Antonio Gambardella

We investigated whether intronic repeat expansions in the SAMD12 , STARD7 , and MARCHF6 genes are present in individuals with juvenile myoclonic epilepsy (JME) and tremor. Given that tremor is a shared feature with familial adult myoclonic epilepsy (FAME), we hypothesized that this phenotype may reflect a common genetic basis involving FAME‐associated pentanucleotide repeat expansions. The study included 31 individuals with JME and tremor (17/31 [54.8%] females, mean age at genetic testing = 34.4 ± 13.8 years) and 100 age‐ and sex‐matched healthy controls. Genomic DNA was analyzed using repeat‐primed polymerase chain reaction and fragment analysis to detect intronic TTTCA repeat expansions in the three established FAME‐associated genes. No pathogenic repeat expansions were identified in SAMD12 , STARD7 , or MARCHF6 among individuals with JME and tremor. The frequency of intronic pentanucleotide repeat expansions did not differ between cases and controls. This is a comprehensive analysis assessing three FAME‐associated repeat‐expansion loci in a clinically well‐characterized cohort of individuals with JME and tremor. Our findings do not support a major contribution of these FAME‐associated loci to tremor in this cohort, suggesting that those intronic repeats did not contribute to genetic susceptibility to the tremor in JME. Further studies are required to identify the factors associated with this phenotype.

Objective: Cenobamate is approved for treatment of focal seizures in adults, but evidence on non‐seizure outcomes remains limited. This interim statistical analysis of the cenoBamate in aduLts with focal‐onsEt SeizureS (BLESS) study evaluated patient‐ and clinician‐reported outcomes for up to 52 weeks of cenobamate treatment. Methods: BLESS is an observational, retrospective and prospective cohort study designed to assess the real‐world effectiveness and safety of adjunctive cenobamate in adults with uncontrolled focal epilepsy. Outcomes included patient‐reported health‐related quality of life, sleepiness, anxiety, mood, and global functioning assessed by the 31‐item Quality of Life in Epilepsy Inventory (QOLIE‐31), the Epworth Sleepiness Scale (ESS), the Hospital Anxiety and Depression Scale (HADS), and the Clinical Global Impression (CGI) scales. Results: A total of 377 participants were included. Among subjects with an available score at 12 ( n = 197), 24 ( n = 363), and 52 ( n = 197) weeks, the QOLIE‐31 overall score remained stable. Subjects with sustained seizure freedom at 24 weeks showed a significantly higher QOLIE‐31 overall score ( p = 0.041) and cognitive functioning scores ( p = 0.019) compared with those who did not reach sustained seizure freedom. More than 68% of participants had normal daytime sleepiness (total ESS score 0–10) and did not report anxiety or depression according to the HADS‐A and HADS‐D subscales at each assessment up to 52 weeks. Clinicians rated 91.3% ( n / N = 179/196), 85.7% ( n / N = 300/350), and 87.4% ( n / N = 167/191) of subjects as improved for their overall condition from the initiation of treatment according to the CGI—Improvement or change (CGI‐I) scale, at 12, 24, and 52 weeks. Significance: This interim analysis provides preliminary descriptive evidence on non‐seizure outcomes in subjects treated with adjunctive cenobamate. Patient‐reported outcome scores remained stable from 12 weeks and up to 52 weeks, consistent with preserved overall well‐being. Better quality of life and cognitive functioning emerged in sustained vs non‐sustained seizure‐free participants. Based on clinicians' judgment, there was signal of improvement in overall condition compared to baseline in most treated subjects throughout the observation period. Study Registration: NCT05859854.

