Combined Mutation And Rearrangement Screening by Quantitative PCR High-Resolution Melting: Is It Relevant for Hereditary Recurrent Fever Genes?

The recent identification of genes implicated in hereditary recurrent fevers has allowed their specific diagnosis. So far however, only punctual mutations have been identified and a significant number of patients remain with no genetic confirmation of their disease after routine molecular approaches such as sequencing. The possible involvement of sequence rearrangements in these patients has only been examined in familial Mediterranean fever and was found to be unlikely. To assess the existence of larger genetic alterations in 3 other concerned genes, MVK (Mevalonate kinase), NLRP3 (Nod like receptor family, pyrin domain containing 3) and TNFRSF1A (TNF receptor superfamily 1A), we adapted the qPCR-HRM method to study possible intragenic deletions and duplications. This single-tube approach, combining both qualitative (mutations) and quantitative (rearrangement) screening, has proven effective in Lynch syndrome diagnosis. Using this approach, we studied 113 unselected (prospective group) and 88 selected (retrospective group) patients and identified no intragenic rearrangements in the 3 genes. Only qualitative alterations were found with a sensitivity similar to that obtained using classical molecular techniques for screening punctual mutations. Our results support that deleterious copy number alterations in MVK, NLRP3 and TNFRSF1A are rare or absent from the mutational spectrum of hereditary recurrent fevers, and demonstrate that a routine combined method such as qPCR-HRM provides no further help in genetic diagnosis. However, quantitative approaches such as qPCR or SQF-PCR did prove to be quick and effective and could still be useful after non contributory punctual mutation screening in the presence of clinically evocative signs

Best Practice Guidelines on molecular diagnostics in Duchenne/Becker muscular dystrophies

Meeting participants: Rosário dos Santos, Porto, PortugalIntroduction: A meeting of 29 senior scientists from Europe, the USA, India and Australia, was held in Naarden, The Netherlands on November 14–16, 2008, to establish consensus Best Practice Guidelines for molecular diagnosis of Duchenne and Becker muscular dystrophy (DMD/BMD). New therapeutic trials for DMD demand accurate diagnosis of the disorder, especially where the therapy is targeted towards specific mutations. These guidelines aim to help diagnostic laboratories attain that accuracy by describing the minimum standards for acceptable molecular diagnostic testing of DMD. For the different types of clinical referral received by a molecular diagnostic laboratory, the guidelines recommend the appropriate tests to be carried out, interpretation of the results and how those results should be reported.The workshop was jointly organised and sponsored by The European Molecular Genetics Quality Network (www.emqn.org); Euro- Gentest (www.eurogentest.org); EU Contract no. FP6-512148); TREAT-NMD (www.treat-nmd.org); EU Contract no. FP6-036825), and hosted by the European Neuro-Muscular Centre (www.enmc.org)

Use of the MLPA Assay in the Molecular Diagnosis of Gene Copy Number Alterations in Human Genetic Diseases

Multiplex Ligation-dependent Probe Amplification (MLPA) assay is a recently developed technique able to evidence variations in the copy number of several human genes. Due to this ability, MLPA can be used in the molecular diagnosis of several genetic diseases whose pathogenesis is related to the presence of deletions or duplications of specific genes. Moreover, MLPA assay can also be used in the molecular diagnosis of genetic diseases characterized by the presence of abnormal DNA methylation. Due to the large number of genes that can be analyzed by a single technique, MLPA assay represents the gold standard for molecular analysis of all pathologies derived from the presence of gene copy number variation. In this review, the main applications of the MLPA technique for the molecular diagnosis of human diseases are described

