Journal of Neurology最新文献

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic (DA) neurons in the substantia nigra. Although familial and sporadic forms of PD have distinct etiological origins, they converge on overlapping molecular pathways that remain incompletely understood. In this study, we aimed to identify shared "hub genes" that may drive DA neuron degeneration across both PD subtypes. We reanalyzed gene expression profiles from three publicly available datasets comprising DA neuron samples derived from postmortem human midbrains and patient-induced pluripotent stem cell-derived DA neurons. Twelve hub genes were consistently dysregulated across all datasets. Functional annotation revealed that these genes are critically involved in membrane trafficking and vesicle-mediated transport-key processes for maintaining neuronal integrity and synaptic function. Network-based analysis further linked these hub genes to a range of other neurological and systemic disorders, indicating broader relevance to disease biology. Experimental validation in neurotoxin-exposed SH-SY5Y cell models of PD confirmed significant dysregulation of several candidate genes at both mRNA and protein levels. Moreover, RNAi-mediated silencing of a key hub gene in Caenorhabditis elegans led to enhanced DA neuron degeneration, reinforcing its functional role in neuronal survival. Together, these findings identify a set of conserved molecular drivers of DA neuron vulnerability and propose novel therapeutic targets for both familial and sporadic PD.

Progression of multiple sclerosis (MS) remains incompletely understood. MS is characterized by demyelination, resulting in a wide variety of symptoms. Conventional magnetic resonance imaging (MRI) is the current standard for diagnosing and monitoring patients. However, conventional MRI has its limitations in visualizing the myelin dynamics. In contrast, advanced myelin-specific MRI techniques enable non-invasive, in vivo quantification of myelin content. Such approaches hold promises for the early detection of pathology and for improving the understanding of disease mechanisms and their relationship to clinical outcomes, particularly since many patients with MS experience progression of symptoms that cannot be fully explained by conventional imaging measures. This narrative literature review aims to summarize recent advances in longitudinal myelin-specific MRI studies in MS and their clinical applications. Overall, longitudinal studies demonstrated that myelin-specific MRI techniques can capture dynamic changes in myelin, possibly aiding in understanding the progression of MS, although inconsistencies persist both between and within techniques. Even though more myelin-sensitive than myelin-specific methods, such as diffusion MRI or multi-contrast methods, are not specific to demyelination, they could aid clinical follow-up by predicting lesion formation, as changes are visualized before being present on conventional MRI. These findings underscore the need for future research that integrates MRI-derived metrics with detailed assessment of disease courses.

Background: This study aims to investigate the association between leukocyte telomere length (LTL) and the risk of incident NDDs using a large-scale cohort from the UK Biobank.

Methods: Data from 459,902 subjects were analyzed using Cox proportional hazards models and machine learning (ML) algorithms to assess LTL's association with NDD risk.

Results: Shorter LTL was associated with an increased risk of NDDs, including Alzheimer's disease (HR: 0.52, 95% CI 0.40-0.67, P < 0.001), dementia in AD (HR: 0.53, 95% CI 0.39-0.73, P < 0.001), unspecified dementia (HR: 0.74, 95% CI 0.58-0.95, P < 0.05), degenerative diseases of the nervous system (including other specified degenerative diseases such as circumscribed brain atrophy and senile degeneration of the brain) (HR: 0.62, 95% CI 0.45-0.84, P < 0.01), extrapyramidal and movement disorders (including other specified extrapyramidal and movement disorders such as a range of tremors, chorea, tics, and other abnormal involuntary movements) (HR: 0.63, 95% CI 0.48-0.82, P < 0.01), and mental and behavioral disorders due to use of alcohol (HR: 0.46, 95% CI 0.38-0.55, P < 0.001). Conversely, longer LTL was associated with a 3.71-fold increased risk of multiple sclerosis (MS) (HR: 3.71, 95% CI 1.91-7.18, P < 0.001). ML models confirmed the predictive value of LTL for NDDs.

Conclusion: Shorter LTL increased the risk of several NDDs, while longer LTL paradoxically predisposed individuals to MS, especially in younger populations. ML models demonstrated strong potential for predicting NDD risks, enhancing our understanding of the role of telomeres in neurodegeneration.

