Multigene Panel Testing in Pediatric Epilepsy: Diagnostic Yield and Clinical Implications

Article information

Ann Child Neurol. 2026;34(3):192-200
Publication date (electronic) : 2026 July 1
doi : https://doi.org/10.26815/acn.2026.01389
1Department of Pediatrics, Seoul National University Hospital, Seoul, Korea
2Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Korea
3Department of Pediatrics, Seoul National University College of Medicine, Seoul, Korea
4Department of Genomic Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
5Department of Genomic Medicine, Seoul National University Hospital, Seoul, Korea
6Department of Laboratory Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
Corresponding author: Hunmin Kim, MD, PhD Department of Pediatrics, Seoul National University Bundang Hospital, 82 Gumi-ro 173beon-gil, Bundang-gu, Seongnam 13620, Korea Tel: +82-31-787-7289 E-mail: hunminkim@snubh.org
Received 2026 January 22; Revised 2026 March 5; Accepted 2026 March 29.

Abstract

Purpose

Genetic testing is increasingly being incorporated into the evaluation of pediatric epilepsy. This study aimed to describe the clinical characteristics of patients with epilepsy who received positive genetic diagnoses through gene panel testing and additional genetic analyses; identify clinical factors associated with a genetic diagnosis; and evaluate the clinical implications of genetic diagnoses.

Methods

We retrospectively reviewed pediatric patients with epilepsy evaluated at a tertiary referral center between January 2020 and December 2024 who underwent testing with a multigene panel curated to include 29 early-onset epilepsy genes. Selected patients with negative results underwent chromosomal microarray analysis and trio-based whole-exome sequencing. Clinical variables, including age at seizure onset, developmental status, neuroimaging findings, and family history, were analyzed. The impact of a positive genetic diagnosis was evaluated with respect to changes in antiseizure medication and family counseling.

Results

A total of 79 patients were included. Pathogenic or likely pathogenic variants were identified in 26.6% (21/79) of patients through gene panel testing. Among panel-negative cases, five additional patients received a genetic diagnosis, yielding an overall diagnostic rate of 32.9% (26/79). Among the clinical variables analyzed, earlier seizure onset (age <12 months) was the only factor significantly associated with gene panel positivity (P=0.002). Genetic diagnoses led to clinically meaningful management changes in 46.2% (12/26) of patients.

Conclusion

In this real-world pediatric epilepsy cohort, multigene panel testing provided substantial diagnostic yield and influenced clinical management. Seizure onset before 12 months was the strongest predictor of gene panel positivity, supporting routine genetic evaluation in early-onset epilepsy.

Introduction

Advances in genomic technologies have substantially expanded the role of genetic testing in the evaluation of pediatric epilepsy, particularly in cases with early seizure onset or suspected familial etiology [1-3]. For some genes, characteristic electroclinical phenotypes with prognostic implications have been identified [4,5]. A growing body of evidence supports targeted epilepsy gene panels as a first-line diagnostic approach, offering a practical balance among diagnostic yield, cost, and turnaround time [6,7]. However, in real-world clinical settings, the phenotypic heterogeneity of epilepsy and variable access to extended genomic testing continue to make it difficult to identify which patients are most likely to benefit from genetic evaluation and how test results translate into meaningful clinical action.

Although previous studies have largely focused on diagnostic yield, fewer have systematically examined factors associated with a genetic diagnosis [8,9]. In addition, the clinical significance of genetic diagnoses, including their effects on antiseizure medication (ASM) selection and family counseling, has not been fully characterized in routine practice [10]. Uncertainty about the immediate clinical benefit of genetic diagnosis may limit access to molecular testing, particularly among patients and families who are reluctant to undergo genetic evaluation [11]. Moreover, the value of stepwise testing strategies, including chromosomal microarray analysis (CMA) and whole-exome sequencing (WES) after negative multigene panel results, has not been fully explored in real-world settings [12].

In this study, we sought to address these gaps by evaluating pediatric patients with suspected genetic epilepsy who underwent targeted epilepsy gene panel testing. Specifically, our objectives were (1) to characterize the clinical features of patients with positive genetic diagnoses identified through gene panel testing; (2) to analyze clinical factors associated with gene panel positivity; and (3) to assess the clinical implications of genetic diagnoses in routine practice. We also evaluated the additional diagnostic value of extended genetic testing in patients with negative gene panel results. 

