Brain communications最新文献

Dominantly inherited intronic GAA repeat expansions in the fibroblast growth factor 14 gene have recently been shown to cause spinocerebellar ataxia 27B. Currently, the pathogenic threshold of (GAA)_≥300 repeat units is considered highly penetrant, while (GAA)_250-299 is likely pathogenic with reduced penetrance. This study investigated the frequency of the GAA repeat expansion and the phenotypic profile in a Cypriot cohort with unresolved late-onset cerebellar ataxia. We analysed this trinucleotide repeat in 155 patients with late-onset cerebellar ataxia and 227 non-neurological disease controls. The repeat locus was examined by long-range PCR followed by fragment analysis using capillary electrophoresis, agarose gel electrophoresis and automated electrophoresis. A comprehensive comparison of all three electrophoresis techniques was conducted. Additionally, bidirectional repeat-primed PCRs and Sanger sequencing were carried out to confirm the absence of any interruptions or non-GAA motifs in the expanded alleles. The (GAA)_≥250 repeat expansion was present in 12 (7.7%) patients. The average age at disease onset was 60 ± 13.5 years. The earliest age of onset was observed in a patient with a (GAA)₂₈₇ repeat expansion, with ataxia symptoms appearing at 25 years of age. All patients with spinocerebellar ataxia 27B displayed symptoms of gait and appendicular ataxia. Nystagmus was observed in 41.7% of the patients, while 58.3% exhibited dysarthria. Our findings indicate that spinocerebellar ataxia 27B represents the predominant aetiology of autosomal dominant cerebellar ataxia in the Cypriot population, as this is the first dominant repeat expansion ataxia type detected in this population. Given our results and existing research, we propose including fibroblast growth factor 14 GAA repeat expansion testing as a first-tier genetic diagnostic approach for patients with late-onset cerebellar ataxia.

Former studies have established that individuals with a cochlear implant (CI) for treating single-sided deafness experience improved speech processing after implantation. However, it is not clear how each ear contributes separately to improve speech perception over time at the behavioural and neural level. In this longitudinal EEG study with four different time points, we measured neural activity in response to various temporally and spectrally degraded spoken words presented monaurally to the CI and non-CI ears (5 left and 5 right ears) in 10 single-sided CI users and 10 age- and sex-matched individuals with normal hearing. Subjective comprehension ratings for each word were also recorded. Data from single-sided CI participants were collected pre-CI implantation, and at 3, 6 and 12 months after implantation. We conducted a time-resolved representational similarity analysis on the EEG data to quantify whether and how neural patterns became more similar to those of normal hearing individuals. At 6 months after implantation, the speech comprehension ratings for the degraded words improved in both ears. Notably, the improvement was more pronounced for the non-CI ears than the CI ears. Furthermore, the enhancement in the non-CI ears was paralleled by increased similarity to neural representational patterns of the normal hearing control group. The maximum of this effect coincided with peak decoding accuracy for spoken-word comprehension (600-1200 ms after stimulus onset). The present data demonstrate that cortical processing gradually normalizes within months after CI implantation for speech presented to the non-CI ear. CI enables the deaf ear to provide afferent input, which, according to our results, complements the input of the non-CI ear, gradually improving its function. These novel findings underscore the feasibility of tracking neural recovery after auditory input restoration using advanced multivariate analysis methods, such as representational similarity analysis.

Visual perceptual learning (VPL), the training-induced improvement in visual tasks, has long been considered the product of neural plasticity at early and local stages of signal processing. However, recent evidence suggests that multiple networks and mechanisms, including stimulus- and task-specific plasticity, concur in generating VPL. Accordingly, early models of VPL, which characterized learning as being local and mostly involving early sensory areas, such as V1, have been updated to embrace these newfound complexities, acknowledging the involvement on parietal (i.e. intra-parietal sulcus) and frontal (i.e. dorsolateral prefrontal cortex) areas, in aspects concerning decision-making, feedback integration and task structure. However, evidence of multiple brain regions differentially involved in different aspects of learning is thus far mostly correlational, emerging from electrophysiological and neuroimaging techniques. To directly address these multiple components of VPL, we propose to use a causal neuromodulation technique, namely transcranial random noise stimulation, to selectively modulate the activity of different brain regions suggested to be involved in various aspects of learning. Specifically, we will target a region in the occipital cortex, which has been associated with stimulus-specific plasticity, and one in the parietal cortex, which has been associated with task-specific plasticity, in a between-subject design. Measures of transfer of learning to untrained stimuli and tasks will be used to evaluate the role of different regions and test for double dissociations between learning effects and stimulated area, shedding lights on learning mechanisms in the visual system. Evidence of dissociable mechanisms of learning can help refine current models of VPL and may help develop more effective visual training and rehabilitation protocols.

