Epilepsy is characterized by widespread structural brain alterations extending beyond the epileptic zone, involving both cortical and subcortical regions. Importantly, the clinical manifestation of epilepsy, including seizure types, psychiatric comorbidities, and treatment responses, has been shown to differ between sexes. However, sex differences in structural alterations in epilepsy have been seldomly reported in neuroimaging studies, partly due to limited sample sizes and single-center designs. Here, we systematically investigated sex differences in common epilepsies and their related clinical variables using structural neuroimaging biomarkers in an international multi-center cohort of 1,253 epilepsy patients and 1,077 healthy controls. We studied cortical thickness and subcortical volume in two types of epilepsy: temporal lobe epilepsy (TLE) and genetic generalized epilepsy (GGE). Both male and female patients with TLE showed widespread cortical and subcortical thinning compared with controls. In GGE, when compared separately to controls, male patients showed only subtle structural alterations, whereas female patients exhibited more widespread structural alterations. Sex-stratified analyses revealed some variation in the extent and distribution of cortical thickness and subcortical volume alterations between male and female patients in both epilepsy cohorts. Yet, we did not find significant sex-by-diagnosis interaction effects in TLE and GGE. Similarly, no significant interaction effects were observed between sex and age of onset or disease duration in either patient group. Overall, although we observed some differences in regional cortical thickness and subcortical volume between male and female patients with epilepsy, we did not find significant sex-by-diagnosis interactions. Our findings indicate that sex differences in behavioral and clinical outcomes of epilepsy may involve biological or functional processes that require further investigation.

Background and Objectives:Disease-causing variants in the syntaxin-binding protein 1 (STXBP1) gene are among the most common genetic causes of developmental and epileptic encephalopathies and are associated with a wide phenotypic spectrum. Qualitative neuroimaging studies are usually unrevealing or uncover variable MRI findings, including cortical atrophy, thin/dysmorphic corpus callosum (CC), hypo/delayed myelination, and focal cortical dysplasia (FCD). Methods:We used quantitative MRI methods to estimate abnormal brain properties of the cortical mantle and volume of subcortical structures in patients with STXBP1 encephalopathy and age- and sex-matched controls.We performed a region-of-interest group statistical analysis between patients with STXBP1 encephalopathy and controls by multivariable linear regression models to identify morphometric patterns and to evaluate the effect of the group (patients/controls) on morphometric features. We conducted a longitudinal analysis to estimate the volumetric changes in 4 patients with serial MRI scans at different ages. We calculated the association between the structural alterations and the known STXBP1 expression levels and explored associations between morphometric and volumetric features and clinical findings (age at seizure onset, intellectual disability [ID]) and genetic variants. Results:Our analysis included 24 patients and 48 controls and revealed widespread cortical thickening, reduced frontal and occipital surface area, and reduced white matter (left/right hemisphere p value = 0.005/0.022) and CC (p value < 0.050) volumes. The longitudinal analysis highlighted that brain growth trends were lower than the average trend in the control cohort. In patients with more severe ID, we observed a significantly increased volume of the lateral ventricles (left/right p value = 0.049/0.030) and CSF (p value = 0.019). Patients with missense variants exhibited more altered morphometric values and more severe reductions of white-matter volumes, possibly because of a dominant negative effect of variants. Two patients were operated for intractable focal seizures, and the histopathologic substrate was FCD-I. Discussion:The altered cortical patterns and WM reductions we observed in STXBP1 encephalopathy might be the structural counterpart of the widespread impaired neurotransmitter release caused by a dysfunctional syntaxin-binding protein. The 2 histopathologic observations we describe, bring to 4 the number of reported patients with STXBP1 encephalopathy and FCD-I, suggesting cortical dyslamination as the architectural substrate for the abnormal morphometric parameters and reduced surface areas.