Materials and Methods

1. Subjects and materials

This study was conducted as a retrospective review of medical records. Children with epilepsy evaluated at Seoul National University Bundang Hospital between January 2020 and December 2024 were screened for eligibility. The inclusion criteria were (1) a clinical diagnosis of epilepsy; (2) a family history of epilepsy or suspected genetic epilepsy; and (3) completion of testing with an ‘early-onset epileptic encephalopathy gene panel’ during the study period. Suspected genetic epilepsy was determined clinically by a pediatric neurologist. The exclusion criteria were (1) age at seizure onset greater than 18 years and (2) the presence of major dysmorphisms, defined as ‘structural abnormality of morphogenesis that has significant medical, surgical, or cosmetic consequences and/or results in functional impairment, morbidity, or mortality, that occurs in <1% of the general population.’ All eligible patients were included in the final analysis.

2. Genetic testing and variant analysis

The multigene test panel consisted of 29 genes frequently associated with early-onset and genetic epilepsies, including genes implicated in developmental and epileptic encephalopathies and familial epilepsy syndromes (ALDH7A1, ARHGEF9, ARX, ATP1A2, CDKL5, CHD2, GABRA1, GABRB3, GABRG2, HCN1, IQSEC2, KCNA2, KCNQ2, KCNQ3, KCNT1, MECP2, MEF2C, PCDH19, PNPO, PRRT2, SCN1A, SCN1B, SCN2A, SCN8A, SLC25A22, SLC2A1, SPTAN1, STXBP1, and SYNGAP1).

Genomic DNA was extracted from peripheral blood samples, enriched using a targeted capture-based sequencing approach, and sequenced on the NextSeq 550Dx (Illumina Inc., San Diego, CA, USA) platform with Local Run Manager software version 2.4.0.2385 (Illumina Inc.). Sequencing yielded a mean depth of >150×, with 99.0% of targeted bases covered at ≥10×.

Sequencing data were processed using a standardized bioinformatics pipeline for alignment, variant calling, and annotation. Exonic variants causing nonsynonymous changes and intronic variants within ±10 base pairs of exon-intron boundaries were included in the analysis.

Identified variants were filtered according to allele frequency in population databases, including the Human Gene Mutation Database (http://www.hmgd.org) and the Genome Aggregation Database (https://gnomad.broadinstitute.org). Variants with a minor allele frequency >0.1% in any population were excluded. In silico pathogenicity was assessed using multiple algorithms, including SIFT, MutationTaster, and Align-GVGD. All retained variants were classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines [13]. Pathogenic variants, likely pathogenic variants, and variants of uncertain significance (VUS) were confirmed by Sanger sequencing when applicable. The gene panel configuration remained unchanged throughout the study period.

The diagnostic rate of gene panel testing was calculated. For patients with negative epilepsy gene panel results, CMA was subsequently performed to evaluate copy number variations. When CMA results were negative, trio-based WES was conducted (Fig. 1). Variant filtering, annotation, and classification for WES followed the same analytical framework used for the targeted gene panel, with a focus on genes previously linked to epilepsy.

Fig. 1.

Overall diagnostic flow of the cohort. CMA, chromosomal microarray analysis; WES, whole-exome sequencing.

3. Clinical analysis

For each eligible patient, data on sex, age at seizure onset, clustered seizures at onset (two or more seizures within 24 hours), and a history of status epilepticus were collected. Developmental status at seizure onset and at the last follow-up was determined clinically. Electroencephalography findings were extracted and categorized as normal, focal interictal epileptiform discharges, or generalized epileptiform discharges. Brain magnetic resonance imaging (MRI) findings were classified as positive if a potentially epileptogenic lesion was identified and as negative otherwise. A family history of epilepsy was also recorded. To identify clinical factors associated with gene panel positivity, associations between these clinical variables and gene panel positivity were analyzed.

To assess the clinical implications of a positive genetic diagnosis, changes in clinical management immediately after diagnosis were evaluated for each patient, with overlapping categories permitted. Specifically, selection or avoidance of ASMs, family screening, and reproductive counseling were assessed.

4. Statistical analysis

For descriptive statistics, medians and interquartile ranges were used for continuous variables. For inferential analyses, the chi-square test or Fisher exact test was used for categorical variables, and the Mann–Whitney U test was used for continuous variables. A P<0.05 was considered statistically significant. Statistical analyses were performed using IBM SPSS Statistics version 31 (IBM Co., Armonk, NY, USA). GraphPad Prism version 10.2.3 (GraphPad Software Inc., San Diego, CA, USA) was used to generate the figures.

