and a large deletion involving two exons in the other copy of a gene called YY1AP1. This gene is related to Grange syndrome, a recessive rare disease, whose symptoms include stenosis or occlusion of multiple arteries, congenital heart defects, brachydactyly, syndactyly, bone fragility, and learning disabilities. Bioinformatic analyses propose these mutations as the most likely cause of the disease, according to its frequency, in silico predictors, conservation analyses, and effect on the protein product. Additionally, we confirmed one mutation in each parent, supporting a compound heterozygous status in the child.

Conclusions

In general, we think that this finding can contribute to the use of whole genome sequencing as a diagnosis tool of rare diseases, and in particular, it can enhance the set of known mutations associated with different diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00328-1.

Genetic analysis of genes associated with epilepsy

Background and aim:

Epilepsy is a neurological disorder in which the altered activity of neurons causes convulsions, periods of unusual behavior and, sometimes, loss of consciousness. The aim of this mini-review is to summarize all the syndromes characterized by epilepsy and for which the associated gene is known.

Methods:

We searched those syndromes in PubMed and OMIM database.

Results:

Genetic causes underlie epilepsy in about 40% of individuals. Epilepsies are phenotypically and genetically heterogeneous. Inheritance can be autosomal dominant or recessive or X-linked recessive/dominant.

Conclusion:

Since epilepsy has high genetic heterogeneity, in diagnostics, the parallel sequencing of a panel of genes may speed up the determination of the molecular etiology and/or establish a risk of recurrence in family members for the purpose of planning appropriate preventive and/or therapeutic measures. (www.actabiomedica.it)

Determining the best candidates for next-generation sequencing-based gene panel for evaluation of early-onset epilepsy

Background

Genetic testing is an emerging diagnostic approach in early‐onset epilepsy. Identification of the heterogeneous genetic causes of epilepsy may mitigate unnecessary evaluations and allow more accurate diagnosis and therapy. We aimed to uncover genetic causes of early‐onset epilepsy using next‐generation sequencing (NGS) to elucidate the diagnostic candidates and evaluate the diagnostic yield of targeted gene panel testing.

Methods

We evaluated 116 patients with early‐onset epilepsy developed before 2 years old and normal brain imaging using a NGS‐based targeted gene panel. Variants were classified according to their pathogenicity, and the diagnostic yield of the targeted genes and associated clinical factors were determined.

Results

We detected 40 disease‐causing variants with diagnostic yield of 34.5% (19 pathogenic, 21 likely pathogenic). Twelve variants were novel. The most commonly detected genes were SCN1A, associated with Dravet syndrome, and PRRT2, associated with benign familial infantile epilepsy. Other variants were identified in ARX, SCN2A, KCNQ2, PCDH19, STXBP1, DEPDC5, and SCN8A. The age of seizure onset and family history were associated with disease‐causing variants.

Conclusion

Next‐generation sequencing‐based targeted testing is an effective diagnostic test, with 30%–40% comparable diagnostic yield. Patients with earlier seizure onset and family history of epilepsy were the best candidates for testing. For pediatric patients with early‐onset epilepsy, genetic diagnosis is important for accurate prognosis and treatment.

Epilepsy and developmental disorders: Next generation sequencing in the clinic

BACKGROUND

The advent of Next Generation Sequencing (NGS) has led to a redefining of the genetic landscape of the epilepsies. Hundreds of single gene epilepsies have been described. Genes associated with epilepsy involve diverse processes. Now a substantial proportion of individuals with epilepsy can receive a high definition molecular genetic diagnosis.

METHODS

In this review we update the current genetic landscape of the epilepsies and categorise the major functional groupings of epilepsy-associated genes. We describe currently available genetic testing approaches. We perform a literature review of NGS studies and review the factors which determine yield in cohorts undergoing testing. We identify factors associated with positive genetic diagnosis and consider the utility of genetic testing in terms of treatment selection as well as more qualitative aspects of care.

FINDINGS

Epilepsy-associated genes can be grouped into five broad functional categories: ion transport; cell growth and differentiation; regulation of synaptic processes; transport and metabolism of small molecules within and between cells; and regulation of gene transcription and translation. Early onset of seizures, drug-resistance, and developmental comorbidity are associated with higher diagnostic yield. The most commonly implicated genes in NGS studies to date, in order, are SCN1A, KCNQ2, CDKL5, SCN2A, and STXBP1. In unselected infantile cohorts PRRT2, a gene associated with self-limited epilepsy, is frequently implicated. Genetic diagnosis provides utility in terms of treatment choice closing the diagnostic odyssey, avoiding unnecessary further testing, and informing future reproductive decisions.

CONCLUSIONS

Genetic testing has become a first line test in epilepsy. As techniques improve and understanding advances, its utility is set to increase. Genetic diagnosis, particularly in early onset developmental and epileptic encephalopathies, influences treatment choice in a significant proportion of patients. The realistic prospect of gene therapy is a cause for optimism.

