Annals of Neurology

Background: Acute necrotizing encephalopathy (ANE) is a rare and severe neurologic complication of viral infection in children, thought to result from a hyperacute cytokine storm causing blood-brain barrier disruption and central nervous system injury. Despite characteristic clinical and radiologic features, ANE remains poorly understood at the molecular level, with no validated biomarkers or targeted therapies. We aimed to determine whether genetic predisposition to ANE due to RANBP2 variants is associated with a distinct immunologic signature. Methods: We conducted a prospective biological study of familial ANE (ANE1, NCT06731790). We included 23 heterozygous carriers of the RANBP2 c.1754C>T (p.Thr585Met) variant from 10 families, and 28 noncarriers (median age, 40 years [range, 4-72]). Soluble immune mediators, transcriptomic analyses, multiparameter flow cytometry, and cellular imaging were analysed in peripheral blood mononuclear cells (PBMCs) and monocytes. Baseline and resiquimod stimulated immune responses were analysed within the same statistical model, with genetic status as the primary predictor. Findings: The RANBP2 Thr585Met mutation was associated with a dysregulated inflammatory phenotype characterized by reduced basal mediator production and exaggerated TNF- responses following stimulation (estimated difference, +2,098 pg/mL; 95% CI, 1,121 to 3,076; P=0.0001). Transcriptomic and flow cytometry analyses showed broad reprogramming of myeloid cells with enrichment of CXCR3-high CD14-high subsets. Expansion of these populations was associated with increased long-term disease burden. The RANBP2 variant was the only independent factor associated this inflammatory phenotype. Interpretation: RANBP2-associated ANE is characterised by a distinct immunological signature that can inform disease stratification and support the development of targeted immunotherapeutic approaches.

ObjectiveLevetiracetam is commonly prescribed for seizure prophylaxis after acute ischemic stroke (AIS) and often continued beyond discharge. While its short-term effectiveness for preventing post-stroke seizures is established, it is unclear whether prolonged use improves survival, particularly in older adults. We estimated the effect of continued levetiracetam use on 90-day mortality among Medicare beneficiaries after AIS. MethodsUsing Traditional Medicare claims data (2008-2021), we identified beneficiaries aged [≥]66 years hospitalized for AIS who initiated outpatient levetiracetam within 90 days of discharge. After one month of continued post-stroke use of levetiracetam (start of follow-up), we compared 90-day mortality between patients with a new levetiracetam dispensation within a 14-day grace period post-follow up and those without one. We performed cloning, censoring and weighting to address immortal time bias and estimated standardized mortality risks, risk differences, and 95% confidence intervals (CI). ResultsAmong 3,212 eligible beneficiaries, 1,779 (55.4%) received a new levetiracetam dispensation within the 14-day grace period. Median age was 76 years (IQR 70-83); 57.8% were female. After adjustment for demographics, hospitalization characteristics, timing of initiation, and comorbidities, continued use was associated with lower 90-day mortality than discontinuation (53 vs 62 deaths per 1,000; risk difference -9 per 1,000; 95% CI: (-12,-5)). The reduction was observed primarily among patients aged [≥]75 years. SignificanceAmong older Medicare beneficiaries who initiated levetiracetam after AIS, continued outpatient use was associated with modestly lower 90-day mortality, particularly in those aged [≥]75 years. These findings suggest potential benefits of levetiracetam continuation beyond the immediate post-stroke period.

BackgroundEpidemiological studies show an inverse association between cigarette smoking and Parkinsons disease (PD), suggesting a potential protective effect of smoking on PD incidence, despite the well-established and overwhelming harms of smoking to human health. We integrated genomic and proteomic approaches to investigate the causality and molecular basis of this potential relationship. MethodsWe analyzed summary statistics from genome-wide association studies (GWAS) of smoking initiation (SmkInit), smoking intensity, and PD. Two-sample Mendelian randomization (MR) tested whether genetic liability to smoking behaviors causally influences PD risk. Shared genomic architecture was quantified using MiXeR, and conjunctional false discovery rate (conjFDR) analysis identified loci jointly associated with smoking and PD, which were then mapped to genes and tested for tissue enrichment. To identify mediating proteins, we integrated dorsolateral prefrontal cortex proteomic data with GWAS using proteome-wide association studies (PWAS), summary-based MR, heterogeneity in dependent instruments testing, and colocalization. Finally, the druggability of convergent genes was evaluated. ResultsMR analyses indicated a protective effect of genetic liability to SmkInit on PD risk (OR = 0.78, 95% CI: 0.67-0.91, P = 1.5 x 10-3), which was consistent across sensitivity analyses and not suggestive of directional pleiotropy. However, no significant effect of genetic liability to cigarettes per day (CigDay) on PD risk was found. MiXeR revealed modest polygenic overlap between SmkInit and PD (13.9%; genetic correlation rg = -0.16) and between CigDay and PD (22.9%; rg = -0.09). ConjFDR identified 95 shared loci for SmkInit-PD and 26 for CigDay-PD. SmkInit-PD loci mapped to genes involved in neurotrophic signaling, synaptic organization, microglial modulation, and mitochondrial stress responses, with expression enriched in substantia nigra, basal ganglia, and interconnected cortical regions. PWAS identified 11 proteins shared by PD and SmkInit and 5 shared with CigDay, several of which (AKT3, MAPT, RIT2, EXD2, and PPP3CC) were supported by both genomic and proteomic analyses. Druggability assessment highlighted six proteins with existing pharmacologic modulation potential, spanning neurotrophic, microglial, proteostatic, and ion-channel pathways. ConclusionsGenetic liability to smoking initiation appears to confer modest protection against PD. Integrative genomic and proteomic evidence converges on neurotrophic, synaptic, microglial, and mitochondrial pathways as shared mechanisms, identifying biologically coherent potential therapeutic targets for advancing smoke-free neuroprotective strategies in PD.

