Neurodevelopmental Disorders and Array-Based Comparative Genomic Hybridization: Sensitivity and Specificity using a Criteria Checklist for Genetic Test Performance.

BACKGROUND: Array-based comparative genomic hybridization (aCGH) is a molecular analysis method for identifying chromosomal anomalies or copy number variants (CNVs) correlating with clinical phenotypes. The aim of our study was to identify the most significant clinical variables associated with a positive outcome of aCGH analyses to develop a simple predictive clinical score. METHODS: We conducted a cross-sectional study in a tertiary center comparing the genotype and phenotype of the cases. A score was developed using multivariate logistic regression. The best score cutoff point, sensitivity, specificity, positive and negative predictive values, and area under the curve were calculated with the receiver operating characteristic curve. RESULTS: aCGH identified structural chromosomal alterations responsible for the disorder in 13.7% (95% confidence interval [CI]: 10.9-16.5) of our sample (570 patients analyzed by aCGH). Based on the most frequent phenotypic characteristics among patients with a pathogenic CNV, we have created a checklist with the following items: alteration of the cranial perimeter, stature < percentile (p) 3, weight < p3, presence of brain malformations, ophthalmological malformations, two or more dysmorphic features in the same patient, and autism spectrum disorder diagnosis. Using a score ≥1.5 as the cutoff point for the test, we obtained a sensitivity of 82.4% (95% CI: 73.1-91.8) and a specificity of 54.2% (95% CI: 49.7-58.7). CONCLUSION: All individuals with a score of 1.5 or higher should be genetically screened by aCGH. This approach can improve clinical indications for aCGH in patients with neurodevelopmental disorders, but the scoring system should be validated in an external group.

Whole-genome sequencing analysis of CNV using low-coverage and paired-end strategies is efficient and outperforms array-based CNV analysis.

BACKGROUND: Copy number variation (CNV) analysis is an integral component of the study of human genomes in both research and clinical settings. Array-based CNV analysis is the current first-tier approach in clinical cytogenetics. Decreasing costs in high-throughput sequencing and cloud computing have opened doors for the development of sequencing-based CNV analysis pipelines with fast turnaround times. We carry out a systematic and quantitative comparative analysis for several low-coverage whole-genome sequencing (WGS) strategies to detect CNV in the human genome. METHODS: We compared the CNV detection capabilities of WGS strategies (short insert, 3 kb insert mate pair and 5 kb insert mate pair) each at 1×, 3× and 5× coverages relative to each other and to 17 currently used high-density oligonucleotide arrays. For benchmarking, we used a set of gold standard (GS) CNVs generated for the 1000 Genomes Project CEU subject NA12878. RESULTS: Overall, low-coverage WGS strategies detect drastically more GS CNVs compared with arrays and are accompanied with smaller percentages of CNV calls without validation. Furthermore, we show that WGS (at ≥1× coverage) is able to detect all seven GS deletion CNVs >100 kb in NA12878, whereas only one is detected by most arrays. Lastly, we show that the much larger 15 Mbp Cri du chat deletion can be readily detected with short-insert paired-end WGS at even just 1× coverage. CONCLUSIONS: CNV analysis using low-coverage WGS is efficient and outperforms the array-based analysis that is currently used for clinical cytogenetics.

An alternative to array-based diagnostics: a prospectively recruited cohort, comparing arrayCGH to next-generation sequencing to evaluate foetal structural abnormalities.

Molecular diagnostic investigations, following the identification of foetal abnormalities, are routinely performed using array comparative genomic hybridisation (aCGH). Despite the utility of this technique, contemporary approaches for the detection of copy number variation are typically based on next-generation sequencing (NGS). We sought to compare an in-house NGS-based workflow (CNVseq) with aCGH, for invasively obtained foetal samples from pregnancies complicated by foetal structural abnormality. DNA from 40 foetuses was screened using both 8 × 60 K aCGH oligoarrays and low-coverage whole genome sequencing. Sequencer-compatible libraries were combined in a ten-sample multiplex and sequenced using an Illumina HiSeq2500. The mean resolution of CNVseq was 29 kb, compared to 60 kb for aCGH analyses. Four clinically significant, concordant, copy number imbalances were detected using both techniques, however, genomic breakpoints were more precisely defined by CNVseq. This data indicates CNVseq is a robust and sensitive alternative to aCGH, for the prenatal investigation of foetuses with structural abnormalities. Impact statement What is already known about this subject? Copy number variant analysis using next-generation sequencing has been successfully applied to investigations of tumour specimens and patients with developmental delays. The application of our approach, to a prospective prenatal diagnosis cohort, has not hitherto been assessed. What do the results of this study add? Next-generation sequencing has a comparable turnaround time and assay sensitivity to copy number variant analysis performed using array CGH. We demonstrate that having established a next-generation sequencing facility, high-throughput CNVseq sample processing and analysis can be undertaken within the framework of a regional diagnostic service. What are the implications of these findings for clinical practice and/or further research? Array CGH is a legacy technology which is likely to be superseded by low-coverage whole genome sequencing, for the detection of copy number variants, in the prenatal diagnosis of structural abnormalities.