Genetic characteristics of non-familial epilepsy

Background

Knowledge of the genetic etiology of epilepsy can provide essential prognostic information and influence decisions regarding treatment and management, leading us into the era of precision medicine. However, the genetic basis underlying epileptogenesis or epilepsy pharmacoresistance is not well-understood, particularly in non-familial epilepsies with heterogeneous phenotypes that last until or start in adulthood.

Methods

We sought to determine the contribution of known epilepsy-associated genes (EAGs) to the causation of non-familial epilepsies with heterogeneous phenotypes and to the genetic basis underlying epilepsy pharmacoresistance. We performed a multi-center study for whole exome sequencing-based screening of 178 selected EAGs in 243 non-familial adult patients with primarily focal epilepsy (122 drug-resistant and 121 drug-responsive epilepsies). The pathogenicity of each variant was assessed through a customized stringent filtering process and classified according to the American College of Medical Genetics and Genomics guidelines.

Results

Possible causal genetic variants of epilepsy were uncovered in 13.2% of non-familial patients with primarily focal epilepsy. The diagnostic yield according to the seizure onset age was 25% (2/8) in the neonatal and infantile period, 11.1% (14/126) in childhood and 14.7% (16/109) in adulthood. The higher diagnostic yields were from ion channel-related genes and mTOR pathway-related genes, which does not significantly differ from the results of previous studies on familial or early-onset epilepsies. These potentially pathogenic variants, which were identified in genes that have been mainly associated with early-onset epilepsies with severe phenotypes, were also linked to epilepsies that start in or last until adulthood in this study. This finding suggested the presence of one or more disease-modifying factors that regulate the onset time or severity of epileptogenesis. The target hypothesis of epilepsy pharmacoresistance was not verified in our study. Instead, neurodevelopment-associated epilepsy genes, such as TSC2 or RELN, or structural brain lesions were more strongly associated with epilepsy pharmacoresistance.

Conclusions

We revealed a fraction of possible causal genetic variants of non-familial epilepsies in which genetic testing is usually overlooked. In this study, we highlight the importance of earlier identification of the genetic etiology of non-familial epilepsies, which leads us to the best treatment options in terms of precision medicine and to future neurobiological research for novel drug development. This should be considered a justification for physicians determining the hidden genetics of non-familial epilepsies that last until or start in adulthood.

Customized multigene panels in epilepsy: the best things come in small packages

Over the past 10 years, the increasingly important role played by next-generation sequencing panels in the genetic diagnosis of epilepsy has led to a growing list of gene variants and a plethora of new scientific data. To date, however, there is still no consensus on what constitutes the "ideal panel design," or on the most rational criteria for selecting the best candidates for gene-panel analysis, even though both might optimize the cost-benefit ratio and the diagnostic efficiency of customized gene panels. Even though more and more laboratories are adopting whole-exome sequencing as a first-tier diagnostic approach, interpreting, "in silico," a set of epilepsy-related genes remains difficult. In the light of these considerations, we performed a systematic review of the targeted gene panels for epilepsy already reported in the available scientific literature, with a view to identifying the best criteria for selecting patients for gene-panel analysis, and the best way to design an "ideal," gold-standard panel that includes all genes with an established role in epilepsy pathogenesis, as well as those that might help to guide decisions regarding specific medical interventions and treatments. Our analyses suggest that the usefulness and diagnostic power of customized gene panels for epilepsy may be greatest when these panels are confined to rationally selected, relatively small, pools of genes, and applied in more carefully selected epilepsy patients (those with complex forms of epilepsy). A panel containing 64 genes, which includes the 45 genes harboring a significant number of pathogenic variants identified in previous literature, the 32 clinically actionable genes, and the 21 ILAE (International League Against Epilepsy) recommended genes, may represent an "ideal" core set likely able to provide the highest diagnostic efficiency and cost-effectiveness and facilitate gene prioritization when testing patients with whole-exome/whole-genome sequencing.

Diagnostik genetisch bedingter Epilepsien

Je nach Anfallssemiologie und EEG-Befund werden Epilepsien klinisch zumeist in fokale bzw. generalisierte Formen unterteilt. Tritt bei einem Kind infolge einer Epilepsie zusätzlich eine Entwicklungsstörung auf, kann dies oft auf eine epileptische Enzephalopathie zurückgeführt werden. Das Mutationsspektrum genetischer Epilepsien ist ausgesprochen heterogen und kann am besten mithilfe der Hochdurchsatzsequenzierung erfasst werden. Insbesondere bei den Enzephalopathien besteht eine hohe Aufklärungsrate. Mittlerweile gibt es für diverse genetisch bedingte Epilepsieerkrankungen individualisierte Therapien, die auf den jeweiligen molekularen Pathomechanismus abzielen, und die Zahl solcher personalisierter Therapieoptionen steigt stetig.