Diagnostic MRI evaluation of temporal lobe epilepsy (TLE) depends on the subjective visual interpretation of MRI images. These interpretations could be enhanced by quantitative artificial intelligence (AI) support tools. Humans often make sequential and conditional decisions during their radiological interpretations, such as whether an abnormality is present and, if present, characterizing the abnormality. It is not known whether it is superior to train AI to treat every decision separately in a similar step-wise manner or to train a model holistically on all decisions simultaneously. Here, we analysed three large epilepsy MRI datasets [n = 3676, 2320 people with epilepsy and 1356 healthy controls (HC)] to perform two tasks: (i) establish the presence of a TLE pattern on MRI and (ii) determine TLE pattern lateralization. We compared Step-wise models that independently classify TLE versus HC and lateralize patients as left TLE (L-TLE) or right TLE (R-TLE), against a simultaneous model trained to distinguish all three classes in a single step. To do this, 3D volumetric T1-weighted images were input into an EfficientNetV2 model multiple times to ensure reproducibility of results. Class prediction, model classification confidence and saliency maps were output for interpretability. Step-wise models outperformed the Simultaneous model on both tasks (both Ps < 0.001), with an average ∼2.8% accuracy increase for discriminating HC from TLE and an average 12.7% accuracy increase for distinguishing L-TLE from R-TLE. For both the Step-wise and Simultaneous models, important features discriminating TLE from HC included the known TLE limbic pattern involving the hippocampus, parahippocampal cortical regions, cingulate cortex and lateral temporal regions. However, there was less concordance between the Step-wise and Simultaneous models for the L-TLE versus R-TLE task (all Fisher's Zs > 10.5, Ps < 0.001); the Step-wise model focused less on subcortical regions such as the thalamus and hippocampus and focused more on distributed cortical pathology. Across the two Step-wise models, 95.1% of TLE patients had accurate classifications in either HC versus TLE and/or L-TLE versus R-TLE tasks. These results included 69.6% of patients being both correctly labelled as TLE and lateralized, 13.9% being correctly labelled TLE but lateralized incorrectly and 11.6% being lateralized correctly but not detected as TLE. These findings provide evidence that diagnostic tasks with simpler, Step-wise AI models may enhance diagnostic performance and interpretability in clinical workflows. Future AI clinical support tools can leverage this step-wise approach in the early identification of TLE-related structural patterns, supporting timely diagnosis and treatment decisions.

INTRODUCTION:Focal epilepsy is a leading cause of neurological disability, with about one-third of patients failing to achieve seizure freedom despite numerous antiseizure medications (ASMs) are available. Most current therapies broadly modulate synaptic transmission, leading to dose-limiting cognitive, psychiatric, and systemic adverse effects. Kv7 (KCNQ) potassium channels, responsible for the neuronal M-current, represent a high-precision therapeutic target that regulates intrinsic excitability and provides a fundamental 'molecular brake' against pathological firing. AREAS COVERED:This mini-review summarizes the clinical evolution of Kv7 modulation, from the first-generation prototype ezogabine to more selective second-generation candidates. We outline the scientific rationale for targeting the M-current, review emerging clinical data for agents such as azetukalner (XEN1101) and opakalim (BHV-7000), and highlight preclinical strategies including dual-mechanism modulators and drug repurposing. EXPERT OPINION:Kv7 agonists offer a mechanistically elegant approach to restoring seizure resistance. Second-generation agents provide encouraging mechanistic and clinical proof-of-concept, but long-term success will depend on clear advantages in patient-centered outcomes over established ASMs. Future value is likely to lie in precision-medicine strategies for KCNQ2/3-related encephalopathies and a carefully defined role in managing neuropsychiatric comorbidities.

OBJECTIVE:The polygenic risk score (PRS) for individuals with genetic generalized epilepsy (GGE) quantifies the common risk variants in genes identified in genome-wide association studies. We hypothesized that the phenotype of GGE patients differs based on their GGE PRS. METHODS:We identified participants with highest (n = 59) versus lowest (n = 48) PRS from the GGE patients (n = 2256) recruited through the Epi25 Collaborative for comparison. Detailed clinical data were acquired retrospectively for the 59 high PRS and 48 low PRS individuals with GGE from the Epi25 database and from the contributing centers. For validation, we accessed a larger cohort (n = 1175) of patients with GGE included in the Epi25 Collaborative. RESULTS:This study found no difference in phenotypic features of patients between the high-PRS GGE and low-PRS GGE subgroups, including age at onset, family history, and specific GGE syndrome. However, more patients from the lowest compared to the highest PRS subgroup were pharmacoresistant (31.7% vs. 8.9%, p = .01). On validation in a larger cohort, the PRS did not differ in the group of pharmacoresistant compared to nonpharmacoresistant patients. SIGNIFICANCE:No meaningful association between PRS and age at onset, history of febrile seizures, pre-/perinatal complications, epilepsy syndromes, seizure types, co-occurrence of functional/dissociative (nonepileptic) seizures, psychiatric comorbidities, electroencephalographic/magnetic resonance imaging findings, or drug response could be demonstrated in this study of people with GGE.