5. Ethics statement

This study was approved by the Institutional Review Board of Seoul National Bundang University Hospital (IRB No. B-2503-958-102). The requirement for informed consent was waived because of the retrospective study design.

Results

1. Clinical characteristics of the study population

A total of 79 patients with suspected genetic epilepsy or a familial epilepsy background were included in the analysis. Forty-five patients (57.0%) were male, and the median age at seizure onset was 11.9 months. Developmental delay was present in 16 patients (20.3%) at seizure onset and increased to 38 patients (48.1%) at the last follow-up. Clustered seizures at onset were reported in 25 patients (31.6%), and seven patients (8.9%) had status epilepticus. Structural abnormalities on brain MRI were identified in 11 cases (13.9%), and 10 patients (12.7%) had a first-degree family history of epilepsy (Table 1).

Clinical characteristics of the study population according to gene panel results

2. Summary of genetic testing results

Through multigene panel testing, seven pathogenic variants, 10 likely pathogenic variants, and 16 VUS were identified. Among the 16 VUS, four were reclassified as likely pathogenic according to ACMG guidelines, yielding a final diagnostic rate of 26.6% (21/79). Among the 58 panel-negative patients, 16 underwent CMA, and two received an additional genetic diagnosis (Table 2 and Fig. 1). WES was performed in five panel-negative patients and yielded three additional genetic diagnoses (DLG4, FMR1, SHANK3) (Table 2). Overall, this stepwise approach resulted in a total diagnostic rate of 32.9%.

Summary of clinical characteristics and changes in management for genetic diagnosis

Variants identified through multigene panel testing involved well-established epilepsy-associated genes, including PRRT2 (n=5), SCN1A (n=5), SCN2A (n=3), PCDH19 (n=3), STXBP1 (n=2), CDKL5 (n=1), KCNQ3 (n=1), and SYNGAP1 (n=1) (Table 2). The distribution of seizure onset ages showed gene-specific patterns. PRRT2 showed a consistent pattern of onset in early infancy, typically between 4 and 6 months. PCDH19 cases presented from early infancy through the first year of life. In contrast, SCN1A cases showed a broader onset range extending from early infancy through later toddlerhood (Fig. 2A).

Fig. 2.

Age at seizure onset and genetic diagnosis. (A) Distribution of specific genes according to age at seizure onset. Each box represents a patient who received a genetic diagnosis through gene panel testing. The distribution of seizure onset ages demonstrated gene-specific patterns. PRRT2 showed clustered onset between 4 and 6 months, PCDH19-associated cases presented around the first year of life, and SCN1A-associated cases exhibited a broader onset range from 4 to 36 months. (B) Age at seizure onset by gene panel positivity. The median age at seizure onset and 95% confidence intervals (CIs) are shown for the panel-positive and panel-negative groups. The median age at seizure onset was 4.6 months (95% CI, 3.30 to 8.50) in the panel-positive group and 13.4 months (95% CI, 10.1 to 25.2) in the panel-negative group. (C) Distribution of age at seizure onset and genetic diagnosis. Each bar represents a patient according to age at seizure onset and genetic diagnostic status. Red bars indicate patients with positive gene panel results, blue bars indicate patients with positive chromosomal microarray analysis (CMA) or whole-exome sequencing (WES) results, and gray bars indicate patients with negative genetic results. The distribution of seizure onset ages demonstrates enrichment of early-onset presentations among gene panel-positive cases, whereas the panel-negative group shows a broader distribution. aSignificant difference between groups.

3. Factors affecting positive gene panel testing

To identify clinical factors associated with gene panel positivity, we compared baseline variables at the time of evaluation, including age at seizure onset, sex, clustered seizures at onset, history of status epilepticus, abnormal brain MRI findings, developmental delay, and first-degree family history of epilepsy. Among these factors, age at seizure onset was the only variable significantly associated with gene panel positivity, whereas the remaining clinical variables did not differ significantly between the positive and negative groups (Table 1 and Fig. 2B).

Consistent with this finding, the distribution of seizure onset age showed enrichment of early-onset presentations among gene panel-positive cases. Seventeen of 21 panel-positive patients had seizure onset within the first 12 months, 19 of 21 within 24 months, and all 21 within 36 months. Seizure onset before 12 months was associated with significantly higher panel positivity (41.5% vs. 10.5%, P=0.002). In contrast, the panel-negative group showed a broader onset distribution, with a larger proportion of later-onset cases beyond early childhood (Fig. 2C).

