Journal of Neurology, Neurosurgery & Psychiatry

Background: Amyotrophic lateral sclerosis (ALS) is a rare neurodegenerative disease with no known cure. Disease progression in people living with ALS is heterogeneous, hindering personalized treatment development. The current gold standard for measuring disease progression in ALS, the ALS Functional Rating Scale - Revised (ALSFRS-R), is widely used but based on subjective measurements. Blood-based neurofilament light (NfL) has been studied as a diagnostic and prognostic biomarker but less information exists on its utility as a disease progression biomarker. Methods: We present results from blood draws of 300 participants in the FDA-funded Clinic-Based Multi-Site ALS Natural History and Biofluid study of the ALS Natural History Consortium (NHC). Plasma NfL levels were measured and analyzed against different disease progression metrics based on the ALSFRS-R. Results: NfL levels were found to be correlated with the ALSFRS-R average rate of change (r=-0.53, 95% CI -0.62 to -0.42). This association differed at a cutoff value of 61 pg/mL, with stronger correlations below this cutoff (r=-0.51 vs r=-0.18). Survival differed stratifying by this cutoff value, with participants under the cutoff having higher survival probabilities. The predictive value of NfL when predicting time to death was higher compared with the first ALSFRS-R across different event horizons. A model including both was better when predicting events up to 2 years after diagnosis. Conclusions: These results highlight the utility of NfL as a disease progression biomarker in ALS alongside ALSFRS-R based disease progression metrics. The cutoff value can aid in clinical trial stratification, pragmatic trial planning, and clinical care.

Background. CNM-Au8, a catalytic nanocrystalline gold suspension, is proposed to support neuronal bioenergetics, but its effect on chronic lesion evolution in multiple sclerosis (MS) has not been reported. Objectives. To evaluate the effect of CNM-Au8 on chronic lesion tissue expansion (CLTE). Results. In this exploratory post hoc analysis of the VISIONARY randomised placebo-controlled trial, CLTE was quantified from serial FLAIR MRI. Fifty-five participants were included (CNM-Au8, n=40; placebo, n=15). Compared with placebo, CNM-Au8 was associated with lower lesion expansion rate (p=0.001; Cliffs =-0.58) and volume (p<0.001; Cliffs =-0.65). Conclusions. CNM-Au8 treatment was associated with substantially reduced chronic lesion tissue expansion.

Persistent neurological symptoms are among the most disabling manifestations of post-COVID-19 syndrome (PCS), yet the contribution of ongoing CNS immune activation remains uncertain. CSF studies including clinically relevant COVID-19 recovered control cohorts are scarce. In this prospective single-center study, we enrolled 50 patients fulfilling the WHO criteria for PCS (COVIDpost, mean age +/- standard deviation [SD] 43.41 +/- 11.99 years, 30 % male, 70 % female) and 50 individuals who had fully recovered from COVID-19 (COVIDreco, mean age +/- SD 39.38 +/- 13.45, 42 % male, 58 % female). Both cohorts were comparable regarding age (p = 0.07), sex (p = 0.30), and education (p = 0.84). All participants underwent paired CSF and serum analyses together with comprehensive neuropsychological assessment. Routine CSF parameters, blood-CSF barrier integrity, oligoclonal bands (OCB), SARS-CoV-2 RNA in CSF and blood, pathogen-specific antibody indices, and neuronal autoantibodies were investigated. Despite marked differences in cognitive performance (p < 0.001) and fatigue severity (p < 0.001), patients with PCS showed no evidence of disease-specific CSF abnormalities compared to recovered controls. Routine CSF parameters, blood-CSF barrier dysfunction, CSF-restricted OCB, SARS-CoV-2 RNA in CSF and blood, intrathecal SARS-CoV-2 antibody synthesis, polyspecific antiviral immune responses, and neuronal autoantibodies were comparable between groups. SARS-CoV-2-specific IgG concentrations in CSF correlated positively with serum concentrations (COVIDpost: r [95%CI] = 0.78 [0.62 - 0.87]; COVIDreco: r [95%CI] = 0.86 [0.75 - 0.92]; both p < 0.001) and albumin quotient (COVIDpost: r [95%CI] = 0.52 [0.26 - 0.71], p < 0.001; COVIDreco: r [95%CI] = 0.37 [0.10 - 0.60]; p = 0.01), consistent with passive transfer across the blood-CSF barrier rather than compartmentalized intrathecal immune activation. Furthermore, SARS-CoV-2-specific antibody measures were not associated with cognitive performance (p > 0.72) or fatigue severity (p > 0.88). This study provides no evidence that persistent neurological symptoms after COVID-19 are accompanied by ongoing adaptive CNS immune activation, disease-specific neuronal autoimmunity, or intrathecal SARS-CoV-2-specific humoral immune responses. The inclusion of a carefully phenotyped COVID-19 recovered comparison cohort strengthens the conclusion that routine CSF abnormalities largely do not seem to reflect mechanisms specific to PCS. These findings argue against routine CSF diagnostics as a source of disease-specific biomarkers in unselected PCS patients and support future studies focusing on alternative mechanisms underlying persistent neurological symptoms.

