Journal of Neurology最新文献

Background: Autoimmune encephalitis is a rapidly progressing neurological disorder caused by aberrant immune responses against neural antigens. It presents with severe neuropsychiatric symptoms such as seizures and cognitive decline, highlighting the need to clarify its neural mechanisms.

Objectives: To investigate functional and structural brain network alterations across autoimmune encephalitis clinical phases and explore their potential as diagnostic and prognostic biomarkers.

Methods: Resting-state functional MRI and diffusion tensor imaging were used to analyze brain network topology in 52 patients, including 30 patients who underwent longitudinal follow-up and 32 age- and sex-matched healthy controls. Functional and structural brain networks were constructed using graph-theoretical approaches, and global and local network measures were compared across groups. Machine learning models classified disease status and disease phase.

Results: Patients with autoimmune encephalitis showed significant disruptions in global and local network efficiencies, particularly in the medial occipital and inferior temporal lobes, more pronounced during the acute phase. Classification models achieved high accuracy distinguishing patients from controls (AUC = 0.97 functional, 0.85 structural) and acute from convalescent phases (AUC = 0.98, 0.83).

Conclusions: Autoimmune encephalitis involves stage-dependent network impairments reflecting disrupted connectivity. Network efficiency may serve as a biomarker for diagnosis and prognosis, supporting multimodal imaging to guide personalized therapeutic strategies.

Background: Patients suffering from persistent postural-perceptual dizziness (PPPD) often experience postural instability that worsens when exposed to visual motion stimuli. We investigated how different visual motion stimuli affect patients' postural sway and their perceived egomotion during stance.

Methods: 28 PPPD patients and 26 gender and healthy control subjects (HC) underwent posturographic measurements on a firm or foam platform while being exposed to either vestibular or visual motion stimuli or their combination. Vestibular stimuli were applied via 1.3 mA galvanic vestibular stimulation (GVS) or a sham stimulus. Visual stimulation (VS) was performed via 20-s video snippets of a silent movie, flow-field animation, or a rollercoaster video from the driver's perspective. Outcome measures included postural sway speed (PSS) and perceived egomotion, collected via self-ratings after each trial.

Results: Compared to HC, PSS of PPPD patients was higher on a firm surface during vestibular stimulation alone and combined visual-vestibular stimulation (except during rollercoaster VS) but not during VS alone. These group differences disappeared on foam, except during the baseline (noVS, noGVS) condition. Egomotion perception was rated consistently higher by PPPD participants in all conditions but in a non-linear ratio.

Conclusion: Our visual motion stimuli were capable of eliciting different magnitudes of perceived egomotion and postural sway without significant group differences in postural sway challenging the notion of increased visual sensitivity in PPPD. Multisensory stimulation alleviates visual sensitivity and counteracts postural misperception in quiet stance. Patients' non-linear increase of egomotion with increasing postural sway differs from HC and reflects a non-linear perceptual-postural scaling as a crucial mechanism in PPPD.

Background and aim: Parkinsonian disorders are hallmarked by gait and balance impairments. Atypical parkinsonian disorders (APD) develop postural instability with falls and gait disorders early on. Sensor-based gait recordings provide objective data in hospital and everyday life, improving mobility assessment accuracy. However, the impact of duration and distance of instrumented assessments on construct validity remains unclear. This exploratory study aims to evaluate the construct validity of gait assessments compared with clinical, functional, and patient-reported scores.

Methods: The multi-centered Mobility_APP study recruited 43 PD and 49 APD patients. Among others, the Berg Balance Scale (BBS) and the postural instability and gait difficulty score (PIGD) were collected. Sensor-based gait parameters were captured during standardized 2 × 10 m and 2-min walk tests (2MWT) in the hospital and for 1 day of physical activity monitoring (PAM) at home. PAM was categorized by short (10-30 s), medium (30-60 s), and long (≥ 60 s) walking bouts (WB). Spearman correlations were applied to investigate associations between scores.

