Many epilepsy-associated genes have been identified over the last three decades, revealing a remarkable molecular heterogeneity with the shared outcome of recurrent seizures. Information about the genetic landscape of epilepsies is scattered throughout the literature and answering the simple question of how many genes are associated with epilepsy is not straightforward. Here, we present a computationally driven analytical review of epilepsy-associated genes using the complete scientific literature in PubMed. Based on our search criteria, we identified a total of 738 epilepsy-associated genes. We further classified these genes into two Tiers. A broad gene list of 738 epilepsy-associated genes (Tier 2) and a narrow gene list composed of 143 epilepsy-associated genes (Tier 1). Our search criteria do not reflect the degree of association. The average yearly number of identified epilepsy-associated genes between 1992 and 2021 was 4.8. However, most of these genes were only identified in the last decade (2010-2019). Ion channels represent the largest class of epilepsy-associated genes. For many of these, both gain- and loss-of-function effects have been associated with epilepsy in recent years. We identify 28 genes frequently reported with heterogenous variant effects which should be considered for variant interpretation. Overall, our study provides an updated and manually curated list of epilepsy-related genes together with additional annotations and classifications reflecting the current genetic landscape of epilepsy.

Objective: Determining the pathogenicity of missense variants in clinical genetic tests for individuals with epilepsy is crucial for guiding personalized treatment. However, achieving a definitive pathogenic classification remains challenging, with most missense variants still classified as variants of uncertain significance (VUS) and with the availability of many computational tools which may provide conflicting predictions. Here, we aim to evaluate the performance of state‐of‐the‐art computational tools in pathogenicity prediction of missense variants in epilepsy‐associated genes. This will assist in selecting the most appropriate tool and critically assess their use in clinical setting.Methods: We assessed the performance of nine in silico pathogenicity prediction tools for missense variants in epilepsy‐associated genes on three carefully curated data sets. The first two data sets comprise missense variants in epilepsy associated genes that have been uploaded to ClinVar in the last year and were, therefore, not part of the training set of any of the nine considered tools. These two data sets are based on two different lists of epilepsy‐associated genes and comprise ~700 and ~ 250 missense variants, respectively. The third data set includes ~400 missense variants within epilepsy‐associated genes for which the functional effects have been determined experimentally and are therefore used here to infer pathogenicity. These three data sets represent the best available approximation to blind and independent test sets.Results: Among the nine assessed tools, AlphaMissense (area under the curve [AUC]: .93, .88, and .95) and REVEL (AUC: .93, .88, and .93) showed the best classification performance, also outperforming other tools in the number of classified variants.Significance: We show which recently developed prediction tools achieve higher performance in epilepsy‐associated genes and should be integrated, therefore, into the American College of Medical Genetics and Genomics/Association of Molecular Pathology (AGMC/AMP) variant classification process. Periodic reevaluation of genetic test results with newly developed or updated tools should be incorporated into standard clinical practice to improve diagnostic yield and better inform precision medicine.