Familial recurrence of amyotrophic lateral sclerosis (ALS) or frontotemporal dementia (FTD) is the clinical cornerstone for assuming Mendelian, monogenic inheritance which informs genetic testing, counselling and gene-discovery strategies in standard practice. Polygenic inheritance can lead to familial clustering of ALS, while pathogenic variants with reduced penetrance may present sporadically in small, modern-day pedigrees. As both rare genetic variants and polygenic disease contribute to the occurrence of ALS, the accuracy of a positive family history to predict the underlying genetic architecture remains unknown. Using growing knowledge of the genetic architecture of ALS, we designed the APECS simulator: a large-scale pedigree simulator using historical demographic parameters, unifying frameworks for monogenic and polygenic disease models. We simulated 1,000,000 three-generation pedigrees and modelled ALS, FTD, and other dementias under both inheritance models. For index patients with ALS, we examined the performance of proposed familial ALS (fALS) definitions to predict the underlying genetic architecture. Simulation results were benchmarked against real-world population estimates, over a wide range of demographic and genetic parameters. We assessed the phenocopy rate for monogenic index patients, defined as relatives with polygenic ALS or a pathogenic allele from a different ancestor. Finally, we illustrated the value of distant relatedness among apparently sporadic, but monogenic ALS patients. Simulations generated 55.3 million individuals, yielding 5,431 ALS-affected index patients (16.4% monogenic). The proposed criterion for 'definite fALS' (2 or more relatives with ALS among relatives within two degrees) had a 31.1% sensitivity, while falsely classifying 10.0% of 'fALS' as monogenic. The sensitivity of 'definite fALS' was improved to 43.3% when also considering relatives with FTD. Considering any type of dementia raised the false positive rate to 35.9%. In total, 5.3% of monogenic index patients had a phenocopy with ALS in relatives up to the third degree. Of seemingly sporadic monogenic index patients, 83.1% had distant relatives with ALS/FTD up to the fifth degree. A family history provides limited accuracy for inferring genetic architecture in ALS. Considering unspecified dementias in the family history reduces this accuracy, while adding definite FTD improves accuracy. Relying on traditional fALS criteria risks both missing cases for genetic testing and treatments, and falsely alarming families with polygenic ALS. Given the limited value of a family history and risk of phenocopies, routine genetic testing regardless of family history and systematic approaches for detecting distant relatedness will help to find known and novel genetic causes in ALS.

Background: Rituximab is used off-label for multiple sclerosis (MS), and biosimilar substitution raises a distinct extrapolation challenge, as MS is not an approved indication for the reference product. Real-world nonmedical switching data inform biosimilar appropriateness decisions by clinicians, societies, and payers. Objective: To report the effectiveness and tolerability of nonmedical switching from originator (MabThera) to biosimilar rituximab (Truxima) in people with MS (pwMS). Methods: A retrospective, single-center observational cohort study of 50 pwMS switched after at least two originator infusions, followed for two years. Results: Annualized relapse rate declined from 0.45 (95% CI 0.28 - 0.68) prerituximab to 0.02 (95% CI 0.00 - 0.13) on originator and 0.00 (95% CI 0.00 - 0.05) on biosimilar (p = 0.367 between products). In paired imaging analysis (n = 29), the proportion with active scans declined progressively (50.0%, 34.5%, 17.2%; Cochrans Q, p = 0.040), with no difference between the originator and biosimilar periods (McNemar, p = 0.227). B-cell depletion deepened progressively. All patients remained on biosimilar through the end of follow-up. Conclusion: Nonmedical switching from originator to biosimilar rituximab was associated with comparable clinical and radiological outcomes, supporting its use in pwMS without concern for inferior efficacy or diminished tolerability.