Objective: To characterize patients with autoantibodies against metabotropic glutamate receptor 8 (mGluR8) and assess the pathogenicity of these antibodies.

Methods: Anti-mGluR8 antibodies were detected via cell-based assay and immunoprecipitation. Clinical data from five anti-mGluR8-positive patients and previously reported cases with other anti-mGluR antibodies were reviewed. Patient-derived IgG was purified and absorbed using mGluR8-expressing or control HEK293T cells. Pathogenicity was tested in hippocampal neuron cultures and via passive transfer into mice, with ataxia evaluated using behavioral tests.

Results: Five patients (4 male, median age 61) presented with subacute ataxia; other symptoms included dysarthria, ophthalmoplegia, dysphagia, and cognitive changes. Brain MRI showed cerebellar and cortical atrophy in all cases. Immunotherapy led to transient improvement in all patients, with stabilization in three of four with follow-up. In vitro, non-mGluR8-absorbed IgG reduced synaptic mGluR8 clusters. Mice injected with non-mGluR8-absorbed IgG developed transient ataxia peaking at 3-6 h and resolving within 24 h, correlating with antibody binding to Purkinje cells.

Conclusion: Anti-mGluR8 antibody is a novel possible biomarker for autoimmune ataxia, with its pathogenicity supported by passive transfer models.

Purpose: Head-Impulse, Nystagmus, Test-of-Skew (HINTS) testing is recommended to identify stroke in the acute vestibular syndrome (AVS). Diagnostic accuracy depends on the vascular territory involved, with lower sensitivity for anterior-inferior cerebellar artery (AICA)- than posterior-inferior cerebellar artery (PICA)-territory strokes. Adding new-onset, acute unilateral hearing loss (AUHL) as a fourth central sign has been proposed ("HINTS+") to improve sensitivity for AICA-stroke detection.

Methods: We performed a systematic search (MEDLINE, Embase) to identify studies reporting diagnostic accuracy of bedside examination in AVS patients, including the diagnostic impact of HINTS+. Results were stratified by stroke location.

Results: We identified 4388 citations and included 11 articles (n = 770 patients). Ischemic strokes (n = 319) and acute unilateral vestibulopathy (n = 391) were the most frequent causes. AUHL was most often assessed by finger rub (n = 311), tuning-fork tests (n = 114), or whispered words (n = 169), and was present in 50 patients (central = 29, peripheral = 21). Bedside head-impulse testing was abnormal in 25/29 central cases with AUHL, with 19/25 cases demonstrating an AICA-stroke. Diagnostic accuracy of HINTS (sensitivity = 92.7% [88.7-96.8%]; specificity = 91.1% [86.3-95.8%]) was high. Adding AUHL (HINTS+) increased sensitivity (95.7% [92.7-98.7%]) but decreased specificity (80.7% [70.6-90.7%]), though the latter was largely from bias in patient selection. AUHL had the biggest impact for AICA-territory strokes, increasing sensitivity from 73.3% (59.0-84.0%) to 91.1% (79.3-96.5%).

Conclusions: Testing for AUHL in AVS increased stroke-sensitivity, but this effect was mainly related to AICA-strokes with abnormal head-impulse testing (n = 19/22), where adding AUHL yielded an absolute increase of 17.8% in stroke-sensitivity. In AVS, AUHL should be assessed at the bedside (and ideally confirmed by audiometry).

Background: The blood biomarker p-tau217 has demonstrated high accuracy in predicting underlying Alzheimer's disease (AD) pathology. However, its feasibility and impact on clinician confidence and diagnosis in real-world clinical settings remain underexplored. We aimed to evaluate the effect of implementing blood p-tau217 testing on both diagnosis and diagnostic confidence in patients with cognitive symptoms across two different clinical settings: general neurology consultations referred from primary care and a specialized memory unit.

Methods: We included 200 consecutive new patients (38.5% with subjective cognitive complaints, 47.5% mild cognitive impairment, and 14% with dementia) evaluated for cognitive symptoms in two distinct clinical settings: general neurology and a memory unit. Attending neurologists were asked to record a pre-biomarker clinical diagnosis and their diagnostic confidence on a scale from 0 to 10. They repeated this assessment after receiving the p-tau217 results.

