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Our researchers discover new evidence that post-brain injury sleep problems can slow the pace of recovery.
The rising incidence of stroke in the young: epidemiology, causes and global impact.
Although reductions in stroke incidence have been reported over recent decades particularly in high-income countries, there has been a worrying trend since the start of the 21st century: stroke incidence in younger individuals (< 55 years) has not showed a similar decrease than at older ages. In high-income countries, several population-based studies have found an increase in the incidence of stroke at younger ages since 2000, reaching up to 90% in Oxfordshire, UK (2010-2018 vs 1981-1986) and 97% in Cincinnati, US (2010 vs 1993-1994). A similar picture has also been documented in low- and middle-income countries, both in population-based studies (Joinville, Brazil, 35% increase in 2012-2013 vs 2005-2006) and in the Global Burden of Diseases Study. The exact reasons for this very different picture seen in younger individuals are unknown. One possibility is that traditional modifiable risk factors are increasingly prevalent and often undertreated at younger ages. However, studies have also found increases in the incidence of young-onset cryptogenic stroke and in people with no traditional modifiable risk factors, suggesting a role for emerging risk factors. Potential culprits might include air pollution, long working hours, psychosocial stress, prior autoimmune diseases, and illicit drug use, although further research is required to determine whether these emerging risk factors are causally related to stroke at younger ages. Without further intervention, the global burden of stroke at younger ages is projected to increase further in the coming years. Therefore, there is an urgent need to better understand the drivers of these time trends in incidence, to potentially alleviate the individual and societal impacts of stroke in the young. In this narrative review, we examine the recent global changes in stroke epidemiology at younger ages, their potential drivers, and their projected consequences.
Interleukin-6, C-Reactive Protein, and Vascular Recurrence After Stroke With and Without Atherosclerosis.
BACKGROUND: Uncertainty remains whether inflammation is implicated in poststroke recurrence in patients without atherosclerosis. We evaluated the contribution of atherosclerosis status to the association between inflammatory markers and major adverse cardiovascular events (MACE) poststroke. METHODS: We performed an individual-participant data meta-analysis of 11 prospective cohorts (12 countries, 1995-2017). Studies included patients with ischemic stroke/transient ischemic attack and measured IL (interleukin)-6/hsCRP (high-sensitivity C-reactive protein) postevent. We analyzed the association between IL-6/hsCRP and recurrent stroke/MACE using multivariable Cox regression analyses (conditional logistic regression for 1 study). Analyses were stratified by the presence/absence of atherosclerosis (definition: prior history of coronary disease, peripheral artery disease, or large artery atherosclerotic stroke) and adjusted for cardiovascular risk factors/preventative medication. RESULTS: Overall 10 148 patients (3448 [34.0%] had atherosclerosis) with 21 177 years of follow-up were included (1707 MACE outcomes/1353 recurrent strokes). In patients with atherosclerosis, IL-6 was independently associated with MACE (risk ratio [RR], 1.22 [95% CI, 1.08-1.37]; per logeunit increase) and recurrent stroke (RR, 1.23 [95% CI, 1.08-1.41]). Compared with patients in the bottom quarter, those in the top quarter of IL-6 levels had double the risk of MACE (RR, 2.05 [95% CI, 1.37-3.08]) and stroke (RR, 1.97 [95% CI, 1.28-3.05]). IL-6 was also associated with MACE (RR, 1.11 [95% CI, 1.01-1.23]) but not stroke (RR, 1.08 [95% CI, 0.98-1.20]; per logeunit) in patients without atherosclerosis. However, there was no evidence of statistical interaction between IL-6 levels and atherosclerosis status for either outcome (Pinteraction=0.25 and 0.13 for MACE/recurrent stroke, respectively). hsCRP was associated with MACE in patients with (RR, 1.12 [95% CI, 1.05-1.21]; per logeunit) and without atherosclerosis (RR, 1.07 [95% CI, 1.01-1.14]; Pinteraction=0.28). No association with recurrent stroke was observed for hsCRP with (RR, 1.06 [95% CI, 0.98-1.14]) or without atherosclerosis (RR, 0.97 [95% CI, 0.91-1.04]; Pinteraction=0.18). CONCLUSIONS: IL-6/hsCRP were associated with poststroke recurrence irrespective of atherosclerosis. These data support the inclusion of patients in trials of anti-inflammatory therapies after stroke with elevated IL-6 or hsCRP, including those without prior atherosclerotic events.
Single neurons and networks in the claustrum integrate input from widespread cortical sources
Abstract The claustrum is thought to be one of the most highly interconnected forebrain structures but its organizing principles have yet to be fully explored at the level of single neurons. Here, we investigated the identity, connectivity, and activity of identified claustrum neurons to understand how the structure’s unique convergence of input and divergence of output support binding information streams. We found that neurons in the claustrum communicate with each other across efferent projection-defined modules which were differentially innervated by sensory and frontal cortical areas. Individual claustrum neurons were responsive to inputs from more than one cortical region in a cell-type and projection-specific manner, particularly between areas of frontal cortex. In vivo imaging of claustrum axons revealed responses to both unimodal and multimodal sensory stimuli. Finally, chronic claustrum silencing specifically reduced animals’ sensitivity to multimodal stimuli. These findings support the view that the claustrum is a fundamentally integrative structure, consolidating information from around the cortex and redistributing it following local computations.
