Annals of Neurology最新文献

Objective: The pharmacological treatment of temporal lobe epilepsy (TLE), a disorder characterized by recurrent seizures and cognitive dysfunction, is limited to symptomatic control. Identifying novel targets to modify disease progression is of great clinical and translational interest. Cellular senescence has been recently implicated in the development and progression of other neurodegenerative diseases, but its role in TLE is unstudied.

Methods: We first investigated cellular senescence markers in resected hippocampi from patients with medically intractable TLE through multiplexed immunofluorescence. We next used a mouse model of TLE (pilocarpine induced status epilepticus [SE]) for a combination of immunohistochemistry, behavioral testing, and electroencephalogram (EEG) monitoring. We implemented 2 strategies for removal of senescent cells (SCs), a genetic mouse model allowing for targeted senolysis, and a pharmacological approach using dasatinib and quercetin.

Results: We found a 5-fold elevation of senescent glia in human TLE cases as compared with controls. In mice, we found increases in senescence markers at both the transcript and protein level and predominantly expressed in microglia, which developed within 2 weeks following SE. Senolytic treatment produced a 50% reduction in SCs, rescued long-term potentiation deficits, normalized spatial memory impairments, reduced seizures, and protected a third of animals from epilepsy.

Interpretation: Our data demonstrate that SCs accumulate in both human TLE and in a mouse model of TLE and suggest that clearing SCs may be a viable strategy to reduce seizures and associated cognitive comorbidities. ANN NEUROL 2026;99:1059-1075.

Objective: Parkinson's disease (PD) is one of the rare diseases in which sleep alteration is a true marker of disease outcome. Yet, how the association between sleep and PD emerges over the healthy lifetime is not established. We examined the association between the polygenic risk score (PRS) for PD and the variability in the electrophysiology of rapid eye movement (REM) sleep in 433 younger (18-31 years) healthy individuals and 85 late-midlife (50-69 years) healthy individuals.

Methods: In this prospective cross-sectional study, in-lab electroencephalography recordings of sleep were recorded to extract REM sleep metrics. PRS was computed using SBayesR approach.

Results: Generalized additive model for location, scale, and shape analysis showed significant association of REM duration (p_corrected = 0.03) and theta energy in REM (p_corrected = 0.004) with PRS for PD in interaction with the age group. In the younger subsample, REM duration and theta energy were positively associated with PD PRS. In contrast, in the late-midlife subsample, the same associations were negative (although only qualitatively for REM theta energy) and may differ between men and women.

Interpretation: REM sleep is associated with the PRS for PD in early adulthood, 2 to 5 decades before typical symptoms onset. The association changes from positive in younger individuals, presumably free of alpha-synuclein, to negative in late-midlife individuals, possibly because of the progressive presence of alpha-synuclein aggregates or of the repeated increased oxidative metabolism imposed by REM sleep. Our findings may unravel core associations between PD and sleep and may contribute to novel intervention targets to prevent or delay PD. ANN NEUROL 2026;99:922-934.

Objective: The objective of this study was to determine whether missing individual doses of anti-seizure medications (ASMs) elevate short-term seizure risk in people with drug-resistant epilepsy.

Methods: In a prospective, community-based cohort, adults with drug-resistant epilepsy (≥ 3 seizures/month) or their caregivers recorded seizures and ASM intake with smartphone applications for 10 months each. Individual level analysis modeled the relationships between ASM adherence with seizure occurrence, as well as with a simplified seizure forecast via a 90-day moving average ("Napkin method"). Group-level analysis with a mixed-effects model was performed to examine the relationship between ASM adherence and simplified forecasts, while controlling for differences in individual seizure frequency via random effects.

Results: Twenty-seven participants (median age = 29 years) contributed 7,853 person-days. Individual analysis showed that only a small (n = 2) number of participants had a weak relationship between ASM adherence with seizure occurrence. Group-level analysis showed that seizure occurrence was highly linked to the Napkin method, but not ASM adherence.

Interpretation: Among individuals with frequent, drug-resistant epilepsy, occasional missed ASM doses did not measurably raise immediate seizure risk. Whereas sustained nonadherence remains a clinical concern, clinicians may reassure patients that infrequent brief lapses are unlikely to trigger seizures acutely, yet they should continue emphasizing overall adherence for long-term seizure control. ANN NEUROL 2026;99:1076-1082.

Objective: The evidence regarding adherence to dietary patterns and Parkinson's disease (PD) risk is inconsistent. Because of the long prodromal PD phase, reverse causation represents a major threat to investigations of diet in relation to PD. We examined whether adherence to the Mediterranean (MED) and Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) diets is associated with PD incidence, while considering reverse causation, in a large cohort of women with a 25-year follow-up.