Background: To determine the crude and age-adjusted point prevalence of motor neuron disease (MND) and its phenotypes (classical amyotrophic lateral sclerosis [ALS], primary lateral sclerosis [PLS] and progressive muscular atrophy [PMA]) using a comprehensive multi-source case ascertainment strategy. Methods: Cross-sectional population-based study with a prevalence date of 1 January 2025. Cases were identified through five complementary regional data sources and confirmed by clinical review against the revised El Escorial and Gold Coast criteria. Cases were classified by phenotype as ALS, PLS or PMA. The reference population was the population aged 15 years or older in Valencian Community (n=4,433,999). Crude prevalence was calculated per 100,000 with 95% Poisson confidence intervals; age-adjusted rates were obtained by direct standardisation to the 2013 European Standard Population. Results: A total of 374 confirmed MND cases were identified. The overall crude prevalence of MND was 8.43 per 100,000 (95% CI: 7.60-9.29) and the age-adjusted prevalence was 7.85 per 100,000 (95% CI: 7.05-8.65). By phenotype, ALS accounted for 325 cases (86.9%; crude prevalence 7.33 per 100,000), PLS for 26 (7.0%; 0.59 per 100,000) and PMA for 23 (6.1%; 0.52 per 100,000). Prevalence was consistent across provinces. Mean age was 65.9 years, the male-to-female ratio was 1.37:1, and 83.4% were receiving riluzole. Conclusions: This is the first comprehensive, multi-source population-based estimate of MND prevalence and its subtypes in the Valencian Community. The estimate is higher than the previous single-unit figure and consistent with recent European data, underscoring the value of multi-source ascertainment.

Progressive multiple sclerosis (PMS) lacks blood-based biomarkers of the neurodegenerative processes driving disability. We measured synaptopodin, a postsynaptic protein, in neuronal-enriched extracellular vesicles (NEVs) across two independent cohorts: the SPRINT-MS trial (n=184) and a real-world validation cohort (n=268). A one SD increase in baseline synaptopodin was associated with ~32% lower risk of confirmed disability progression in PMS (p=0.011), with the strongest effect in secondary PMS (SPMS) (~57% lower odds, p=0.019). This SPMS association was replicated in the validation cohort (~60% lower odds, p=0.009). Higher baseline synaptopodin was associated with future slower whole-brain atrophy and preserved microstructural integrity across MRI metrics (p=0.007-0.013). Longitudinal changes in NEV synaptopodin were associated with disability worsening (p=0.007) and paralleled MRI microstructural changes. NEV synaptopodin, but not NfL, was associated with confirmed disability progression in PMS participants with both biomarkers measured (HR 0.71 vs 1.12, p=0.007 vs 0.22 for NEV synaptopodin and NfL, respectively) and SPMS (HR 0.58 vs 1.10, p=0.003 vs 0.50). Adding synaptopodin, but not NfL, to a base model improved discrimination for disability progression in SPMS in both cohorts (e.g. validation AUC 0.755 to 0.838, p=0.005). These findings identify NEV synaptopodin as a prognostic and longitudinal, blood biomarker of synaptic integrity in PMS, particularly SPMS, complementing NfL.

Background and Objectives. Prion disease is an untreatable, typically rapidly progressive dementia. New drug candidates designed to lower prion protein are now entering clinical trials. To support future pivotal trials, we sought to assemble and analyze a public dataset of natural history data characterizing the symptomatic course of prion disease in order to provide a quantitative basis for modelling and rational trial design. Methods. We extracted data from medical publications between 2000 and 2024 reporting on n[&ge;]5 prion disease patients. Information about demographics, ascertainment, and clinical milestones, such as time from onset to death, akinetic mutism, diagnostic testing and outcomes, were extracted for aggregate cohorts of [&ge;]2 patients and individual patient-level data (PLD). We computed summary statistics of cohorts and PLD, visualized survival through forest plots and Kaplan-Meier curves, analyzed covariates regarding survival, and identified biases and heterogeneity within the literature. Results. From 245 included publications we extracted 418 aggregate cohort medians and 1,400 rows of individual PLD. 90% of cohorts and 91% of individual patients had symptom-to-death milestones, while only 7% and 11% had a time interval from a clinical presentation milestone to death, respectively. Symptom-to-death intervals varied as much as 3.2-fold even between cohorts of the same histopathologic subtype, and akinetic mutism occurred 73% sooner than death when both endpoints were reported (N=53). Indicators of disease severity, such as a cognitive test, were rarely present in either aggregate data (11%) or PLD (6%). Discussion. Data routinely reported in publications can quantify diagnostic delay and covariates affecting survival time, but are limited in ability to inform pivotal trial design because most such data are aggregated, cross-sectional, lack indicators of disease severity, and present timelines beginning with onset rather than more relevant clinical milestones, such as diagnosis, that may better reflect the moment of potential for trial enrollment. There is a need for clinical data to report milestones such as intervals from diagnosis to death, for longitudinal cognitive and functional scores, and for deposition of publicly accessible PLD.

