Are SCN2A-related BFNISs also responsible for seizures in adulthood? A case report opens new scenarios.

Large cohort studies and variant-specific electrophysiology have enabled the delineation of different SCN2A-epilepsy phenotypes, phenotype-genotype correlations, prediction of pharmacosensitivity to sodium channel blockers, and long-term prognostication for clinicians and families. One of the most common clinical presentations of SCN2A pathological variants is benign familial neonatal-infantile seizures (BFNIS), which are characterized by seizure onset between the first day of life and 23 months of age and typically resolve, either spontaneously or with the aid of sodium channel blockers, within the first 2 years of life. In 2004, Berkovic et al. reported the case of a young boy affected by SCN2A-related BFNIS whose mother, who carried the same pathological variant, had also presented with BFNIS in infancy. Our case report focuses on the aforementioned woman who, more than 40 years later, presented two additional seizures, therefore opening the possibility of a role for SCN2A-related seizures in adulthood.

KCNQ2 mutations cause unique neonatal behavior arrests without motor seizures: Functional characterization.

OBJECTIVE: KCNQ2 gene mutation usually manifests as neonatal seizures in the first week of life. Nonsense mutations cause a unique self-limited familial neonatal epilepsy (SLFNE), which is radically different from developmental epileptic encephalopathy (DEE). However, the exact underlying mechanisms remain unclear. METHODS: The proband, along with their mother and grandmother, carried the c.1342C > T (p.Arg448Ter) mutation in the KCNQ2 gene. The clinical phenotypes, electroencephalography (EEG) findings, and neurodevelopmental outcomes were comprehensively surveyed. The mutant variants were transfected into HEK293 cells to investigate functional changes. RESULTS: The proband exhibited behavior arrests, autonomic and non-motor neonatal seizures with changes in heart rate and respiration. EEG exhibited focal sharp waves. Seizures were remitted after three months of age. The neurodevelopmental outcomes at three years of age were unremarkable. A functional study demonstrated that the currents of p.Arg448Ter were non-functional in homomeric p.Arg448Ter compared with that of the KCNQ2 wild type. However, the current density and V1/2 exhibited significant improvement and close to that of the wild-type after transfection with heteromeric KCNQ2 + p.Arg448Ter and KCNQ2 + KCNQ3 + p.Arg448Ter respectively. Channel expression on the cell membrane was not visible after homomeric transfection, but not after heteromeric transfection. Retigabine did not affect homomeric p.Arg448Ter but improved heteromeric p. Arg448Ter + KCNQ2 and heteromeric KCNQ2 + Arg448Ter + KCNQ3. CONCLUSIONS: The newborn carrying the p. Arg448Ter mutation presented frequent behavioral arrests, autonomic, and non-motor neonatal seizures. This unique pattern differs from KCNQ2 seizures, which typically manifest as motor seizures. Although p.Arg448Ter is a non-sense decay, the functional study demonstrated an almost-full compensation mechanism after transfection of heteromeric KCNQ2 and KCNQ3.

MLe-KCNQ2: An Artificial Intelligence Model for the Prognosis of Missense KCNQ2 Gene Variants.

Despite the increasing availability of genomic data and enhanced data analysis procedures, predicting the severity of associated diseases remains elusive in the absence of clinical descriptors. To address this challenge, we have focused on the KV7.2 voltage-gated potassium channel gene (KCNQ2), known for its link to developmental delays and various epilepsies, including self-limited benign familial neonatal epilepsy and epileptic encephalopathy. Genome-wide tools often exhibit a tendency to overestimate deleterious mutations, frequently overlooking tolerated variants, and lack the capacity to discriminate variant severity. This study introduces a novel approach by evaluating multiple machine learning (ML) protocols and descriptors. The combination of genomic information with a novel Variant Frequency Index (VFI) builds a robust foundation for constructing reliable gene-specific ML models. The ensemble model, MLe-KCNQ2, formed through logistic regression, support vector machine, random forest and gradient boosting algorithms, achieves specificity and sensitivity values surpassing 0.95 (AUC-ROC > 0.98). The ensemble MLe-KCNQ2 model also categorizes pathogenic mutations as benign or severe, with an area under the receiver operating characteristic curve (AUC-ROC) above 0.67. This study not only presents a transferable methodology for accurately classifying KCNQ2 missense variants, but also provides valuable insights for clinical counseling and aids in the determination of variant severity. The research context emphasizes the necessity of precise variant classification, especially for genes like KCNQ2, contributing to the broader understanding of gene-specific challenges in the field of genomic research. The MLe-KCNQ2 model stands as a promising tool for enhancing clinical decision making and prognosis in the realm of KCNQ2-related pathologies.