Diagnostic Yield of Epilepsy Panel Testing in Patients With Seizure Onset Within the First Year of Life

Purpose: We aimed to evaluate the diagnostic yield of epilepsy gene panel testing in epilepsy patients whose seizures began within the first year after birth. We included 112 patients with seizure onset before 12 months and no known etiology.

Methods: Deep targeted sequencing with a custom-designed capture probe was performed to ensure the detection of germline or mosaic sequence variants and copy number variations (CNVs).

Results: We identified pathogenic or likely pathogenic variants in 53 patients (47.3%, 53/112), including five with pathogenic CNVs. Two putative pathogenic mosaic variants in SCN8A and KCNQ2 were also detected and validated. Those with neonatal onset (61.5%, 16/26) or early infantile onset (50.0%, 29/58) showed higher diagnostic rates than those with late infantile onset (28.5%, 8/28). The diagnostic rate was similar between patients with a specific syndrome (51.9%, 27/52) and those with no recognizable syndrome (43.3%, 26/60).

Conclusion: Epilepsy gene panel testing identified a genetic cause in nearly half of the infantile onset epilepsy patients. Since the phenotypic spectrum is expanding and characterizing it at seizure onset is difficult, this group should be prioritized for epilepsy gene panel testing.

Diagnostic Yield and Treatment Impact of Targeted Exome Sequencing in Early-Onset Epilepsy

Targeted whole-exome sequencing (WES) is a powerful diagnostic tool for a broad spectrum of heterogeneous neurological disorders. Here, we aim to examine the impact on diagnosis, treatment and cost with early use of targeted WES in early-onset epilepsy. WES was performed on 180 patients with early-onset epilepsy (≤5 years) of unknown cause. Patients were classified as Retrospective (epilepsy diagnosis >6 months) or Prospective (epilepsy diagnosis <6 months). WES was performed on an Ion Proton™ and variant reporting was restricted to the sequences of 620 known epilepsy genes. Diagnostic yield and time to diagnosis were calculated. An analysis of cost and impact on treatment was also performed. A molecular diagnoses (pathogenic/likely pathogenic variants) was achieved in 59/180 patients (33%). Clinical management changed following WES findings in 23 of 59 diagnosed patients (39%) or 13% of all patients. A possible diagnosis was identified in 21 additional patients (12%) for whom supporting evidence is pending. Time from epilepsy onset to a genetic diagnosis was faster when WES was performed early in the diagnostic process (mean: 145 days Prospective vs. 2,882 days Retrospective). Costs of prior negative tests averaged $8,344 per patient in the Retrospective group, suggesting savings of $5,110 per patient using WES. These results highlight the diagnostic yield, clinical utility and potential cost-effectiveness of using targeted WES early in the diagnostic workup of patients with unexplained early-onset epilepsy. The costs and clinical benefits are likely to continue to improve. Advances in precision medicine and further studies regarding impact on long-term clinical outcome will be important.

Biallelic SCN2A Gene Mutation Causing Early Infantile Epileptic Encephalopathy: Case Report and Review

The voltage-gated sodium channel neuronal type 2 alpha subunit (Na_vα1.2) encoded by the SCN2A gene causes early infantile epileptic encephalopathy (EIEE) inherited in an autosomal dominant manner. Clinically, it has variable presentations, ranging from benign familial infantile seizures (BFIS) to severe EIEE. Diagnosis is achieved through molecular DNA testing of the SCN2A gene. Herein, we report on a 30-month-old Saudi girl who presented on the fourth day of life with EIEE, normal brain magnetic resonance imaging (MRI), normal electroencephalography (EEG), and well-controlled seizures. Genetic investigation revealed a novel homozygous missense mutation (c.5242A > G; p.Asn1748Asp) in the SCN2A gene (NM_001040142.1). This is the first reported autosomal recessive inheritance of a disease allele in the SCN2A and therefore expands the molecular and inheritance spectrum of the SCN2A gene defects.

Precision in pediatric epilepsy

Epilepsy in infants and children is one of the most common and devastating neurological disorders. In the past, we had a limited understanding of the causes of epilepsy in pediatric patients, so we treated pediatric epilepsy according to seizure type. Now with new tools and tests, we are entering the age of precision medicine in pediatric epilepsy. In this review, we use the new etiological classification system proposed by the International League Against Epilepsy to review the advances in the diagnosis of pediatric epilepsy, describe new tools to identify seizure foci for epilepsy surgery, and define treatable epilepsy syndromes.

Diagnostic yield of genetic tests in epilepsy: A meta-analysis and cost-effectiveness study

OBJECTIVE

To compare the cost-effectiveness of genetic testing strategies in patients with epilepsy of unknown etiology.