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest

Improving CNV detection from short-read MPS data in neuromuscular disorders

Neuromuscular disorders (NMD) are highly heterogenic with around 1000 reported different subtypes. Most are genetic in origin, and some 500 genes are currently identified to cause NMDs. Massively parallel sequencing (MPS) approaches have been widely used to increase the cost-effectiveness and diagnostic yield in the work-up of the genetic molecular diagnosis and to speed up the process. Copy number variants (CNVs), deletions and duplications larger than 50 base pairs, explain approximately 10% of the Mendelian disorders. No best practices pipelines have been developed yet for CNV analysis from MPS data. Therefore, the detection and verification of CNV findings has often involved complementary methods, such as array comparative genomic hybridization (array CGH), multiplex ligation-dependent probe amplification (MLPA) and quantitative PCR approaches. Recently, various CNV detection programs have been developed, but for widely different types of designated research settings, which complicates choosing the correct approach for NMDs. These individual programs have generally exhibited less than ideal sensitivity and specificity for CNV detection. Our aim was to develop a comprehensive pipeline for the detection and annotation of CNVs with high accuracy from targeted gene panel sequencing and whole exome sequencing (WES) data of patients with NMDs. Four different CNV analysis programs were chosen for this study: CoNIFER, XHMM, ExomeDepth and CODEX. The targeted gene panel MYOcap includes 349 genes for myopathic disorders and MNDcap 302 genes for neurogenic disorders in their current panel versions. 2359 samples were sequenced with MYOcap, 942 samples with MNDcap and 262 samples with WES. This included for the targeted gene panels 24 positive control samples with previously characterized CNVs and 31 negative control samples with certain genes verified to not have CNVs. A detection sensitivity of 100% and specificity of 100% were reached for these control samples. Previously undetected CNVs from MYOcap or MNDcap sequenced samples were verified as true positive detections in 36 cases with MLPA, PCR or array CGH, and eight CNVs were verified as false positive detections. These and the positive control samples were utilized in validation of a predictive logistic regression model. In silico CNV generation into MYOcap sequenced samples provided 18,677 specific and 3892 unspecific CNV detections to initially train the model. The model was trained to differentiate true positive detections from false positive detections in order to increase the specificity of the CNV detection pipeline. The advantage of using four different CNV detection programs compared to using them individually, or with any other combination, was demonstrated by CNV detection sensitivity from the set of in silico CNVs. The predictive model with variables from all four programs provided the highest sensitivity (96.6%) and specificity (87.5%) for predicting CNV detections correctly, indicating an accuracy of 95.5% (95% CI 87.3–99.1%). The CNV detection pipeline together with the predictive model was validated for WES samples with control samples with 235 previously characterized CNVs. For CNVs spanning at least three exons, the detection sensitivity was 97.3% and the sensitivity of the predicative model was 99.3% after adjusting the model threshold for WES data. The CNV annotation platform cnvScan was expanded to contain the most recent CNV population databases as well as in-house CNV databases for all the sequenced sample sets. CNV detection results were filtered by < 1% frequency with reciprocal overlap of 90% in the common CNV population databases, with both it and < 5% frequency with 50% reciprocal overlap in the in-house CNV database, and by the true positive prediction with the model. These procedures significantly decreased the workload (with 3–13% of the original CNV detections preserved) in evaluating the CNVs further regarding clinical significance. The added value, i.e. the additional diagnostic yield from CNVs for both the targeted gene panel sequenced samples and WES samples was estimated to be 1.9%. Altogether 39 final genetic diagnoses were solved with these CNV findings. In addition, 18 patient cases had a likely pathogenic finding, and five had a heterozygous CNV likely pathogenic for a recessive disease without association to the patient’s phenotype. The clarified cases included six different DMD deletions or duplications