KCNQ2-Related Epilepsy: Genotype-Phenotype Relationship with Tailored Antiseizure Medication (ASM)-A Systematic Review.

BACKGROUND: Autosomal dominant mutations of the KCNQ2 gene can cause two epileptic disorders: benign familial neonatal seizures (BFNS) and developmental epileptic encephalopathy (DEE). This systematic review aims to identify the best reported therapy for these patients, relating to phenotype, neurodevelopmental outcome, and an eventual correlation between phenotype and genotype. METHODS: We searched on PubMed using the search terms "KCNQ2" AND "therapy" and "KCNQ2" AND "treatment"; we found 304 articles. Of these, 29 met our criteria. We collected the data from 194 patients. All 29 articles were retrospective studies. RESULTS: In all, 104 patients were classified as DEE and 90 as BFNS. After treatment began, 95% of BFNS patients became seizure free, whereas the seizures stopped only in 73% of those with DEE. Phenobarbital and sodium channel blockers were the most used treatment in BFNS. Most of the DEE patients (95%) needed polytherapy for seizure control and even that did not prevent subsequent developmental impairment (77%).Missense mutations were discovered in 96% of DEE patients; these were less common in BFNS (50%), followed by large deletion (16%), truncation (16%), splice donor site (10%), and frameshift (7%). CONCLUSION: Phenobarbital or carbamazepine appears to be the most effective antiseizure medication for children with a "benign" variant. On the contrary, polytherapy is often needed for DEE patients, even if it does not seem to improve neurological outcomes. In DEE patients, most mutations were located in S4 and S6 helix, which could serve as a potential target for the development of more specific treatment in the future.

PRRT2 benign familial infantile seizures (BFIS) with atypical evolution to encephalopathy related to status epilepticus during sleep (ESES).

PURPOSE: Heterozygous variants in PRRT2 are mostly associated with benign phenotypes, being the major genetic cause of benign familial infantile seizures (BFIS), as well as in paroxysmal disorders. We report two children from unrelated families with BFIS that evolved to encephalopathy related to status epilepticus during sleep (ESES). METHODS AND RESULTS: Two probands presented with focal motor seizures at 3 months of age, with a limited course. Both children presented, at around 5 years of age, with centro-temporal interictal epileptiform discharges with a source in the frontal operculum, markedly activated by sleep, and associated with stagnation on neuropsychological development. Whole-exome sequencing and co-segregation analysis revealed a frameshift mutation c.649dupC in the proline-rich transmembrane protein 2 (PRRT2) in both probands and all affected family members. CONCLUSION: The mechanism leading to epilepsy and the phenotypic variability of PRRT2 variants remain poorly understood. However, its wide cortical and subcortical expression, in particular in the thalamus, could partially explain both the focal EEG pattern and the evolution to ESES. No variants in the PRRT2 gene have been previously reported in patients with ESES. Due to the rarity of this phenotype, other possible causative cofactors are likely contributing to the more severe course of BFIS in our probands.

Temporal Changes in Cholangiocarcinoma Incidence and Mortality in the United States from 2001 to 2017.