4. Clinical implications of genetic diagnosis

Among the 26 patients with a genetic diagnosis, 12 (46.2%) experienced clinically meaningful management changes attributable to the genetic findings. These implications were summarized as discrete action items, with overlapping categories permitted. Specifically, the most frequent consequence was selection or avoidance of ASMs (n=7). In addition, family screening was undertaken in four patients, and family planning-related genetic counseling was performed in two. Notably, 11 of the 12 patients with management changes after genetic diagnosis were identified through gene panel testing, highlighting the practical utility of this approach.

Discussion

1. Real-world diagnostic utility of targeted epilepsy gene panel testing

In this study, we showed that targeted epilepsy gene panel testing provided substantial diagnostic value in a real-world pediatric epilepsy cohort. The diagnostic yield of 26.6% is consistent with previously reported yields for targeted multigene panel-based approaches, which range from 18 to 28% [3,14,15]. Seizure onset before 12 months of age was significantly associated with gene panel positivity, consistent with previous reports [7].

Our cohort reflects routine clinical practice rather than a highly selected research population. Patients were referred for genetic testing based on broadly applicable clinical indicators, such as early seizure onset or a family history of epilepsy, rather than predefined electroclinical syndromes or severe developmental impairment. The relatively high diagnostic yield observed in our cohort suggests that clinically meaningful genetic diagnoses can be obtained even when classic ‘red flags’ for genetic epilepsy are not uniformly present [2].

Despite the continued expansion in the number of genes associated with epilepsy, a limited subset accounts for most identified variants [14]. In our cohort, variants were identified in eight of the 29 curated genes, and the top five genes (SCN1A, PRRT2, PCDH19, SCN2A, and STXBP1) accounted for 69.2% of genetic diagnoses. Previous studies have shown that 20 to 30 genes account for more than 80% of genetic diagnoses in epilepsy, supporting the use of multigene panel testing as a first-tier diagnostic approach for pediatric epilepsy [12,14]. A meta-analysis showed that gene panel testing was the most cost-effective diagnostic modality [16].

In our cohort, CMA was positive in two of 16 patients, yielding a diagnostic rate of 12.5%. The reported diagnostic yield of copy number variants is approximately 10%, which is consistent with our findings [3,14]. Because copy number variants may not be detected by gene panel testing or short-read WES, CMA can be considered in panel-negative cases before conducting WES [12].

In the rapidly evolving landscape of genetic testing technology, recent studies suggest the utility of WES or whole-genome sequencing (WGS) as first-tier testing in epilepsy [17]. More recently, WGS has emerged as a robust tool for genetic evaluation in neonatal and infantile epilepsy in research settings [18]. As a first-tier test, WGS not only improved diagnostic performance but also showed potential cost savings in 94.05% of simulations [19]. However, because access to WES and WGS remains variable, expert agreement on first-tier testing in epilepsy remains below 50%, according to an online survey of 45 centers across 23 European countries [20]. In Korea, lack of insurance coverage remains a major barrier to the use of WES or WGS as a first-tier test. Therefore, targeted epilepsy gene panels offer a favorable balance between diagnostic yield and feasibility in real-world clinical practice at the time of writing.

2. Clinical impact of genetic diagnosis on patient management

Our study shows that genetic diagnosis in pediatric epilepsy can lead to meaningful clinical changes beyond etiologic classification. Among patients with a confirmed genetic diagnosis, approximately half underwent direct modifications in clinical management, consistent with previous reports [7,12]. One of the most important effects of genetic diagnosis was on ASM management. In patients with PRRT2-related epilepsy, identification of a pathogenic variant supported the diagnosis of self-limited familial infantile epilepsy and facilitated rapid tapering of ASMs in accordance with the typically favorable natural course [21]. In these cases, the genetic diagnosis increased clinician confidence in avoiding overtreatment and in counseling families regarding expected seizure remission.

In addition, genetic diagnoses informed medication avoidance and expectation management in other genetic epilepsies. In patients with SCN1A variants, confirmation of a genetic etiology supported avoidance of sodium channel-blocking ASMs (e.g., oxcarbazepine), which are known to exacerbate seizures in this population [8,22]. Similarly, in patients with SCN2A variants, decisions regarding sodium channel-targeting agents were optimized, either supporting their use in early-onset cases or prompting reconsideration and treatment modification in others [23].