Extensive neuroimaging research in temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) has identified brain atrophy as a disease phenotype. While it is also related to a complex genetic architecture, the transition from genetic risk factors to brain vulnerabilities remains unclear. Using a population-based approach, we examined the associations between epilepsy-related polygenic risk for HS (PRS-HS) and brain structure in healthy developing children, assessed their relation to brain network architecture, and evaluated its correspondence with case-control findings in TLE-HS diagnosed patients relative to healthy individuals. We used genome-wide genotyping and structural T1-weighted MRI of 3826 neurotypical children from the Adolescent Brain Cognitive Development (ABCD) study. Surface-based linear models related PRS-HS to cortical thickness measures, and subsequently contextualized findings with structural and functional network architecture based on epicentre mapping approaches. Imaging-genetic associations were then correlated to atrophy and disease epicentres in 785 patients with TLE-HS relative to 1512 healthy controls aggregated across multiple sites. Higher PRS-HS was associated with decreases in cortical thickness across temporo-parietal as well as fronto-central regions of neurotypical children. These imaging-genetic effects were anchored to the connectivity profiles of distinct functional and structural epicentres. Compared with disease-related alterations from a separate epilepsy cohort, regional and network correlates of PRS-HS strongly mirrored cortical atrophy and disease epicentres observed in patients with TLE-HS and were highly replicable across different studies. Findings were consistent when using statistical models controlling for spatial autocorrelations and robust to variations in analytic methods. Capitalizing on recent imaging-genetic initiatives, our study provides novel insights into the genetic underpinnings of structural alterations in TLE-HS, revealing common morphological and network pathways between genetic vulnerability and disease mechanisms. These signatures offer a foundation for early risk stratification and personalized interventions targeting genetic profiles in epilepsy.

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for exploring cellular diversity, but isolating intact cells from complex tissues like the brain remains challenging. Single-nucleus RNA sequencing (snRNA-seq) overcomes these limitations by profiling nuclear RNA from frozen or archived tissue, reducing dissociation bias. Here, we present a simplified protocol for nuclei isolation from frozen human brain biopsies optimized for high yield and minimal debris, enabling robust snRNA-seq analysis. To validate it, we applied the protocol to biopsies from two pediatric patients with mild malformation of cortical development with oligodendroglial hyperplasia and epilepsy (MOGHE) carrying somatic SLC35A2 variants. snRNA-seq of isolated nuclei revealed a marked increase in oligodendrocytes in MOGHE samples, consistent with histopathological observations. Differential gene-expression analysis of oligodendrocyte-derived nuclei showed potential dysregulation of key pathways, including NOTCH, WNT/β-catenin, SLIT/ROBO, and Rho-GTPases signaling, as well as pathways associated with oxidative stress and neuroinflammation, and impaired neuron-glia communication. Despite advances in transcriptomic chemistries allowing fixed-cell analyses, reliable and debris-free nuclei isolation remains essential for generating high-quality single-nucleus data. Our streamlined protocol offers a reproducible, adaptable approach compatible with current and emerging snRNA-seq technologies.