METHODS

This meta-analysis and cost-effectiveness study compared strategies involving 3 genetic tests: chromosomal microarray (CMA), epilepsy panel (EP) with deletion/duplication testing, and whole-exome sequencing (WES) in a cost-effectiveness model, using "no genetic testing" as a point of comparison.

RESULTS

Twenty studies provided information on the diagnostic yield of CMA (8 studies), EP (9 studies), and WES (6 studies). The diagnostic yield was highest for WES: 0.45 (95% confidence interval [CI]: 0.33-0.57) (0.32 [95% CI: 0.22-0.44] adjusting for potential publication bias), followed by EP: 0.23 (95% CI: 0.18-0.29), and CMA: 0.08 (95% CI: 0.06-0.12). The most cost-effective test was WES with an incremental cost-effectiveness ratio (ICER) of $15,000/diagnosis. However, after adjusting for potential publication bias, the most cost-effective test was EP (ICER: $15,848/diagnosis) followed by WES (ICER: $34,500/diagnosis). Among combination strategies, the most cost-effective strategy was WES, then if nondiagnostic, EP, then if nondiagnostic, CMA (ICER: $15,336/diagnosis), although adjusting for potential publication bias, the most cost-effective strategy was EP ± CMA ± WES (ICER: $18,385/diagnosis). While the cost-effectiveness of individual tests and testing strategies overlapped, CMA was consistently less cost-effective than WES and EP.

CONCLUSION

WES and EP are the most cost-effective genetic tests for epilepsy. Our analyses support, for a broad population of patients with unexplained epilepsy, starting with these tests. Although less expensive, CMA has lower yield, and its use as the first-tier test is thus not supported from a cost-effectiveness perspective.

A mutation update for the PCDH19 gene causing early-onset epilepsy in females with an unusual expression pattern

The PCDH19 gene consists of six exons encoding a 1,148 amino acid transmembrane protein, Protocadherin 19, which is involved in brain development. Heterozygous pathogenic variants in this gene are inherited in an unusual X-linked dominant pattern in which heterozygous females are affected, while hemizygous males are typically unaffected, although they pass on the pathogenic variant to each affected daughter. PCDH19-related disorder is known to cause early-onset epilepsy in females characterized by seizure clusters exacerbated by fever and in most cases, onset is within the first year of life. This condition was initially described in 1971 and in 2008 PCDH19 was identified as the underlying genetic etiology. This condition is the result of pathogenic loss-of-function variants that may be de novo or inherited from an affected mother or unaffected father and cellular interference has been hypothesized to be the culprit. Heterozygous females are symptomatic because of the presence of both wild-type and mutant cells that interfere with one another due to the production of different surface proteins, whereas nonmosaic hemizygous males produce a homogenous population of cells. Here, we review novel pathogenic variants in the PCDH19 gene since 2012 to date, and summarize any genotype-phenotype correlations.

Contemporary scope of inborn errors of metabolism involving epilepsy or seizures

Many inborn errors of metabolism may present with epilepsy or seizures, however, current scope of these diseases is unknown. Due to available precision medicine approaches in many inborn errors of metabolism and sophisticated traditional diagnostics, this group of disorders is of special relevance to clinicians. Besides, as current treatment is challenging and unsuccessful in more than 30% of all epilepsy patients, these diseases may provide valuable models for ictogenesis and epileptogenesis studies and potentially pave the ways to identification of novel treatments. The aim of this study was to elucidate genetic architecture of inborn errors of metabolism involving epilepsy or seizures and to evaluate their diagnostic approaches. After extensive search, 880 human genes were identified with a considerable part, 373 genes (42%), associated with inborn errors of metabolism. The most numerous group comprised disorders of energy metabolism (115, 31% of all inborn errors of metabolism). A substantial number of these diseases (26%, 97/373) have established specific treatments, therefore timely diagnosis comes as an obligation. Highly heterogenous, overlapping and non-specific phenotypes in most of inborn errors of metabolism presenting with epilepsy or seizures usually preclude phenotype-driven diagnostics. Besides, as traditional diagnostics involves a range of specialized metabolic tests with low diagnostic yields and is generally inefficient and lengthy, next-generation sequencing-based methods were proposed as a cost-efficient one-step way to shorten "diagnostic odyssey". Extensive list of 373 epilepsy- or seizures-associated inborn errors of metabolism genes may be of value in development of gene panels and as a tool for variants' filtration.