The molecular circadian clock: From fundamental mechanisms to therapeutic promise in neurological disorders.
Circadian rhythms are intrinsic biological processes in all forms of life, governed by a molecular clock, organising physiological and behavioural cycles to align with a 24-hour light-dark cycle. The disruption of these rhythms has been linked to a plethora of neurological conditions and impacting cognitive and metabolic functions. This review offers a clear overview of the genetic and molecular mechanisms that govern the circadian clock. It focuses on the core clock feedback loops, the pathways involved and how these mechanisms are regulated. We explore how clocks in peripheral tissues are synchronised to the suprachiasmatic nucleus and how this is achieved through neuronal and humoral pathways. Additionally, we discuss how dysregulation in circadian rhythms contribute to neurological conditions and potential therapeutic treatments targeting circadian mechanisms. Understanding the mechanisms of circadian dysregulation provides insight into disease pathology and potential therapies. Interventions targeting circadian mechanisms, such as gene and drug delivery systems, show promise to restore rhythms and mitigate neurological symptoms. This review collates current knowledge on circadian biology and its applications addressing neurological dysfunctions, providing a foundation for potential chronotherapeutic interventions.
Evaluating functional brain organization in individuals and identifying contributions to network overlap
Abstract Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting-state networks can be derived using high-quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that overlap between 2-network pairs is indicative of coupling. These results suggest that regions of network overlap concurrently process information from both contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.
An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank.
Functional magnetic resonance imaging (fMRI) has been widely used to identify brain regions linked to critical functions, such as language and vision, and to detect tumors, strokes, brain injuries, and diseases. It is now known that large sample sizes are necessary for fMRI studies to detect small effect sizes and produce reproducible results. Here we report a systematic association analysis of 647 traits with imaging features extracted from resting-state and task-evoked fMRI data of more than 40,000 UK Biobank participants. We used a parcellation-based approach to generate 64,620 functional connectivity measures to reveal fine-grained details about cerebral cortex functional organizations. The difference between functional organizations at rest and during task was examined, and we have prioritized important brain regions and networks associated with a variety of human traits and clinical outcomes. For example, depression was most strongly associated with decreased connectivity in the somatomotor network. We have made our results publicly available and developed a browser framework to facilitate the exploration of brain function-trait association results (http://fmriatlas.org/).
A Phase 3 Trial of Inebilizumab in Generalized Myasthenia Gravis.
BACKGROUND: Autoimmune generalized myasthenia gravis is a disease that manifests with fluctuating muscle weakness. Inebilizumab is a monoclonal antibody that depletes CD19+ B cells, which are central to disease pathogenesis. METHODS: In this phase 3, double-blind, randomized, placebo-controlled trial, we enrolled participants with myasthenia gravis who had anti-acetylcholine receptor antibodies or anti-muscle-specific kinase antibodies. Participants were randomly assigned, in a 1:1 ratio, to receive intravenous inebilizumab (300 mg administered on days 1 and 15 for all, and additionally on day 183 for participants who were acetylcholine receptor antibody-positive) or matching placebo for 52 weeks (in participants who were acetylcholine receptor antibody-positive) or 26 weeks (in those who were muscle-specific kinase antibody-positive). Glucocorticoid therapy was tapered, starting at week 4, to a target of 5 mg per day by week 24. The primary end point was the change from baseline in the score on the Myasthenia Gravis Activities of Daily Living scale (MG-ADL; scores range from 0 to 24, with higher scores indicating greater disease activity) at week 26 in the combined acetylcholine receptor antibody-positive and muscle-specific kinase antibody-positive trial populations. A key secondary end point was the change from baseline in the score on the Quantitative Myasthenia Gravis scale (QMG; scores range from 0 to 39, with higher scores indicating greater disease activity) at week 26 in the combined population. Safety was assessed. RESULTS: A total of 238 participants underwent randomization (119 per group). Participants who received inebilizumab had a greater reduction in the MG-ADL score than those who received placebo (least-squares mean change, -4.2 vs. -2.2; adjusted difference, -1.9; 95% confidence interval [CI], -2.9 to -1.0; P<0.001) at week 26. Participants who received inebilizumab had a greater reduction in the QMG score than those who received placebo (least-squares mean change, -4.8 vs. -2.3; adjusted difference, -2.5; 95% CI, -3.8 to -1.2; P<0.001). The most common adverse events with inebilizumab were headache, cough, nasopharyngitis, infusion-related reactions, and urinary tract infections. Inebilizumab was not associated with a higher incidence of serious adverse events. CONCLUSIONS: In participants with acetylcholine receptor antibody-positive or muscle-specific kinase antibody-positive generalized myasthenia gravis, inebilizumab improved function and reduced disease severity. (Funded by Amgen; MINT ClinicalTrial.gov number, NCT04524273.).
