This study shows that individual oligogenic analysis is implementable in selected patients and represents a feasible addition to monogenic analysis, and could not identify any definite oligogenic combination.
Abstract
Objective
Genetic factors contribute to the majority of epilepsies, but the exact genetic cause remains unknown in most patients. Incomplete penetrance and variable expressivity are frequent, and recent studies showed a burden of deleterious variants in epilepsy genes, suggesting a role for oligogenic inheritance. Here, we investigated both monogenic and oligogenic inheritance in a large cohort of patients with epilepsy.
Methods
We used exome data of 422 patients and 5308 nonepileptic individuals generated by the Epi25 Collaborative project. First, a stepwise monogenic analysis was performed on all patients. Next, we restricted the cases and controls to samples sequenced with the same capture kit and removed ancestry outliers using a principal component analysis approach. We performed an oligogenic analysis on this set of samples using bioinformatic tools that predict the pathogenicity of variant combinations. We used two different approaches, a cohort-based approach in 240 patients and an individual approach in six severely affected patients.
Results
Monogenic pathogenic variants were identified in 16 patients. Oligogenic cohort-based analysis identified 12 gene combinations significantly overrepresented in cases compared to controls. Individual-based analysis identified networks of variants in six patients. Manual curation of each of the variant combinations and phenotypes could not definitively confirm pathogenicity, and all combinations were finally discarded.
Significance
Although we could not identify any definite oligogenic combination, our study shows that individual oligogenic analysis is implementable in selected patients and represents a feasible addition to monogenic analysis.
Abstract Objective To determine the frequency of monogenic variants and pathogenic copy number variants (CNVs) in adults with surgically treated temporal lobe epilepsy (TLE). Methods We performed exome sequencing (ES), including CNV analysis, in 45 adults with TLE who had previously undergone epilepsy surgery. A diagnostic exome‐wide analysis was conducted to identify (likely) pathogenic variants related to epilepsy. In an exploratory approach, we screened a curated list of 45 common epilepsy genes for rare deleterious variants based on AlphaMissense and REVEL in silico predictions. Results No highly penetrant monogenic variants were identified in this cohort. Pathogenic CNVs were detected in two individuals, corresponding to 4.4% of the cohort: a 16p13.11 deletion in a surgery responder and a 22q11.2 duplication in a surgery nonresponder. Both CNVs are characterized by reduced penetrance and broad phenotypic variability. Moreover, we identified two predicted deleterious missense variants in the epilepsy‐associated genes KCNT1 and SLC2A1, both of which were detected in surgery nonresponders. In silico analyses, including structural evidence, suggested a potential impact on protein function; however, their clinical significance remains uncertain. Significance Monogenic causes are exceedingly rare in adults with surgically treated TLE, whereas CNVs may contribute to disease susceptibility in a small subset of patients. Our findings are consistent with previous reports indicating a low diagnostic yield of presurgical genetic testing and further support a predominantly polygenic architecture of TLE. Plain Language Summary Temporal lobe epilepsy (TLE) is a common type of epilepsy in adults, and some patients undergo surgery when medications fail. It is unclear whether genetic testing can help predict surgical success. In this study, we used comprehensive genetic testing in 45 adult TLE patients who had undergone epilepsy surgery. We did not find single‐gene causes of epilepsy. Two patients had structural genetic changes, which increase epilepsy risk but show variable effects. We also identified a few rare variants in epilepsy‐related genes, but their clinical relevance remains uncertain. Overall, our results suggest that single‐gene causes are rare in adults with TLE. Genetic testing may therefore have a low diagnostic rate in this population.
Antonia P. Pirker, Margot Ernst, Matias Wagner et al.· Epilepsia Open· 0 citations
This is the second report of autosomal recessive epilepsy associated with biallelic CACNB4 variants and genetic investigations play a crucial role in identifying mutation hotspots, facilitating more accurate diagnoses and enhancing the design of diagnostic panels for early detection.
Epilepsy represents a highly prevalent neurological disorder with a significant genetic component, particularly implicating ion channel genes, including SCN1A. In this study, 431 individuals with heterogeneous paediatric-onset epilepsy phenotypes were assessed at the Department of Medical Genetics, University of Pécs between 2018 and 2024. Genetic investigations employed Sanger sequencing, targeted epilepsy gene panels, whole exome sequencing, and multiplex ligation-dependent probe amplification for SCN1A copy number analysis. Thirty-six pathogenic or likely pathogenic SCN1A variants were identified, including 15 variants which have not been reported previously. Furthermore, 9 novel variants were detected in 12 additional epilepsy-associated genes. Diagnostic yield was proportional to the breadth of genomic interrogation. WES analysis revealed 6 novel variants in 19 genes. These findings underscore the considerable genetic heterogeneity of epilepsy and demonstrate the clinical utility of gene panels and WES, particularly in complex phenotypes. The identification of novel variants enhances molecular understanding and facilitates more precise genotype-phenotype correlations, reinforcing the value of comprehensive genomic diagnostics in epilepsy management.