Defining the limits of detection for chromosome rearrangements in the preimplantation embryo using next generation sequencing.

STUDY QUESTION: Is next generation sequencing (NGS) capable of detecting smaller sub-chromosomal rearrangements in human embryos than the manufacturer's quoted resolution suggests? SUMMARY ANSWER: NGS was able to detect unbalanced chromosome segments smaller than the manufacturer's resolution. WHAT IS KNOWN ALREADY: Array Comparative Genomic Hybridization (array-CGH) has been the gold standard platform used for PGD of chromosome rearrangements. NGS is a viable alternative to array-CGH for PGD of chromosome arrangements given that the manufacturer's guidelines quote a resolution of ≥20 Mb. However, as many patients carry a chromosome rearrangement <20 Mb, the detection limits of NGS warrant further investigation. STUDY DESIGN, SIZE, DURATION: This study involved a retrospective assessment of stored DNA samples from embryos that had previously been diagnosed as unbalanced by array-CGH as part of routine PGD in two separate IVF clinics between November 2013 and April 2017. SurePlex whole genome amplification (WGA) products derived from DNA extracted from an embryo biopsy sample known to carry an unbalanced form of a chromosome rearrangement were subjected to a specific NGS workflow (VeriSeq PGS). The results from the two technologies were compared for each sample. PARTICIPANTS/MATERIALS, SETTING, METHODS: WGA products from 200 embryos known to carry unbalanced rearrangements were sequenced and analysed. These embryos had been created by 75 patients known to carry a chromosome rearrangement (68 reciprocal translocations, 3 pericentric inversions, 1 paracentric inversion, 2 insertions and 1 dual reciprocal and inversion). Each sample was assessed for the size of the segmental gain/loss (Mb), copy number for each segment and chromosome, segregation pattern, the number of bins in the analysis software used and concordance with array-CGH results. MAIN RESULTS AND THE ROLE OF CHANCE: A total of 294 unbalanced chromosome segments were assessed. NGS was capable of detecting 285/294 (97%) unbalanced segments previously identified using array-CGH. The final PGD diagnosis was concordant for 200/200 (100%) embryos. In total, 44/75 (59%) patients contained an unbalanced chromosome segment below the quoted 20 Mb manufacturer's stated resolution. Of these, 35/44 (80%) patients had segments that were able to be detected using NGS, whilst maintaining clinical outcome concordance. LIMITATIONS, REASONS FOR CAUTION: Our study subset did not include any rearrangements involving the Y chromosome. NGS has less available bins per chromosome compared to the array-CGH platform used, thus it remains possible that chromosome rearrangements predicted to be small but still detectable by array-CGH may not be feasible for testing using NGS. This should be considered when undertaking a theoretical feasibility assessment for detecting the chromosome rearrangement in question. Only one specific workflow for WGA and NGS was investigated in this study. WIDER IMPLICATIONS OF THE FINDINGS: This study has shown that NGS is available for the detection of unbalanced chromosome rearrangements ≥10 Mb. STUDY FUNDING/COMPETING INTEREST(S): Part sponsorship of the VeriSeq PGS kits used was provided by Illumina. The remainder of the kits were provided by two commercial IVF clinics. None of the authors has any conflicting interests to declare. TRIAL REGISTRATION NUMBER: N/A.

Custom Array Comparative Genomic Hybridization: the Importance of DNA Quality, an Expert Eye, and Variant Validation.