BACKGROUND: Previous studies report increasing cholangiocarcinoma (CCA) incidence up to 2015. This contemporary retrospective analysis of CCA incidence and mortality in the US from 2001-2017 assessed whether CCA incidence continued to increase beyond 2015. PATIENTS AND METHODS: Patients (≥18 years) with CCA were identified in the National Cancer Institute Surveillance, Epidemiology, and End Results 18 cancer registry (International Classification of Disease for Oncology [ICD-O]-3 codes: intrahepatic [iCCA], C221; extrahepatic [eCCA], C240, C241, C249). Cancer of unknown primary (CUP) cases were identified (ICD-O-3: C809; 8140/2, 8140/3, 8141/3, 8143/3, 8147/3) because of potential misclassification as iCCA. RESULTS: Forty-thousand-and-thirty CCA cases (iCCA, n=13,174; eCCA, n=26,821; iCCA and eCCA, n=35) and 32,980 CUP cases were analyzed. From 2001-2017, CCA, iCCA, and eCCA incidence (per 100 000 person-years) increased 43.8% (3.08 to 4.43), 148.8% (0.80 to 1.99), and 7.5% (2.28 to 2.45), respectively. In contrast, CUP incidence decreased 54.4% (4.65 to 2.12). CCA incidence increased with age, with greatest increase among younger patients (18-44 years, 81.0%). Median overall survival from diagnosis was 8, 6, 9, and 2 months for CCA, iCCA, eCCA, and CUP. From 2001-2016, annual mortality rate declined for iCCA (57.1% to 41.2%) and generally remained stable for eCCA (40.9% to 37.0%) and for CUP (64.3% to 68.6%). CONCLUSIONS: CCA incidence continued to increase from 2001-2017, with greater increase in iCCA versus eCCA, whereas CUP incidence decreased. The divergent CUP versus iCCA incidence trends, with overall greater absolute change in iCCA incidence, provide evidence for a true increase in iCCA incidence that may not be wholly attributable to CUP reclassification.

TMEM151A phenotypic spectrum includes paroxysmal kinesigenic dyskinesia with infantile convulsions.

In a three-generation family, five individuals exhibited the typical phenotype of paroxysmal kinesigenic dyskinesia (PKD). Intriguingly, one of the individuals also showed benign familial infantile convulsions (BFIC) at age 4 months and spontaneously resolved at age 18 months. At age 12, she developed a typical PKD, and was gradually relieved at age 21. Therefore, the clinical phenotype was consistent with PKD with infantile convulsions (PKD/IC). Whole exome sequence and co-segregation analysis revealed a novel heterozygous variant c.1085A > G in the TMEM151A gene. Our study suggests that the TMEM151A gene may be associated with the disease spectrum of PKD-PKD/IC-BFIC.

[Clinical and genetic analysis of a Chinese pedigree affected with benign familial neonatal convulsion].

OBJECTIVE: To analyze the clinical phenotype and genetic variant in a Chinese pedigree affected with benign familial neonatal convulsion (BFNC). METHODS: Clinical data and peripheral blood samples of the pedigree were obtained with informed consent. Whole exome sequencing (WES) was carried out for the proband. Candidate variants were verified by Sanger sequencing. RESULTS: The pedigree comprised 9 individuals, among whom 4 were affected, including 3 males and 1 female. All patients had developed seizures during the neonatal period, which had ceased in 4 to 6 months. One patient had recurrence in between 1 and 2 years old. Genetic testing has identified a novel nonsense c.810G>A (p.W270X) variant in exon 5 of the KCNQ2 gene, which has co-separated with the BFNC phenotype in the pedigree. CONCLUSION: The patients from this pedigree have conformed to the diagnosis of BFNC with good prognosis, which was in keeping with previously reported cases. The heterozygous c.810G>A (p.W270X) nonsense variant of the KCNQ2 gene probably underlay the pathogenesis of BFNC in this pedigree, which has expanded the mutational spectrum of the disease.

Flexible Stoichiometry: Implications for KCNQ2- and KCNQ3-Associated Neurodevelopmental Disorders.