Background and Objectives Huntington's disease is a rare neurodegenerative disease in which optimizing clinical trial design is essential. Although baseline characteristics are known to predict disease progression, the statistical efficiency gains achievable by formally integrating prognostic predictions into trial analyses have not been systematically quantified. We aimed to benchmark prognostic modeling approaches, quantify the trial efficiency gains from prognostic covariate adjustment, and deliver a ready-to-deploy framework for immediate implementation. Methods: We developed a two-step modeling pipeline using longitudinal Enroll-HD natural history data (NCT01574053) to train nine machine learning algorithms to predict disease progression across five UHDRS endpoints. For this, we used 16 predictive baseline covariates representing stage of disease (baseline score levels), disease specific (CAP, CAG length), demographics and co-medication use that could be quantified in one clinical visit. For Total Function Capacity (TFC), frequently used as a primary endpoint in clinical trials, we also devised a minimal prognostic model based on 6 covariates. Model performance was tested using the placebo arm of the GENERATION HD1 phase 3 trial (NCT03761849). Results: Models were trained on 16,398 Enroll-HD participants and tested on 260 participants from the GENERATION HD1 placebo arm. Models that take into account nonlinear relationships between the covariates showed no performance advantage over linear-based models on the test set. For TFC, a minimal six-covariate linear prognostic model performed on par with the full 16-feature model. Adjusting for the prognostic score increased the signal-to-noise ratio across different trial visits by 8-18%, raising statistical power from 80% to up to 90% at a fixed sample size, or, equivalently, reducing required sample size by 15-28% compared to unadjusted analyses (no covariate adjustment). Compared to routinely used covariate adjustments (including baseline score, age, CAG repeat length, and CAP score), adjusting for a prognostic score consistently delivered meaningful additional efficiency gains. Discussion: Prognostic covariate adjustment using a simple six-covariate linear score derived from a single baseline visit yields meaningful gains in statistical power for HD clinical trials, while remaining fully embedded within standard, regulator-accepted analysis frameworks. This approach offers a practical and immediately deployable tool to improve trial design.

Background: Haemorrhagic stroke, comprising intracerebral haemorrhage (ICH) and subarachnoid haemorrhage (SAH), accounts for a disproportionate share of stroke mortality and disability, and its incidence rises steeply with age. Secondary injury processes, including neuroinflammation, cerebral oedema, autonomic dysfunction and vasospasm, are potentially modifiable. Vagus nerve stimulation (VNS) engages several of these pathways, but its therapeutic role remains uncertain. We reviewed the preclinical and clinical evidence for VNS in haemorrhagic stroke. Methods: PubMed and MEDLINE were searched from inception to 1 June 2026 for preclinical studies and randomised clinical trials of VNS in ICH or SAH. Evidence was synthesised narratively; quality was assessed using SYRCLE and PEDro. Comparable binary functional outcomes (modified Rankin Scale [mRS] 0 to 2) were pooled using a random-effects inverse-variance model. Results: Nine reports were included: four preclinical (179 animals) and five clinical (166 participants representing four independent cohorts). Preclinical studies reported reduced inflammatory signalling, smaller haematoma volume, lower aneurysm rupture rates, improved survival and enhanced motor recovery, with attenuated effects in severe injury models. Clinically, non-invasive VNS was feasible and well tolerated, with signals of reduced tumour necrosis factor alpha and interleukin 6, less radiographic vasospasm and delayed cerebral ischaemia, and increased parasympathetic activity. Pooled favourable functional outcome favoured VNS but was not statistically significant (odds ratio [OR] 1.82, 95% confidence interval [CI] 0.68 to 4.86; p = 0.24; I squared = 0%). Excluding major haemorrhage yielded OR 2.85 (95% CI 0.97 to 8.36; p = 0.06). Conclusions: VNS is biologically active and feasible after haemorrhagic stroke but remains unproven. Adequately powered, severity-stratified multicentre trials with standardised stimulation protocols and age-appropriate outcomes are required.

