Maria Sole Borioni

Objective: Lennox–Gastaut syndrome (LGS) is a developmental and epileptic encephalopathy defined by polymorphic seizures, intellectual disability (ID), and characteristic electroencephalographic (EEG) patterns. The applicability and biological validity of current electroclinical criteria remain debated. This study evaluated the concordance between clinical and electroclinical definitions of LGS and applied unsupervised clustering to identify data‐driven profiles within LGS. Methods: We retrospectively analyzed patients clinically fulfilling LGS criteria, with longitudinal electroclinical documentation and at least one sleep EEG. Patients meeting complete electroclinical criteria were compared with those meeting clinical criteria alone. Additionally, exploratory unsupervised K‐modes clustering and discriminant correspondence analysis were applied in adolescent and adult patients. Results: We included 105 patients (60.9% female), with a median age of 24 years (interquartile range = 16–35). Sixty‐nine patients (65.7%) met complete electroclinical criteria, yet neurodevelopmental features, seizure types, magnetic resonance imaging (MRI) findings, and treatment refractoriness were comparable to the clinically defined subgroup. K‐modes clustering ( n = 97 patients) identified three data‐driven electroclinical profiles. Cluster 1 comprised patients with the earliest seizure onset, profound intellectual and motor impairment, EEG background slowing, lower prevalence of generalized paroxysmal fast activity (GPFA), highest prevalence of structural etiologies, and lowest likelihood of meeting complete electroclinical criteria for LGS. Among clusters more frequently fulfilling complete electroclinical criteria, Cluster 2 represented an early onset profile with higher rates of ID, EEG background slowing, and high prevalence of polymorphic seizures. Cluster 3 included comparatively preserved patients, characterized by later onset, milder neurodevelopmental impairment, and higher frequency of normal MRI. Despite similar clinical severity, Cluster 1 patients had undergone fewer antiseizure medication trials. Significance: Exploratory data‐driven clustering identified clinically relevant electroclinical profiles that may help refine phenotypic stratification within clinically defined LGS. These included a severe GPFA‐underrepresented profile and two GPFA‐positive phenotypes differing in developmental severity, seizure profile, and age at onset.

Objective: Developmental and epileptic encephalopathies (DEEs) are associated with high premature mortality and increased risk of sudden unexpected death in epilepsy (SUDEP). However, epidemiological data remain limited, particularly for specific syndromes such as Dravet syndrome (DS), Lennox–Gastaut syndrome (LGS), and infantile epileptic spasms syndrome (IESS). To address this gap, we conducted a Bayesian meta‐analysis of randomized controlled trials (RCTs) and corresponding long‐term open‐label extension (OLE) studies. Methods: All‐cause mortality and SUDEP incidence rates were estimated using hierarchical Bayesian models with moderately informative priors derived from the literature. A negative binomial likelihood was used for all‐cause mortality, whereas a Poisson likelihood was used for SUDEP. Subgroup analysis were conducted for DS, LGS, and IESS. Results: Thirty‐seven RCTs and 15 OLE studies were included, comprising 3757 patients with DEEs (2221 LGS, 998 DS, 369 IESS, and 169 other DEEs). Across pooled data, 37 deaths occurred, including 2 definite, 12 probable, and 1 possible SUDEP. In the overall DEE population, the Bayesian posterior median estimated mortality rate was 8.76 per 1000 person‐years (PY; 95% credible interval [CrI], 5.50–13.89), and SUDEP rate was 4.32 per 1000 PY (95% CrI, 2.66–6.64). In LGS, mortality was 7.05 per 1000 PY and SUDEP was 3.4 per 1000 PY. In DS, mortality was 8.0 per 1000 PY, with a SUDEP rate of 7.59 per 1000 PY. In IESS, mortality was 9.41 per 1000 PY and SUDEP was 2.79 per 1000 PY. Significance: SUDEP accounted for approximately half of deaths in the overall DEE population and in LGS, with a proportionally greater contribution in DS. Potential trial‐related underestimation should be considered when interpreting these findings, as features of trial‐based datasets could have contributed to lower observed mortality and SUDEP estimates. Prospective population‐based studies are needed to more accurately define the real‐world incidence of SUDEP in DEEs.

Introduction: Autosomal dominant Alzheimer’s disease (ADAD), especially due to presenilin‐1 (PSEN‐1) gene mutations, may display a broad spectrum of clinical manifestations and neuroradiological findings. Occasionally, these manifestations may be rare and atypical, challenging the clinician’s ability to recognize the disease. The description of the clinical characteristics and neuroradiological remarks of patients with specific mutations may improve clinicians’ ability to identify them. Case Presentation: We report the case of a woman who presented with early‐onset, rapidly progressive dementia associated with bilateral hyperintensity of the medial temporal lobe on T2‐weighted MRI. After more common etiologies were excluded, genetic testing revealed a PSEN‐1 C779T mutation. Notably, her brother, who carried the same mutation, did not exhibit these atypical neuroradiological findings. Conclusions: This case underscores the phenotypic variability associated with PSEN‐1 mutations, even among individuals within the same family. Such variability and the possibility of atypical presentations may complicate the diagnostic process. In the presence of early‐onset and rapidly progressive dementia associated with bilateral hyperintensity of the medial temporal lobe, ADAD and PSEN‐1 mutation may be suspected and need to be addressed.

Background and Objectives: Different pathophysiological mechanisms, especially involving astrocytes, could contribute to Tuberous Sclerosis Complex (TSC). We assessed neurodegeneration and astrocytopathy plasma biomarkers in TSC adult patients to define TSC biomarker profile and investigate clinical-radiological correlations. Methods: TSC patients≥15 years followed at Policlinico “Umberto I” of Rome were consecutively enrolled (July 2021-June 2022). The plasma levels of the following biomarkers were compared between patients and age/sex-matched healthy controls (HC): tTau, pTau181, Abeta₄₀, Abeta₄₂, Neurofilament Light Chain, Glial Fibrillary Acid Protein (GFAP). Results: Thirty-one patients (20 females/11 males; median age 30 years, IQR 24-47) and 38 HC were enrolled. Only GFAP was significantly higher in the whole TSC population than in HC [132.71 (86.14-231.06) vs 44.80 (32.87-66.76) pg/mL, p<0.001], regardless of genotype. GFAP correlated with the disease clinical (ρ=0.498, p=0.005) and radiological severity (ρ=0.417, p=0.001). It was significantly higher in patients with epileptic spasms [254.50 (137.54-432.96) vs 86.92 (47.09-112.76) pg/mL, p<0.0001], moderate-severe intellectual disability [200.80 (78.40-427.6) vs 105.08 (46.80-152.58) pg/mL, p=0.040] and autism spectrum disorder [306.26 (159.07-584.47) vs 109.34 (72.56-152.08) pg/mL, p=0.021]. Discussion: Our exploratory study documented a significant increase of GFAP plasma concentration in TSC adult patients, correlated with their neurological severity, supporting the central role of astrocytopathy in TSC pathophysiology.