Focal cortical dysplasias (FCDs) are one of the most common structural causes of drug-resistant epilepsy in children but are frequently subtle and difficult to detect on conventional MRI. Many automated lesion detection methods have therefore been proposed to support neuroradiological assessment. In this study, we externally validated two recently developed deep-learning approaches for FCD detection, MELD Graph and 3D-nnUNet, in a pediatric cohort. In this retrospective single-center study, brain MRI scans of 71 children evaluated for epilepsy were analyzed, including 35 MRI-positive patients with suspected FCD and 36 MRI-negative cases based on the primary radiology reports. Both models were applied to standard 3D T1-weighted and 3D FLAIR images. Detected lesions were reviewed by an experienced pediatric neuroradiologist and classified as true positive, false positive, or false negative. Clinical semiology and EEG findings were additionally evaluated for cases with false-positive detections. At the lesion level, MELD Graph achieved a precision of 0.85 and recall of 0.52, while 3D-nnUNet achieved a precision of 0.91 and recall of 0.48. In the MRI-negative patients, MELD Graph produced more false-positive detections than 3D-nnUNet (0.53 vs. 0.14 false-positive lesions per patient). At the patient level, MELD Graph showed slightly higher sensitivity than 3D-nnUNet (0.63 vs. 0.54), whereas 3D-nnUNet demonstrated markedly higher specificity (0.86 vs. 0.56). Improved FLAIR image quality was associated with trends toward improved model performance. Both models demonstrated high precision but moderate sensitivity, indicating that they are valuable decision-support tools but cannot replace expert neuroradiological evaluation. Optimized MRI acquisition protocols are needed to further improve automated lesion detection in pediatric epilepsy.

Background: Sleep wake and circadian disturbances are increasingly recognised in people living with amyotrophic lateral sclerosis (plwALS), but endogenous circadian phase timing and its prognostic significance in early disease remain unclear. We assessed whether salivary dim-light melatonin onset (DLMO), an objective marker of central circadian phase, is altered in early plwALS and whether it provides prognostic information. Methods: In this prospective longitudinal observational study, plwALS within 18 months of symptom onset underwent home-based salivary melatonin sampling under dim light conditions at six predefined time points around habitual sleep onset (HSO). Melatonin profiles were modeled using cubic smoothing splines, and DLMO was defined as the first time the fitted curve reached 3 pg/mL. Clinical, respiratory, and sleep assessments were collected at baseline (T0) and after 6 months (T6); a subgroup repeated saliva sampling at T6. Age and sex matched controls underwent melatonin profiling. Associations with disease progression, incident respiratory symptoms, and survival/tracheostomy were examined using regressions and survival analyses. Results: Fifty plwALS were enrolled. Compared with controls, plwALS showed an earlier DLMO (20:24 vs 20:58; p=0.028) despite similar HSO and chronotype. Within ALS cohort, a later baseline DLMO correlated with worse functional/motor status, faster progression of disease, incident dyspnea/orthopnea by T6 (adjusted OR 3.02; p=0.017), and poorer survival/tracheostomy-free outcome. In re-sampled subgroup (n=28), DLMO and other melatonin-derived metrics did not change over 6 months. Conclusions: Circadian phase alterations are detectable in early ALS. Baseline DLMO may represent a non-invasive prognostic biomarker for progression, respiratory symptom emergence and survival, warranting validation in larger multicentre cohorts.

Background Friedreich ataxia (FRDA) is a rare neurodegenerative disorder with substantial heterogeneity in clinical presentation and progression, complicating prognosis and trial design. Neuroimaging offers objective biomarkers to track disease evolution, yet variability in progression patterns remains poorly understood. Objective To identify biologically meaningful FRDA progression subtypes using longitudinal multimodal MRI and assess their associations with demographic, genetic, and clinical factors. Methods Longitudinal structural and diffusion MRI data from 54 FRDA and 57 controls were analysed. Annualised progression rates of macrostructural (volumetric) and microstructural (diffusion) features across cerebellum, brainstem, and spinal cord regions were clustered using Gaussian Mixture Models. Cluster robustness was assessed using per-cluster Jaccard similarity and other validation metrics. Random Forest classification examined predictors of cluster membership. Results Three reproducible clusters/subtypes emerged: micro-dominant/dual progression, characterised by widespread microstructural deterioration with modest volumetric decline; macro-dominant, marked by pronounced volumetric decline with minimal microstructural change; and minimal/no progression, showing negligible change in all measures. FRDA participants predominated in the first two clusters. Random Forest prediction of cluster membership using clinical and demographic variables identified length of the trinucleotide repeat expansion in the FXN gene as key predictor. Conclusions Data-driven clustering of longitudinal MRI identified distinct FRDA subtypes with unique co-progression patterns, underscoring genetic burden as a key driver. Recognising such heterogeneity can improve patient stratification, enable personalised monitoring, and guide targeted therapeutic strategies. Future studies should validate these subtypes in larger, more diverse cohorts and integrate additional biomarkers for enhanced precision.