The presence of false positive and false negative results in the Array Comparative Genomic Hybridization (aCGH) design is poorly addressed in literature reports. We took advantage of a custom aCGH recently carried out to analyze its design performance, the use of several Agilent aberrations detection algorithms, and the presence of false results. Our study provides a confirmation that the high density design does not generate more noise than standard designs and, might reach a good resolution. We noticed a not negligible presence of false negative and false positive results in the imbalances call performed by the Agilent software. The Aberration Detection Method 2 (ADM-2) algorithm with a threshold of 6 performed quite well, and the array design proved to be reliable, provided that some additional filters are applied, such as considering only intervals with average absolute log2ratio above 0.3. We also propose an additional filter that takes into account the proportion of probes with log2ratio exceeding suggestive values for gain or loss. In addition, the quality of samples was confirmed to be a crucial parameter. Finally, this work raises the importance of evaluating the samples profiles by eye and the necessity of validating the imbalances detected.

Comparison of the results of preimplantation genetic screening obtained by a-CGH and NGS methods from the same embryos.

Chromosomal aneuploidies are known for being the main cause of abnormal development of embryos with normal morphology, their implantation failure and early reproductive losses in IVF treatments. Preimplantation genetic screening (PGS) allows selecting embryos with normal chromosomal content and increases IVF treatment efficiency due to higher implantation rates and less frequent early pregnancy losses. New technologies used for PGS allow making genome-wide analysis of the presence of all chromosomes in embryos. This article presents our study of evaluation of two techniques used for PGS: previously developed and used in our laboratory a-CGH assay based on Agilent technology and newly tested semi-conductive NGS technique (Torrent technology).

Rescue karyotyping: a case series of array-based comparative genomic hybridization evaluation of archival conceptual tissue.

BACKGROUND: Determination of fetal aneuploidy is central to evaluation of recurrent pregnancy loss (RPL). However, obtaining this information at the time of a miscarriage is not always possible or may not have been ordered. Here we report on "rescue karyotyping", wherein DNA extracted from archived paraffin-embedded pregnancy loss tissue from a prior dilation and curettage (D&C) is evaluated by array-based comparative genomic hybridization (aCGH). METHODS: A retrospective case series was conducted at an academic medical center. Patients included had unexplained RPL and a prior pregnancy loss for which karyotype information would be clinically informative but was unavailable. After extracting DNA from slides of archived tissue, aCGH with a reduced stringency approach was performed, allowing for analysis of partially degraded DNA. Statistics were computed using STATA v12.1 (College Station, TX). RESULTS: Rescue karyotyping was attempted on 20 specimens from 17 women. DNA was successfully extracted in 16 samples (80.0%), enabling analysis at either high or low resolution. The longest interval from tissue collection to DNA extraction was 4.2 years. There was no significant difference in specimen sufficiency for analysis in the collection-to-extraction interval (p=0.14) or gestational age at pregnancy loss (p=0.32). Eight specimens showed copy number variants: 3 trisomies, 2 partial chromosomal deletions, 1 mosaic abnormality and 2 unclassified variants. CONCLUSIONS: Rescue karyotyping using aCGH on DNA extracted from paraffin-embedded tissue provides the opportunity to obtain critical fetal cytogenetic information from a prior loss, even if it occurred years earlier. Given the ubiquitous archiving of paraffin embedded tissue obtained during a D&C and the ease of obtaining results despite long loss-to-testing intervals or early gestational age at time of fetal demise, this may provide a useful technique in the evaluation of couples with recurrent pregnancy loss.

ACMG Standards and Guidelines for constitutional cytogenomic microarray analysis, including postnatal and prenatal applications: revision 2013.

Microarray methodologies, including array comparative genomic hybridization and single-nucleotide polymorphism-detecting arrays, are accepted as an appropriate first-tier test for the evaluation of imbalances associated with intellectual disability, autism, and multiple congenital anomalies. This technology also has applicability in prenatal specimens. To assist clinical laboratories in validation of microarray methodologies for constitutional applications, the American College of Medical Genetics and Genomics has produced the following revised professional standards and guidelines.

[Generation and application of dynamic standard reference intervals for analyzing results of comparative genomic hybridization].