Results: Mean gait velocity (GV) and stride length correlated more strongly with functional, clinical, and patient-reported scores in 2MWT than in 2 × 10 m. Additionally, the GV variability in the 2MWT correlated with BBS and PIGD (r = │0.3-0.7│), but was less prominent in 2 × 10 m (r = │0.0-0.5│). In PAM, GV of long WB correlated more strongly with the PIGD (r = │0.5-0.6│) than short WB (r = │0.2-0.4│).

Conclusion: The 2MWT tended to show the highest construct validity. PAM offered complementary but weaker correlations, highlighting that PAM provides novel insights into daily life mobility of APD patients.

Introduction: Structural MRI analysis for Alzheimer's disease (AD) is limited by balancing group-level comparability in standard space with anatomical fidelity in native space. We therefore propose a multi-space, hybrid-feature framework, integrating radiomics and network metrics from both spaces to classify AD and predict mild cognitive impairment (MCI) progression.

Methods: An integrated dual-space analytical framework was applied to T1-weighted MRI data. Models were developed on 1,477 participants from Alzheimer's Disease Neuroimaging Initiative (ADNI) and externally tested on an independent cohort of 1,349 participants from National Alzheimer's Coordinating Center (NACC). The framework extracts parallel radiomic and graph-based network features from both Montreal Neurological Institute (MNI) standard space and native space. These features were used to build machine learning models for three-class diagnosis (NC vs. MCI vs. AD) and 6-year prognostic prediction of MCI-to-AD conversion. For each task, the models using standard-space, native-space, and combined-space features were systematically compared. Model interpretation was performed using Shapley Additive Explanations (SHAP), and the features were validated against established AD biomarkers.

Results: The combined-space model demonstrated superior performance in both diagnostic classification (Macro-Averaged AUC: 0.96 in ADNI cohort, 0.94 in NACC cohort) and prognostic prediction of MCI-to-AD conversion (C-index: 0.83; HRs: 7.60, 95%CIs: 4.57-12.64). The extracted features in the ADNI cohort demonstrated significant correlations with APOE ε4 genotype, cognitive scores, and CSF biomarkers.

Conclusion: Integrating multi-scale features from both standard and native spaces enhances AD diagnosis and prognosis accuracy more effectively than conventional single-space analysis.

Relationship status influences mental and physical health in the general population and may mitigate radiological abnormalities in multiple sclerosis (MS). However, there are limited data about whether one's relationship status impacts the neurobehavioral symptoms of MS, such as depression, anxiety, fatigue, or self-reported cognitive concerns. This study's objective was to explore the influence of relationship status on the neurobehavioral sequelae of MS. At a Canadian neuropsychiatry clinic, 1393 people with MS (pwMS) consecutively completed psychometric testing with the Hospital Anxiety and Depression Scale sub-scales for anxiety (HADS-A) and depression (HADS-D), the Modified Fatigue Impact Scale (MFIS), and the Perceived Deficits Questionnaire (PDQ) for self-reported cognitive concerns. Participants were categorized by the presence or absence of an intimate relationship. Analyses of covariance (ANCOVA) were undertaken to examine whether relationship status influenced HADS-A, HADS-D, MFIS, or PDQ scores, adjusting for age, sex, education, Expanded Disability Status Scale scores, disease subtype, illness duration, and disease-modifying therapy use. Mean age was 43.37 years, 73.33% were female, median EDSS was 2.00, and 55.86% were married. Controlling for covariates, the presence of a relationship was associated with decreased HADS-D scores (p = .006). Relationship status did not independently influence HADS-A, MFIS, or PDQ scores. Overall, being in a relationship is linked to decreased depressive symptoms in pwMS.

Introduction: Serum neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) may synergistically enhance early risk stratification of multiple sclerosis (MS) diagnosis after clinically isolated syndromes (CIS). We investigated the prognostic value of combined NfL and GFAP for McDonald 2024 MS diagnosis after CIS and associations with key genetic and environmental risk factors.

Methods: CIS participants, within six months after symptom onset, were included in a prospective cohort. We measured baseline serum NfL and GFAP levels and calculated z-scores. We evaluated weighted genetic risk scores for MS susceptibility, HLA-DRB1*15:01 risk and measured Anti-Epstein Barr virus Nuclear Antigen-1 (anti-EBNA1) immunoglobulin G (IgG) antibodies. Associations with MS diagnosis were evaluated using Cox proportional hazards models and time-dependent receiver operating characteristic (ROC) analyses.