Methods: Participants from the E3N (Etude Epidémiologique auprès des femmes de la Mutuelle Générale de l'Education Nationale) study were prospectively followed-up from 1993 to 2018. PD diagnoses were validated using medical records and drug claim databases. Baseline MED and MIND scores were computed using a validated food questionnaire. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using multivariable Cox regression models. Exposures were lagged by 5 years in main analyses and longer lags in sensitivity analyses. We performed age-stratified analyses and adjusted for prodromal symptoms.

Results: Analyses (5-year-lag) are based on 71,542 women (845 PD patients). Higher adherence to MED and MIND diets was not associated with PD overall, but was associated with lower PD incidence in women <71 years old (MED, HR_{high vs. low+medium} = 0.76 [0.58-1.00], p-Age × MED interaction = 0.038; MIND, HR_{high vs. low+medium} = 0.75 [0.58-0.97], p-Age × MIND interaction = 0.035). Legumes and high unsaturated to saturated fat ratio had the strongest contribution for the MED diet, while beans and olive oil had the strongest contribution for the MIND diet. Results were consistent after adjustment for constipation/depression and in analyses with lags up to 20 years.

Interpretation: Adherence to the MED and MIND diets was associated with lower PD incidence <71 years in women. These findings are important for planning preventative interventions. ANN NEUROL 2026;99:1014-1029.

We used targeted immunopurification-mass spectrometry (IP-MS) to characterize human neurofilament light chain (NfL) proteoforms across various compartments to assess their alterations in amyotrophic lateral sclerosis (ALS). NfL is truncated in cerebrospinal fluid (CSF) and blood in patients with sporadic ALS (sALS) and these proteoforms differ between compartments. Mid-domain species were elevated in CSF whereas plasma NfL proteoforms were mostly comprised of the tail subdomain region. Our results suggest NfL isoforms are proteolyzed and differentially distributed between ALS biofluid compartments and that analyzing by these specific regions or in ratios between regions can provide improvements in biomarker utility. These insights enhance the understanding of NfL and its potential for disease monitoring and therapeutic targeting in ALS. ANN NEUROL 2026;99:857-862.

Objective: Sleep-predominant network hyperexcitability is increasingly recognized as a potential disease-accelerating comorbidity in Alzheimer's disease (AD). However, its prevalence and risk-factors remain debated, largely due to cohort-specific and methodological differences across studies. In this prospective case-control study, we investigated potential ways of improving detection, from translational approaches focusing on rapid eye movement (REM)-sleep to refined electroencephalogram (EEG) setups and added clinical questionnaires.

Methods: We recruited 30 patients with early-stage AD without a history of epilepsy and 30 age-matched controls. Participants underwent overnight polysomnography with video-EEG. Interictal epileptic discharges (IEDs) were identified through a structured 3-step review by multiple independent experts using recommended criteria. Neuroanatomic patterns and sleep-related abnormalities were investigated as potential risk factors. Clinical symptoms in favor of epileptic seizures were evaluated through a tailored questionnaire at follow-up.

Results: IEDs were detected in 3 patients (10%) and 1 control (3.33%), a difference not reaching statistical significance (p = 0.612). Most events occurred during non-REM (NREM) sleep. Eight patients (26.67%) reported symptoms compatible with epileptic seizures-one of whom also presented with IEDs. Patients with IEDs or reported symptoms suggestive of potential seizures exhibited more severe sleep-disordered breathing and reduced precuneus volume compared with those without.

Interpretation: Despite efforts to optimize detection accuracy, our findings reveal a lower-than-expected percentage of patients with AD with IEDs, yet support previous findings suggesting that sleep-disordered breathing and specific atrophy patterns could flag at-risk patients, guiding screening in clinical settings. Our findings also favor validation efforts of questionnaires to support the diagnostic process. Finally, we highlight methodological issues in IED detection and call for the re-evaluation and standardization of diagnostic methods and criteria in this population to improve patient care. ANN NEUROL 2026;99:1046-1058.

Objectives: Leg dystonia in cerebral palsy (CP) is debilitating but remains underdiagnosed. Routine clinical evaluation has only 12% accuracy for leg dystonia diagnosis compared to gold-standard expert consensus assessment. We determined whether expert-cited leg dystonia features could be quantified to train machine learning (ML) models to detect leg dystonia in videos of children with CP.

Methods: Eight pediatric movement disorders physicians assessed 298 videos of children with CP performing a seated task at 2 CP centers. We extracted leg dystonia features cited by these experts during consensus-building discussions, quantified these features in videos, used these quantifications to train 4,664 ML models on 163 videos from one center, and tested the best performing models on a separate set of 135 videos from both centers.

Results: We identified 69 quantifiable features corresponding to 12 expert-cited leg dystonia features. ML models trained using these quantifications achieved 88% sensitivity, 74% specificity, 82% positive predictive value, 84% negative predictive value, and 82% accuracy for identifying leg dystonia across both centers. Of the 25 features contributing to the best performing ML models, 17 (68%) quantified leg movement variability. We used these ML models to develop DxTonia, open-source software that identifies leg dystonia in videos of children with CP.