Renata Szalai, Á. Till, Krisztina Galimurka et al.· Human Genetics· 0 citations
This study may expand the mutation and phenotypic spectrum of SETD1A-related disorders, establishing the relationship between SETD1A variants and isolated early-onset epilepsy without accompanying severe neurodevelopmental deficits, and highlighting the value of genetic testing in infants with unexplained epilepsy.
Rina Su, Lei Zhu, Lin Jiang et al.· Frontiers in Neuroscience· 0 citations
BACKGROUND AND OBJECTIVES
Hypertrophic cardiomyopathy is a life-threatening disease with limited studies in Middle Eastern populations. This pilot study (n = 8) aimed to identify rare genetic variants to enable future presymptomatic diagnosis and primary prevention. While the sample size precludes establishing population-level prevalence, our findings provide a springboard for generating testable hypotheses for future multicenter trials.
METHODS
Whole-exome sequencing was performed on eight unrelated Egyptian patients. We prioritised variants using stringent criteria: allele frequency < 0.01 in gnomAD, combined annotation dependent depletion (CADD) score > 10, and focused analysis of 29 genes with definitive or moderate evidence for hypertrophic cardiomyopathy causation according to Clinical Genome Resource (ClinGen). Variants were ACMG/AMP-classified and correlated with detailed clinical phenotypes.
RESULTS
We identified 21 rare variants across 10 hypertrophic cardiomyopathy-associated genes. Core sarcomeric genes accounted for seven variants: MYBPC3 (n = 2; one likely pathogenic, p.Gly1206Asp), MYH7 (n = 2; one pathogenic, p.Phe252Ser), and TNNT2 (n = 3; all variants of uncertain significance). Additionally, likely pathogenic variants were found in PLN (p.Arg25Cys) and KLHL24 (p.Arg103*). Patients with pathogenic or likely pathogenic sarcomeric variants exhibited severe phenotypes, including septal thickness up to 30 mm, left ventricular outflow tract gradients up to 60 mmHg, and a high arrhythmic burden, influencing decisions like implantable cardioverter-defibrillator implantation and myectomy. Notably, all three TNNT2 carriers manifested atrial fibrillation or non-sustained ventricular tachycardia, reinforcing its arrhythmic risk. Four novel or likely pathogenic variants were submitted to ClinVar.
CONCLUSION
As the first genetic study of hypertrophic cardiomyopathy in an Egyptian population, this work expands the global mutational spectrum, demonstrates the utility of genetic testing for risk stratification and personalised management, and underscores the need to diversify genomic datasets for equitable precision medicine.
Rana E Negm, R. Gabre, Ahmed A. El‐Sherif et al.· Cardiology in the Young· 0 citations
Epilepsy genetics has often been interpreted through a useful but simplified dichotomous framework in which severe epilepsies, particularly developmental and epileptic encephalopathies, are attributed mainly to rare, high-effect variants, whereas more common epilepsies are viewed as arising largely from the cumulative effects of common, small-effect variation. Although this framework has been instrumental for gene discovery, molecular diagnosis, and mechanism-based treatment, it does not fully explain incomplete penetrance, intrafamilial phenotypic heterogeneity, or marked differences in severity among individuals sharing the same molecular diagnosis. Evidence from exome sequencing, copy number variant (CNV) studies, and genome-wide association studies increasingly suggests that rare SNVs/indels, CNVs, and common variant should not be interpreted as entirely independent risk sources, but may partially converge on shared genes, pathways, cell types, and neurobiological processes relevant to neuronal excitability, network stability, and seizure susceptibility. Here, we review evidence across epilepsy subtypes, focusing on convergence and divergence across the allelic spectrum, and discuss how polygenic background and other modifiers may influence penetrance and clinical expressivity among carriers of rare pathogenic variants and CNVs. We also consider implications for variant interpretation, genetic counseling, risk stratification, and precision medicine, while emphasizing that most rare–common integrated models remain insufficiently validated for routine clinical decision-making.
Ming-Shan Cai, Hou-Rui Li, Peng Liao et al.· Frontiers in Genetics· 0 citations