γ2 GABAAR Trafficking and the Consequences of Human Genetic Variation

GABA type A receptors (GABA_ARs) mediate the majority of fast inhibitory neurotransmission in the central nervous system (CNS). Most prevalent as heteropentamers composed of two α, two β, and a γ2 subunit, these ligand-gated ionotropic chloride channels are capable of extensive genetic diversity (α1-6, β1-3, γ1-3, δ, 𝜀, 𝜃, π, ρ1-3). Part of this selective GABA_AR assembly arises from the critical role for γ2 in maintaining synaptic receptor localization and function. Accordingly, mutations in this subunit account for over half of the known epilepsy-associated genetic anomalies identified in GABA_ARs. Fundamental structure-function studies and cellular pathology investigations have revealed dynamic GABA_AR trafficking and synaptic scaffolding as critical regulators of GABAergic inhibition. Here, we introduce in vitro and in vivo findings regarding the specific role of the γ2 subunit in receptor trafficking. We then examine γ2 subunit human genetic variation and assess disease related phenotypes and the potential role of altered GABA_AR trafficking. Finally, we discuss new-age imaging techniques and their potential to provide novel insight into critical regulatory mechanisms of GABA_AR function.

Molecular Genetic Characterization of Patients With Focal Epilepsy Using a Customized Targeted Resequencing Gene Panel

Objective: Focal epilepsy is the most common subtype of epilepsies in which the influence of underlying genetic factors is emerging but remains largely uncharacterized. The purpose of this study is to determine the contribution of currently known disease-causing genes in a large cohort (n = 593) of common focal non-lesional epilepsy patients.

Methods: The customized focal epilepsy gene panel (21 genes) was based on multiplex polymerase chain reaction (PCR) and sequenced by Illumina MiSeq platform.

Results: Eleven variants (1.85%) were considered as pathogenic or likely pathogenic, including seven novel mutations. There were three SCN1A (p.Leu890Pro, p.Arg1636Ter, and p.Met1714Val), three PRRT2 (two p.Arg217Profs^*8 and p.Leu298Pro), two CHRNA4 (p.Ser284Leu, p.Ile321Asn), one DEPDC5 (p.Val516Ter), one PCDH19 (p.Asp233Asn), and one SLC2A1 (p.Ser414Ter) variants. Additionally, 16 other rare variants were classified as unknown significance due to inconsistent phenotype or lack of segregation data.

Conclusion: Currently known focal epilepsy genes only explained a very small subset of focal epilepsy patients. This indicates that the underlying genetic architecture of focal epilepsies is very heterogeneous and more novel genes are likely to be discovered. Our study highlights the usefulness, challenges and limitations of using the multi-gene panel as a diagnostic test in routine clinical practice in patients with focal epilepsy.

Incorporating epilepsy genetics into clinical practice: a 360°evaluation

We evaluated a new epilepsy genetic diagnostic and counseling service covering a UK population of 3.5 million. We calculated diagnostic yield, estimated clinical impact, and surveyed referring clinicians and families. We costed alternative investigational pathways for neonatal onset epilepsy. Patients with epilepsy of unknown aetiology onset < 2 years; treatment resistant epilepsy; or familial epilepsy were referred for counseling and testing. We developed NGS panels, performing clinical interpretation with a multidisciplinary team. We held an educational workshop for paediatricians and nurses. We sent questionnaires to referring paediatricians and families. We analysed investigation costs for 16 neonatal epilepsy patients. Of 96 patients, a genetic diagnosis was made in 34% of patients with seizure onset < 2 years, and 4% > 2 years, with turnaround time of 21 days. Pathogenic variants were seen in SCN8A, SCN2A, SCN1A, KCNQ2, HNRNPU, GRIN2A, SYNGAP1, STXBP1, STX1B, CDKL5, CHRNA4, PCDH19 and PIGT. Clinician prediction was poor. Clinicians and families rated the service highly. In neonates, the cost of investigations could be reduced from £9362 to £2838 by performing gene panel earlier and the median diagnostic delay of 3.43 years reduced to 21 days. Panel testing for epilepsy has a high yield among children with onset < 2 years, and an appreciable clinical and financial impact. Parallel gene testing supersedes single gene testing in most early onset cases that do not show a clear genotype-phenotype correlation. Clinical interpretation of laboratory results, and in-depth discussion of implications for patients and their families, necessitate multidisciplinary input and skilled genetic counseling.

Screening for epilepsy-related gene variants can lead to effective, personalized treatment plans while reducing costs. UK and Danish scientists, led by Deb Pal, King’s College London, evaluated a new service within the UK that searches for genetic variants in patients that cause epilepsy. The authors assessed the impact of next-generation gene panel tests, as well as the necessary resources to make such a service effective. Genetic testing was most effective in patients with seizure onset under 2 years old (21% diagnosed) and yield even higher in neonatal-onset epilepsy (63% diagnosed). For many patients with pathogenic variants, the diagnoses allowed for recommendations on treatment or enrolment in clinical trials. The researchers found that diagnostic delay and financial burden in neonatal epilepsy could be drastically reduced with gene panel testing. The scheme was highly rated by users and patients alike.