Transcriptional risk scores, an integrated score of genomic susceptibility variants with expression Quantitative Trait Loci (eQTL) data, may more accurately distinguish clinical phenotypes compared to polygenic risk scores. This approach has not been applied to multiple sclerosis. We integrated data from the largest GWAS of MS, involving 14,802 MS patients, with eQTL data from 7,466 blood donors and 5,494 brain donors, using summary-data-based Mendelian randomization (SMR) followed by the heterogeneity in dependent instruments (HEIDI) test. MS SNVs with a significant eQTL were integrated with single-cell RNA sequencing data from 1,27 million peripheral blood mononuclear cells from 927 donors and 750,614 single nucleus RNA sequencing central nervous system cells from 192 individuals using Bayesian colocalization. Derived polygenic and cell-line specific transcriptional risk scores were compared with age-related MS severity score (ARMSS) in a cohort of 1,077 MS patients from the South Wales MS Registry and with MRI-derived age-adjusted total brain volumes of 272 MS patients within the UK Biobank. Cell-line specific transcriptional risk scores were associated with MS outcomes in two independent cohorts. Our results identified MS-associated eGenes enriched across several biological pathways, providing insights into pathophysiological mechanisms in MS that could facilitate precision medicine and identify novel druggable pathways.

Background: Therapy development in ultra-rare, progressive and fatal diseases like vanishing white matter (VWM) is hampered by very low patient numbers and ethical constraints regarding placebo-controlled studies. Under such conditions, standard randomized controlled trials may not be feasible. The use of historical control information could be part of a solution, but would require extra considerations regarding selection of patients and choice of endpoints. We used the VWM registry as a case study to outline key methodological considerations for informing trial design in ultra-rare disease. Methods: The study included 462 patients, available in the VWM registry. Prospective clinical data were collected since 2004 using VWM-specific questionnaire and Health Utility Index (HUI) assessments, while retrospective data from clinical charts were available from 1988 on. We evaluated methodological aspects relevant to trial design, including patient selection, drift in the disease course over time, endpoint selection, and clinically relevant stratification into subgroups. Results: Regarding patient selection, patients with comorbidities impacting disease course, and pre-symptomatic individuals without clinical onset were considered not suitable as historical controls. After excluding patients before 1991, we found no evidence of drift in the disease course from 1991 onwards. Regarding choice of endpoints, episodes of rapid decline were relatively infrequent and occurred mostly at disease onset, limiting their usefulness as trial endpoint. Multi-state modelling and clinical evaluation showed ambulation as preferable endpoint over survival. For longitudinal HUI multiscores, baseline imputation allowed modelling of early disease. The scores showed a distinct ordering, reflecting the association between multi-domain function and disease progression. Regarding stratification, the combination of data-driven analyses and clinical expertise informed revised age of onset groups. Females showed later onset and milder disease; adjustment for age of onset eliminated the effect of sex. Conclusion: This case study provides key considerations for evaluating registry data as historical control and demonstrates how these considerations can inform clinical trial design in ultra-rare diseases.

Objective To examine whether prospectively recorded maternal BMI in early pregnancy is associated with offspring multiple sclerosis (MS) risk, including childhood-onset and adult-onset MS. Design Nationwide population-based cohort study. Setting Swedish national health and demographic registers. Participants 1,524,863 singleton children born in Sweden from 1992 to 2007 and followed through 2025. Exposures Maternal BMI recorded at the first antenatal visit, categorised as underweight (<18.5), normal weight (18.5-24.9), overweight (25.0-29.9), and obesity ([&ge;]30.0), and also modelled continuously. Main outcome measures MS in offspring, identified as at least three ICD-10 G35 codes recorded on separate dates. Cox models estimated adjusted hazard ratios (HR) and 95% confidence intervals (CI) adjusting for confounders. Results During follow-up, 1539 offspring (0.1%) were diagnosed with MS at a median age of 24 years (interquartile range, 20-27 years). MS incidence rates by maternal BMI category were 0.37 per 10,000 person-years for both underweight, and normal weight, 0.42 for overweight, and 0.45 for obesity. Compared with normal weight women, maternal overweight and obesity were associated with higher hazards of offspring MS, with adjusted HRs of 1.20 (95% CI, 1.05 to 1.37) and 1.35 (95% CI, 1.11 to 1.64), respectively. Onset-specific analyses showed similar findings for adult-onset MS and less precise but directionally consistent estimates for paediatric-onset MS. Each 1-unit increase in maternal BMI was associated with a 3%, 4%, and 3% higher hazard of overall, paediatric-onset, and adult-onset offspring MS, respectively. Conclusions In this population-based cohort study, higher maternal BMI were associated with an increased rate of MS in offspring. The findings provide large-scale prospective evidence that maternal adiposity may be related to offspring MS risk and support further investigation of the prenatal metabolic environment in the early-life origins of MS.