Interpretation: DxTonia primarily leverages detection of leg movement variability to achieve 82% accuracy in identifying leg dystonia in children with CP, a significant improvement over routine clinical diagnostic accuracy of 12%. Observing or quantifying leg movement variability during a seated task can facilitate leg dystonia detection in CP. ANN NEUROL 2026;99:1001-1013.

Objectives: Multiple system atrophy (MSA) is classified into parkinsonian (MSA-P) and cerebellar (MSA-C) phenotypes based on predominant motor features, with corresponding pathological classifications of striatonigral (SN) degeneration and olivopontocerebellar (OPC) atrophy; however, disease progression patterns remain poorly understood. We aimed to identify novel MSA subtypes based on neuronal loss patterns using unsupervised machine learning.

Methods: We applied the Subtype and Stage Inference (SuStaIn) algorithm to analyze neuronal loss patterns in 167 autopsy-confirmed MSA. Neuronal loss was semi-quantitatively assessed in 5 brain regions: putamen, substantia nigra, pontine nucleus, inferior olivary nucleus, and cerebellar Purkinje cells. Obtained subtypes were validated by clinicopathological information.

Results: Three distinct subtypes were identified: SN-early subtype (54% [86/160]) with initial SN neuronal loss, OPC-early subtype (28% [44/160]) with early OPC involvement, and SN-OPC-synchronous subtype (19% [30/160]) with concurrent early neuronal loss in both systems. These subtypes corresponded well with clinical phenotypes. The SN-OPC-synchronous subtype exhibited significantly shorter survival (median 6.2 years vs 6.9 and 7.4 years in SN-early and OPC-early subtypes; p = 0.0049), more frequent rapid progression (57% vs 24% and 41% in SN-early and OPC-early subtypes; p = 0.0048), and more frequent early falls (70% vs 36% and 50% in SN-early and OPC-early subtypes; p = 0.0039). Immunohistochemical validation confirmed extensive α-synuclein pathology in both SN and OPC systems in the SN-OPC-synchronous subtype.

Interpretation: The SN-OPC-synchronous subtype provides insights into α-synuclein propagation mechanisms, suggesting multiple initial seeding sites rather than unidirectional spread. This computational approach uncovered disease heterogeneity undetectable by conventional methods, potentially benefiting clinical trials through patient stratification. ANN NEUROL 2026;99:989-1000.

Objective: Whether cognitive decline in patients with Parkinson's disease (PD) carrying GBA1 variants is accelerated after subthalamic deep brain stimulation (STN-DBS) remains controversial. Clarifying long-term cognitive outcomes is essential for informed decision making.

Methods: We assembled matched cohorts of patients carrying GBA1 variants with STN-DBS (PD_GBA1+DBS+, n = 28) and without (PD_{G BA1+DBS-}, n = 28). Additional cohorts included non-carriers with STN-DBS (PD_GBA1-DBS+, n = 40) and without (PD_GBA1-DBS-, n = 43). Clinical, genetic, and cerebrospinal fluid (CSF) biomarkers (Aβ1-42, h-Tau, p181-Tau, and neurofilament light chain) were analyzed. Cognition was assessed using the Montreal Cognitive Assessment (MoCA). Cognitive slopes were estimated using linear mixed models and the minimally detectable slope difference at 3-year follow-up was 1.33 MoCA points enabling sensitivity to clinically meaningful changes. Secondarily, conversion to dementia was analyzed with Kaplan-Meier-analysis once the MoCA was < 21.

Results: There was no significant difference in cognitive decline between PD_GBA1+DBS+ and PD_GBA1+DBS- (-0.24 MoCA points/year; 95% confidence interval [CI] = -1.11 to 0.70) projecting to -0.72 MoCA points at 3-year-follow-up (p = 0.583). Secondarily, the risk for conversion to dementia did not differ between PD_GBA1+DBS+ and PD_GBA1+DBS- (HR = 0.55, 95% CI = 0.23-1.34, p = 0.119) or between PD_GBA1-DBS+ and PD_GBA1-DBS- (HR = 1.22, 95% CI = 0.53-2.83, p = 0.897). Dementia risk was associated with GBA1 status (HR = 3.04, 95% CI = 1.05-8.79, p = 0.041), baseline MoCA < 26 (HR = 3.05, 95% CI = 1.29-7.21, p = 0.011), and baseline age > 69 years (HR = 4.42, 95% CI = 1.79-10.89, p = 0.001). In GBA1 carriers, a visuospatial/executive domain score < 4/5 predicted dementia (HR = 4.71, 95% CI = 1.25-17.86, p = 0.022).

Interpretation: GBA1 variant carriers meeting general STN-DBS indication criteria did not show accelerated cognitive decline in the presence of STN-DBS. In addition, exploratory predictors of dementia could support counseling of DBS candidates. ANN NEUROL 2026;99:976-988.