The present work was aimed at generating the dynamic standard reference intervals (DSRI) and their application for chromosomal-aberration (CA) analysis. The evaluation of the generated DSRI was performed using the DNA samples from four patients with already known CA. High-resolution comparative genomic hybridization analysis (HR-CGH) allowed us to not only identify all of the CAs, that were not revealed by CGH, but also to detect the breakpoints and to determine the size of chromosomal imbalance.

Genome-wide arrays: quality criteria and platforms to be used in routine diagnostics.

Whole-genome analysis using genome-wide arrays, also called "genomic arrays," "microarrays," or "arrays," has become the first-tier diagnostic test for patients with developmental abnormalities and/or intellectual disabilities. In addition to constitutional anomalies, genomic arrays are also used to diagnose acquired disorders. Despite the rapid implementation of these technologies in diagnostic laboratories, external quality control schemes (such as CEQA, EMQN, UK NEQAS, and the USA QA scheme CAP) and interlaboratory comparisons show that there are huge differences in quality, interpretation, and reporting among laboratories. We offer guidance to laboratories to help assure the quality of array experiments and to standardize minimum detection resolution, and we also provide guidelines to standardize interpretation and reporting.

Reference-unbiased copy number variant analysis using CGH microarrays.

Comparative genomic hybridization (CGH) microarrays have been used to determine copy number variations (CNVs) and their effects on complex diseases. Detection of absolute CNVs independent of genomic variants of an arbitrary reference sample has been a critical issue in CGH array experiments. Whole genome analysis using massively parallel sequencing with multiple ultra-high resolution CGH arrays provides an opportunity to catalog highly accurate genomic variants of the reference DNA (NA10851). Using information on variants, we developed a new method, the CGH array reference-free algorithm (CARA), which can determine reference-unbiased absolute CNVs from any CGH array platform. The algorithm enables the removal and rescue of false positive and false negative CNVs, respectively, which appear due to the effects of genomic variants of the reference sample in raw CGH array experiments. We found that the CARA remarkably enhanced the accuracy of CGH array in determining absolute CNVs. Our method thus provides a new approach to interpret CGH array data for personalized medicine.

Methods for comprehensive chromosome screening of oocytes and embryos: capabilities, limitations, and evidence of validity.

Preimplantation aneuploidy screening of cleavage stage embryos using fluorescence in situ hybridization (FISH) may no longer be considered the standard of care in reproductive medicine. Over the last few years, there has been considerable development of novel technologies for comprehensive chromosome screening (CCS) of the human genome. Among the notable methodologies that have been incorporated are whole genome amplification, metaphase and array based comparative genomic hybridization, single nucleotide polymorphism microarrays, and quantitative real-time PCR. As these methods become more integral to treating patients with infertility, it is critical that clinicians and scientists obtain a better understanding of their capabilities and limitations. This article will focus on reviewing these technologies and the evidence of their validity.

Clinical laboratory implementation of cytogenomic microarrays.

Examination of the whole genome for copy number alterations by microarray is now routinely done in many laboratories. The field of cytogenetics has evolved to adapt this technology, and the current phase of transition has resulted in the need for standardization in methodologies and interpretation of data. This review will outline some of the changes addressed in the field over the last several years and briefly discuss some of the trends in data processing, analysis and interpretation.

SNP array analysis in constitutional and cancer genome diagnostics--copy number variants, genotyping and quality control.

Array-based comparative genomic hybridization analysis of genomic DNA was first applied in postnatal diagnosis for patients with intellectual disability (ID) and/or congenital anomalies (CA). Genome-wide single-nucleotide polymorphism (SNP) array analysis was subsequently implemented as the first line diagnostic test for ID/CA patients in our laboratory in 2009, because its diagnostic yield is significantly higher than that of routine cytogenetic analysis. In addition to the detection of copy number variations, the genotype information obtained with SNP array analysis enables the detection of stretches of homozygosity and thereby the possible identification of recessive disease genes, mosaic aneuploidy, or uniparental disomy. Patient-parent (trio) information analysis is used to screen for the presence of any form of uniparental disomy in the patient and can determine the parental origin of a de novo copy number variation. Moreover, the outcome of a genotype analysis is used as a final quality control by ruling out potential sample mismatches due to non-paternity or sample mix-up. SNP array analysis is now also used in our laboratory for patients with disorders for which locus heterogeneity is known (homozygosity pre-screening), in prenatal diagnosis in case of structural ultrasound anomalies, and for patients with leukemia. In this report, we summarize our array findings and experiences in the various diagnostic applications and demonstrate the power of a SNP-based array platform for molecular karyotyping, because it not only significantly improves the diagnostic yield in both constitutional and cancer genome diagnostics, but it also enhances the quality of the diagnostic laboratory workflow.