Treatment targeting progressive multiple sclerosis (MS) have limited efficacy, as central nervous system (CNS) resident B cells are resistant to peripheral B cell depletion by antiCD20 monoclonal antibodies. CD19 targeted chimeric antigen receptor (CAR)T cells offer the promise to deplete B cells more extensively in both the peripheral and CNS compartments. Two adult participants with treatment-refractory progressive MS were treated with 0.33e8 autologous anti CD19 CAR T cells (mivocabtagene autoleucel, miv-cel) intravenously after a preconditioning regimen. Participant 1 (50's year old female, EDSS 6) had no cytokine release syndrome (CRS) or immune effector cell-associated neurotoxicity syndrome (ICANS). Participant 2 (60's year old female, EDSS 4.5) had grade 1 CRS and no ICANS. Expansion of CAR T cells in the cerebrospinal fluid (CSF) at Day 14 was noted in both participants, remarkably with sustained disappearance of disease-associated oligoclonal band (OCB) or normalization of IgG index despite peripheral naive B cell reconstitution. MRI and clinical outcomes showed sustained stability at Week 48. Serologic studies showed a decline in anti-Epstein Barr Virus seropositivity. Single cell myeloid and proteomic signatures showed a decline in proinflammatory profiles. In the 2 subjects with progressive MS reported here, low dose anti CD19 CAR T cell therapy (miv-cel) was safe, penetrated the CSF effectively, reduced intrathecal humoral activity, modulated peripheral immune tone, and appeared to stabilize EDSS scores. Overall, these results support the continued investigation of CAR T cell therapy in MS.

Background: Relapsing-remitting multiple sclerosis (RRMS) often progresses to secondary-progressive MS (SPMS), but diagnosis is typically retrospective, delaying potential interventions. Existing rule-based and machine learning approaches often lack prospective validation and provide no uncertainty estimates, limiting clinical adoption. Objective: To prospectively evaluate a conformal prediction (CP)-enabled random forest model for reproducing clinician-recorded disease course labels in the Swedish Multiple Sclerosis Registry (SMSReg) and compare its classifications with the Lorscheider criteria. Methods: The CP model was trained and calibrated on SMSReg-2022 (10,787 individuals, 85,461 hospital visits) and then validated on SMSReg-2025 (15,719 individuals, 45,077 hospital visits; not included in the SMSReg-2022 training/calibration/testing datasets). Performance was assessed at the hospital visit and individual levels and compared with the Lorscheider criteria. Results: The model maintained good calibration on the prospective dataset. At the per-hospital visit-level, the model accuracies were 92% (RRMS) and 95% (SPMS). At the individual level, sensitivity was 98%, specificity 89%, and F1-score 0.75. With clinician-recorded labels as reference, the model showed higher sensitivity than the Lorscheider criteria (98% vs. 71%), more transition assignments (90% vs. 57%), and higher F1-score (0.76 vs. 0.69). Conclusion: The CP-enabled model prospectively reproduced clinician-recorded disease course labels with calibrated uncertainty, supporting harmonization and decision support.