Next Generation Sequencing Methods for Diagnosis of Epilepsy Syndromes

Epilepsy is a neurological disorder characterized by an increased predisposition for seizures. Although this definition suggests that it is a single disorder, epilepsy encompasses a group of disorders with diverse aetiologies and outcomes. A genetic basis for epilepsy syndromes has been postulated for several decades, with several mutations in specific genes identified that have increased our understanding of the genetic influence on epilepsies. With 70-80% of epilepsy cases identified to have a genetic cause, there are now hundreds of genes identified to be associated with epilepsy syndromes which can be analyzed using next generation sequencing (NGS) techniques such as targeted gene panels, whole exome sequencing (WES) and whole genome sequencing (WGS). For effective use of these methodologies, diagnostic laboratories and clinicians require information on the relevant workflows including analysis and sequencing depth to understand the specific clinical application and diagnostic capabilities of these gene sequencing techniques. As epilepsy is a complex disorder, the differences associated with each technique influence the ability to form a diagnosis along with an accurate detection of the genetic etiology of the disorder. In addition, for diagnostic testing, an important parameter is the cost-effectiveness and the specific diagnostic outcome of each technique. Here, we review these commonly used NGS techniques to determine their suitability for application to epilepsy genetic diagnostic testing.

Efficient strategy for the molecular diagnosis of intractable early-onset epilepsy using targeted gene sequencing

Background

We intended to evaluate diagnostic utility of a targeted gene sequencing by using next generation sequencing (NGS) panel in patients with intractable early-onset epilepsy (EOE) and find the efficient analytical step for increasing the diagnosis rate.

Methods

We assessed 74 patients with EOE whose seizures started before 3 years of age using a customized NGS panel that included 172 genes. Single nucleotide variants (SNVs) and exonic and chromosomal copy number variations (CNVs) were intensively examined with our customized pipeline and crosschecked with commercial or pre-built software. Variants were filtered and prioritized by in-depth clinical review, and finally classified according to the American College of Medical Genetics and Genomics guidelines. Each case was further discussed in a monthly consensus meeting that included the participation of all laboratory personnel, bioinformaticians, geneticists, and clinicians.

Results

The NGS panel identified 28 patients (37.8%) with genetic abnormalities; 25 patients had pathogenic or likely pathogenic SNVs in 17 genes including SXTBP1 (n = 3), CDKL5 (n = 2), KCNQ2 (n = 2), SCN1A (n = 2), SYNGAP1 (n = 2), GNAO1 (n = 2), KCNT1 (n = 2), BRAT1, WWOX, ZEB2, CHD2, PRICKLE2, COL4A1, DNM1, SCN8A, MECP2, SLC9A6 (n = 1). The other 3 patients had pathogenic CNVs (2 duplications and 1 deletion) with varying sizes (from 2.5 Mb to 12 Mb). The overall diagnostic yield was 37.8% after following our step-by-step approach for clinical consensus.

Conclusions

NGS is a useful diagnostic tool with great utility for patients with EOE. Diagnostic yields can be maximized with a standardized and team-based approach.

Electronic supplementary material

The online version of this article (10.1186/s12920-018-0320-7) contains supplementary material, which is available to authorized users.

The NIH NeuroBioBank: creating opportunities for human brain research

The National Institutes of Health (NIH) NeuroBioBank is a federally funded research resource for human neurologic diseases and disorders. This chapter will discuss the principles that guided the creation of the NIH NeuroBioBank and the rationale for the resource model selected. In addition, we will describe some performance metrics in the first 2 years and highlight recent advances in biomedical neuroscience that could only have been achieved using postmortem human tissues. The NIH NeuroBioBank was created in order to increase availability of high-quality postmortem human brain tissues to the research community across a broad spectrum of neurologic diseases and disorders, and to achieve economies of scale over previous funding and organizational models. In addition, we aim to increase public awareness about the value of human tissue donation for research by providing web-based information to the public and through active outreach to disease advocacy communities. Studies with human brain tissue have led to a rapid increase in our knowledge of the biologic differences between humans and are bridging the divide between humans and model organisms. Studies of human brain are beginning to give us a glimpse not only into what makes us uniquely human as well as how individual biology may be connected to health and disease.