causing dystrophinopathies. In three sequenced familial cases, the detected CNVs in CACNA1A, SGCD and TTN genes co-segregated with the disease. One case had two separate genetic diseases, tibial muscular dystrophy (TMD) and BMD, caused by the founder mutation FINmaj in the gene TTN and a deletion in DMD. Some of the solved cases had novel findings: the second ever reported large intragenic deletion in NEB causing dominant disease, and the first CNV, an intragenic deletion, in TIA1 in a patient diagnosed with Welander distal myopathy (WDM). Some of the genes associated with NMDs are challenging to analyze from short-read sequencing data due to homology or repetitive regions. An additional script was thus written to differentiate copy numbers of the highly homologous genes, SMN1 and SMN2. Two SMN1/SMN2 copy number 0/3 control cases were successfully recognized, and five cases were identified with a possible exon 7 conversion in SMN1 and a compatible spinal muscular atrophy phenotype. The latter findings were considered likely pathogenic and are awaiting further validation on the genomic level. Comparison of CNV detections within the in-house CNV database revealed divergences in the CNV detections within the triplicate repetitive region of NEB with potentially clinically significant changes. One array CGH validated change correlated well with the nemaline rod pathology observed in the patient. CNV analysis utilizing MPS data from targeted gene panels and WES samples provided increased diagnostic yield as reported also in other studies on NMDs. Our multi-algorithm and -platform approach decreased the workload in variant analysis and provided more insight into the many difficult to analyze genomic regions involved in NMDs. In the future, whole genome sequencing and long-read sequencing will likely provide higher resolution for CNV detections and reveal an even wider spectrum of structural genomic variants, together with other emerging comprehensive methods, such as optical mapping.Lihastaudit ovat hyvin heterogeenisiä, ja niistä on kuvattu noin tuhat alatyyppiä. Suurin osa on perinnöllisiä tauteja, ja tähän mennessä on tunnistettu noin 500 eri lihastauteja aiheuttavaa geeniä. Massiivista rinnakkaissekvensointia (MPS) on käytetty laajalti perinnöllisten tautien diagnostisen prosessin nopeuttamiseksi, kustannustehokkuuden parantamiseksi ja lopullisen geeniperäisen diagnoosin saavuttamiseksi. Kopiolukumuutokset, yli 50 emäsparin deleetiot tai duplikaatiot, aiheuttavat arviolta 10 % Mendelin mukaisesti periytyvistä taudeista. Kopiolukumuutosten havaitsemiseen sekvensointidatasta ei ole vielä kehitetty yleisesti hyväksyttyjä ja suositeltuja käytänteitä. Kopiolukumuutosten havaitsemiseksi ja varmistamiseksi käytetäänkin usein täydentäviä menetelmiä, kuten vertaileva genominen hybridisaatio sirulla (aCGH), rinnastettu ligaatio-riippuvainen alukemonistus (MLPA) ja kvantitatiivinen PCR. Kopiolukumuutosten havaitsemiseen sekvensointidatasta on kehitetty useita työkaluja vaihtelevissa tutkimusasetelmissa, mikä hankaloittaa oikean lähestymistavan valitsemista lihastaudeille. Yksittäisten ohjelmien on todettu tuottavan usein epätäsmällisiä ja herkkyydeltään vaihtelevia tai riittämättömiä havaintoja. Tämän tutkimuksen tavoitteena oli kehittää kattava menetelmä kopiolukumuutosten havaitsemiseen ja annotointiin suurella tarkkuudella kohdennetun geenipaneelin ja koko eksomin (WES) sekvensointidatasta lihastautipotilailta. Tutkimukseen valittiin neljä kopiolukumuutosanalyysin työkalua: CoNIFER, XHMM, ExomeDepth ja CODEX. Kohdennetuista geenipaneeleista MYOcap kattaa 349 geeniä lihaspainotteisille taudeille ja MNDcap 302 hermopainotteisille taudeille nykyisissä paneeliversioissa. MYOcap:lla sekvensointiin 2359 näytettä, MNDcap:lla 942 ja WES:llä 262. Kohdennetuilla geenipaneeleilla sekvensointiin 24 positiivista kontrollinäytettä, joissa on aiemmin tunnistettu kopiolukumuutos, ja 31 negatiivista kontrollinäytettä, joissa tietyt geenit oli varmistettu kopiolukumuutoksia sisältämättömiksi. Kontrollinäytteille saavutettiin kehittämällämme menetelmällä 100 % havaitsemisherkkyys ja 100 % tarkkuus. MYOcap:lla tai MNDcap:lla sekvensoiduista näytteistä havaituista kopiolukumuutoksista 36 varmistettiin todellisiksi havainnoiksi MLPA:lla, PCR:lla tai aCGH:llä ja kahdeksan varmistettiin vääriksi positiivisiksi. Nämä ja positiiviset kontrollinäytteet sisällytettiin logistiseen regressioon perustuvan tilastollisen mallin validointiin. Erottelumallin kehitysvaiheessa MYOcap-sekvensoituihin näytteisiin tehtiin in silico kopiolukumuutoksia, mikä tuotti 18677 