A new normalizing algorithm for BAC CGH arrays with quality control metrics.

The main focus in pin-tip (or print-tip) microarray analysis is determining which probes, genes, or oligonucleotides are differentially expressed. Specifically in array comparative genomic hybridization (aCGH) experiments, researchers search for chromosomal imbalances in the genome. To model this data, scientists apply statistical methods to the structure of the experiment and assume that the data consist of the signal plus random noise. In this paper we propose "SmoothArray", a new method to preprocess comparative genomic hybridization (CGH) bacterial artificial chromosome (BAC) arrays and we show the effects on a cancer dataset. As part of our R software package "aCGHplus," this freely available algorithm removes the variation due to the intensity effects, pin/print-tip, the spatial location on the microarray chip, and the relative location from the well plate. removal of this variation improves the downstream analysis and subsequent inferences made on the data. Further, we present measures to evaluate the quality of the dataset according to the arrayer pins, 384-well plates, plate rows, and plate columns. We compare our method against competing methods using several metrics to measure the biological signal. With this novel normalization algorithm and quality control measures, the user can improve their inferences on datasets and pinpoint problems that may arise in their BAC aCGH technology.

Detection of copy-number variations from NGS data using read depth information: a diagnostic performance evaluation.

The detection of copy-number variations (CNVs) from NGS data is underexploited as chip-based or targeted techniques are still commonly used. We assessed the performances of a workflow centered on CANOES, a bioinformatics tool based on read depth information. We applied our workflow to gene panel (GP) and whole-exome sequencing (WES) data, and compared CNV calls to quantitative multiplex PCR of short fluorescent fragments (QMSPF) or array comparative genomic hybridization (aCGH) results. From GP data of 3776 samples, we reached an overall positive predictive value (PPV) of 87.8%. This dataset included a complete comprehensive QMPSF comparison of four genes (60 exons) on which we obtained 100% sensitivity and specificity. From WES data, we first compared 137 samples with aCGH and filtered comparable events (exonic CNVs encompassing enough aCGH probes) and obtained an 87.25% sensitivity. The overall PPV was 86.4% following the targeted confirmation of candidate CNVs from 1056 additional WES. In addition, our CANOES-centered workflow on WES data allowed the detection of CNVs with a resolution of single exons, allowing the detection of CNVs that were missed by aCGH. Overall, switching to an NGS-only approach should be cost-effective as it allows a reduction in overall costs together with likely stable diagnostic yields. Our bioinformatics pipeline is available at: https://gitlab.bioinfo-diag.fr/nc4gpm/canoes-centered-workflow .

Assessment of comparative genomic hybridization experiment by an in situ synthesized CombiMatrix microarray with Yersinia pestis vaccine strain EV76 DNA.

OBJECTIVE: The quality of microarray data influences the accuracy of comparative genomic analyses to a large extent. To ensure that the results obtained by using an in situ synthesized microarray are accurate, data quality is to be assessed by evaluating the melting temperature (Tm) of probes, probability of false synthesis rates, and fragmentation of labeled targets. METHODS: DNA from the Yersinia pestis vaccine strain EV76 was used for microarray analyses. Microarray results were confirmed by PCR. Statistical and bioinformatics methods were employed to perform microarray data analyses and evaluation. RESULTS: Correlation coefficients of the three datasets were above 0.95 after two-time stripping and hybridization with a labeled DNA with the size of fragmentation being 200 bp - 2 kb, which showed that the hybridization results were highly reproducible. Correlation coefficients were lower with the values ranging from 0.87 to 0.92 between the datasets generated from hybridization with different sizes of the labeled DNA fragment. For the relationship between Tm and signal intensity, there was a different distribution of Tm in the lowest 300 or 3,000 probes with a range of 70 °C-72 °C and the highest 300 or 3,000 probes with a range of 72 °C-74 °C. CONCLUSION: The results of this study suggest that the initial microarray design may affect the accuracy of final analyses and that the probe Tm and the size of the labeled fragment may be the two factors of the greatest importance.