Corrigendum to “Relating TMS measures of GABAergic and Cholinergic signalling to attention” [Brain Stimul 18 (1) (2025) 507–508, (S1935861X24010489), (10.1016/j.brs.2024.12.853)]
The authors regret that some of the authors are omitted in the original publication. The correct list of authors is as presented above. The authors also regret the errors in the abstract text. The corresponding corrections are provided below: The first line of paragraph 3 of the abstract should read: Here we investigated the role of GABA and ACh in healthy vision (n = 35). The last two paragraphs of the abstract should read as follows: We found that higher GABAergic Cholinergic inhibition in the motor cortex relates to better orienting attention allocation, as indicated by a significant correlation between the alerting orienting index of the ANT and SICI-1msSAI (r = −0.5942, p = 0.004). Despite the proposed role of Cholinergic signalling024). Our results are in line with evidence suggesting cholinergic mechanisms are responsible for successful orienting of attention, we did not find a significant correlation between SAI and any of the attentional indices (alerting, orienting, executive) of the ANT. Our findings suggest that GABAergic Cholinergic inhibition plays an important role in success fulorienting attention allocation and have guided the design of our ongoing pharmaco-TMS study investigating the effects of Zolpidem (GABA agonist) and Donepezil (cholinesterase antagonist) on behavioural and neurophysiological indices of attention. The authors would like to apologise for any inconvenience caused.
Automated quality control of T1-weighted brain MRI scans for clinical research datasets: methods comparison and design of a quality prediction classifier
Abstract T1-weighted (T1w) MRI is widely used in clinical neuroimaging for studying brain structure and its changes, including those related to neurodegenerative diseases, and as anatomical reference for analysing other modalities. Ensuring high-quality T1w scans is vital as image quality affects reliability of outcome measures. However, visual inspection can be subjective and time consuming, especially with large datasets. The effectiveness of automated quality control (QC) tools for clinical cohorts remains uncertain. In this study, we used T1w scans from elderly participants within ageing and clinical populations to test the accuracy of existing QC tools with respect to visual QC and to establish a new quality prediction framework for clinical research use. Four datasets acquired from multiple scanners and sites were used (N = 2438, 11 sites, 39 scanner manufacturer models, 3 field strengths—1.5T, 3T, 2.9T, patients and controls, average age 71 ± 8 years). All structural T1w scans were processed with two standard automated QC pipelines (MRIQC and CAT12). The agreement of the accept–reject ratings was compared between the automated pipelines and with visual QC. We then designed a quality prediction framework that combines the QC measures from the existing automated tools and is trained on clinical research datasets. We tested the classifier performance using cross-validation on data from all sites together, also examining the performance across diagnostic groups. We then tested the generalisability of our approach when leaving one site out and explored how well our approach generalises to data from a different scanner manufacturer and/or field strength from those used for training, as well as on an unseen new dataset of healthy young participants with movement-related artefacts. Our results show significant agreement between automated QC tools and visual QC (Kappa = 0.30 with MRIQC predictions; Kappa = 0.28 with CAT12’s rating) when considering the entire dataset, but the agreement was highly variable across datasets. Our proposed robust undersampling boost (RUS) classifier achieved 87.7% balanced accuracy on the test data combined from different sites (with 86.6% and 88.3% balanced accuracy on scans from patients and controls, respectively). This classifier was also found to be generalisable on different combinations of training and test datasets (average balanced accuracy of leave-one-site-out = 78.2%; exploratory models on field strengths and manufacturers = 77.7%; movement-related artefact dataset when including 1% scans in the training = 88.5%). While existing QC tools may not be robustly applicable to datasets comprising older adults, they produce quality metrics that can be leveraged to train more robust quality control classifiers for ageing and clinical cohorts.
Neurodegenerative disease in C9orf72 repeat expansion carriers: population risk and effect of UNC13A.
The C9orf72 hexanucleotide repeat expansion (HRE) is the most common monogenetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Neurodegenerative disease incidence in C9orf72 HRE carriers has been studied using cohorts from disease-affected families or by extrapolating from population disease incidence, potentially introducing bias. Age-specific cumulative incidence of ALS and dementia was estimated using Kaplan-Meier and competing risk models in C9orf72 HRE carriers compared to matched controls in UK Biobank. Risk modification by UNC13A genotype was examined. Of 490,331 individuals with valid genetic data, 701 had >100 repeats in C9orf72 (median age 55 [IQR 48-62], follow-up 13.4 years [12.3-14.1]). The cumulative incidence of ALS or dementia was 66% [95% CI 57-73%] by age 80 in C9orf72 HRE carriers versus 5.8% [4.5-7.0%] in controls, or 58% [50-64%] versus 5.1% [4.1-6.4%] accounting for the competing risk of other-cause mortality. Forty-one percent of dementia incidence accrued between age 75-80. C-allele homozygosity at rs12608932 in UNC13A increased ALS or dementia risk in C9orf72 HRE carriers (hazard ratio 1.81 [1.18 - 2.78]). C9orf72 HRE disease was incompletely penetrant in this population-based cohort, with risk modified by UNC13A genotype. This has implications for counselling at-risk individuals and modelling expected phenoconversion for prevention trials.