Tissue-based assays provide broad screening for neural autoantibodies but remain vulnerable to technical and reader-dependent variability. We evaluated an integrated workflow combining automated 3,3'-diaminobenzidine tissue-based assay processing, digital whole-slide imaging, and interpretable deep learning. Model development used 2,357 retrospective serum and cerebrospinal fluid images referred from more than 80 institutions and processed in a centralized laboratory, with reference labels established by expert-consensus tissue-based assay interpretation. A prospective validation cohort included 200 images from 200 unique patients (154 positive and 46 negative; 100 serum and 100 cerebrospinal fluid). The same images were evaluated by two expert and two novice readers in a fixed-order two-round study, with unaided interpretation followed by artificial-intelligence-assisted interpretation after a washout of at least two weeks. The standalone binary classifier achieved an area under the receiver operating characteristic curve of 0.922, accuracy of 86.5%, sensitivity of 85.7%, and specificity of 89.1% in prospective validation. Pooled reader accuracy was 90.4% in the unaided round and 97.4% in the artificial-intelligence-assisted round (McNemar P < 0.001), with specificity of 82.6% and 99.5%, respectively. Novice-reader accuracy was 83.3% unaided and 96.5% with artificial-intelligence assistance (P < 0.001), approaching unaided expert accuracy of 97.5%. Among tissue-based-assay-positive cases, reader accuracy for cytoplasmic/nuclear antigen-associated versus neural surface antigen-associated staining-pattern subclassification was 88.8% unaided and 94.0% with artificial-intelligence assistance (P < 0.001). These findings support further multicentre, cross-platform evaluation of artificial-intelligence-assisted neural autoantibody tissue interpretation.

Background: The Progressive Supranuclear Palsy Clinical Deficits Scale (PSP-CDS) is a brief rating scale of clinical severity in PSP. However, its longitudinal performance has not been evaluated. We aimed to assess the ability of the PSP-CDS to track disease progression over time and to compare progression across PSP phenotypes in a real-world Asian cohort. Methods: Patients who met the Movement Disorder Society PSP diagnostic criteria and underwent at least 2 PSP-CDS assessments were recruited from movement disorders clinics in Malaysia. Longitudinal progression was evaluated using linear mixed-effects models. Domain-specific progression and subtype-specific trajectories were also analyzed. Associations between annualized changes in PSP-CDS and Barthel Index (BI) scores were examined. Results: 104 patients (including 59 with PSP-Richardson's syndrome [PSP-RS], 28 with predominant parkinsonism [PSP-P], and 14 with progressive gait freezing [PSP-PGF]) contributed 394 PSP-CDS assessments over a median follow-up of 33.2 months (range, 8.7-73.1 months). PSP-CDS scores increased significantly over time ({beta}=0.126 points/month), corresponding to estimated increases of 1.13 points over 9 months and 2.27 points over 18 months. Subtype-specific analyses demonstrated the fastest progression in PSP-RS (0.156 points/month), followed by PSP-PGF (0.081 points/month) and PSP-P (0.077 points/month). Exploratory domain-level analyses showed that finger dexterity, communication, and dysphagia were the most rapidly worsening domains. Annualized PSP-CDS progression correlated significantly with annualized decline in BI scores (Spearman's {rho}=-0.474, P<0.001). Conclusions: The PSP-CDS is sensitive to longitudinal disease progression in PSP and captures clinically-meaningful functional decline. Its brevity and ability to distinguish differential progression across PSP phenotypes support its utility as a pragmatic outcome measure for routine clinical practice and research.

Background: The primary neuroanatomical site of Huntington-s disease (HD) pathology resides in the striatum and its atrophy identifies important disease progression from HD-ISS Stage 0 to Stage 1. Immune-associated proteins may capture variation in HD that is incompletely represented by markers of neuroaxonal injury. Objectives: To determine whether cerebrospinal-fluid myeloperoxidase contributes information about striatal volume loss beyond genetic disease burden and neurofilament light. Methods: Cross-sectional data from 88 persons with HD were analyzed. Cerebrospinal-fluid myeloperoxidase and neurofilament light were measured with a nucleic acid-linked immunosandwich assay. Normalized putamen volume was derived from structural magnetic resonance imaging. Linear regression adjusted for genetic disease burden and sex. Results: Higher neurofilament light was associated with smaller normalized putamen volume (standardized {beta} = -0.322, (P=.0066)). Higher myeloperoxidase was associated with larger normalized putamen volume after adjustment for genetic disease burden, sex, and neurofilament light (standardized {beta} = 0.183, (P=.0386)). Adding myeloperoxidase increased explained variance in striatal loss. Conclusions: Cerebrospinal fluid myeloperoxidase contributed modest incremental information about striatal volume in this cross-sectional sample. Independent longitudinal studies are needed to determine its biological source, temporal behavior, and potential biomarker value. Findings advance efforts to characterize multicomponent biological markers of HD.