KCNQ2 and KCNQ3 pathogenic channel variants have been associated with a spectrum of developmentally regulated diseases that vary in age of onset, severity, and whether it is transient (i.e., benign familial neonatal seizures) or long-lasting (i.e., developmental and epileptic encephalopathy). KCNQ2 and KCNQ3 channels have also emerged as a target for novel antiepileptic drugs as their activation could reduce epileptic activity. Consequently, a great effort has taken place over the last 2 decades to understand the mechanisms that control the assembly, gating, and modulation of KCNQ2 and KCNQ3 channels. The current view that KCNQ2 and KCNQ3 channels assemble as heteromeric channels (KCNQ2/3) forms the basis of our understanding of KCNQ2 and KCNQ3 channelopathies and drug design. Here, we review the evidence that supports the formation of KCNQ2/3 heteromers in neurons. We also highlight functional and transcriptomic studies that suggest channel composition might not be necessarily fixed in the nervous system, but rather is dynamic and flexible, allowing some neurons to express KCNQ2 and KCNQ3 homomers. We propose that to fully understand KCNQ2 and KCNQ3 channelopathies, we need to adopt a more flexible view of KCNQ2 and KCNQ3 channel stoichiometry, which might differ across development, brain regions, cell types, and disease states.

Pathogenic variants in KCNQ2 cause intellectual deficiency without epilepsy: Broadening the phenotypic spectrum of a potassium channelopathy.

High-throughput sequencing (HTS) improved the molecular diagnosis in individuals with intellectual deficiency (ID) and helped to broaden the phenotype of previously known disease-causing genes. We report herein four unrelated patients with isolated ID, carriers of a likely pathogenic variant in KCNQ2, a gene usually implicated in benign familial neonatal seizures (BFNS) or early onset epileptic encephalopathy (EOEE). Patients were diagnosed by targeted HTS or exome sequencing. Pathogenicity of the variants was assessed by multiple in silico tools. Patients' ID ranged from mild to severe with predominance of speech disturbance and autistic features. Three of the four variants disrupted the same amino acid. Compiling all the pathogenic variants previously reported, we observed a strong overlap between variants causing EOEE, isolated ID, and BFNS and an important intra-familial phenotypic variability, although missense variants in the voltage-sensing domain and the pore are significantly associated to EOEE (p < 0.01, Fisher test). Thus, pathogenic variants in KCNQ2 can be associated with isolated ID. We did not highlight strong related genotype-phenotype correlations in KCNQ2-related disorders. A second genetic hit, a burden of rare variants, or other extrinsic factors may explain such a phenotypic variability. However, it is of interest to study encephalopathy genes in non-epileptic ID patients.

The ILAE classification of seizures and the epilepsies: Modification for seizures in the neonate. Position paper by the ILAE Task Force on Neonatal Seizures.

Seizures are the most common neurological emergency in the neonatal period and in contrast to those in infancy and childhood, are often provoked seizures with an acute cause and may be electrographic-only. Hence, neonatal seizures may not fit easily into classification schemes for seizures and epilepsies primarily developed for older children and adults. A Neonatal Seizures Task Force was established by the International League Against Epilepsy (ILAE) to develop a modification of the 2017 ILAE Classification of Seizures and Epilepsies, relevant to neonates. The neonatal classification framework emphasizes the role of electroencephalography (EEG) in the diagnosis of seizures in the neonate and includes a classification of seizure types relevant to this age group. The seizure type is determined by the predominant clinical feature. Many neonatal seizures are electrographic-only with no evident clinical features; therefore, these are included in the proposed classification. Clinical events without an EEG correlate are not included. Because seizures in the neonatal period have been shown to have a focal onset, a division into focal and generalized is unnecessary. Seizures can have a motor (automatisms, clonic, epileptic spasms, myoclonic, tonic), non-motor (autonomic, behavior arrest), or sequential presentation. The classification allows the user to choose the level of detail when classifying seizures in this age group.

Early initial video-electro-encephalography combined with variant location predict prognosis of KCNQ2-related disorder.