Appropriateness of array-CGH in the ADHD clinics: A comparative study.

Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorder with a worldwide prevalence of about 5%. The disorder is characterized by inattentive, hyperactive and impulsive behavior and is often comorbid with other neuropsychiatric conditions. Array comparative genomic hybridization (array-CGH) testing has been proved to be useful to detect chromosomal aberrations in several neuropsychiatric conditions including autism spectrum disorders (ASD) and intellectual disability (ID). The usefulness of array-CGH in the ADHD clinics is still debated and no conclusive evidence has been reached to date. We performed array-CGH in 98 children and adolescents divided in two similarly sized groups according to the clinical diagnosis: (a) one group diagnosed with ADHD as primary diagnosis; (b) the other group in which ADHD was co-morbid with ASD and/or ID. We detected pathogenetic and likely pathogenetic copy number variants (CNVs) in 12% subjects in which ADHD was co-morbid with autism and/or intellectual disability and in 8.5% subjects diagnosed with ADHD as primary diagnosis. Detection of CNVs of unknown clinical significance was similar in the two groups being 27% and 32%, respectively. Benign and likely benign CNVs accounted for 61% and 59.5% in the first and second group, respectively. Differences in the diagnostic yield were not statistically significant between the two groups (P > .05). Our data strongly suggest that array-CGH (a) is a valuable diagnostic tool to detect clinically significant CNVs in individuals with ADHD even in the absence of comorbidity with ASD and/or ID and (b) should be implemented routinely in the ADHD clinics.

Clinical error rates of next generation sequencing and array comparative genomic hybridization with single thawed euploid embryo transfer.

We investigated clinical error rates with single thawed euploid embryo transfer (STEET) diagnosed by next generation sequencing (NGS) and array comparative genomic hybridization (aCGH). A total of 1997 STEET cycles after IVF with preimplantation genetic testing for aneuploidy (PGT-A) from 2010 to 2017 were identified; 1151 STEET cycles utilized NGS, and 846 STEET cycles utilized aCGH. Any abortions, spontaneous or elective, in which products of conception (POCs) were collected were reviewed. Discrepancies between chorionic villus sampling, amniocentesis, or live birth results and PGT-A diagnosis were also included. Primary outcomes were clinical error rate per: ET, pregnancy with gestational sac, live birth, and spontaneous abortion with POCs available for analysis. Secondary outcomes included implantation rate (IR), spontaneous abortion rate (SABR), and ongoing pregnancy/live birth rate (OPR/LBR). The clinical error rates in the NGS cohort were: 0.7% per embryo, 1% per pregnancy with gestational sac, and 0.1% rate per OP/LB. The error rate per SAB with POCs was 13.3%. The IR was 69.1%, the OPR/LBR was 61.6%, and the spontaneous abortion rate was 10.2%. The clinical error rates in the aCGH cohort were: 1.3% per embryo, 2% per pregnancy with gestational sac, and 0.4% rate per OP/LB. The error rate per SAB with POCs was 23.3%. The IR was 63.8%, the OPR/LBR was 54.6%, and the SAB rate was 12.4%. Our findings demonstrate that, although NGS and aCGH are sensitive platforms for PGT-A, errors still occur. Appropriate patient counseling and routine prenatal screening are recommended for all patients undergoing IVF/PGT-A.

A comparison of genomic diagnostics in adults and children with epilepsy and comorbid intellectual disability.

Next generation sequencing provides an important opportunity for improved diagnosis in epilepsy. To date, the majority of diagnostic genetic testing is conducted in the paediatric arena, while the utility of such testing is less well understood in adults with epilepsy. We conducted whole exome sequencing (WES) and copy number variant analyses in an Irish cohort of 101 people with epilepsy and co-morbid intellectual disability to compare the diagnostic yield of genomic testing between adult and paediatric patients. Variant interpretation followed American College of Medical Genetics and Genomics (ACMG) guidelines. We demonstrate that WES, in combination with array-comparative genomic hybridisation, provides a diagnostic rate of 27% in unrelated adult epilepsy patients and 42% in unrelated paediatric patients. We observe a 2.7% rate of ACMG-defined incidental findings. Our findings indicate that WES has similar utility in both adult and paediatric cohorts and is appropriate for diagnostic testing in both epilepsy patient groups.