Results: During follow-up, 162/221 CIS participants were diagnosed with McDonald 2024 MS. Separately, high NfL and GFAP associated with earlier MS diagnoses (hazard ratio (HR) 1.36, 95% confidence interval (CI) 1.12-1.66, p = 0.002, HR 1.12, 95% CI 1.02-1.42, p = 0.01, respectively). In combined models, only NfL remained independently predictive (HR 1.30, 95% CI 1.02-1.60, p = 0.01). Time-dependent ROC analyses showed similar results for NfL alone and combined with GFAP. HLA-DRB1*15:01-risk, but not GFAP or anti-EBNA1 IgG, improved predictive value.

Conclusion: Our study found that serum NfL outperformed GFAP in predicting early MS diagnoses after CIS. Baseline NfL, together with HLA-DRB1*15:01 status, provides robust early risk stratification for MS after CIS, whereas GFAP and anti-EBNA1 titres add limited prognostic value. Additional immunological and imaging markers are essential to further refine predictive models.

Objective: This study aims to systematically evaluate the relationships and effects of different exercise modalities and exercise doses on the quality of life in patients with Parkinson's disease (PD).

Methods: Randomized controlled trials published from database inception to November 2025 were identified by searching PubMed, Web of Science, Embase, and the Cochrane Library. The Cochrane Risk of Bias 2.0 (RoB 2.0) tool was used to assess the methodological quality of the included studies. Stata version 17.0 and R version 4.4.3 were used to analyze and compare the relationships and effects of different exercise modalities and exercise doses on quality of life in patients with PD.

Results: A total of 44 randomized controlled trials (RCTs), including 2,273 patients with PD, were analyzed. The network meta-analysis showed that aerobic exercise (AE) (SMD =  - 0.66; 95% CI: - 0.93 to - 0.39; P < 0.01), aerobic and resistance training (ART) (SMD =  - 0.71; 95% CI: - 1.09 to - 0.33; P < 0.01), mind-body exercise (MBE) (SMD =  - 0.73; 95% CI: - 1.04 to - 0.43; P < 0.01), and resistance training (RT) (SMD =  - 0.66; 95% CI: - 1.02 to - 0.29; P < 0.01) all significantly improved quality of life, whereas balance and resistance training (BRT) and stretching training (ST) showed no statistically significant effects. Cumulative ranking probabilities indicated that MBE had the highest probability of being the most effective intervention (80.6%), followed by ART (76.7%), AE (70.5%), and RT (69.7%), while ST (30.7%) and BRT (18.3%) ranked lower. Dose-response analysis revealed a nonlinear U-shaped relationship between total exercise dose and improvement in quality of life, with an optimal dose of 950 MET-min/week. The optimal doses varied across exercise modalities, ranging from 550 MET-min/week for MBE to 920 MET-min/week for AE.

Conclusions: Exercise interventions can significantly improve quality of life in patients with PD, with MBE demonstrating the greatest benefit. The U-shaped association between exercise dose and quality of life suggests that a moderate amount of exercise is most conducive to improving quality of life. This study provides evidence supporting non-pharmacological treatment strategies for PD and may inform the formulation of individualized exercise prescriptions.

Background: The optimal timing of surgery for aneurysmal subarachnoid hemorrhage (aSAH) remains controversial. This study aims to identify the optimal surgical window within 72 h of symptom onset.

Methods: Patients with aSAH who underwent surgical treatment within 72 h of onset were identified from the Chinese Multicenter Cerebral Aneurysm Database (2017-2020). Multivariable Cox and logistic regression models with restricted cubic splines (RCS) were used to assess associations between onset-to-treatment time and all-cause mortality and 2-year dependent survival, respectively.