Mitochondrial disorders are multiorgan disorders resulting in significant morbidity and mortality. We aimed to characterize death-associated factors in an international cohort of deceased individuals with mitochondrial disorders. This cross-sectional multicenter observational study used data provided by 26 mitochondrial disease centers from 8 countries from January 2022 to March 2023. Individuals with genetically confirmed mitochondrial disorders were included, along with patients with clinically or genetically diagnosed Leigh syndrome. Collected data included demographic and genetic diagnosis variables, clinical phenotype, involvement of organs and systems, conditions leading to death, and supportive care. We defined pediatric and adult groups based on age at death before or after 18 years, respectively. We used Kruskal-Wallis with post hoc Dunn test with Bonferroni correction and Fisher exact test for comparisons, Spearman rank test for correlations, and multiple linear regression for multivariable analysis. Data from 330 deceased individuals with mitochondrial disorders (191 [57.9%] pediatric) were analyzed. The shortest survival times were observed in hepatocerebral syndrome (median 0.3, interquartile range [IQR] 0.2-0.6 years) and mitochondrial cardiomyopathy (median 0.3, IQR 0.2-5.2 years) and the longest in chronic progressive external ophthalmoplegia plus (median 26.5, IQR 22.8-40.2 years) and sensory ataxic neuropathy, dysarthria, and ophthalmoparesis (median 21.0, IQR 13.8-28.5 years). Respiratory failure and pulmonary infections were the most common conditions associated with death (52/330, 15.7% and 46/330, 13.9%, respectively). Noninvasive ventilation was required more often in children (57/191, 29.8%) than adults (12/139, 8.6%, p < 0.001), as was nasogastric or gastric tube (131/191, 68.6% in children and 39/139, 28.1% in adults, p < 0.001). On multivariate analysis, individuals with movement disorders and nuclear gene involvement had increased odds of any respiratory support use (OR 2.42 (95% CI 1.17-5.22) and OR 2.39 (95% CI 1.16-5.07), respectively). This international collaboration highlights the importance of respiratory care and infection management and provides a reference for prognostication across different mitochondrial disorders.

Purpose: The majority of missense variants in clinical genetic tests are classified as variants of uncertain significance. Broadening the evidence of the PS1 and PM5 criteria has the potential to increase conclusive variant interpretation. Methods: We hypothesized that incorporation of pathogenic missense variants in conserved residues across paralogous genes can increase the number of variants where ACMG PS1/PM5 criteria can be applied. We mapped over 2.5 million pathogenic and general population variants from ClinVar, HGMD, and gnomAD databases onto 9,990 genes and aligned these by gene families. Subsequently, we developed a novel framework to extend PS1/PM5 by incorporating pathogenic paralogous variants annotations (para-PS1/PM5). Results: We demonstrate that para-PS1/PM5 criteria increase the number of classifiable amino acids 3.6-fold compared to PS1 and PM5. Across all gene families with at least two disease-associated genes, the calculated likelihood ratios suggest moderate evidence for pathogenicity. Moreover, for 36 genes, the extended para-PS1/PM5 criteria reach strong evidence level. Conclusion: We show that single pathogenic paralogous variants incorporation at paralogous protein positions increases the applicability of the PS1 and PM5 criteria, likely leading to a reduction of variants of uncertain significance across many monogenic disorders. Future iterations of the ACMG guidelines may consider para-PS1 and para-PM5.

Background and objectives: multiple sclerosis (MS) is a chronic demyelinating disorder of the CNS with a variable course and disability progression. The latter may be prevented with disease-modifying therapy (DMT). Initial misdiagnosis may postpone the use of DMT. There are no studies to explore whether initial misdiagnosis is indeed associated with a higher rate of reaching disability in MS patients. We aimed to investigate the association between initial misdiagnosis and reaching disability milestones in relapsing-remitting MS (RR-MS) patients. Materials and methods: Data from 128 RR-MS patients were retrospectively reviewed. EDSS 4 and EDSS 6 were chosen as disability milestones as those associated with a significant decrease in ambulation. Survival analysis was used, and Kaplan–Meier curves were generated to investigate how initial misdiagnosis affects reaching the defined milestones. Results: 53 patients (41.4%, 31 females, 22 males) were initially misdiagnosed. Initially misdiagnosed patients had a lesser risk of reaching EDSS 4 up to 11 years and EDSS 6 up to 22 years from the onset than non-misdiagnosed patients (p = 0.22 and p = 0.25 correspondingly). Median time to reaching EDSS 4 and 6 was eight years (95% CI 0.0–17.6) and 10 years (95% CI 4.25–20.75) in misdiagnosed and three years (95% CI 0.0–20.0 years) and five years (95% CI 0.0–13.73 years) in non-misdiagnosed patients correspondingly. Conclusions: Initially misdiagnosed RR-MS patients tended to reach disability milestones later than non-misdiagnosed ones, which might reflect an intrinsically milder disease. Individuals presenting with mild or non-specific symptoms suspicious of MS, must be deliberately managed.