BackgroundPhenoconversion to Parkinsons disease (PD) or dementia with Lewy bodies (DLB) currently relies on established clinical diagnostic criteria. Availability of in vivo biomarkers--CSF -synuclein seed amplification assay (CSFaSynSAA) and dopamine transporter (DAT) imaging--offer the opportunity to investigate congruency between clinical phenoconversion and biologically defined disease. MethodsWe analyzed Parkinso[n]s Progression Markers Initiative participants who phenoconverted to PD, DLB, multiple system atrophy (MSA), Alzheimers disease (AD) or other dementias from prodromal and non-manifesting genetic carrier (NMC) groups and controls. Site investigators determined phenoconversion based on established diagnostic criteria. All phenoconverters with [≥]1 annual follow-up visit, with available biomarkers and persistent clinically defined diagnosis at last observation were included. Neuronal alpha-Synuclein Disease Integrated Staging System (NSD-ISS) staging was applied. ResultsAmong 121 phenoconverters, 103 had evaluable CSFaSynSAA and DAT data and were included in analysis: 92 PD, 7 DLB, 2 MSA, 2 AD/other dementias. Phenoconversion annual rates varied widely across groups: iRBD 7.9%, hyposmia 4.2%, GBA1 0.3%, LRRK2 1.3%, LRRK2+GBA1 0.9%, and controls 0.5%. Median time from baseline to phenoconversion ranged from 13-14 months in iRBD and hyposmia to 36-85 months in NMCs. The expected biomarker profile (CSFaSynSAA+/DAT+) for clinically-diagnosed synucleinopathy occurred in 74 (71.8%) participants. Biological alignment (CSFaSynSAA+/DAT+) was present in 87% hyposmics and 72% iRBD phenoconverters. CSFaSynSAA negativity was high among LRRK2 phenoconverters (67%), who also were more likely to have a preserved sense of smell (83%). Phenoconversion occurred later than onset of functional impairment: 15/47 (31.9%) iRBDs and 7/38 (18.4%) hyposmics were already NSD-ISS stage [≥]4 at time of phenoconversion. ConclusionsClinical phenoconversion did not necessarily align with biological evidence of synucleinopathy or dopaminergic loss and can be delayed compared to onset of meaningful functional impairment. Longitudinal follow up on converters without biological evidence of PD is required to confirm conversion diagnosis and evaluate for a later occurrence of biomarker positivity.

Abstract/SummaryO_ST_ABSBackgroundC_ST_ABSCerebrospinal fluid (CSF) -synuclein seed amplification assay (SAA) has emerged as a diagnostic biomarker for Parkinsons disease (PD) and has been linked to differences in disease severity and progression. However, whether SAA status predicts responsiveness to levodopa remains unknown. We investigated the longitudinal association between SAA status, levodopa responsiveness, dopaminergic denervation, and motor complications in sporadic PD. MethodsIn this longitudinal analysis, PD participants from the Parkinsons Progression Markers Initiative (PPMI) cohort with CSF SAA testing who initiated levodopa treatment were included. SAA- and SAA+ patients were matched on sex, age, and disease duration at treatment initiation. Motor severity was assessed using MDS-UPDRS Part III, with proportional and absolute responsiveness derived from ON and OFF medication states. Motor complications were assessed using MDS-UPDRS Part IV, and dopaminergic dysfunction was quantified using caudate DAT-SPECT. Linear mixed-effects models examined longitudinal differences as a function of SAA status. FindingsIn this analysis, 40 SAA- patients were compared to 183 matched SAA+ patients. SAA+ patients showed a slower rate of ON-state motor progression than SAA- patients (0.87 vs 3.47 points/year; p = 0.01). Consistently, proportional levodopa responsiveness increased over time in SAA+ patients while declining in SAA- patients (p = 0.036). These differences were accompanied by lower caudate DAT binding at treatment initiation in SAA- patients (p = 0.002) and faster dopaminergic decline over time (p = 0.008). Although SAA+ patients had fewer motor complications at treatment initiation, their progression was similar. InterpretationCSF -synuclein SAA status is associated with divergent levodopa response in PD, with SAA+ patients showing sustained and progressively greater motor benefit, while SAA- patients show declining responsiveness. Faster dopaminergic denervation in SAA- patients may underlie this difference. SAA status captures clinically relevant heterogeneity that may inform patient stratification and therapeutic decision-making.