Results: A total of 3560 patients with aSAH were included. During a mean follow-up of 30.9 ± 22.5 months, 521 deaths were recorded, yielding a 2-year mortality rate of 12.9%. The RCS analysis revealed a significant U-shaped relationship between onset-to-treatment time and all-cause mortality (χ² = 5.88, df = 1, P = 0.015), as well as a significant overall association (χ² = 6.73, df = 2, P = 0.035). The lowest risk of all-cause mortality was observed at 32.6 h after onset. A monotonically decreasing association was observed between onset-to-treatment time and 2-year dependent survival (χ² = 3.70, df = 1, P = 0.055). Specifically, the risk of 2-year dependent survival declined rapidly with treatment delay during the first 12 h after onset and plateaued at approximately 32.6 h.

Conclusion: The time from onset to treatment demonstrated a nonlinear (U-shaped) association with all-cause mortality and a linear association with 2-year dependent survival, with the lowest estimated mortality risk observed at approximately 32.6 h after onset.

Early detection and monitoring of neurodegenerative processes in persons with multiple sclerosis (PwMS) is currently a major challenge. Optical coherence tomography angiography (OCTA) is an emerging method to visualize retinal vascular architecture. However, its use has mainly been investigated in relapsing MS. We evaluated OCTA as a possible complementary method in progressive MS (PMS) in a monocentric, retrospective, cross-sectional study. Eyes with evidence of optic neuritis were excluded from analysis. OCTA images acquired using a Spectralis OCT (Heidelberg Engineering) were analyzed with an established deep learning-based segmentation algorithm. After rigorous quality control, 85 eyes of 62 PwPMS were compared with 64 eyes of 43 age and gender-matched healthy controls (HC). The vessel density in the superficial vascular complex (VD_SVC (%)) was reduced in PMS compared to HC (p = 0.018). VD_SVC correlated negatively with age in PwPMS and HC. Using a Johnson-Neyman analysis, we identified that the disease duration influences the VD_SVC in PMS individuals < 57.5 years of age. PwPMS with disease duration > 10 years had reduced VD_SVC compared to subjects with ≤ 5 years of disease duration (p = 0.049) (corrected for age). Clinical disability (EDSS) negatively correlated with VD_SVC in PwPMS (β = -0.487, p = 0.010). These results suggest that OCTA might be suitable to detect retinal vascular changes in PwPMS. One consequence could be structured and harmonized OCTA investigations as part of routine clinical practice. External validation and longitudinal studies are necessary to further elaborate OCTA´s potential in monitoring PwPMS.

Objective: Our study aimed to determine the prevalence and clinical phenotypes of JAK2 pathogenic mutation carriers in the CNSR-III ischemic stroke (IS) cohort, and to develop a pre-test genetic screening model for identifying high-risk individuals.

Methods: We performed retrospective characterization of JAK2 pathogenic variants using targeted sequencing data in the CNSR-III cohort. Clinical and laboratory characteristics of JAK2 V617F mutation carriers and non-carriers were tested in a logistic regression model to identify key features. V617F screening score was developed to predict positive JAK2 V617F test results.

Results: 46 cases (0.4%, 46/10428) harbored the JAK2 V617F-exclusive mutation. Mutation carriers manifested significantly inferior functional outcomes following stroke relative to non-carriers (adjusted OR 2.74[1.07, 6.49]). Significant predictors of mutation status comprised elevated platelet count (PLT, OR 1.02[1.02, 1.03]), increased hemoglobin concentrations (HGB, OR 1.06 [1.04, 1.08]), and a reduced burden of traditional stroke risk factors, such as history of hypertension (OR 0.24[0.11, 0.52]), smoking history (OR 0.08[0.02, 0.24]), and body mass index (BMI, OR 0.8[0.75, 0.97]). We constructed the JAK2 V617F screening score, which efficiently discriminated between carriers and non-carriers (area under the ROC curve, AUC 0.98), achieving sensitivity of 85%, specificity of 94%, and accuracy of 94% for a cut-off score of 3 points. Internal validation confirmed robust performance, with a consistent AUC of 0.98.

Conclusions: Despite low prevalence (0.4%), JAK2 V617F mutation represents a clinically actionable stroke subtype with distinct pathophysiology. The prediction model offers a precision medicine approach, potentially reducing the need for comprehensive genetic testing.