Background and ObjectivesAutosomal recessive DNAJC12 disease, the most recently identified disorder of biogenic amine synthesis, presents with a broad clinical spectrum and variable outcomes, ranging from asymptomatic patients to early-onset parkinsonism. This study aimed to better outline the clinical phenotype and outcomes of DNAJC12 disease, the prognostic value of the metabolic and genetic biomarkers, and the treatment response.MethodsWe systematically collected clinical, biochemical, and genetic data from 56 patients with DNAJC12 disease in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines: 51 from the literature since the disease was first described and 5 unpublished personal cases.ResultsThree prevalent clinical patterns of presentation and outcome were identified: (1) asymptomatic condition, (2) neurodevelopmental disorders (NDD) leading to intellectual disability with psychiatric issues and dystonia-parkinsonism (D-P) during the second decade of life in some patients, and (3) early-onset static l-dopa-responsive parkinsonism in previously asymptomatic adult patients. Hyperphenylalaninemia was the most consistent metabolic alteration. CSF depletion of homovanillic acid (HVA) and 5-HIAA was detected in 18 and 20 of 29 symptomatic patients, respectively. Three stepwise regression analyses identified significant predictors of clinical outcomes in patients with phenylketonuria (PKU). CSF HVA levels and phenylalanine levels at diagnosis predicted the occurrence of D-P, while 26% of intellectual disability variability was explained by CSF HVA at diagnosis, and 31% of psychiatric disorder variability by later age at diagnosis. The phenotype was consistently associated with only a few DNAJC12 pathogenic variants, primarily for phenotypes A and C.Movement disorders responded positively to the various therapies in all symptomatic patients. The preventive effects on NDD and psychiatric problems were less clear.ResultsThree prevalent clinical patterns of presentation and outcome were identified: (1) asymptomatic condition, (2) neurodevelopmental disorders (NDD) leading to intellectual disability with psychiatric issues and dystonia-parkinsonism (D-P) during the second decade of life in some patients, and (3) early-onset static l-dopa-responsive parkinsonism in previously asymptomatic adult patients. Hyperphenylalaninemia was the most consistent metabolic alteration. CSF depletion of homovanillic acid (HVA) and 5-HIAA was detected in 18 and 20 of 29 symptomatic patients, respectively. Three stepwise regression analyses identified significant predictors of clinical outcomes in patients with phenylketonuria (PKU). CSF HVA levels and phenylalanine levels at diagnosis predicted the occurrence of D-P, while 26% of intellectual disability variability was explained by CSF HVA at diagnosis, and 31% of psychiatric disorder variability by later age at diagnosis. The phenotype was consistently associated with only a few DNAJC12 pathogenic variants, primarily for phenotypes A and C.Movement disorders responded positively to the various therapies in all symptomatic patients. The preventive effects on NDD and psychiatric problems were less clear.DiscussionDNAJC12 disease is a new metabolic neurodevelopmental disorder linked to parkinsonism. The combined effects of neurotransmitter depletion and disrupted enzyme proteostasis in dopaminergic and serotoninergic neurons may underlie the early neurodevelopmental presentation and subsequent neurologic and psychiatric disorders.

Background: Lysosomal storage disorders (LSDs) comprise a heterogeneous group of inherited metabolic diseases that lead to severe, irreversible complications if diagnosis is delayed. Newborn screening (NBS) provides a crucial opportunity for early identification and timely initiation of disease-modifying interventions. Methods: We analyzed 234,642 newborns screened over a 10-year period in Tuscany, Italy, for Fabry disease (FD), Pompe disease (PD), and mucopolysaccharidosis type I (MPS I), using evolving methodologies, including tandem mass spectrometry and digital microfluidics-based assays. We report the epidemiological data, molecular characterization, and the clinical impact of our screening program. Approximately 18% of screened newborns were of non-Italian origin, predominantly from Chinese, North African, and sub-Saharan African communities, providing unique insights into the genetic landscape of LSDs in a multiethnic population. Results: We identified 422 initial positive screens (recall rate 0.18%), of which 170 were confirmed on second dried blood spot (DBS). Molecular analysis revealed 17 late-onset PD individuals (incidence 1:13,802), 24 FD individuals, including five classical and 19 late-onset phenotypes (incidence 1:9776 total, 1:46,928 classical). No MPS I cases were confirmed, despite 45 positive initial screens. Nineteen novel variants were detected across the three genes: 4 in GAA, 5 in GLA, and 10 in IDUA. Evidence of regional founder effects emerged for the GLA variants c.335G > A and c.640-823 T > C. Conclusions: Our 10-year experience demonstrates the effectiveness of NBS for LSDs while highlighting important challenges, particularly the high burden of pseudodeficiencies and variants of uncertain significance (VUS). In MPS I screening, the substantial prevalence of pseudodeficiency alleles underscores the need for robust second-tier testing strategies to improve positive predictive value, especially in ethnically diverse populations.

