Brain communications最新文献

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive motor neuron degeneration, with significant clinical and genetic variability. While the role of genetic factors is well-established in ALS pathogenesis, their impact on survival outcomes remains poorly understood, particularly in the Indian population. We performed whole-exome sequencing in 159 ALS patients from North India (familial = 2, sporadic = 157). Clinical parameters, including age at onset, site of onset, sex, family history and survival, were recorded. Males exhibited shorter survival than females, but did not achieve statistical significance (median: 48 versus 60 years, P = 0.05). Bulbar-onset patients developed ALS at a significantly older age (mean: 59.7 versus 54 years, P = 0.007) and experienced poorer survival outcomes than spinal-onset patients (median: 48 versus 60 months, P = 0.03). A small subset of ALS patients (6.3%, n = 10) had very long survival duration of more than 10 years. We identified 102 genetic variants in 92 ALS patients, of which 45 variants were novel. According to American College of Medical Genetics and Genomics guidelines, 13.5% of total variants were pathogenic, 19.8% were likely pathogenic, and 66.7% were variants of uncertain significance. The presence of genetic variations was significantly associated with delayed onset (mean: 53.4 versus 57.1 years, P = 0.049) and diminished life expectancy (median: 48 versus 60 months, P = 0.029). Variations in more than one gene were detected in 16.7% of the patients, supporting the theory of oligogenic basis for ALS. After adjusting for age at onset, increased risk of mortality was associated with males [hazard ratio = 1.740, 95% confidence interval (CI) = 1.105-2.740] and rare genetic variations (hazard ratio = 1.533, 95% CI = 1.001-2.350). Furthermore, bulbar onset (hazard ratio = 1.75, 95% CI = 1.11-2.75) was found to be a negative prognostic factor for survival. Our study provides valuable insights into the genetic complexity and its impact on clinical outcomes in ALS patients of North Indian origin.

Our Guest Editor, Jon Stone, introduces a special collection of articles focusing on functional neurological disorder.

Diffusion Tensor Image Analysis ALong the Perivascular Space (DTI-ALPS) was originally proposed to quantify glymphatic functioning. Although a direct interpretation is now questioned, cross-sectional studies show associations with disability in people with multiple sclerosis (pwMS). Regardless, serial DTI-ALPS studies are largely lacking in MS. In a longitudinal study, we investigated DTI-ALPS with respect to confirmed disability progression (CDP) and progression independent of relapse activity (PIRA) in people with relapsing-remitting MS (pwRRMS) and progressive MS (pwPMS). This study included 72 pwRRMS, 27 pwPMS, and 23 healthy controls (HC) imaged with 3T MRI and again after 5 years. The DTI-ALPS index was calculated using an automated pipeline using template-defined regions of interest (ROIs) in the superior longitudinal fasciculus and superior corona radiata. Areas corresponding to T2 hyperintensities were removed to avoid the influence of overt pathology. CDP and PIRA were assessed after 5 years and in 64 pwRRMS/17 pwPMS after 10 years. Comparisons between those with and without follow-up CDP or PIRA were assessed using analysis of covariance and repeated including normal appearing white matter (NAWM) mean diffusivity (MD) as an additional covariate. Multivariable binary logistic regression was used to explore whether DTI-ALPS offers independent value beyond general disease burden. Although significantly lower in pwMS compared with HCs (1.347 ± 0.178 versus 1.437 ± 0.132, P = 0.034, partial η ² = 0.021), the difference was no longer so after controlling for NAWM MD (P = 0.094, partial η ² = 0.024). DTI-ALPS decreases over 5 years were similar between HC and pwMS (P = 0.188, partial η ² = 0.021). In pwRRMS, baseline DTI-ALPS was lower in those who developed CDP or PIRA at 5- and 10 years of follow-up (all P ≤ 0.019, partial η ² > 0.080, except for PIRA at 5 years, P = 0.051, partial η ² = 0.055). When controlling for NAWM MD, results were in line with original findings. Baseline T2-LV was the only retained imaging predictor of CDP and PIRA over 5 years while only baseline DTI-ALPS was selected for in 10 year models. No associations were found in the pwPMS group. Changes in DTI-ALPS over 5 years did not relate to CDP nor PIRA in neither group. In conclusion, although DTI-ALPS values were not significantly different compared with HCs after considering NAWM MD, decreased baseline DTI-ALPS is associated with disability progression in pwRRMS. The lack of associations in pwPMS suggests that DTI-ALPS may be less informative with more advanced disease.