BACKGROUND: The clinical features of KCNQ2-related disorders range from benign familial neonatal seizures 1 to early infantile epileptic encephalopathy 7. The genotype-phenotypic association is difficult to establish. OBJECTIVE: To explore potential factors in neonatal period that can predict the prognosis of neonates with KCNQ2-related disorder. METHODS: Infants with KCNQ2-related disorder were retrospectively enrolled in our study in Children's Hospital of Fudan University in China from Jan 2015 to Mar 2020. All infants were older than age of 12 months at time of follow-up, and assessed by Bayley Scales of Infant and Toddler Development-Third Edition (BSID-III) or Wechsler preschool and primary scale of intelligence-fourth edition (WPPSI-IV), then divided into three groups based on scores of BSID-III or WPPSI-IV: normal group, mild impairment group, encephalopathy group. We collected demographic variables, clinical characteristics, neuroimaging data. Considered variables include gender, gestational age, birth weight, age of the initial seizures, early interictal VEEG, variant location, delivery type. Variables predicting prognosis were identified using multivariate ordinal logistic regression analysis. RESULTS: A total of 52 infants were selected in this study. Early interictal video-electro-encephalography (VEEG) (ß = 2.77, 1.20 to 4.34, P = 0.001), and variant location (ß = 2.77, 0.03 to 5.5, P = 0.048) were independent risk factors for prognosis. The worse the early interictal VEEG, the worse the prognosis. Patients with variants located in the pore-lining domain or S4 segment are more likely to have a poor prognosis. CONCLUSIONS: The integration of early initial VEEG and variant location can predict prognosis. An individual whose KCNQ2 variant located in voltage sensor, the pore domain, with worse early initial VEEG background, often had an adverse outcome.

Neonatal genetic epilepsies display convergent white matter microstructural abnormalities.

White matter undergoes rapid development in the neonatal period. Its structure during and after development is influenced by neuronal activity. Pathological neuronal activity, as in seizures, might alter white matter, which in turn may contribute to network dysfunction. Neonatal epilepsy presents an opportunity to investigate seizures and early white matter development. Our objective was to determine whether neonatal seizures in the absence of brain injury or congenital anomalies are associated with altered white matter microstructure. In this retrospective case-control study of term neonates, cases had confirmed or suspected genetic epilepsy and normal brain magnetic resonance imaging (MRI) and no other conditions independently impacting white matter. Controls were healthy neonates with normal MRI results. White matter microstructure was assessed via quantitative mean diffusivity (MD). In 22 cases, MD was significantly lower in the genu of the corpus callosum, compared to 22 controls, controlling for gestational age and postmenstrual age at MRI. This finding suggests convergent abnormal corpus callosum microstructure in neonatal epilepsies with diverse suspected genetic causes. Further study is needed to determine the specific nature, causes, and functional impact of seizure-associated abnormal white matter in neonates, a potential pathogenic mechanism.

EEG Monitoring of the Epileptic Newborn.

PURPOSE OF REVIEW: Although differentiating neonatal-onset epilepsies from acute symptomatic neonatal seizures has been increasingly recognized as crucial, existing guidelines, and recommendations on EEG monitoring are mainly based on acute symptomatic seizures, especially secondary to hypoxic-ischemic encephalopathy. We aimed to narratively review current knowledge on neonatal-onset epilepsies of genetic, metabolic, and structural non-acquired origin, with special emphasis on EEG features and monitoring. RECENT FINDINGS: A wide range of rare conditions are increasingly described, reducing undiagnosed cases. Although distinguishing features are identifiable in some, how to best monitor and detect less described etiologies is still an issue. A comprehensive approach considering onset, seizure evolution, ictal semiology, clinical, laboratory, EEG, and neuroimaging data is key to diagnosis. Phenotypic variability prevents precise recommendations, but a solid, consistent method moving from existing published guidelines helps in correctly assessing these newborns in order to provide better care, especially in view of expanding precision therapies.

Risk factors for neonatal seizures: A case-control study in the province of Parma, Italy.

PURPOSE: The present study evaluated the risk factors for electroencephalographic (EEG)-confirmed seizures during the whole neonatal period in preterm and term neonates born in the province of Parma between January 2009 and December 2014. METHODS: We selected as cases the infants that presented EEG-confirmed neonatal seizures (NS). Two population controls for each case were matched by gestational age (GA), sex, hospital, and period of birth. Information on the mother, the pregnancy, the labor and delivery, and the neonates were taken from the Emilia-Romagna Certificate of Delivery Assistance database and from hospital charts and ICD-9-CM codes. RESULTS AND INTERPRETATION: In the 6-year period of this study, 22 patients were recorded with NS. The association between at least one pregnancy complication and at least one neonatal complication, a low Apgar score, the need for resuscitation at birth, intraventricular hemorrhages (IVH) grades II-IV for preterm, and acute perinatal asphyxia/hypoxic-ischemic encephalopathy (HIE) for term infants were all statistically significant among cases. Neonates presenting these risk factors are more prone to develop NS and have to be strictly monitored.