The multisubunit RNA exosome complex provides an essential, highly conserved multifunctional 3' to 5' exoribonuclease activity in the eukaryotic nucleus and cytoplasm. Inherited bi-allelic single amino acid variants in the core of the RNA exosome complex have been implicated in causing Mendelian syndromes that affect brain development, collectively termed exosomopathies. The core RNA exosome consists of nine subunits, and pathogenic variants in eight of them (EXOSC1- 5 and EXOSC7-9) have been described in exosomopathies. Here, we describe a patient with cerebellar atrophy, ataxia, and global developmental delay. Trio exome sequencing identified compound heterozygous variants in the final subunit EXOSC6. Previous patients with exosomopathies all have an RNA exosome with only a single amino acid changed, but our patient is missing multiple amino acid residues. The maternal allele is an in-frame deletion that removes 4 amino acids, while the paternal allele introduces a stop codon that removes the last 16 amino acids of EXOSC6. Functional analyses of the variants in a yeast model suggest that both variants are damaging and may affect protein stability. The paternal variant affects a C-terminal α-helix. We tested several other alleles in this helix in our yeast model and show it is important. Overall, our findings broaden the variants implicated in exosomopathies.

Background and ObjectivesLevetiracetam (LEV) is widely used in pediatric epilepsies because of its favorable pharmacokinetics, ease of administration, and perceived tolerability. However, its comparative efficacy relative to established antiseizure medications (ASMs) in children remains uncertain. We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate LEV efficacy in pediatric epilepsies and compare outcomes vs placebo and active comparators.MethodsWe systematically searched PubMed/MEDLINE and Embase (2000-6 August 2025) for RCTs enrolling patients 16 years or younger with epilepsy and reporting seizure freedom and/or >= 50% responder rate. Trials including both pediatric and adult patients were eligible if pediatric participants were represented. Comparisons included LEV vs placebo or active ASMs as monotherapy or adjunctive therapy. Primary outcomes were seizure freedom and responder rate at the trial's primary endpoint or, if not specified, longest reported follow-up. We assessed risk of bias using Cochrane Risk of Bias 2. We pooled risk differences (RDs) with 95% CIs using random-effects models, stratified by comparator and epilepsy subtype.ResultsWe included 25 RCTs (4,070 participants): 23 contributed to pooled meta-analyses. Across 25 trials, the mean age ranged from 0.4 to 39.3 years, reflecting pediatric-only and mixed-age RCTs; 43.8% were female. In placebo/no-therapy-controlled trials (mainly add-on studies), LEV was associated with higher seizure freedom (RD 11.0%; 95% CI 5.3%-16.7%) and responder rates (RD 24.3%; 95% CI 19.1%-29.4%). In active-comparator-controlled trials (mainly monotherapy head-to-head studies), LEV showed no overall advantage vs active comparators for seizure freedom (RD -2.4%; 95% CI -5.6% to 0.7%) or responder rate (RD -7.4%; 95% CI -23.0% to 8.1%). Fourteen trials were at high risk of bias. Sensitivity analyses confirmed benefit vs placebo but showed significant disadvantage vs active comparators in low risk-of-bias trials. Findings in pediatric-only trials (16 RCTs; 1,380 participants) were consistent with the overall results.DiscussionLEV confers benefit vs placebo, mostly as adjunctive therapy, but does not consistently outperform established ASMs in pediatric epilepsies and may be inferior in some subgroups when higher-quality evidence is considered. Limitations include substantial heterogeneity, frequent high risk of bias, variable follow-up durations, publication bias, and limited pediatric-only comparative data.