Objective: Spinocerebellar ataxia type 1 (SCA1) is a rare, inherited neurodegenerative disease characterised by progressive deterioration of motor and cognitive function. Here, we illustrate the pattern and evolution of brain atrophy in people with SCA1 using a large multisite dataset. Methods: Structural magnetic resonance imaging data from SCA1 (n=152) and healthy control (n=131) participants from seven sites and two consortia were analyzed using voxel-based morphometry. Cross-sectional stratification and correlations were undertaken with ataxia severity and duration to profile disease evolution. Cerebrocerebellar structural covariance analysis was used to understand the relationship between cerebral and cerebellar tissue atrophy. Results: Atrophy in SCA1 first manifests in the lower brainstem and cerebellar white matter (WM), before progressing to the pons, anterior cerebellum, and cerebellar lobule IX. The midbrain and peri-thalamic WM and the remainder of the cerebellar cortex are then affected, with preferential involvement of specific motor and cognitive areas. Finally, degeneration in the striatum and cerebral WM corresponding to the corticospinal tract become apparent. Atrophy and correlations with ataxia severity are most pronounced in the cerebellar WM and pons. Structural covariance analysis showed reduced correlations between cerebellar and cerebral WM volume in SCA1 participants. Interpretation: Cross-sectional stratification of a large SCA1 cohort by ataxia severity indicates a pattern of atrophy spread across the brainstem, cerebellum, and subcortical grey and white matter. Ongoing volume loss throughout the disease course is most evident in a core set of infra-tentorial brain regions. Atrophy of cerebellum spans both motor and cognitive functional zones. Cerebellar degeneration is not directly mirrored by downstream effects in the cerebrum.

1.PurposeSYNGAP1-related developmental and epileptic encephalopathy (SYNGAP1-DEE) is characterized by high rates of both epilepsy and autism spectrum disorder (ASD). While the clinical spectrum is well-documented, the link between specific seizure semiologies and caregiver-reported autistic behaviors is not well understood. This study analyzed the correlation between ten distinct seizure types, their frequencies, and a caregiver-reported autistic behavior score. MethodClinical data were extracted from the PATRE (PATient-based phenotyping and evaluation of therapy for Rare Epilepsies) Registry for SYNGAP1, in the framework of the EURAS project (Grant No. 101080580, Horizon Europe). This study employed a retrospective cross-sectional analysis of caregiver-reported registry data. Analysis was restricted to an analytic cohort of N=337 participants with complete data for both the epilepsy questionnaire (including epilepsy status, seizure semiology, and peak seizure frequency items) and the behavior questionnaire (from a total N=522 registry participants). Caregiver-reported autistic behaviors were quantified using a standardized caregiver-reported scale (Likert 1-5). Statistical associations were evaluated using the Wilcoxon rank-sum test to compare caregiver-reported autistic behavior scores across different seizure semiologies and Spearmans rank correlation to assess the impact of seizure frequency (9-point scale). ResultsWithin the analytic cohort (N=337), epilepsy was reported in 259 patients. Eyelid myoclonia was the most prevalent semiology, affecting 64.9% (n=168) of the epilepsy-positive group. Atypical absences (n=77) demonstrated the most profound and statistically robust association with higher caregiver-reported autistic behavior scores (FDR-adjusted p = 0.001). Significant associations were also observed for typical absences (n=70, FDR-adjusted p = 0.018), eyelid myoclonia (FDR-adjusted p = 0.018), myoclonic-atonic seizures (n=40, FDR-adjusted p = 0.019), and atonic seizures (n=72, FDR-adjusted p = 0.025). Focal and tonic-clonic seizures showed weaker associations (FDR-adjusted p = 0.026 and p = 0.047, respectively). Crucially, quantitative analysis revealed no significant correlation between ordinal caregiver-reported peak seizure frequency ratings and caregiver-reported autistic behavior scores across all semiologies (e.g., Eyelid Myoclonia: p=0.096; Atypical Absences: p=0.744), indicating no detectable association between peak-frequency ratings and caregiver-reported autistic behavior scores. ConclusionHigher caregiver-reported autistic behavior scores in SYNGAP1-DEE were most strongly associated with the presence of atypical absences, representing a generalized, thalamocortical seizure network dysfunction. In contrast, no detectable association was observed between caregiver-reported autistic behavior scores and the ordinal caregiver-reported peak seizure frequency metric. Atypical absences and related semiologies may serve as clinical "red flags" for increased neurodevelopmental comorbidity severity, regardless of reported peak seizure frequency. Abstract SummaryThis study investigates the relationship between ten seizure semiologies, seizure frequency, and severity of caregiver-reported autistic behaviors in a large-scale international cohort of N=337 patients with SYNGAP1-DEE. We identify a robust association between elevated caregiverreported autistic behavior scores and specific thalamocortical seizure patterns, most prominently atypical absences. Notably, our analysis reveals that this association is independent of seizure frequency, demonstrating no detectable association between this ordinal, caregiver-reported seizure frequency metric and caregiver-reported autistic behaviors.