Electroencephalography in neonatal epilepsies.

Neonatal epilepsies - neonatal seizures caused by remote symptomatic etiologies - are infrequent compared with those caused by acute symptomatic etiologies. The etiologies of neonatal epilepsies are classified into structural, genetic, and metabolic. Electroencephalography (EEG) and amplitude-integrated EEG (aEEG) are essential for the diagnosis and monitoring of neonatal epilepsies. Electroencephalography / aEEG findings may differ substantially among infants, even within infants with variants in a single gene. Unusual EEG/aEEG findings, such as downward seizure patterns on aEEG, can be found. Neonatal seizures are exclusively of focal onset. An International League Against Epilepsy task force proposed that the seizure type is typically determined by the predominant clinical feature and is classified into motor or non-motor presentations. Ictal EEG usually demonstrates a sudden, repetitive, evolving, and stereotyped activities with a minimum duration of 10 s. In epileptic spasms and myoclonic seizures, the cut-off point of 10 s cannot be applied. One must always be aware of electro-clinical dissociation in neonates suspected to have seizures. Amplitude-integrated EEG is also useful for the diagnosis and monitoring of neonatal epilepsies but aEEG cannot be recommended as the mainstay because of its relatively low sensitivity and specificity. At present, EEG findings are not pathognomonic, although some characteristic ictal or interictal EEG findings have been reported in several neonatal epilepsies. Deep learning will be expected to be introduced into EEG interpretation in near future. Objective EEG classification derived from deep learning may help to clarify EEG characteristics in some specific cases of neonatal epilepsy.

Further corroboration of distinct functional features in SCN2A variants causing intellectual disability or epileptic phenotypes.

BACKGROUND: Deleterious variants in the voltage-gated sodium channel type 2 (Nav1.2) lead to a broad spectrum of phenotypes ranging from benign familial neonatal-infantile epilepsy (BFNIE), severe developmental and epileptic encephalopathy (DEE) and intellectual disability (ID) to autism spectrum disorders (ASD). Yet, the underlying mechanisms are still incompletely understood. METHODS: To further elucidate the genotype-phenotype correlation of SCN2A variants we investigated the functional effects of six variants representing the phenotypic spectrum by whole-cell patch-clamp studies in transfected HEK293T cells and in-silico structural modeling. RESULTS: The two variants p.L1342P and p.E1803G detected in patients with early onset epileptic encephalopathy (EE) showed profound and complex changes in channel gating, whereas the BFNIE variant p.L1563V exhibited only a small gain of channel function. The three variants identified in ID patients without seizures, p.R937C, p.L611Vfs*35 and p.W1716*, did not produce measurable currents. Homology modeling of the missense variants predicted structural impairments consistent with the electrophysiological findings. CONCLUSIONS: Our findings support the hypothesis that complete loss-of-function variants lead to ID without seizures, small gain-of-function variants cause BFNIE and EE variants exhibit variable but profound Nav1.2 gating changes. Moreover, structural modeling was able to predict the severity of the variant impact, supporting a potential role of structural modeling as a prognostic tool. Our study on the functional consequences of SCN2A variants causing the distinct phenotypes of EE, BFNIE and ID contributes to the elucidation of mechanisms underlying the broad phenotypic variability reported for SCN2A variants.

Pitfalls of clinical exome and gene panel testing: alternative transcripts.

PURPOSE: Clinical exome and gene panel testing can provide molecular diagnoses for patients with rare Mendelian disorders, but for many patients these tests are nonexplanatory. We investigated whether interrogation of alternative transcripts in known disease genes could provide answers for additional patients. METHODS: We integrated alternative transcripts for known neonatal epilepsy genes with RNA-Seq data to identify brain-expressed coding regions that are not evaluated by popular neonatal epilepsy clinical gene panel and exome tests. RESULTS: We found brain-expressed alternative coding regions in 89 (30%) of 292 neonatal epilepsy genes. The 147 regions encompass 15,713 bases that are noncoding in the primary transcripts analyzed by the clinical tests. Alternative coding regions from at least 5 genes carry reported pathogenic variants. Three candidate variants in these regions were identified in public exome data from 337 epilepsy patients. Incorporating alternative transcripts into the analysis of neonatal epilepsy genes in 44 patient genomes identified the pathogenic variant for the epilepsy case and 2 variants of uncertain significance (VUS) among the 43 control cases. CONCLUSION: Assessment of alternative transcripts in exon-based clinical genetic tests, including gene panel, exome, and genome sequencing, may provide diagnoses for patients for whom standard testing is unrevealing, without introducing many VUS.