A single genomic assay that delivers complete information across variant classes remains an aspirational goal. Currently, researchers and clinicians rely on an inefficient, expensive combination of short-read sequencing for single-nucleotide variants (SNVs) and small indels, comparative genomic hybridization (CGH) arrays for copy number variants (CNVs), and optical mapping and long-read sequencing for complex rearrangements, limiting the full potential of genomic discovery. To address these issues, TruPath Genome provides a one-test-for-all solution. By combining PCR-free whole-genome sequencing (WGS) with proximity-mapped read technology, it achieves high-resolution detection of SNVs and indels alongside long-range phasing for CNVs and structural variant (SV) refinement. We applied TruPath Genome on six clinical samples that were previously resolved by conventional methods. Across the cohort, TruPath Genome delivered coverage and variant-calling performance comparable to conventional WGS while achieving superior long-range phasing and enabling precise breakpoint resolution for clinically relevant structural events. This highlights TruPath Genome’s potential to consolidate genomic testing pipelines, accelerate diagnosis, and expand access to advanced genomic insights. Furthermore, its ultra-long-range data facilitates telomere-to-telomere assemblies and pangenome development, advancing our understanding of genome biology at an unprecedented scale.

Most pathogenic tubulin variants arise de novo in sporadic patients, causing severe brain malformations and significant neurodevelopmental impairment. The resulting reproductive disadvantage typically prevents these mutations from being transmitted to offspring. While a few variants are inherited from somatic or gonadal mosaic parents, vertical transmission of constitutional variants remains rare, though increasingly documented. Here, we report the father-to-daughter transmission of a novel constitutional TUBB variant [NM_178014.4:c.991C>T; p.(Leu331Phe)]. Both individuals presented with intellectual disability and a malformation of cortical development (MCD). To validate the pathogenicity of this variant, we performed functional and immunofluorescence assays in vitro on patient-derived fibroblast cultures. These experiments supported the involvement of the variant in significantly impairing cell motility, altering cytoskeleton organization, and affecting cellular morphology. Our findings from this family, alongside literature review of constitutional and mosaic tubulinopathies, suggest that pathogenic germline TUBB variants can occasionally be inherited. Transmission is facilitated by the relatively mild clinical anatomoclinical phenotype. When a pathogenic TUBB variant is identified in an index patient, comprehensive parental clinical, neuroradiological, and genetic evaluation is crucial to accurately assess reproductive risk.

