Annals of Clinical and Translational Neurology最新文献

Objective: Status epilepticus (SE) is associated with significant mortality. Sleep architecture may reflect normal brain function. Impaired sleep architecture is associated with poorer outcomes in numerous conditions. Here we investigate the association of sleep architecture in continuous EEG (cEEG) with survival in SE.

Methods: Retrospective single-centre study of all adult cEEGs in 2015-2019 with electrographic SE. Patients were dichotomized by the presence of sleep architecture (REM or non-REM) in any epoch per an epileptologist blinded to patient outcome. Categorical variables were assessed using Fisher's exact test. Two-sample t-tests and Wilcoxon rank-sum tests compared normally and non-normally distributed variables, respectively. Survival analysis at 6 months used the Mantel-Cox log-rank test. Multivariate analysis using Firth logistic regression assessed for confounders.

Results: Twenty-five adults (68% male) had electrographic SE (median cEEG duration 2 days, hospitalization 13 days). Mean number of intravenous sedatives was 1.44 and anti-seizure medication 2.96. Thirteen adults had sleep architecture, with shorter cEEG delays (median 1 vs. 2 days, p = 0.0104) and younger age (median 56 vs. 72.5 years, p = 0.0386). Sleep architecture was associated with better outcomes at 6-months (p = 0.0073), higher survival rates at 6-months (76.9% vs. 25%, p = 0.017), and longer survival durations at 6-months (160.9 vs. 73.3 days, p = 0.0034). cEEG delay was not associated with survival (p = 0.107).

Significance: In addition to younger age-a known positive SE prognosticator-sleep architecture during cEEG in adults with electrographic SE was associated with increased survival, possibly due to the resilience of younger brains generating sleep architecture in the face of SE, acting as a marker for improved prognosis.

Objective: Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF-restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real-world cohort and the 2024 McDonald criteria; (2) equivalence to OCB in the specific clinical scenario when demonstration of intrathecal immunoglobulin synthesis is essential for MS diagnosis; (3) which KFLC metric has the best diagnostic performance.

Methods: A retrospective study of 740 cases was conducted, categorised into three groups: MS (2024 McDonald criteria), other neuroinflammatory disorders and non-inflammatory groups. CSF and serum KFLC and albumin were assayed with immunoturbidimetry. OCB status was assessed using isoelectric focusing. Eight KFLC metrics were tested: CSF KFLC, KFLC index, three population-based models of the upper limit for the CSF/serum kappa quotient corrected for CSF/serum albumin quotient, and their corresponding intrathecal fractions.

Results: The KFLC index and the KFLC intrathecal fraction performed as well as OCB; no cases were missed when KFLC was mandatory to achieve a MS diagnosis. Intrathecal fraction computation improved the performance of the population-based models.

Interpretation: In the setting of the 2024 McDonald criteria, KFLC metrics correcting for the CSF/serum albumin quotient were equivalent to OCBs. The intrathecal fraction provided no advantage over the KFLC index, which is simpler to compute. Importantly, the KFLC index can replace OCB when CSF positivity is essential for diagnosis. We provide an explanation for KFLC's comparable diagnostic performance despite its inability to identify CSF-only clones.

Objective: Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks. Single-cell combined spatial transcriptomics (ST) offers innovative solutions.

Methods: We analyzed glioma mRNA data from TCGA and single-cell and ST data from GEO. Following quality control, dimensionality reduction, clustering, and cell annotation of single-cell sequencing data, we identified cell types exhibiting significantly aberrant distributions between primary and recurrent samples by analyzing the deviation degree of Ro/e values. Fibroblasts demonstrating the greatest intergroup differences were subsequently selected as the key cellular population for further investigation. Key differentially expressed genes (DEGs) were identified via random survival forest analysis. Drug sensitivity was assessed using GDSC. Deconvolution algorithms mapped cellular spatial distribution, while PROGENy quantified pathway activity. MISTy modeling revealed cell-cell interactions.

Results: Fibroblasts were the primary recurrence-associated subpopulation, with marker genes enriched in extracellular matrix and adhesion pathways. AEBP1, ZNF708, and TSHZ2 were identified as key genes: AEBP1/TSHZ2 correlated with poor prognosis, while ZNF708 showed an inverse trend. These genes were linked to chemosensitivity (Irinotecan, Carmustine, Vincristine, and Cisplatin). Recurrent tumors exhibited increased plasma cell infiltration, with key genes regulating IL-17, Notch, and Toll-like receptor pathways. Spatial analysis highlighted oligodendrocyte-astrocyte interactions in the tumor microenvironment.