This systematic review and meta-analysis has several major aims, including evaluation of global and continent wise prevalence of diabetic peripheral neuropathies (DPNs), a detail assessment of DPN associated risk factors and most importantly to explore mechanistic basis of DPN by capturing its different pathophysiological hallmarks Diabetic peripheral neuropathy (DPN) imposes a substantial global burden, yet its mechanistic underpinnings and integrated risk architecture remain incompletely characterized. This systematic review and meta-analysis of 74 studies across 24 countries (83,560 participants) provides the most comprehensive quantitative synthesis of DPN prevalence, hallmark-based pathogenesis, and multi-covariate risk profiling to date. The global pooled DPN prevalence was 57.42% (95% CI: 48.56 to 66.05), with continent-specific gradients: Americas (74.52%), Europe (59.95%), and Asia (45.44%). Hallmark stratified subgroup analyses encompassing neuronal damage, metabolic dysregulation, neuroinflammation, and microvascular alteration identified microvascular alteration as the sole statistically significant mechanistic determinant (Q = 15.78, p = 0.0004), with prevalence escalating monotonically from 53% to 92% across increasing hallmark severity scores, constituting a compelling dose response relationship. Risk factor meta analysis of 27 covariates identified 12 significant determinants, including the novel meta analytic confirmation of peripheral vascular disease (OR: 3.70; highest effect size), male sex (OR: 1.52), and height (OR: 1.26) as independent DPN risk factors. Notably, HbA1c, BMI, and blood pressure were nonsignificant, challenging glycemia-centric paradigms. These findings collectively support a precision medicine framework grounded in hallmark stratified phenotyping and mechanism-targeted pharmacotherapy for DPN.

Patients presenting with a Glasgow Coma Scale (GCS) score of 13-15, conventionally labelled mild traumatic brain injury (mTBI), account for most hospital-presenting TBI; a substantial proportion have not recovered to pre-injury health at six months, fewer than one in ten receives structured follow-up, and at presentation they are largely indistinguishable from those who recover. Prognostic models based on clinical variables discriminate poorly here, and established protein biomarkers add little. Lipidomics reflects membrane turnover and repair rather than injury magnitude, offering a potentially complementary perspective. Blood collected within 24 h of injury from 929 patients with mTBI in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort was processed to serum and analysed by Ultra-high performance liquid chromatography - Quadrupole-Time-of-flight mass spectrometry (UHPLC-QTOF). After quality-control, 278 lipid features were retained and clustered by Gaussian mixture modelling. Associations between lipid features, six protein biomarkers, Corticosteroid Randomisation After Significant Head injury (CRASH) clinical variables and 6-month Glasgow Outcome Scale-Extended (GOSE) outcome were assessed by Spearman correlation and Jonckheere-Terpstra trend tests. Variables were selected by ordinal elastic-net and modelled by proportional odds logistic regression, comparing CRASH-only with CRASH-plus-marker models, built in a development set (n = 411 with complete covariates) and assessed in a test set (n = 367). Lipid clusters rich in lysophosphatidylcholines (LPCs), sphingomyelins/ceramides and ether-linked phosphatidylcholines (PC-O) correlated positively with favourable outcome and inversely with the injury proteins. Summed choline-containing lipid intensity rose across GOSE (p < 0.0001). Elastic-net selected three proteins (GFAP, NfL, S100B) and seven lipid features, three annotated (LPC(18:2), LPC(20:5), PC(O-34:3)). Adding lipids and proteins increased the area under the receiver operating characteristic curve (AUC) at every threshold, reaching nominal significance at GOSE [&ge;] 7 (AUC 0.728, 95% CI 0.671 - 0.785, p = 0.022), not surviving correction for four comparisons. The averaged c-index rose from 0.720 to 0.751 and Nagelkerke R2 from 0.125 to 0.242. The three proteins and three annotated lipids showed opposing trends across GOSE (all p < 0.001). The acute serum lipidome is associated with 6-month functional outcome after mTBI. LPCs and PC-Os moved opposite to the injury proteins and may index membrane repair rather than injury burden, offering pathophysiological insight and possible therapeutic targets. Adding them to clinical variables gave modest gains, greatest at the upper end of the outcome scale, where existing models perform worse. The gain is small and exploratory; replication with targeted assays is needed first.