Identification of PCDH19 variants helped explain seizure clustering patterns and variable treatment responsiveness, thereby reducing uncertainty when seizure control remained incomplete despite multiple medication trials [24]. In these cases, the genetic diagnosis shifted the focus of management from aggressive escalation of ASMs to a more expectant approach, thereby minimizing adverse effects. These examples illustrate that the clinical impact of genetic diagnosis is not limited to the availability of gene-specific therapies.

3. Implications of genetic diagnosis on family screening and reproductive counseling

Genetic diagnoses also had important implications for family screening. In one patient with an SCN1A variant, a family history of febrile seizures in the paternal lineage prompted genetic testing of a second-degree relative, which identified the same variant and enabled a diagnosis of genetic epilepsy with febrile seizures plus. In another patient with an SCN1A variant, both parents had a history of early-life seizures and underwent genetic testing with negative results, supporting a diagnosis of Dravet syndrome in the patient. In one patient with a PRRT2 variant, genetic testing was performed in a sibling with febrile seizures; the result was negative, providing reassurance regarding the sibling’s prognosis.

Genetic diagnoses also had important implications for reproductive counseling. In one patient with a PCDH19 variant, the patient’s mother had intellectual disability and a history of clustered seizures. Identification of the same pathogenic variant clarified the mother’s diagnosis and enabled appropriate reproductive counseling. In another patient with a PCDH19 variant, a male sibling was screened to determine whether he carried the same variant. The result was negative, providing reassurance to the family.

4. Limitations

Several limitations of this study should be acknowledged. First, this was a retrospective, single-center study with a relatively small sample size, which may limit the generalizability of our findings and reduce statistical power to detect associations with less prevalent clinical factors. As a result, some potentially relevant predictors of genetic diagnosis may not have reached statistical significance. Second, patient selection was based on clinical suspicion of genetic epilepsy, including early seizure onset or a family history of epilepsy, introducing inherent referral and selection bias. Consequently, the diagnostic yield observed in this cohort may not be directly applicable to unselected pediatric epilepsy populations. Third, genetic testing strategies were not uniform across all patients. Although all patients underwent targeted epilepsy gene panel testing, subsequent CMA or trio-based WES was performed only in a subset of panel-negative patients, depending on clinical judgment and parental consent. This heterogeneity in sequential testing may have led to underestimation of the true overall genetic diagnostic yield. Fourth, the inherent technical limitations of multigene panel testing should be acknowledged, as such panels cannot detect repeat expansions, deep intronic variants, and methylation defects. Rapid technological advances in WES and WGS, together with increasing accessibility, should also be considered. Finally, although we documented clinically meaningful management changes following genetic diagnosis, the study was not designed to systematically evaluate long-term outcomes, such as sustained seizure control, neurodevelopmental trajectories, or quality of life. Future prospective studies with standardized follow-up are warranted to assess the longitudinal impact of genetic diagnosis on long-term clinical outcomes in pediatric epilepsy.

5. Conclusion

In this real-world pediatric epilepsy cohort, targeted epilepsy gene panel testing yielded a substantial diagnostic rate and provided clinically meaningful information that influenced patient management and family counseling. Earlier seizure onset was the key predictor of gene panel positivity. These findings support the integration of genetic testing into routine epilepsy care, particularly for patients with early-onset seizures.

Notes

Conflicts of interest

Anna Cho and Jaeso Cho are managing editors and Jong-Hee Chae is a member of the editorial board of this journal, but they were not involved in the peer reviewer selection, evaluation, or decision process of this article. No other potential conflicts of interest relevant.

Author contribution

Conceptualization: YHK, JC, SL, HK, BCL, and JHC. Data Curation: YHK, JC, and SHS. Formal analysis: YHK. Funding Acquisition: AC, HK, and JHC. Methodology: YHK, JC, SL, SHS, and AC. Project administration: SL, AC, HK, BCL, and JHC. Writing-original draft: YHK and JC. Writing-review & editing: YHK, JC, AC, and HK.

Acknowledgments

This work was supported by Seoul National University Bundang Hospital Research Fund (grant number 16-2024-0012).

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Article information Continued

Fig. 1.

Overall diagnostic flow of the cohort. CMA, chromosomal microarray analysis; WES, whole-exome sequencing.

Fig. 2.