Objective: Epilepsy is characterized by widespread cortical and subcortical structural alterations beyond the epileptic zone. 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 are seldomly reported in neuroimaging studies, partly due to limited sample sizes and single‐center designs. We therefore tested whether epilepsy‐related structural alterations differ between males and females, and whether the associations between structural measures and clinical characteristics vary by sex. Methods: We analyzed clinician‐assigned biological sex differences in common epilepsies and their related clinical variables using structural neuroimaging biomarkers in an international multicenter cohort of 1253 epilepsy patients and 1077 healthy controls. We studied cortical thickness and subcortical volume in temporal lobe epilepsy (TLE) and genetic generalized epilepsy (GGE). Results: Both male and female patients with TLE showed widespread cortical and subcortical alterations in sex‐stratified analyses, whereas GGE showed more extensive alterations in female patients and only subtle alterations in male patients. However, no significant sex‐by‐diagnosis interactions were identified in either the TLE ( t = −2.153 to 1.705, all p _FDR >.05) or GGE ( t = −1.797 to 2.774, all p _FDR >.05) cohort. Likewise, no significant interactions were found between sex and age at onset ( t _TLE = −1.835 to 1.092, t _GGE = −2.394 to 1.392, all p _FDR >.05) or disease duration ( t _TLE = −2.643 to 2.048, t _GGE = −1.234 to 2.017, all p _FDR >.05) in either patient group. Significance: Overall, although sex differences in behavioral and clinical outcomes of epilepsy have been consistently reported in previous studies, our results indicate that sex‐related clinical differences in epilepsy are not strongly captured by macroscale structural magnetic resonance imaging measures, and may instead arise from hormonal, neurochemical, or functional–network mechanisms.

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.

Objective: To evaluate the effectiveness and tolerability of cenobamate in patients with a significant reduction in concomitant antiseizure medication (ASM) in European cenobamate Early Access Programs (EAPs). Method: Anonymized patient data from real‐world studies/registries associated with European cenobamate EAPs were pooled. Patients were included if they had significantly reduced their concomitant drug load (i.e., converted to cenobamate monotherapy or reduced from multiple to one concomitant ASM) between baseline and the last visit. Effectiveness, tolerability, and dosage of cenobamate were evaluated. Responses according to therapeutic regimen at last visit were studied. Results: Of 694 patients within cenobamate EAPs, 75 (10.7%) met the inclusion criteria (mean age 39.5 years [range 19–65]). At baseline, the median number of prior ASMs was 10 (interquartile range [IQR] 6–13); 46 patients (61.3%) were taking two, 23 (30.7%) were taking three, and six (8%) were taking four concomitant ASMs at baseline. At the last visit, seven patients (9.3%) were converted to monotherapy and 68 (90.7%) were receiving one concomitant ASM. The median cenobamate dosage at last visit was 300 mg (IQR 200–350). Median cenobamate follow‐up was 22 months; 73 patients (97%) had at least 1 year of follow‐up and one discontinued cenobamate at 1 year. Twenty‐five patients (33.3%) were seizure‐free at last visit; 51 (68%) had a ≥50% reduction in seizure frequency. The seizure‐freedom rate was numerically, but not significantly, higher in patients converted to monotherapy (57.1%) versus those receiving one concomitant ASM (30.9%; p = 0.16). Cenobamate plus clobazam was the most effective combination. Adverse events (AEs) were reported in 55/75 patients (73.3%); the most common were somnolence (30.7%), dizziness/vertigo (28%), and fatigue (26.7%). No AEs led to treatment discontinuation. Significance: Cenobamate demonstrated good effectiveness and tolerability in a population of patients within European EAPs who achieved a significant reduction of concomitant ASM. Plain Language Summary: People with highly drug‐resistant epilepsy often need to take several antiseizure medications at the same time. Combined data from European Early Access Programs show that about 10% of people treated with cenobamate were able to stop all other antiseizure medications or reduce treatment to cenobamate plus one other medication. Despite this simplification of treatment, one‐third of these patients became seizure‐free and more than two‐thirds experienced at least a 50% reduction in seizure frequency. Within this group, no patients stopped cenobamate because of side effects.