RNA sequencing (RNA-seq) provides a powerful complement to DNA sequencing for uncovering pathogenic defects affecting gene expression and splicing in individuals with genetically undiagnosed rare disorders. However, as large rare disease consortia adopt RNA-seq, challenges arise due to cohort heterogeneity, variability in tissues and sample sizes, and differences in interpretation practices. Here, we present a harmonized analytical and interpretation framework developed by the pan-European Solve-RD consortium to address these challenges. We analyzed 521 RNA-seq samples from whole blood, fibroblasts, muscle and peripheral blood mononuclear cells collected across more than 30 clinics and five European Reference Networks. Aberrant expression and splicing events were identified using OUTRIDER and FRASER 2.0 and analysed through a standardized four-level scoring framework that encompassed RNA-seq outlier reliability, phenotype relevance, variant mechanism, and segregation evidence, captured in structured reports for interpretation. Regular meetings, and collaborative Solvathon workshops were used to evaluate variant pathogenicity. This effort resulted in molecular diagnoses for 19 families out of 248 (7.7%) for whom DNA analyses had been inconclusive. Furthermore, three cases diagnosed using DNA analyses were confirmed, and 49 candidate events and five novel candidate disease genes were identified in the remaining families. Our results demonstrate the feasibility and impact of large-scale, standardized RNA-seq analysis in a transnational research setting. This framework provides a model for other international initiatives such as the Undiagnosed Diseases Network and ERDERA, paving the way for broader clinical implementation of transcriptome-based rare disease diagnostics. ### Competing Interest Statement V.A.Y., F.B., and C.M., are founders, shareholders and managing directors of OmicsDiscoveries. The other authors declare no competing interests. ### Clinical Trial NCT03491280 ### Funding Statement The SolveRD project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 779257. SolveRD research is supported (not financially) by ERN ITHACA (project ID no. 101085231), ERN RND (project ID no. 101155994), ERN EURO NMD (project ID no. 101156434), ERN EpiCARE (project ID 101156811), and ERN RITA (project ID 101155878). All ERNs are cofunded by the European Union within the framework of the Third Health Programme. ERDERA has received funding from the European Union Horizon Europe research and innovation programme under grant agreement 101156595. Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or any other granting authority, who cannot be held responsible for them. VAY, RL, CM and JG were supported by the Deutsche Forschungsgemeinschaft (German Research Foundation) via the project NFDI 1/1 GHGA German Human Genome Phenome Archive(441914366). The TUM IT infrastructure was cofunded via the Deutsche Forschungsgemeinschaft (German Research Foundation, project ID 461264291). BEA was supported by the predoctoral program Joan Oro of the Secretary of Universities and Research of the Department of Research and Universities of the Government of Catalonia with codes 2024 FI1 00075 and 2025 FI2 00075, cofinanced by the European Union. HM was supported by the Wellcome Trust grant 220906/Z/20/Z and UCL Global Engagement Fund scheme (2022/23 GEF project). HL receives support from the Canadian Institutes of Health Research (CIHR) for Foundation Grant FDN167281 (Precision Health for Neuromuscular Diseases), Transnational Team Grant ERT 174211 (ProDGNE) and Network Grant OR2 189333 (NMD4C), from the Canada Foundation for Innovation (CFI JELF 38412), the Canada Research Chairs program (Canada Research Chair in Neuromuscular Genomics and Health, 950 232279), the European Commission (101080249) and the Canada Research Coordinating Committee New Frontiers in Research Fund (NFRFG 2022 00033) for SIMPATHIC, and from the Government of Canada First Research Excellence Fund (CFREF) for the Brain-Heart Interconnectome (CFREF 2022 00007). KP is a recipient of a Canadian Institutes of Health Research (CIHR) postdoctoral fellowship award under award no: MFE 491707. JP was supported by the Else Kroener Fresenius Stiftung Clinician Scientist program precise.net and by the intramural TUFF program (3049 0 0). AP has received funding from the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia (2021SGR00899), and the Instituto de Salud Carlos III (ISCIII) (FIS PI23/00835) Fondo Europeo de Desarrollo Regional (FEDER), Union Europea, una manera de hacer Europa. ASC was supported by the grants FPU20/06692 and EST23/00463 from Ministerio de Universidades, Spain. AH was supported by a ZonMW (The Netherlands Organization for Health Research and Development) Vici grant (No. 09150182310053). KL receives support from the German Research Foundation (DFG, LO1555/10 1). DNdB was supported by Instituto de Salud Carlos III (Grant CP22/00141). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The ethics committee of University Hospital of Tuebingen gave ethical approval for this work (ClinicalTrials.gov ID: [NCT03491280][1], https://clinicaltrials.gov/study/[NCT03491280][1]). Informed consent for data sharing, including indirect identifiers within Europe for research, was obtained from all recruited individuals. All data submitters confirmed the code of conduct of RD-connect GPAP. This study adheres to the principles set out in the Declaration of Helsinki. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Raw data will be available at the European Genome-Phenome Archive (https://ega-archive.org/datasets/) under the Solve-RD study EGAS00001003851, and can be accessed following approval from the Solve-RD Data Access Committee. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT03491280&atom=%2Fmedrxiv%2Fearly%2F2026%2F02%2F14%2F2026.02.10.26345954.atom

PURPOSE:MRI detection of subtle focal cortical dysplasia (FCD)-like abnormalities remains challenging in focal epilepsy. Higher signal-to-noise ratio and spatial resolution offered by ultra-high-field 7T MRI and surface-based graph-neural-network (GNN) analysis may improve detection of subtle cortical abnormalities. We evaluated whether combining 7T MRI with a surface-based GNN classifier improves lesion detection in focal epilepsy of suspected structural origin. METHODS:We analyzed paired 7T and 3T MRI datasets from 87 patients with focal epilepsy (78.1% pediatric) and 10 internal healthy control individuals. We processed T1-weighted and Fluid-Attenuated-Inversion-Recovery MRI using a surface-based framework and a pre-trained GNN classifier developed within the Multi-centre-Epilepsy-Lesion-Detection project. We compared classifier outputs with expert visual MRI assessment, clinical and surface electroencephalography (EEG) localization (all patients), stereo-EEG (ten patients) and histopathological (17 patients) findings. We evaluated diagnostic yield and lesion conspicuity, and performed within-subject comparisons between 7T and 3T. RESULTS:Following quality controls, we included 70 patients. The 7T MRI-based classifier identified lesion clusters concordant with visual 3T MRI and electroclinical localization in 25/37 (67.6%) MRI-positive patients, electroclinical-concordant clusters in 15/33 (45.4%) 3T MRI-negatives, stereo-EEG-concordant clusters in 7/10 (70.0%) patients and surgically-concordant clusters in 11/17 (64.7%). Among classifier-positive patients (40/70, 57.1%), 7T allowed detection of previously hidden lesions in 15/40 (37.5%) patients, and improved detection of known lesions in 11/40 (27.5%). CONCLUSION:Combining 7T MRI with surface-based GNN analysis improves detection and characterization of FCD-like abnormalities in focal epilepsy, particularly in patients with unrevealing 3T MRI, supporting the adoption of advanced neuroimaging in presurgical epilepsy assessment.