spesifiä ja 3892 ei-spesifiä kopiolukumuutoshavaintoa mallinnukseen. Malli kehitettiin erottelemaan todelliset kopiolukumuutoshavainnot vääristä positiivista havainnoista havaintomenetelmän tarkkuuden lisäämiseksi. Neljän ohjelman havaintojen käyttämisen paremmuus verrattuna ohjelmien käyttämiseen yksittäin tai muilla yhdistelmillä todennettiin in silico kopiolukumuutosten havaitsemisen herkkyyden tuloksilla. Erottelumalli, jossa oli muuttujia kaikilta neljältä ohjelmalta, saavutti korkeimman herkkyyden (96,6 %), täsmällisyyden (87,5 %) ja tarkkuuden 95,5 % (95 % CI 87,3–99,1 %) kopiolukumuutosten erottelulle. Kopiolukumuutoshavaitsemismenetelmä ja erottelumalli validoitiin WES-kontrollinäytteillä, joissa oli 235 aiemmin tunnistettua kopiolukumuutosta. Havaitsemisherkkyys kopiolukumuutoksille, jotka sisältävät vähintään kolme eksonia oli 97,3 %, ja erottelumallin herkkyys oli 99,3 % kunhan mallin arviointiraja oli uudelleensäädetty WES-datalle. Kopiolukumuutosten annotaatiotyökalu cnvScan laajennettiin sisältämään uusimmat kopiolukumuutospopulaatiotietokannat ja talonsisäinen kopiolukumuutostietokanta kaikista sekvensointinäytejoukoista. Alkuperäiset kopiolukumuutoshavainnot neljältä ohjelmalta suodatettiin 1 % enimmäisyleisyyden ja vastavuoroisen 90 % muutoksen kattamisen vaatimuksella yleisissä kopiolukumuutospopulaatiotietokannoissa, tällä sekä 5 % enimmäisyleisyyden ja vastavuoroisen 50 % muutoksen kattamisen vaatimuksella talonsisäisessä tietokannassa, ja lisäksi erottelumallilla todellisiin havaintoihin. Nämä toimenpiteet vähensivät merkittävästi työmäärää kliinisen merkityksen arvioinnille kopiolukumuutoksille säästäen 3–13 % alkuperäisistä havainnoista. Lisääntyneiden diagnoosien määrä kopiolukumuutoshavaintojen myötä sekä kohdennetuilla geenipaneeleilla että WES-sekvensoiduilla näytteillä oli noin 1,9 %. Kopiolukumuutoshavainnoilla saavutettiin 39 lopullista geneettistä diagnoosia potilaille. Lisäksi 18:lla tutkitulla oli todennäköisesti patogeeninen löydös, ja viidellä tutkitulla havaittiin heterotsygoottinen kopiolukumuutos, jonka arvioitiin olevan patogeeninen peittyvästi periytyvän taudin variantti ilman yhteyttä potilaan taudinkuvaan. Selvitettyihin tapauksiin sisältyi kuusi eri DMD-geenissä olevaa deleetiota tai duplikaatiota, jotka aiheuttivat dystrofinopatioita. Kolme potilasta, joilla oli oireisia perheenjäseniä, sekvensointiin perhetapauksina, ja havaitut kopiolukumuutokset geeneissä CACNA1A, SGCD ja TTN segregoituivat yhdessä taudin kanssa. Yhdellä tutkitulla havaittiin kaksi perinnöllistä tautia, tibiaalinen lihasdystrofia (TMD) ja BMD, joiden aiheuttajina olivat perustajamutaatio FINmaj TTN-geenissä ja deleetio DMD-geenissä. Osalla selvitetyistä tapauksista oli ennen havaitsemattomia löydöksiä: NEB-geenissä toinen koskaan raportoitu iso geeninsisäinen deleetio, joka aiheuttaa vallitsevasti periytyvän taudin, sekä TIA1-geenin geeninsisäinen deleetio, joka on ensimmäinen havaittu kopiolukumuutos TIA1:ssä Welanderin distaalimyopatiaa (WDM) sairastavalla potilaalla. Jotkin geeneistä, jotka on liitetty lihastauteihin, ovat haastavia analysoitavia lyhytlukuisesta sekvensointidatasta homologian ja toistojaksojen takia. Hyvin homologisille geeneille SMN1 ja SMN2 kehitettiin erillinen ohjelma erottelemaan geenien kopiolukumäärät. Kaksi kontrollitapausta tunnistettiin onnistuneesti SMN1 ja SMN2 kopiolukumäärillä 0 ja 3, ja lisäksi tunnistettiin viisi tapausta, joilla on mahdollisesti eksonin 7 konversio SMN1:ssä ja yhteensopiva spinaalinen lihasatrofia. Jälkimmäiset löydökset luokiteltiin todennäköisesti patogeeniseksi, ja ne odottavat genomista lisävarmistusta. Kopiolukumuutoshavaintojen vertailu NEB-geenin triplikaattitoistoalueella talonsisäisessä tietokannassa paljasti eroavaisuuksia, joilla on potentiaalisesti kliinisesti merkitystä. Yksi aCGH:llä varmistettu muutos korreloi selkeästi nemaliinisauvakappalepatologian kanssa, joka potilaalla oli havaittu. Kopiolukumuutoshavainnointi käyttäen sekvensointidataa kohdennetusta geenipaneelista tai WES-näytteistä lisäsi diagnoosien määrää kuten aiemmissa vastaavissa tutkimuksissa lihastaudeille. Käyttämämme usean algoritmin ja alustan lähestymistapa vähensi varianttianalyysin työmäärää ja tarjosi lisää tietoa useista hankalasti analysoitavista genomisista alueista, jotka on liitetty lihastauteihin. Tulevaisuudessa koko genomin sekvensointi ja pitkälukuinen sekvensointi tarjonnevat paremman resoluution kopiolukumuutoksille ja paljastavat enemmän rakenteellisia genomin muutoksia yhdessä muiden kehitteillä olevien kattavien menetelmien kanssa, kuten optinen kartoitus