Molecular diagnosis of patients with epilepsy and developmental delay using a customized panel of epilepsy genes

Pediatric epilepsies are a group of disorders with a broad phenotypic spectrum that are associated with great genetic heterogeneity, thus making sequential single-gene testing an impractical basis for diagnostic strategy. The advent of next-generation sequencing has increased the success rate of epilepsy diagnosis, and targeted resequencing using genetic panels is the a most cost-effective choice. We report the results found in a group of 87 patients with epilepsy and developmental delay using targeted next generation sequencing (custom-designed Haloplex panel). Using this gene panel, we were able to identify disease-causing variants in 17 out of 87 (19.5%) analyzed patients, all found in known epilepsy-associated genes (KCNQ2, CDKL5, STXBP1, SCN1A, PCDH19, POLG, SLC2A1, ARX, ALG13, CHD2, SYNGAP1, and GRIN1). Twelve of 18 variants arose de novo and 6 were novel. The highest yield was found in patients with onset in the first years of life, especially in patients classified as having early-onset epileptic encephalopathy. Knowledge of the underlying genetic cause provides essential information on prognosis and could be used to avoid unnecessary studies, which may result in a greater diagnostic cost-effectiveness.

Genetic Variants Identified from Epilepsy of Unknown Etiology in Chinese Children by Targeted Exome Sequencing

Genetic factors play a major role in the etiology of epilepsy disorders. Recent genomics studies using next generation sequencing (NGS) technique have identified a large number of genetic variants including copy number (CNV) and single nucleotide variant (SNV) in a small set of genes from individuals with epilepsy. These discoveries have contributed significantly to evaluate the etiology of epilepsy in clinic and lay the foundation to develop molecular specific treatment. However, the molecular basis for a majority of epilepsy patients remains elusive, and furthermore, most of these studies have been conducted in Caucasian children. Here we conducted a targeted exome-sequencing of 63 trios of Chinese epilepsy families using a custom-designed NGS panel that covers 412 known and candidate genes for epilepsy. We identified pathogenic and likely pathogenic variants in 15 of 63 (23.8%) families in known epilepsy genes including SCN1A, CDKL5, STXBP1, CHD2, SCN3A, SCN9A, TSC2, MBD5, POLG and EFHC1. More importantly, we identified likely pathologic variants in several novel candidate genes such as GABRE, MYH1, and CLCN6. Our results provide the evidence supporting the application of custom-designed NGS panel in clinic and indicate a conserved genetic susceptibility for epilepsy between Chinese and Caucasian children.

A Data Fusion Approach to Enhance Association Study in Epilepsy

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.

Epileptic Encephalopathy in Childhood: A Stepwise Approach for Identification of Underlying Genetic Causes

Epilepsy is one of the most common neurological disorders in childhood. Epilepsy associated with global developmental delay and cognitive dysfunction is defined as epileptic encephalopathy. Certain inherited metabolic disorders presenting with epileptic encephalopathy can be treated with disease specific diet, vitamin, amino acid or cofactor supplementations. In those disorders, disease specific therapy is successful to achieve good seizure control and improve long-term neurodevelopmental outcome. For this reason, intractable epilepsy with global developmental delay or history of developmental regression warrants detailed metabolic investigations for the possibility of an underlying treatable inherited metabolic disorder, which should be undertaken as first line investigations. An underlying genetic etiology in epileptic encephalopathy has been supported by recent studies such as array comparative genomic hybridization, targeted next generation sequencing panels, whole exome and whole genome sequencing. These studies report a diagnostic yield up to 70%, depending on the applied genetic testing as well as number of patients enrolled. In patients with epileptic encephalopathy, a stepwise approach for diagnostic work-up will help to diagnose treatable inherited metabolic disorders quickly. Application of detailed genetic investigations such as targeted next generation sequencing as second line and whole exome sequencing as third line testing will diagnose underlying genetic disease which will help for genetic counseling as well as guide for prenatal diagnosis. Knowledge of underlying genetic cause will provide novel insights into the pathogenesis of epileptic encephalopathy and pave the ground towards the development of targeted neuroprotective treatment strategies to improve the health outcome of children with epileptic encephalopathy.

Gene Panel Testing in Epileptic Encephalopathies and Familial Epilepsies

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.

Effect of dietary lysine restriction and arginine supplementation in two patients with pyridoxine-dependent epilepsy

Pyridoxine-Dependent Epilepsy (PDE) is a recessive disorder caused by deficiency of α-aminoadipic semialdehyde dehydrogenase in the catabolic pathway of lysine. It is characterized by intractable seizures controlled by the administration of pharmacological doses of vitamin B6. Despite seizure control with pyridoxine, intellectual disability and developmental delays are still observed in some patients with PDE, likely due to the accumulation of toxic intermediates in the lysine catabolic pathway: alpha-aminoadipic semialdehyde (AASA), delta-1-piperideine-6-carboxylate (P6C), and pipecolic acid. Here we evaluate biochemical and clinical parameters in two PDE patients treated with a lysine-restricted diet and arginine supplementation (100-150mg/kg), aimed at reducing the levels of PDE biomarkers. Lysine restriction resulted in decreased accumulation of PDE biomarkers and improved development. Plasma lysine but not plasma arginine, directly correlated with plasma levels of AASA-P6C (p<0.001, r(2)=0.640) and pipecolic acid (p<0.01, r(2)=0.484). In addition, plasma threonine strongly correlated with the levels of AASA-P6C (p<0.0001, r(2)=0.732) and pipecolic acid (p<0.005, r(2)=0.527), suggesting extreme sensitivity of threonine catabolism to pyridoxine availability. Our results further support the use of dietary therapies in combination with pyridoxine for the treatment of PDE.