BackgroundAcute basilar artery occlusion (BAO) causes devastating strokes. Despite the benefit of endovascular treatment, the optimal management remains sometimes controversial, such as for patients with mild deficits, and would benefit from robust prognostic tools. Given the dense white matter networks within the posterior fossa, we tested whether quantifying disconnections from acute diffusion-weighted imaging (DWI) could improve outcome prediction and responders to recanalization compared with conventional metrics. MethodsWe conducted a secondary analysis from a prospective multicenter stroke registry, including consecutive patients (2017-2024) with BAO and admission MRI. Ultra-high-resolution diffusion MRI was acquired in healthy participants to build normative tractograms with optimized posterior fossa quality. Patient infarcts delineated on DWI were projected onto these tractograms to estimate disconnected fiber volume. The primary outcome was 90-day modified Rankin Scale (mRS) 0-3 vs 4-6. Predictive performance of disconnected fiber volume was compared with baseline NIHSS, infarct volume, and posterior circulation ASPECTS (pc-ASPECTS) using logistic regressions and areas under receiver operating characteristic curves (AUC). Ordinal regressions tested associations across the full mRS spectrum, stratified by recanalization status. Analyses were repeated in patients with NIHSS [&le;]10. ResultsAmong 201 patients (median age 70; NIHSS 10), 97 (48.3%) had poor outcome. Despite small median infarct volume (4.75 mL), disconnected fiber volume was substantial (median 25.15 mL). Disconnected fiber volume achieved an AUC of 0.84, outperforming NIHSS (0.67; p<0.0001), infarct volume (0.75; p=0.00059), and pc-ASPECTS (0.76; p=0.0127). Low disconnected fiber volume predicted better outcomes across the full mRS (OR=0.12 [95% CI, 0.065-0.204]) and greater benefit from successful recanalization (OR=0.33 [95% CI, 0.15-0.70]). In patients with NIHSS [&le;]10 (n=102), disconnected fiber volume remained the strongest predictor (AUC=0.83). ConclusionsDisconnected fiber volume derived indirectly is a robust prognostic marker of BAO outcomes that outperforms conventional predictors and may support future treatment decisions. Registrationhttps://clinicaltrials.gov - NCT03776877.

ObjectiveIn individuals with drug-resistant epilepsy, accurately identifying the brain regions where seizures originate is a critical prerequisite to guide surgical treatment and achieve seizure freedom. To accomplish this, intracranial EEG is considered the gold standard, providing the spatiotemporal high-resolution data necessary to pinpoint epileptogenic activity. However, this precision is achieved through an invasive procedure with significant patient burden, which is fundamentally limited by the electrode placement and spatial coverage. MethodsIn this study, we investigated the potential utility of preoperative resting-state fMRI to non-invasively map alterations in brain dynamics at the whole brain level. Region-wise brain dynamics were quantified with complementary measures of local autocorrelation decay rates. We assessed the capacity of these derived features to effectively identify intracranial EEG confirmed seizure onset zones in 18 individuals with drug-resistant medial temporal lobe epilepsy. Overall, the study cohort contained 3867 implanted electrodes of which 159 classified as seizure onset zones by two independent board-certified epileptologists. ResultsOverall, our findings reveal more constrained temporal dynamics for brain regions associated with seizure onsets compared to non-seizure onset zones. Individual-level prediction showed a performance better than chance in 15 of the 18 patients. The overall predictive performance across all patients yielded a median AUC of 0.81, a median true positive rate of 0.75, and a median true negative rate of 0.83. Furthermore, in a subset of 13 patients, those with negative seizure outcomes showed higher probabilities of seizure onset zone predictions outside the resection area compared to those with good outcomes. SignificanceOverall, our findings suggest that altered temporal dynamics derived from preoperative resting-state fMRI represent a promising non-invasive approach for delineating epileptogenic tissue, potentially informing intervention strategies and guiding electrode placement.

INTRODUCTIONAlzheimers disease (AD) manifests a specific spatial progression pattern, but its propagation mechanisms remain unclear. METHODSWe employed nine brain connectomes spanning multiple biological levels to investigate the mechanisms underlying cortical atrophy propagation in AD. Individual gray matter atrophy maps were quantified using normative modeling and were then mapped onto the connectomes by assessing the relationship between regional atrophy and the atrophy of neighboring regions defined by each connectome. RESULTSCross-sectionally, node-neighbor relationship was weak in the preclinical stage, suggesting limited influence of connectome architecture. Longitudinally, atrophy became progressively more aligned with the neurotransmitter receptor similarity connectome in individuals with MCI converting to AD dementia and dementia patients. DISCUSSIONOur findings described a stage-dependent shift in cortical atrophy propagation, with neurotransmitter receptor similarity playing an increasing role as AD progresses.