Molecular diagnostics of rare inherited SYNDROMES with a view on diagnostic test development

CHARGE syndrome, Sotos syndrome and 3p deletion syndrome are examples of rare inherited syndromes that have been recognized for decades but for which the molecular diagnostics only have been made possible by recent advances in genomic research. Despite these advances, development of diagnostic tests for rare syndromes has been hindered by diagnostic laboratories having limited funds for test development, and their prioritization of tests for which a (relatively) high demand can be expected. In this study, the molecular diagnostic tests for CHARGE syndrome and Sotos syndrome were developed, resulting in their successful translation into routine diagnostic testing in the laboratory of Medical Genetics (UTUlab). In the CHARGE syndrome group, mutation was identified in 40.5% of the patients and in the Sotos syndrome group, in 34%, reflecting the use of the tests in routine diagnostics in differential diagnostics. In CHARGE syndrome, the low prevalence of structural aberrations was also confirmed. In 3p deletion syndrome, it was shown that small terminal deletions are not causative for the syndrome, and that testing with arraybased analysis provides a reliable estimate of the deletion size but benign copy number variants complicate result interpretation. During the development of the tests, it was discovered that finding an optimal molecular diagnostic strategy for a given syndrome is always a compromise between the sensitivity, specificity and feasibility of applying a new method. In addition, the clinical utility of the test should be considered prior to test development: sometimes a test performing well in a laboratory has limited utility for the patient, whereas a test performing poorly in the laboratory may have a great impact on the patient and their family. At present, the development of next generation sequencing methods is changing the concept of molecular diagnostics of rare diseases from single tests towards whole-genome analysis.Siirretty Doriast

Copy number variant discrepancy resolution using the ClinGen dosage sensitivity map results in updated clinical interpretations in ClinVar