Lessons learned from gene identification studies in Mendelian epilepsy disorders

Next-generation sequencing (NGS) technologies are now routinely used for gene identification in Mendelian disorders. Setting up cost-efficient NGS projects and managing the large amount of variants remains, however, a challenging job. Here we provide insights in the decision-making processes before and after the use of NGS in gene identification studies. Genetic factors are thought to have a role in ~70% of all epilepsies, and a variety of inheritance patterns have been described for seizure-associated gene defects. We therefore chose epilepsy as disease model and selected 35 NGS studies that focused on patients with a Mendelian epilepsy disorder. The strategies used for gene identification and their respective outcomes were reviewed. High-throughput NGS strategies have led to the identification of several new epilepsy-causing genes, enlarging our knowledge on both known and novel pathomechanisms. NGS findings have furthermore extended the awareness of phenotypical and genetic heterogeneity. By discussing recent studies we illustrate: (I) the power of NGS for gene identification in Mendelian disorders, (II) the accelerating pace in which this field evolves, and (III) the considerations that have to be made when performing NGS studies. Nonetheless, the enormous rise in gene discovery over the last decade, many patients and families included in gene identification studies still remain without a molecular diagnosis; hence, further genetic research is warranted. On the basis of successful NGS studies in epilepsy, we discuss general approaches to guide human geneticists and clinicians in setting up cost-efficient gene identification NGS studies.

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

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 late-onset 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.

PaPI: pseudo amino acid composition to score human protein-coding variants

Background

High throughput sequencing technologies are able to identify the whole genomic variation of an individual. Gene-targeted and whole-exome experiments are mainly focused on coding sequence variants related to a single or multiple nucleotides. The analysis of the biological significance of this multitude of genomic variant is challenging and computational demanding.

Results

We present PaPI, a new machine-learning approach to classify and score human coding variants by estimating the probability to damage their protein-related function. The novelty of this approach consists in using pseudo amino acid composition through which wild and mutated protein sequences are represented in a discrete model. A machine learning classifier has been trained on a set of known deleterious and benign coding variants with the aim to score unobserved variants by taking into account hidden sequence patterns in human genome potentially leading to diseases. We show how the combination of amphiphilic pseudo amino acid composition, evolutionary conservation and homologous proteins based methods outperforms several prediction algorithms and it is also able to score complex variants such as deletions, insertions and indels.

Conclusions

This paper describes a machine-learning approach to predict the deleteriousness of human coding variants. A freely available web application (http://papi.unipv.it) has been developed with the presented method, able to score up to thousands variants in a single run.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0554-8) contains supplementary material, which is available to authorized users.

Diagnostic yield of genetic testing in epileptic encephalopathy in childhood

OBJECTIVE

Epilepsy is a common neurologic disorder of childhood. To determine the genetic diagnostic yield in epileptic encephalopathy, we performed a retrospective cohort study in a single epilepsy genetics clinic.

METHODS

We included all patients with intractable epilepsy, global developmental delay, and cognitive dysfunction seen between January 2012 and June 2014 in the Epilepsy Genetics Clinic. Electronic patient charts were reviewed for clinical features, neuroimaging, biochemical investigations, and molecular genetic investigations including targeted next-generation sequencing of epileptic encephalopathy genes.

RESULTS

Genetic causes were identified in 28% of the 110 patients: 7% had inherited metabolic disorders including pyridoxine dependent epilepsy caused by ALDH7A1 mutation, Menkes disease, pyridox(am)ine-5-phosphate oxidase deficiency, cobalamin G deficiency, methylenetetrahydrofolate reductase deficiency, glucose transporter 1 deficiency, glycine encephalopathy, and pyruvate dehydrogenase complex deficiency; 21% had other genetic causes including genetic syndromes, pathogenic copy number variants on array comparative genomic hybridization, and epileptic encephalopathy related to mutations in the SCN1A, SCN2A, SCN8A, KCNQ2, STXBP1, PCDH19, and SLC9A6 genes. Forty-five percent of patients obtained a genetic diagnosis by targeted next-generation sequencing epileptic encephalopathy panels. It is notable that 4.5% of patients had a treatable inherited metabolic disease.

SIGNIFICANCE

To the best of our knowledge, this is the first study to combine inherited metabolic disorders and other genetic causes of epileptic encephalopathy. Targeted next-generation sequencing panels increased the genetic diagnostic yield from <10% to >25% in patients with epileptic encephalopathy.