Age at seizure onset and genetic diagnosis. (A) Distribution of specific genes according to age at seizure onset. Each box represents a patient who received a genetic diagnosis through gene panel testing. The distribution of seizure onset ages demonstrated gene-specific patterns. PRRT2 showed clustered onset between 4 and 6 months, PCDH19-associated cases presented around the first year of life, and SCN1A-associated cases exhibited a broader onset range from 4 to 36 months. (B) Age at seizure onset by gene panel positivity. The median age at seizure onset and 95% confidence intervals (CIs) are shown for the panel-positive and panel-negative groups. The median age at seizure onset was 4.6 months (95% CI, 3.30 to 8.50) in the panel-positive group and 13.4 months (95% CI, 10.1 to 25.2) in the panel-negative group. (C) Distribution of age at seizure onset and genetic diagnosis. Each bar represents a patient according to age at seizure onset and genetic diagnostic status. Red bars indicate patients with positive gene panel results, blue bars indicate patients with positive chromosomal microarray analysis (CMA) or whole-exome sequencing (WES) results, and gray bars indicate patients with negative genetic results. The distribution of seizure onset ages demonstrates enrichment of early-onset presentations among gene panel-positive cases, whereas the panel-negative group shows a broader distribution. aSignificant difference between groups.

Table 1.

Clinical characteristics of the study population according to gene panel results

Clinical variables Panel positive (n=21) Panel negative (n=58) P value
Sex
 Male 12 33 0.984
 Female 9 25
Age of seizure onset 4.6 (3.25-10.3) 13.4 (5.83-34.7) <0.001
 Age <12 mo 17 24 0.002
 Age >12 mo 4 34
Clustered seizurea 8 17 0.586
Status epilepticus 0 7 0.180
EEG at onset 0.466
 Normal 10 25
 Focal IED 10 29
 Generalized IED 0 4
Abnormal MRI 3 8 0.999
Developmental delayb 12 26 0.442
Family history of epilepsy 4 6 0.445

Values are presented as number or median (interquartile range).

EEG, electroencephalography; IED, interictal epileptiform discharge; MRI, magnetic resonance imaging.

a

Defined as two or more seizures within 24 hours;

b

Developmental delay at the last follow-up.

Table 2.

Summary of clinical characteristics and changes in management for genetic diagnosis

Gene name Position Sex Seizure onset age (mo) Seizure clustering history Status epilepticus history Abnormality in brain MRI Delayed development at onset Family history of epilepsy Development at last follow-up Change in management
CDKL5 p.Asp135Val M 2 Yes No Yes No No Yes None
DLG4 p.Gly324AlafsTer56 F 72 No No No Yes No Yes None
FMR1 p.Gln541Ter M 45 No Yes Yes Yes No Yes Re-phenotyping
KCNQ3 p.Arg330Leu F 0 Yes No No No No No None
PCDH19 p.Asp121Asn F 4 No No No Yes Yes Yes Family screening
PCDH19 p.Lys116Asnfs*2 F 7 Yes No No Yes Yes Yes Family planning
PCDH19 p.Asp124His M 12 Yes No No Yes No Yes None
PRRT2 p.Lys206Ilefs*17 F 4 Yes No No No Yes No ASM change, family screening
PRRT2 p.Arg217Profs*8 M 5 No No No No No No ASM change
PRRT2 p.Arg217Glufs*12 M 5 No No No No No No ASM change
PRRT2 p.Arg217Profs*8 F 6 No No No No No No None
PRRT2 p.Arg217Profs*8 M 6 Yes No No No Yes Yes None
SCN1A c.965-3C>G F 3 No No No No Yes Yes ASM change
SCN1A p.Tyr349His M 27 No No No No Yes No ASM change, family screening
SCN1A p.Tyr426Cys M 3 No No No No No Yes ASM change
SCN1A p.Val971Ile F 9 No No No Yes No Yes None
SCN1A p.Val244Ala F 20 No No No No Yes No Family screening
SCN2A p.Ala202Val M 0 No No Yes Yes No Yes None
SCN2A p.Val892Ile M 4 No No No Yes No No Family planning
SCN2A p.Asn990Ile M 3 No No No No Yes No ASM change
SHANK3 p.Leu1602SerfsTer4 F 65 No No No Yes No Yes None
STXBP1 p.Gly193Glu M 0 No No Yes Yes No Yes None
STXBP1 p.Met252Val F 25 Yes No No No No Yes None
SYNGAP1 p.Lys114fs M 12 Yes No No Yes No Yes None
2p25.3 deletion M 8 No No Yes No Yes No None
2q24.3 deletion M 7 No No No Yes Yes Yes None

MRI, magnetic resonance imaging; ASM, antiseizure medication.