Conflict resolution in genomic variant interpretation is a critical step toward improving patient care. Evaluating interpretation discrepancies in copy number variants (CNVs) typically involves assessing overlapping genomic content with focus on genes/regions that may be subject to dosage sensitivity (haploinsufficiency (HI) and/or triplosensitivity (TS)). CNVs containing dosage sensitive genes/regions are generally interpreted as â likely pathogenicâ (LP) or â pathogenicâ (P), and CNVs involving the same known dosage sensitive gene(s) should receive the same clinical interpretation. We compared the Clinical Genome Resource (ClinGen) Dosage Map, a publicly available resource documenting known HI and TS genes/regions, against germline, clinical CNV interpretations within the ClinVar database. We identified 251 CNVs overlapping known dosage sensitive genes/regions but not classified as LP or P; these were sent back to their original submitting laboratories for reâ evaluation. Of 246 CNVs reâ evaluated, an updated clinical classification was warranted in 157 cases (63.8%); no change was made to the current classification in 79 cases (32.1%); and 10 cases (4.1%) resulted in other types of updates to ClinVar records. This effort will add curated interpretation data into the public domain and allow laboratories to focus attention on more complex discrepancies.The ClinGen Dosage Sensitivity (DS) Map provides evidenceâ based assessments of the haploinsufficiency and triplosensitivity of genes/genomic regions. We identified 251 clinical copy number variants (CNVs) in ClinVar that overlapped known DS genes/regions but were not interpreted as â likely pathogenicâ or â pathogenic;â these were sent back to their original laboratories for reâ evaluation. Of the 246 that were reâ evaluated, 63.0% resulted in updated classifications, showing that the ClinGen DS Map can be an effective initial step in CNV classification discrepancy resolution.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146425/1/humu23610_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146425/2/humu23610.pd

Spinal muscular atrophy type I associated with a novel SMN1 splicing variant that disrupts the expression of the functional transcript

IntroductionSpinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disorder caused by pathogenic variants in the SMN1 gene. The majority of SMA patients harbor a homozygous deletion of SMN1 exon 7 (95%). Heterozygosity for a conventional variant and a deletion is rare (5%) and not easily detected, due to the highly homologous SMN2 gene interference. SMN2 mainly produces a truncated non-functional protein (SMN-d7) instead of the full-length functional (SMN-FL). We hereby report a novel SMN1 splicing variant in an infant with severe SMA.MethodsMLPA was used for SMN1/2 exon dosage determination. Sanger sequencing approaches and long-range PCR were employed to search for an SMN1 variant. Conventional and improved Real-time PCR assays were developed for the qualitative and quantitative SMN1/2 RNA analysis.ResultsThe novel SMN1 splice-site variant c.835-8_835-5delinsG, was identified in compound heterozygosity with SMN1 exons 7/8 deletion. RNA studies revealed complete absence of SMN1 exon 7, thus confirming a disruptive effect of the variant on SMN1 splicing. No expression of the functional SMN1-FL transcript, remarkable expression of the SMN1-d7 and increased levels of the SMN2-FL/SMN2-d7 transcripts were observed.DiscussionWe verified the occurrence of a non-deletion SMN1 variant and supported its pathogenicity, thus expanding the SMN1 variants spectrum. We discuss the updated SMA genetic findings in the Cypriot population, highlighting an increased percentage of intragenic variants compared to other populations

Genetically complex epilepsies, copy number variants and syndrome constellations

Epilepsy is one of the most common neurological disorders, with a prevalence of 1% and lifetime incidence of 3%. There are numerous epilepsy syndromes, most of which are considered to be genetic epilepsies. Despite the discovery of more than 20 genes for epilepsy to date, much of the genetic contribution to epilepsy is not yet known. Copy number variants have been established as an important source of mutation in other complex brain disorders, including intellectual disability, autism and schizophrenia. Recent advances in technology now facilitate genome-wide searches for copy number variants and are beginning to be applied to epilepsy. Here, we discuss what is currently known about the contribution of copy number variants to epilepsy, and how that knowledge is redefining classification of clinical and genetic syndromes