Emerging evidence suggests that hallucinations may arise because of an over-reliance on prior knowledge during perception. While best established in psychosis-spectrum illness, data also support the presence of this abnormality in other hallucination-prone neuropsychiatric illnesses that vary in their association with disruption of sensory circuits. In this piece, we ask whether an over-weighting of expectations may be conceived of as a compensatory response to degraded incoming sensory information. We make the case that visual hallucinogenesis across a wide array of neuropsychiatric disorders can be captured within a common Bayesian computational framework, as a compensatory response to sensory signal disruptions at different levels of the visual processing hierarchy. We focus on three specific disorders (Charles Bonnet syndrome, dementia with Lewy Bodies and psychosis) with prominent visual hallucinations and highlight the fact that these disorders describe a spectrum of visual impairment where the overtness and localization of the visual processing disruption is reflected in the characteristics of the emergent visual hallucinations. We examine how discrete sensory disruptions in Charles Bonnet syndrome translate to hallucinations via known circuits, and then how different disruptions in dementia with Lewy Bodies and Schizophrenia may lead to hallucinations with distinct phenomenology, comorbidities and circuit involvement. Finally, we appeal to emerging computational theories to unite these observations under a common conceptual umbrella. Taken together, this work presents a means of understanding how sensory disruptions could interact with other aspects of cognitive and neural architecture to produce hallucinations across neuropsychiatric disease. It is our hope that this framework will help in efforts to identify pathophysiologically distinct patient subgroups and new pharmacological and circuit-based interventions.

Blood-based biomarkers are crucial for individualized management of multiple sclerosis (MS). Blood neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) have shown promising clinical utility in MS, but they are insufficient to guide clinical management. Plasma tau proteins remain underexplored despite the growing evidence of shared pathology in Alzheimer's disease and MS. We aimed to: (i) assess the utility of plasma tau biomarkers [phosphorylated tau 181 (p-tau181), p-tau217 and total tau (t-tau)] in MS diagnosis, subtyping and prognosis; and (ii) compare their performance with NfL and GFAP. From a clinic-based prospective cohort, we evaluated 160 people with MS [pwMS; 117 with relapsing-remitting MS, 43 with progressive MS (PMS)] and 20 non-MS controls, all with baseline plasma samples. We measured baseline plasma concentrations of p-tau181, p-tau217, t-tau, NfL and GFAP using ultrasensitive immunoassays. We collected demographics, clinical information, and longitudinal multi-modal outcomes (Patient Determined Disease Steps, normalized age-related MS severity score, walking speed, manual dexterity, cognitive performance, retinal nerve fibre layer thickness, total brain volume and grey matter volume) over a median follow-up of 3.0 years (interquartile range, 3.5). Adjusting for demographic and clinical covariates, we evaluated associations between biomarkers and MS diagnosis, subtypes, and prognosis. We examined the enhanced value of tau markers, in addition to NfL and GFAP, for subtype distinction and outcome prediction. Participants were enrolled between 2017 and 2023. Assays were performed in August 2023. Analyses were conducted in December 2024. Participants (n = 180) had a median age of 51 years and were predominantly women (68%) and non-Hispanic white (91%). Compared with controls, pwMS had higher levels of p-tau217 (1.0 versus 0.7 pg/ml; P = 0.04) and NfL (14.1 versus 9.0 pg/ml; P < 0.01). Among pwMS, higher p-tau181 (adjusted odds ratio (aOR) [95% confidence interval (CI)] = 2.3 [1.4, 4.1]) and p-tau217 (aOR [95% CI] = 3.0 [1.8, 5.7]) were associated with PMS. These markers improved MS subtype classification accuracy beyond clinical features, NfL and GFAP. Higher baseline p-tau181 and p-tau217 predicted worse disability, functional outcomes and imaging outcomes independent of other biomarkers. Plasma p-tau181 and p-tau217 are promising biomarkers for MS subtype classification and disability prediction, providing complementary information to NfL and GFAP. Further studies to validate their potential clinical utility in guiding MS management are warranted.

Previous genome-wide association studies (GWAS) have identified several risk genes for stroke; however, it remains unclear how they confer risk for the disease. We conducted an integrative analysis to identify candidate genes for stroke and stroke subtypes by integrating blood-derived multi-omics data with genetic data. We systematically integrated the latest stroke GWAS database with human plasma proteomes and performed proteome-wide association studies, Mendelian randomization (MR), Bayesian colocalization analysis and transcriptome-wide association study to prioritize genes that associate the risk of stroke and its subtypes with their expression and protein abundance in plasma. The target genes were verified by performing tissue and cell type specificity, and functional analysis using the Genotype-Tissue Expression database, single-cell RNA sequencing and Gene Ontology databases. A two-step MR analysis was followed to explore the potential mechanisms. We found that the protein abundance of seven genes (MMP12, F11, SH3BGRL3, ENGASE, SCARA5, SWAP70 and SPATA20) in the plasma was associated with stroke and its subtypes, and six genes (MMP12, F11, SH3BGRL3, SCARA5, SWAP70 and SPATA20) causally related with stroke and its subtypes. The effect of F11, SH3BGRL3, SPATA20 and SWAP70 on each subtype was mediated by Factor XI inhibitors, atrial fibrillation, type 2 diabetes and systolic blood pressure, respectively (P < 0.05). We also found that SCARA5 and SWAP70 were related to stroke and ischemic stroke at the transcriptome level. Our present proteomic findings may offer potential future therapeutic targets for stroke prevention.