Characteristics of KCNQ2 variants causing either benign neonatal epilepsy or developmental and epileptic encephalopathy.

OBJECTIVE: Pathogenic variants of KCNQ2, which encode a potassium channel subunit, cause either benign (familial) neonatal epilepsy-B(F)NE)-or KCNQ2 encephalopathy (KCNQ2 DEE). We examined the characteristics of KCNQ2 variants. METHODS: KCNQ2 pathogenic variants were collected from in-house data and two large disease databases with their clinical phenotypes. Nonpathogenic KCNQ2 variants were collected from the Genome Aggregation Database (gnomAD). Pathogenicity of all variants was reevaluated with clinical information to exclude irrelevant variants. The cumulative distribution plots of B(F)NE, KCNQ2 DEE, and gnomAD KCNQ2 variants were compared. Several algorithms predicting genetic variant pathogenicity were evaluated. RESULTS: A total of 259 individuals or pedigrees with 216 different pathogenic KCNQ2 variants and 2967 individuals with 247 different nonpathogenic variants were deemed eligible for the study. Compared to the distribution of nonpathogenic variants, B(F)NE and KCNQ2 DEE missense variants occurred in five and three specific KCNQ2 regions, respectively. Comparison between B(F)NE and KCNQ2 DEE sets showed that B(F)NE missense variants frequently localized to the intracellular domain between S2 and S3, whereas those of KCNQ2 DEE were more frequent in S6, and its adjacent pore domain, as well as in the intracellular domain between S6 and helix A. The scores of Protein Variation Effect Analyzer (PROVEAN) and Percent Accepted Mutation (PAM) 30 prediction algorithms were associated with phenotypes of the variant loci. SIGNIFICANCE: Missense variants in the intracellular domain between S2 and S3 are likely to cause B(F)NE, whereas those in S6 and its adjacent regions are more likely to cause KCNQ2 DEE. With such regional specificities of variants, PAM30 is a helpful tool to examine the possibility that a novel KCNQ2 variant is a B(F)NE or KCNQ2 DEE variant in genetic analysis.

Genetic analysis of benign familial epilepsies in the first year of life in a Chinese cohort.

Benign familial epilepsies that present themselves in the first year of life include benign familial neonatal epilepsy (BFNE), benign familial neonatal-infantile epilepsy (BFNIE) and benign familial infantile epilepsy (BFIE). We used Sanger sequencing and targeted next-generation sequencing to detect gene mutations in a Chinese cohort of patients with these three disorders. A total of 79 families were collected, including 4 BFNE, 7 BFNIE, and 68 BFIE. Genetic testing led to the identification of gene mutations in 60 families (60 out of 79, 75.9%). A total of 42 families had PRRT2 mutations, 9 had KCNQ2 mutations, 8 had SCN2A mutations, and 1 had a GABRA6 mutation. In total three of four BFNE families were detected with KCNQ2 mutations. Mutations were detected in all BFNIE families, including 3 KCNQ2 mutations, 3 SCN2A mutations, and 1 PRRT2 mutation. Gene mutations were identified in 50 out of 68 BFIE families (73.5%), including 41 PRRT2 mutations (41 out of 68, 60.3%), 5 SCN2A mutations, 3 KCNQ2 mutations, and 1 GABRA6 mutation. Our results confirmed that mutations in KCNQ2, SCN2A, and PRRT2 are major genetic causes of benign familial epilepsy in the first year of life in the Chinese population. KCNQ2 is the major gene related to BFNE. PRRT2 is the main gene responsible for BFIE.