Post-stroke cognitive recovery is difficult to predict using focal lesion characteristics alone. The brain's capacity to maintain cognitive function depends also on structural integrity of the whole brain. One way to measure brain health is through the severity of cerebral small vessel disease (CSVD) markers, which reflect aging-related pathologies that erode structural integrity. Here, we propose a composite measure of CSVD (cCSVD) integrating three independently validated biomarkers automatically quantified using T1-weighted MRIs: white matter hyperintensity volume (WMH; representing vascular injury), perivascular space count (PVS; putative glymphatic clearance), and brain-predicted age difference (brain-PAD; structural atrophy). We hypothesize that cCSVD, which captures the shared variance across these CSVD biomarkers, will be a robust indicator of whole-brain structural integrity and predict cognitive changes 3 months after stroke. We analyzed 65 early subacute stroke survivors with assessments within 21 days (baseline) and at 90 days (follow-up) post-stroke. WMH volume, PVS count, and brain-PAD were quantified from baseline T1-weighted MRIs, and then residualized for age, sex, days since stroke, and intracranial volume. Principal component analysis (PCA) of the residualized biomarkers was used to derive cCSVD. Beta regression with stability selection using LASSO was used to model three outcomes: baseline Montreal Cognitive Assessment (MoCA) scores, follow-up MoCA scores, and longitudinal change (follow-up score adjusted for baseline score). Logistic regression was used to test if baseline cCSVD predicted improvement in those with baseline cognitive impairment (MoCA < 26). The PCA revealed that the first principal component (PC1) explained 43.1% of the total variance among WMH volume, PVS count, and brain-PAD. The three biomarkers contributed nearly equally to PC1, which was subsequently used as the baseline cCSVD score. Lower baseline cCSVD was significantly associated with better MoCA scores at follow-up ({beta} = -0.19, p = 0.009), even after adjusting for baseline MoCA ({beta} = -0.12, p = 0.042), and, importantly, outperformed all individual biomarkers. Furthermore, lower cCSVD at baseline significantly increased the likelihood of improving to cognitively unimpaired status at three months (OR = 0.34, p = 0.036), independent of age and education. The composite CSVD captures the additive impact of vascular injury, glymphatic dysfunction, and structural atrophy on recovery in a way that individual measures do not. cCSVD accounts for shared variance across these domains, reflecting a patient's latent capacity for cognitive recovery, where relative integrity in one CSVD domain may mitigate effects of another. This automated, T1-based framework offers a scalable tool for predicting post-stroke recovery.

Objectives: To evaluate the diagnostic performance of the -synuclein seed amplification assay (SAA) and characterize the impact of -synuclein co-pathology on cognitive and biological profiles in routine clinical practice. Methods: We included 398 patients from the prospective multicenter ALZAN cohort recruited from memory clinics in Montpellier, Nimes, and Perpignan. All participants underwent CSF and blood sampling with measurement of CSF biomarkers (A{beta}42/40, tau, ptau181) and plasma biomarkers (A{beta}42/40, ptau181, ptau217, GFAP, NfL). Cognitive assessment was performed using the Mini-Mental State Examination (MMSE). Clinical diagnoses were independently confirmed by two senior neurologists. Syn status was determined by SAA (RT-QuIC). Results: Of 398 patients, 19 out of 20 patients with Lewy body dementia (LBD) (95.0%) and 32 out of 203 patients with AD (15.8%) were SAA+. SAA-positivity presented a sensitivity of 95% and a specificity of 93.5% for distinguishing LBD from patients without LBD or AD. In the entire cohort, SAA+ patients showed lower MMSE scores (p<0.01), lower CSF A{beta}42/40 ratio (p<0.01), and elevated plasma GFAP (p<0.05). Within the AD group, no significant differences in CSF or blood biomarkers were observed between SAA+ and SAA- patients. Within the AD subgroup, no significant differences in CSF or blood biomarkers were observed between SAA+ and SAA- patients, except for a lower CSF A{beta}42/40 ratio in SAA+ patients (p<0.01). Interpretation: SAA demonstrates good diagnostic capabilities for detecting LBD and confirms notable Syn co-pathology in AD. This study highlights the limitations of routine CSF and emerging blood biomarkers in capturing Syn pathology and the value of integrating SAA into routine neurodegenerative disease assessment.

BackgroundAccelerated long-term forgetting (ALF), defined as an increased rate of memory loss over extended intervals, has so far been detected in a pilot study of patients with mild multiple sclerosis (MS). This study aimed to (I) confirm the presence of ALF in a larger, heterogeneous MS sample, (II) explore associations with patient-reported outcomes, and (III) assess the diagnostic performance of ALF tests for subjective memory impairment. MethodsThis study compared 62 MS patients and 65 age-, sex-, and education-matched healthy controls using standardized memory tests (RAVLT, WMS-IV Logical Memory subtest). Recall was assessed immediately, after 30 minutes, and after 7 days. Seven-day/30-minute recall ratios (QRAVLT, QWMS) served as primary outcomes. Self-report measures included memory complaints, fatigue, depression, and sleep disturbances. Linear regression and Receiver operating characteristic (ROC) analyses assessed predictors and diagnostic accuracy. ResultsALF was observed in multiple sclerosis since QRAVLT was lower in patients than in controls (0.64 [95% CI 0.59-0.69] vs. 0.78 [0.73-0.82], p < 0.001), as was QWMS (0.79 [95% CI 0.74-0.84] vs. 0.95 [0.90-1.00], p < 0.001), despite comparable initial learning. Greater fatigue, higher memory complaints, longer disease duration, older age, and greater disability were associated with lower ALF scores. The combined ALF score moderately discriminated subjective memory impairment (AUC 0.74; sensitivity 0.73; specificity 0.73). ConclusionMS patients showed ALF despite normal initial learning, indicating a specific memory deficit undetected by standard tests. Long-delay recall using RAVLT and WMS-IV Logical Memory subtest may improve cognitive impairment detection in MS.