Background: We aimed to identify the proportion of individuals with a confirmed diagnosis of childhood absence epilepsy (CAE) or juvenile absence epilepsy (JAE) who show a negative routine EEG (rEEG), and to determine the main factors associated with this finding. Methods: Individuals with CAE or JAE underwent both an rEEG and a 24‐h ambulatory EEG (24‐h‐aEEG). Participants were classified as ‘rEEG positive’ if generalised spike–wave discharges (GSWs) and/or typical absences (TAs) were observed, and as ‘rEEG negative’ if no such features were detected. 24‐h‐aEEG recordings served as the ground truth to confirm the diagnosis in cases with a negative rEEG. Results: Eighty‐two individuals [40/82 (48.8%) females; mean age 12.5 ± 5.6 years] were included, of whom 39/82 (47.6%) were not receiving anti‐seizure medications (ASMs) at the time of the EEG. Overall, 31/82 (37.8%) had a negative rEEG, including 10/39 (25.6%) in the cohort of ASM‐naïve individuals. Compared with rEEG‐positive participants, those in the rEEG‐negative group had a later age at epilepsy onset (12.1 ± 4.5 years; p < 0.001) and were older at the time of EEG (16.5 ± 5.3 years; p < 0.0001). Older age at EEG emerged as significantly associated with a negative rEEG (OR = 1.23; 95% CI = 1.03–1.46; p = 0.019), independent of age at onset, epilepsy syndrome (CAE or JAE) and ASM exposure. Sensitivity analyses confirmed the association between older age and rEEG negativity across all cohorts: ASM‐naïve individuals (OR = 1.41; 95% CI = 1.12–1.78), CAE (OR = 1.27; 95% CI = 1.02–1.58), and JAE (OR = 1.36; 95% CI 1.09–1.69) groups. Youden's exploratory analysis identified ≥ 14 years as the optimal threshold for predicting a rEEG negative. Conclusion: Age significantly reduces the diagnostic yield of rEEG in CAE and JAE, regardless of ASM treatment.

Dravet spectrum, a phenotype previously referred to as Severe Myoclonic Epilepsy Borderland (SMEB), is genetically heterogeneous and most frequently associated with pathogenic variants in SCN1A. However, additional molecular pathways are increasingly implicated. Here, we report a Dravet spectrum patient identified through whole-exome sequencing carrying a rare heterozygous missense variant in HDAC4 (p.Arg543Trp). The variant was inherited from an unaffected father, indicating incomplete penetrance. The affected residue lies within the central regulatory domain of HDAC4 and is evolutionarily conserved. Structural modelling revealed subtle disturbance of local polar interactions without major backbone rearrangement, consistent with a mild regulatory perturbation aligned with the attenuated Dravet spectrum phenotype. No additional clinically relevant variants were identified. These findings expand the genetic and phenotypic landscape of Dravet spectrum, illustrating how altered transcriptional regulation may contribute to disease.

Objective: To investigate changes in quality of life (QoL) dimensions and their relationship with seizure outcome, depression, and suicidality after the addition or substitution of an anti‐seizure medication (ASM) in adults with drug‐resistant focal epilepsy. Methods: A total of 665 consecutively enrolled patients were followed prospectively and assessed with Quality of Life in Epilepsy Inventory 31 (QOLIE‐31) and the Neurological Disorders Depression Inventory for Epilepsy (NDDI‐E). QoL changes over time for the overall population and seizure outcome categories were analyzed with analysis of variance (ANOVA), whereas factors affecting QoL changes were assessed by using a linear regression model. Results: Seizure freedom was associated with a marked improvement across all QoL domains, ranging from 11 points for Seizure worry to 4 points for Emotional well‐being . The presence of depression before starting medication and its persistence during the observation period was associated with a global worsening of QoL across all domains, ranging from 10 points worse for Social functioning, almost 8 points for Energy and fatigue , 6 points for Cognitive functioning, and to nearly 5 points for Seizure worry . The new development of depression during treatment was associated with worsening in specific QoL domains such as Cognitive functioning , Social functioning , and Overall QoL subscales. Persistent positive suicidality screening was associated with progressive worsening in the domain Emotional well‐being . Significance: Seizure freedom can improve all domains of QoL, but mainly Seizure worry, although this can be negatively affected by depressed mood. Improvement in the domain of Social functioning requires a period of sustained seizure freedom longer than 6 months to improve, and it is negatively influenced by persistent depressed mood. In contrast, changes in Emotional well‐being are negatively influenced by suicidality. Clinical and demographic variables, including duration of epilepsy and number of comorbidities or concomitant medical problems, showed no correlation with changes in QoL.

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 analyzed three large epilepsy MRI datasets [n=3,676, 2,320 people with epilepsy and 1,356 healthy controls (HC)] to perform two tasks: 1) establish the presence of a TLE pattern on MRI and 2) 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<.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, para-hippocampal 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<.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 labeled as TLE and lateralized, 13.9% being correctly labeled 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.