Abstract The SCN1A gene is implicated in a broad spectrum of epilepsy phenotypes, ranging from self‐limited genetic epilepsy with febrile seizures plus (GEFS+) to severe developmental and epileptic encephalopathies such as Dravet syndrome (DS). While fenfluramine (FFA) has demonstrated strong efficacy in DS, its role in SCN1A‐related epilepsies beyond DS has not been thoroughly investigated. We conducted a multicenter observational study including 11 patients with SCN1A‐related GEFS+ who received FFA as adjunctive therapy. All patients had previously failed to achieve adequate seizure control with valproate and, in most cases, additional antiseizure medications. FFA was introduced following the DS titration protocol, with a mean dose of 0.39 mg/kg/day. FFA addition led to a mean seizure frequency reduction of 91%, with more than half of the patients achieving complete seizure freedom. Reduced EEG abnormalities were documented in 5/11 patients of the cohort, including complete normalization in 3/11 patients. Furthermore, subjective caregiver reports indicated perceived improvements in patients' alertness and behavioral responses. FFA was well tolerated, with only mild and transient adverse events reported. These findings support the potential role of FFA as an effective and well‐tolerated treatment option in patients with SCN1A‐related GEFS+. Plain Language Summary GEFS+ is a genetic epilepsy frequently caused by changes in the SCN1A gene. In a multicenter real‐world study of 11 people with SCN1A‐related GEFS+, adding fenfluramine to usual care substantially reduced seizures, with several becoming seizure‐free. EEG recordings improved, and caregivers reported better alertness in some patients. Treatment was generally well tolerated, with only mild, temporary side effects.

Introduction Brain structural differences consistent with an older-appearing brain have been reported in people with epilepsy, but the extent to which these differences reflect clinical characteristics vs broader socioeconomic context is unclear. We investigated whether country-level socioeconomic factors are associated with neuroanatomical differences in adults with epilepsy using MRI-based age prediction, along with epilepsy subtype, sex, and clinical factors. Methods Structural MRI and clinical data were collected from 26 epilepsy centres across 12 countries in the Americas, Australia, Europe, Asia and Africa. MRI-based age estimates were estimated using a previously developed prediction model trained on 29,175 healthy subjects. Brain predicted age difference (BrainPAD) was calculated as the difference between MRI-predicted brain age and chronological age. National gross domestic product (GDP) per capita and income inequality (Gini index) were obtained from the World Bank. Associations between BrainPAD and epilepsy subtype (temporal lobe epilepsy, extratemporal epilepsy, and genetic generalised epilepsy), national socioeconomic context (GDP per capita and Gini index), age and sex were assessed using regression models. Results We analyzed 2,109 individuals with epilepsy and 1,041 healthy non-epilepsy controls (57% female; median age = 35; range 17-83). BrainPAD was higher in epilepsy than controls (β 4.2 years, SE 0.4; t=10.6), with increases ranging from 2.5 to 6 years across subtypes. Male sex was associated with 1 year higher BrainPAD relative to females (SE 0.33, t=3.12). There were no main effects of GDP or Gini index; however, significant interactions between were observed. The effect of epilepsy on BrainPAD was greater in countries with lower GDP per capita (t=-2.74) and higher income inequality (t=2.72). Conclusions Clinical factors and socioeconomic context both influence brain structural ageing in epilepsy. These findings highlight the importance of geographic and economic diversity in neuroimaging research and underscore the relevance of global socioeconomic context when interpreting brain health measures.