BackgroundTau aggregation is the defining feature of tauopathies, however, the mechanisms by which distinct tau strains drive disease-specific responses remain unclear. Existing models largely rely on recombinant tau seeding or tau overexpression, which fail to capture the biochemical diversity of pathological tau. The aim of this study was to develop a robust and reproducible human cell-based model of disease-specific tau pathology and to use this model to determine how tau from unique diseases impact tau accumulation and lysosomal dysfunction. MethodsPatient-derived tau aggregates were enriched from post-mortem brain tissue obtained from sporadic Alzheimers disease (AD), Picks disease (PiD), progressive supranuclear palsy (PSP), and control cases using phosphotungstic acid precipitation. Patient-derived tau preparations were biochemically characterised by immunoblotting and mass spectrometry and normalised for tau content prior to seeding. Patient-derived tau aggregates were seeded into multiple human immortalised cell lines (SH-SY5Y, M03.13, U-87 MG, and U-118 MG cells) and iPSC-derived astrocytes. Tau seeding efficiency, aggregate morphology, and integrity of the autophagy-lysosomal pathway was assessed using quantitative imaging approaches. ResultsPatient-derived tau seeds retained disease-specific phosphorylation patterns and isoform composition and led to reproducible, dose-dependent insoluble tau accumulation in all cell lines tested. Despite equivalent tau input and similar background protein composition, PiD-derived tau had the most aggressive pathological signature, showing the highest number of tau aggregates per cell and inducing system wide disruptions in the autophagy lysosomal system including increased SQSTM1 puncta and lysosomal damage markers. Seeding with AD-derived tau led to a high number of tau aggregates per cell and more specifically depleted the lysosomal protease CTSD and uniquely co-seeded A{beta} pathology. Seeding with PSP-derived tau resulted in only a moderate number of tau aggregates per cell and uniquely caused increased lysosomal biogenesis. ConclusionsTogether, these results demonstrate that intrinsic properties of human tau strains drive disease-specific cellular responses and establish a scalable, physiologically relevant platform for dissecting tau-cell interactions and screening therapeutics across tauopathies.

BackgroundGangliogliomas (GGs) are low-grade glioneuronal tumors that frequently present with drug-resistant epilepsy. Although their indolent course contrasts with their high epileptogenic potential, the oncogenic mechanisms sustaining neuronal precursor-like populations within the tumor microenvironment remain poorly defined. MethodsWe performed spatial transcriptomic profiling on eight histologically confirmed GGs and matched healthy cortex to map the cellular and molecular architecture of the tumor microenvironment. Integrated analysis with weighted gene correlation network analysis (WGCNA) defined recurrent oncogenic programs and spatially resolved tumor-stroma interactions. ResultsEight conserved gene modules emerged, encompassing physiological cortical, reactive glial, and oncopathological programs. The latter captured extracellular matrix (ECM) remodeling, vascular-immune signaling, and persistence of immature, proliferative neuronal-like states. Spatial modeling revealed that these oncopathological programs form structured niches at the tumor-brain interface, where radial glia-derived neuronal-like tumor cells coexist with immune and stromal elements engaged in ECM turnover and cytokine signaling. ConclusionsGanglioglioma represents a hybrid glioneuronal neoplasm in which developmental neuronal programs are co-opted by tumor-associated stromal and immune cues. This convergence establishes a permissive oncogenic niche that sustains precursor-like tumor cells and provides a mechanistic basis for both the tumors benign growth and its intrinsic epileptogenicity. Key PointsO_LISpatial transcriptomics identifies reproducible transcriptional programs that define the ganglioglioma microenvironment. C_LIO_LITumor-associated regions show transcriptional programs consistent with immature neuronal states together with ECM remodelling and immune activity. C_LIO_LISingle-cell reference data indicate that immature neuronal programs in ganglioglioma resemble radial glia-derived developmental states. C_LI Importance of the StudyGanglioglioma is a low-grade glioneuronal tumor that combines benign growth with pronounced epileptogenicity, yet the molecular basis of this dual behavior remains poorly understood. Through spatial transcriptomics integrated with single-cell analysis, we reveal that ganglioglioma architecture is defined by two interacting transcriptional axes: a residual glioneuronal network and a tumoral niche enriched for extracellular-matrix, vascular, and immune programs. Within these niches, immature neuronal-like tumor cells persist in a developmentally arrested state maintained by ECM-immune signaling. This spatially organized interplay between physiological and pathological programs explains both the low oncologic aggressiveness and high excitability of these lesions. Our findings provide molecular signatures that may refine diagnostic classification within the LEAT spectrum, delineate epileptogenic zones, and identify candidate pathways for therapeutic modulation of the ganglioglioma microenvironment.