Interpretation: Fibroblasts drive glioma recurrence, with AEBP1, ZNF708, and TSHZ2 predicting recurrence and chemoresistance. These genes promote immune suppression (via plasma cells) and activate recurrence pathways. Oligodendrocyte-astrocyte interactions shape the recurrent microenvironment, suggesting new therapeutic targets.

Adaptor protein complex 4-associated hereditary spastic paraplegia (AP-4-HSP), a childhood-onset neurogenetic disorder and frequent mimic of cerebral palsy, is caused by biallelic variants in the adaptor protein complex 4 (AP-4) subunit genes (AP4B1 [for SPG47], AP4M1 [for SPG50], AP4E1 [for SPG51], and AP4S1 [for SPG52]). Diagnosis is often confounded by variants of uncertain significance. We evaluated the ATG9A ratio, a measure of ATG9A mislocalization in patient-derived fibroblasts, as a functional assay of AP-4 deficiency. In six of eight individuals with suspected AP-4-HSP, the assay demonstrated loss of AP-4 function, establishing pathogenicity of novel variants. These findings support the ATG9A ratio as a clinically useful diagnostic tool for confirming AP-4-HSP and aiding the classification of novel variants. Trial Registration: ClinicalTrials.gov identifier: NCT06948019, NCT05518188, NCT06692712, NCT04712812.

Background: Limb girdle muscular dystrophy type R9 (LGMDR9) results from biallelic variants in FKRP. There is limited data to predict loss of ambulation (LOA) among those with LGMDR9.

Methods: Participants in an ongoing dystroglycanopathy natural history study (NCT00313677) with FKRP variants who had achieved ambulation and were more than 3 years old were included (n = 97). LOA was defined as self-reported full-time wheelchair use, weakness preventing completion of the 10-m walk-run test (10MWT) or 10MWT time > 30 s. Interval-censored time-to-event analysis was used to determine median age at LOA. Receiver operating characteristic curves were used to examine the ability of 10MWT and 4-stair climb (4SC) times to predict LOA.

Results: Of 97 participants, 55 (57%) were homozygous for the c.826C>A founder variant. Thirty-one participants lost ambulation; 15 (49%) were homozygous for c.826C>A. Earliest age at LOA was 9 years (non-homozygous for c.826C>A). Median age at LOA for the cohort was 46.0 years. Performances on 10MWT and 4SC were highly predictive of LOA within 3 years, with areas under the ROC curve of 0.89 (10MWT) and 0.87 (4SC) when genotype was included in analysis. Optimal cutoffs for predicting LOA within 3 years differed by genotype and had acceptable sensitivity and specificity.

Discussion: LOA among those with LGMDR9 is strongly predicted by performance on 10MWT and 4SC. These results demonstrate the real-world significance of standardized motor function tests used in LGMDR9 clinical trials and aid in anticipatory guidance.

Objective: To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high-grade gliomas.

Methods: This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high-grade gliomas (52 cases as a train cohort and 20 cases as a test cohort). The regions of interest (ROIs) were annotated accordingly. In MRI processing, the ROI was further divided into clusters to extract habitat radiomics features. For whole slide imaging (WSI), the ROI was cropped into equal-sized image patches for weakly supervised learning and deep learning using various network architectures. The optimal model architecture was selected, and pathological features were extracted. After feature selection, four independent models were constructed: habitat radiomics model, pathomics-based model, clinical model, and combined model integrating all information. Model performance was evaluated using the concordance index (C-index) and the area under the receiver operating characteristic curve (AUC).

Results: The combined model demonstrated the best predictive performance, with a C-index of 0.883 and an AUC of 0.965 in the train cohort. In the test cohort, the C-index was 0.840, and the AUC was 0.927. Based on the combined model, patients with high-grade gliomas were divided into high-risk and low-risk groups, with median progression-free survival (mPFS) of 9 months and 77 months, respectively (p < 0.001).

Conclusion: Compared with the habitat radiomics model or the pathomics-based model alone, the combined model can better predict the risk of progression in high-grade gliomas and provides valuable guidance for personalized treatment of high-grade gliomas.

Objectives: In our previous study, we investigated in de novo PD patients salivary biomarkers targeting different molecular pathways, including alpha-synuclein (a-syn), tau pathology, autophagy (MAPLC3beta), and inflammation (TNFalpha). Here, we aimed to investigate longitudinal changes in these salivary biomarkers with the goal of assessing their dynamic changes over time and their predictive value for clinical progression.

Methods: A clinical and molecular 4-year follow-up (T1) was conducted on 43 PD patients of our previously molecularly characterized cohort of de novo PD patients (T0). Salivary levels of oligomeric and total a-syn, pS199-tau, total-tau, activated MAP-LC3beta, and TNFalpha were quantified using ELISA. Clinical assessments included motor and non-motor symptom scales. The Wilcoxon test was used to verify molecular and clinical variations from T0 to T1; regression analysis to determine whether salivary biomarkers at T0 could predict clinical progression and Spearman's correlations to explore correlations between changes in molecular biomarkers and clinical scores.

