Annals of Neurology最新文献

Objective: Vanishing white matter is a leukodystrophy with remarkable regional variation in disease severity. The cerebral and cerebellar white matter chronically degenerates, while stress-induced episodes of rapid neurological deterioration coincide with the appearance of acute focal lesions in the deep gray structures and brainstem. With clinical recovery, these acute lesions spontaneously improve or completely resolve on magnetic resonance imaging, suggesting endogenous repair. Repair is not observed in cerebral and cerebellar white matter. Here, we investigated whether differences in cellular pathology might explain the regional variation in repair potential.

Methods: We assessed the pathology of astrocytes, microglia, oligodendrocytes, myelin and axons in postmortem human brain tissue of vanishing white matter patients, who died either during or long after episodes of clinical decline, and of controls. We compared the most severely affected frontal white matter with the least affected pons white matter.

Results: In the frontal white matter, astrocytes, microglia and oligodendrocytes were abnormal with evident failure of their mature functions, whereas in the pons white matter, their morphology was relatively preserved with evidence of better preserved functions, suggesting that differences in neuropathology underlie the divergent regional potential for intrinsic repair.

Interpretation: Loss of glial cell functions in the cerebral white matter relates to irreversible degeneration, whereas preserved glial functions and valid inflammatory response in the pons coincide with spontaneous repair in vanishing white matter. Unraveling the cellular behavior underlying the potential for repair in the pons could pave the way to novel treatment strategies for this still incurable disease. ANN NEUROL 2025.

Objective: We aimed to evaluate the clinical utility of serum neurofilament light chain (sNfL) and cardiac troponin T (cTnT) in amyotrophic lateral sclerosis (ALS) and assess whether their combination improves diagnostic accuracy.

Methods: We retrospectively analyzed 293 ALS patients, 85 neurodegenerative disease controls, and 29 healthy controls. A validation cohort of 501 ALS patients was analyzed to confirm reproducibility of the results. Receiver operating characteristic (ROC) curve analysis was performed for sNfL, cTnT, and their combination, and the area under the curve (AUC) was compared across groups. An ALS-specific cTnT cut-off of 8.35ng/L was determined using the Youden index and applied in subgroup analyses, in which "biomarker-negative" ALS patients were compared to "biomarker-positive" patients regarding disease duration and progression.

Results: sNfL showed excellent performance in discriminating ALS patients from healthy controls (AUC = 0.94), but only moderate performance in discriminating neurodegenerative disease controls (AUC = 0.82). Combining sNfL and cTnT improved diagnostic accuracy for ALS over neurodegenerative controls, with an AUC of 0.90, whereas cTnT alone showed an AUC of 0.77. The validation cohort showed similar AUCs. "Biomarker-negative" ALS patients had a longer disease duration (73.0 vs 18.0 months, p = 0.0003) and a lower progression rate (0.19 vs 0.70 points per months, p < 0.0001) than "biomarker-positive" patients.

Interpretation: Although sNfL alone performs well in distinguishing ALS from healthy controls, repurposing cTnT for ALS provides additional value in discriminating ALS from disease controls. The combination of sNfL and cTnT improves diagnostic accuracy and may help identify prognostically distinct ALS subgroups. ANN NEUROL 2025.

Roberts J.A, Kim C.Y, Hwang S.A, et al. Clinical, Prognostic, and Longitudinal Functional and Neuropsychological Features of West Nile Virus Neuroinvasive Disease in the United States: A Systematic Review and Meta-Analysis. Ann Neurol 2025 Jul; 98(1):93–106. doi:10.1002/ana.27220.

In the above article, the affiliation for James Sejvar was incorrectly listed as the Centers for Disease Control and Prevention. The correct affiliation should be listed as the University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Department of Neurology.

Objective: The objective of this study was to test if blood-brain barrier (BBB) disruption, detected using dynamic susceptibility contrast (DSC) imaging, would predict progression of white matter hyperintensities (WMHs) over the subsequent year in patients with chronic cerebrovascular disease.

Methods: The study included patients with a history of stroke and at least early confluence of WMH. Magnetic resonance imaging (MRI) scans performed at baseline (> 3 months from stroke) and again 1 year later were segmented to calculate the WMH volume expressed as a fraction of the total brain volume. Change in WMH volume between the 2 timepoints and progression of WMH were the outcome measures. BBB disruption was measured using DSC imaging on the baseline MRI. WMH masks were dilated by 3 mm to create a mask of the adjacent normal appearing white matter (penumbra). BBB disruption was averaged within the WMH and the penumbra.

Results: Fifty patients were included; median age was 69 years, and 46% were women. The mean WMH fraction was 1.25% at baseline and 1.36% at 1 year. The mean baseline BBB disruption was 0.20% in the WMH and 0.22% in the penumbra. More severe BBB disruption was associated with greater WMH progression when measured in the WMH (ß = 0.95, confidence interval [CI] = 0.39-1.51, r² = 0.19, p = 0.001) and in the penumbra (ß = 0.81, CI = 0.10-1.53, r² = 0.10, p = 0.027). The best predictor of progression was BBB disruption in the penumbra with an odds ratio (OR) of 2 (OR = 2, CI = 1.01-3.96, p = 0.046) for each 0.1% increase in BBB disruption.

Interpretation: More severe BBB disruption was predictive of greater WMH progression in patients with chronic cerebrovascular disease. ANN NEUROL 2025.

Objective: Wearable technology allows accurate measurement of turning while walking, with cross-sectional studies indicating that difficulty turning presents even in preclinical phases of Parkinson's disease. The aim of our study was to quantify rate of change of turning performance in a cohort of older adults, and test whether turning decline can predict future diagnosis of Parkinson's disease.

Methods: A total of 1,051 participants from the Tübingen Evaluation of Risk Factors for Early Detection of Neurodegeneration (TREND) study were included for a 5-visit analysis over 10 years, with development of clinically evident Parkinson's disease tracked. Participants walked a 20-m hallway for 1 minute at their preferred pace, with a wearable device on the lower back. Longitudinal trajectories of turning performance were modelled using random effects linear mixed models to establish the interval between initial turning changes and Parkinson's disease diagnosis. Cox regression assessed whether initial turning measures could predict time to Parkinson's disease onset, controlling for age and sex.

Results: Of all participants, 23 were diagnosed with Parkinson's disease an average of 5.3 years post-baseline. Slower peak angular velocity at baseline was associated with a higher hazard of Parkinson's disease diagnosis, with deviations from controls emerging approximately 8.8 years before diagnosis. Additional analysis with a machine learning model using baseline characteristics of age, sex and peak angular velocity, identified 60% of prediagnostic Parkinson's disease (sensitivity: 0.600) and 80.5% non-prediagnostic Parkinson's disease (specificity: 0.805), with an area under the curve of 80.5%.

Interpretation: Peak angular velocity during turning shows promise identifying and tracking motor progression in the pre-diagnostic phase of Parkinson's disease. ANN NEUROL 2025.