BackgroundChronic relapsing inflammatory optic neuropathy (CRION) is a steroid-dependent form of optic neuritis with incompletely understood pathophysiology. The identification of myelin oligodendrocyte glycoprotein antibodies (MOG-IgG) in a substantial patient subset has challenged the diagnostic and therapeutic management. The aim of this study was to investigate clinical profiles and treatment outcomes of patients with CRION, comparing MOG-IgG-positive (MOG+) and seronegative (MOG-) subgroups. MethodsPatients from six European tertiary centers fulfilling diagnostic criteria for CRION were included. All underwent cell-based autoantibody testing. Clinical outcomes (visual acuity, annualized relapse rate), laboratory and imaging findings (MRI, OCT), and treatment responses were retrospectively analyzed. ResultsSixty patients were included (median age 33 years; 70% female); 27 (45%) were MOG+. MOG+ CRION was associated with later onset, higher ARR before treatment (median [IQR] 2 [1-3] vs. 1 [1-2], p = 0.023), and a trend toward shorter inter-relapse intervals. Additional distinguishing features included higher frequencies of antinuclear antibody positivity, elevated CSF interleukin-6, and extensive optic neuritis on MRI. Relapse burden correlated with visual acuity decline and retinal thinning. In MOG+ patients, monoclonal antibody therapy reduced the ARR (n = 21; 2 [1-3] vs. 0 [0-2], p = 0.024), primarily driven by tocilizumab (n = 11; 2 [1-3] vs. 0 [0-1], p = 0.023). In MOG-patients, rituximab and azathioprine showed a trend toward ARR reduction. ConclusionCRION represents a heterogeneous syndrome encompassing distinct subgroups. MOG+ patients demonstrate higher disease activity but respond favorably to tocilizumab. Serological testing is critical for treatment stratification and preventing relapses.

Biological aging is accelerated in people with multiple sclerosis, but whether such acceleration occurs during the pre-symptomatic phase or varies by organ system is understudied. We analyzed two independent proteomics datasets profiled using distinct platforms: the Johns Hopkins cohort profiled using the SomaScan platform (348 multiple sclerosis/49 age-matched controls) and the Department of Defense cohort profiled using the Olink platform (134 multiple sclerosis/79 age-matched controls), including 117 pre-symptomatic samples from people with multiple sclerosis (median lead time: 4.0 years), to estimate systemic and organ-specific proteomic age gaps using established clocks in pre-symptomatic and symptomatic phases, and assess their associations with severity. In the Johns Hopkins cohort, people with multiple sclerosis demonstrated acceleration of systemic ({beta}=2.2, 95% CI 1.2-3.2, P<0.001, FDR<0.001), brain ({beta}=1.7, 95% CI 0.6-2.7, P=0.003, FDR=0.01), muscle ({beta}=2.5, 95% CI 1.3-3.7, P<0.001, FDR<0.001), and immune age ({beta}=1.8, 95% CI 0.6-2.9, P=0.003, FDR=0.01), with findings reproduced in the Department of Defense cohort for systemic ({beta}=0.7, 95% CI 0.0-1.4, P=0.04, FDR=0.34) and brain age (3.2 years, 95% CI 2.1-4.3, P<0.001, FDR<0.001). Proteomic age acceleration was evident prior to symptom onset [systemic: ({beta}=1.0, 95% CI 0.4-1.7, P=0.002, FDR=0.02); brain: ({beta}=2.4, 95% CI 1.2-3.7, P<0.001, FDR=0.002)], whereas no immune age acceleration was detected before or after onset. Higher systemic age gap was associated with greater global Age-Related Multiple Sclerosis Severity Score ({beta}=0.14, 95% CI 0.05-0.24, P=0.005, FDR=0.03) and slower walking speed ({beta}=0.02, 95% CI 0.01-0.03, P=0.006, FDR=0.04), while higher muscle age gap was associated with greater global Age-Related Multiple Sclerosis Severity Score ({beta}=0.17, 95% CI 0.10-0.24, P<0.001, FDR<0.001), poorer manual dexterity ({beta}=0.28, 95% CI 0.04-0.52, P=0.03, FDR=0.30), slower walking speed ({beta}=0.02, 95% CI 0.01-0.03, P=0.002, FDR=0.02), lower peripapillary retinal nerve fiber layer ({beta}= -0.26, 95% CI -0.41 to -0.10, P=0.001, FDR=0.02) and ganglion cell-inner plexiform layer thicknesses ({beta}= -0.35; 95% CI -0.65 to -0.05; P=0.02, FDR=0.30). Higher brain age gap was associated with several imaging measures, including lower whole-brain ({beta}= -0.002, 95% CI -0.003 to -0.001, P=0.002, FDR=0.02), and lower peripapillary retinal nerve fiber layer thickness ({beta}= -0.21, 95% CI -0.39 to -0.03, P=0.02, FDR=0.10). Proteomic age acceleration in multiple sclerosis is detectable years before symptom onset and distinct organ-specific aging signatures are associated with disease severity. Proteomic aging may provide a biologically informative marker of early disease processes and a clinically relevant readout of disease heterogeneity.