Results: Oligomeric a-syn and MAPLC3beta dramatically decrease, while total a-syn, phosphorylated-tau, total-tau, and TNFalpha exhibited significantly higher levels from T0 to T1. Oligomeric and total a-syn, phosphorylated and total-tau at baseline predicted motor progression, while TNFalpha predicted non-motor worsening. Significant correlations were found for MAPLC3beta, phosphorylated tau, and TNFalpha with motor and non-motor scores, while no correlations emerged between a-syn species and clinical scores both at T0 and T1.

Interpretation: Salivary biomarkers dynamically reflect PD progression and predict long-term clinical outcomes. These findings support the use of saliva as a noninvasive, accessible source for predicting and monitoring disease progression in PD.

Objective: Cognitive decline can occur following ischaemic stroke. How cognition changes over time and associations with cognitive change are poorly understood. This study aimed to explore these issues over 2 years following ischaemic stroke.

Methods: This analysis used data from the XILO-FIST study, a clinical trial of allopurinol versus placebo in people with ischaemic stroke according to Tissue-Based Definition. Participants underwent clinical assessment, brain MRI at baseline, and Montreal Cognitive Assessment (MoCA) at baseline, year 1 and year 2. We defined cognitive impairment as a MoCA score < 26 and cognitive change as a difference in MoCA score of 2 points or more at year 1 or year 2 after randomisation. Associations with cognitive impairment and cognitive change were assessed by univariable analysis and multiple logistic regression.

Results: Three hundred and sixty participants with complete MoCA data were included. Mean age was 65.4 (SD 8.36) years, and mean baseline MoCA score was 26.4 (SD 2.7). Seventy-seven participants had second-year cognitive improvement. Eighty-four had second-year cognitive decline. After adjustment for age and education year, second-year cognitive improvement was associated with smaller brain volume, lower albumin level, smoking and greater white-matter hyperintensity, and second-year cognitive decline was associated with peripheral arterial disease, higher cholesterol level, small-vessel stroke and greater white-matter hyperintensity.

Interpretation: Cognition is dynamic following stroke, with different patterns of change. Brain reserve and vascular risk factors relate to later post-stroke cognitive change. This complex nature of cognitive trajectory has implications for cognitive rehabilitation provision and cognitive impairment detection after stroke.

The practice of neurology requires an understanding of clinical ethics for decision-making. In multiple sclerosis (MS) care, there are a wide range of ethical considerations that may arise. These involve shared decision-making around selection of a disease-modifying therapy (DMT), risks and benefits of well-studied medications in comparison to supplements with limited information, allocation of resources and accessibility to MS care, and disparities in healthcare. We share a series of cases that illustrate ethical issues that may arise in the care of patients with MS. This narrative review articulates relevant ethical theories and frameworks that can be applied to common clinical scenarios in the current practice of MS.

Objective: To characterize whole-body intramuscular fat distribution pattern in patients with sarcoglycanopathies and explore correlations with disease severity, duration and age at onset.

Methods: Retrospective, cross-sectional, multicentric study enrolling patients with variants in one of the four sarcoglycan genes who underwent whole-body muscle MRI. Intramuscular fatty replacement was evaluated on T1-weighted images and represented by heatmaps. Dimensionality reduction and linear spline models examined relationships between patterns of intramuscular fat replacement and clinical findings.

Results: MRI scans from 64 patients (age range 4-67 years) covering 4160 muscles were analyzed. Disease severity ranged from asymptomatic (9%) to non-ambulant (39%) patients. Sarcoglycanopathies showed consistent, selective patterns of muscle involvement across genotypes. Latissimus dorsi and subscapularis were the earliest affected muscles in the upper body, whereas head, neck and forearm muscles remained largely preserved. Distinct gradients characterized the topography of degeneration both within individual muscles and along body and limb axes. Disease severity correlated with MRI changes in both upper and lower body muscles, and with one of the dimensions identified by the multi-correspondence analysis. Patients with onset in the first decade showed a steeper cross-sectional association between disease duration and MRI abnormalities, while later-onset patients displayed a more gradual, linear relationship.

Interpretation: Sarcoglycanopathies display selective muscle vulnerability with characteristic gradients of fat replacement. Scapular girdle muscles are affected early in the disease course. Intramuscular fat correlates with functional impairment and disease duration, supporting its use as a surrogate endpoint in clinical trials. Age at onset emerges as a critical prognostic factor.