Results: Across the whole sample, 51/200 patients (25.5%) had a change in their diagnostic category after receiving p-tau217 levels. Furthermore, diagnostic confidence significantly improved from 6.90 ± 1.74 at the first visit to 8.49 ± 1.68 after the test. Changes in diagnosis and confidence were observed in both general neurology and memory unit settings, and across all clinical stages (subjective cognitive complaints, mild cognitive impairment, and dementia). Compared with the final diagnosis, the pre-biomarker diagnosis was maintained in 71/200 cases (75.5%) (Kappa = 0.576), while the post-biomarker diagnosis was maintained in 189/200 cases (94.5%) (Kappa = 0.906).

Conclusions: Implementing p-tau217 in real-world clinical practice has a strong clinical impact, substantially improving diagnostic accuracy and confidence in both general neurology and memory units across all stages of cognitive decline.

Background: Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB) are two synucleinopathies that share considerable overlap in their clinical and pathological characteristics.

Objective: This study aimed to evaluate the profile of phenotypic features across PDD and DLB to highlight their shared and distinctive features to explore any possible neurobiological underpinnings.

Methods: Patients diagnosed with Parkinson's disease dementia (PDD) (n=31) and dementia with Lewy bodies (DLB) (n=30) underwent evaluation for motor and non-motor symptoms using the International Parkinson and Movement Disorder Society -Unified Parkinson's Disease Rating Scale, the Scales for Outcomes in Parkinson's Disease-Psychiatric Complications, the Montreal Cognitive Assessment, the Hospital Anxiety and Depression Scale and the Epworth Sleepiness Scale.

Results: Patients with PDD showed a more severe phenotype than those with DLB, with higher scores in motor severity, hallucinations, delusions, somnolence, and urinary dysfunction (all p≤0.01). The correlations between neuropsychiatric symptoms differed between groups. In both PDD and DLB, depression correlated with anxiety (PDD ρ=0.54; DLB ρ=0.65; both p<0.001). In PDD, depression was additionally correlated with delusions (ρ=0.47; p<0.001), apathy (ρ=0.41; p<0.001), and sexual preoccupation (ρ=0.35; p<0.001), whereas in DLB depression correlated with hallucinations (ρ=0.38; p<0.001). PDD patients showed greater impairment in activities of daily living (ADLs) than DLB patients (p<0.001), correlating with motor severity (ρ=0.65; p<0.001) and fatigue (ρ=0.58; p<0.001). In DLB, impaired ADLs were linked to hallucinations (ρ=0.39; p<0.05), poorer cognition (ρ=0.47; p<0.01), urinary dysfunction (ρ=0.38; p<0.001), and fatigue (ρ=0.45; p<0.001).

Conclusion: Despite being grouped under Lewy body dementias, these findings show PDD and DLB have distinct phenotypes reflecting their neurobiological underpinnings. This has implications for symptomatic and disease-modifying management. Future research should explore pathological mechanisms of these characteristics to improve diagnosis and treatment strategies.

Oculomotor abnormalities are a common finding in neurodegenerative diseases due to degeneration of neural pathways and brain regions involved in controlling eye movements. Pathological changes to the dorsolateral prefrontal cortex, basal ganglia, superior colliculus and cerebellum produce subtle changes in eye-movement metrics that may not be detected by clinical examination. The present review addresses the potential use of eye-movement biomarkers in neurodegenerative conditions such as multiple sclerosis, Parkinson's disease, Alzheimer's disease and other dementias, and amyotrophic lateral sclerosis. Eye-movement metrics such as saccades, anti-saccades, fixation and smooth pursuit are prognostic of disease progression, can differentiate pathologic subtypes as an aid to diagnosis, and enable clinicians to evaluate early worsening of motor and cognitive function. The cost of medical technologies limits their optimal use and accessibility in clinical practice. The shortage of subspecialist neurologists further limits access to care. New eye-tracking technologies incorporated into widely-accessible digital devices such as smart phones and tablets now permit detailed assessments with minimal equipment requirements, providing an important non-invasive and potentially cost-effective method for patient evaluation in routine clinical practice and as an aid to treatment decision-making. Digital biomarkers can be readily employed by healthcare professionals such as family physicians, nurses and pharmacists to bridge the care gaps, potentially providing them with powerful tools that can be broadly adopted to improve the delivery of care to patients with neurodegenerative conditions.

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 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.