Epidemiological evidence associates Toxoplasma gondii latent infection with the development of neuropsychiatric disorders, and various immunological and environmental factors play key pathophysiological roles through host immune response alterations. We investigated the cognitive and motor alterations occurring in the terminal stage of T. gondii infection in rats, and whether a low-protein diet, a high-fat diet or ovariectomy may accelerate their development, given the role of malnutrition and menopause on immunity and resistance to infection. In two sets of experiments, 2-month-old (157.5 ± 4.3 g, n = 42) male (n = 18) and female (n = 24) Wistar rats were infected with T. gondii (ATCC 40050). Open-field and elevated plus maze tests were performed in the terminal stage of infection first and then in the early stage in low-protein diet-fed, high-fat diet-fed and ovariectomized infected rats. Late-stage (90 days) infected and early-stage (17 days) low-protein diet-fed groups showed significant decreases in body weight (42.42%↓, P = 0.016 and 57.14%↓, P < 0.001 versus non-infected, respectively), increases in body temperature (P = 0.001 and P < 0.001, respectively), decreases in blood glucose levels (P = 0.006 and P = 0.020, respectively), signs of cognitive and motor impairment and lower neuron counts. The alterations observed in high-fat diet-fed and ovariectomized infected animals were milder. Low-protein diet feeding to T. gondii-infected rats accelerated the occurrence of the infection terminal stage. Thus, a diet low in proteins could transform a slow early-stage T. gondii infection into an active neurotoxoplasmosis with neuropsychiatric manifestations and possible neurodegeneration in rats.

Accurate and early diagnosis of Alzheimer's disease and vascular dementia is crucial for enabling timely interventions and improving patient outcomes. This study evaluates the diagnostic performance of plasma biomarkers (neurofilament light chain and phosphorylated tau181) and retinal biomarkers (retinal nerve fibre layer and ganglion cell-inner plexiform layer), individually and in combination, in differentiating moderate cognitive impairment and dementia from mild cognitive impairment and no cognitive impairment. A cross-sectional study was conducted involving 509 participants, aged 50 and older, recruited from a memory clinic. The participants were categorized as normal (n = 100), mild cognitive impairment (n = 144), moderate cognitive impairment (n = 90) or dementia (n = 175) based on detailed clinical assessments, neuropsychological testing and MRI scans. The thickness of the ganglion cell-inner plexiform layer (P < 0.001) and retinal nerve fibre layer (P = 0.030) decreased progressively from normal cognition to cognitive impairment and dementia. The thickest layers were observed in individuals with no cognitive impairment (mean ± standard deviation: ganglion cell-inner plexiform layer: 76 ± 11 µm, retinal nerve fibre layer: 92 ± 10 µm), while the thinnest layers were found in individuals with dementia (ganglion cell-inner plexiform layer: 72 ± 14 µm, retinal nerve fibre layer: 89 ± 12 µm). Plasma biomarker levels increased progressively from normal cognition to cognitive impairment and dementia (P < 0.001). Levels were lowest in individuals with no cognitive impairment [median (interquartile range): neurofilament light chain: 15 (9) pg/mL, phosphorylated tau181: 1.85 (1.00) pg/mL] and highest in those with dementia [neurofilament light chain: 34 (27) pg/mL, phosphorylated tau181: 3.24 (2.81) pg/mL]. After adjusting for retinal scan signal strength, neurofilament light chain showed a stronger negative association with retinal nerve fibre layer thickness [standardized beta estimate (β) = -0.184] and ganglion cell-inner plexiform layer thickness (β = -0.139) compared to phosphorylated tau181, which exhibited weaker associations with ganglion cell-inner plexiform layer (β = -0.091) and retinal nerve fibre layer (β = -0.059). While retinal parameters provided modest discriminatory ability (AUC = 0.60), plasma biomarkers demonstrated superior diagnostic performance (AUC = 0.76). Notably, neurofilament light chain had a stronger association with retinal thinning than phosphorylated tau181 and offered superior diagnostic value for identifying moderate cognitive decline. These findings underscore the potential of plasma biomarkers, particularly neurofilament light chain, for the early detection of dementia.

This scientific commentary refers to 'A data-driven model of disability progression in progressive multiple sclerosis', by Garbarino et al. (https://doi.org/10.1093/braincomms/fcae434).

Neurocognitive impairment (NCI) is present in around 40% of people with HIV and substantially affects everyday life, adherence to combined antiretroviral therapy (cART) and overall life expectancy. Suboptimal therapy regimen, opportunistic infections, substance abuse and highly prevalent psychiatric co-morbidities contribute to NCI in people with HIV. In this review, we highlight the need for efficacious treatment of HIV-related NCI through pharmacological approaches and cognitive neurorehabilitation, discussing recent randomized controlled trials in this domain. We also discuss the benefits of a thorough and interdisciplinary diagnostic work-up between specialists in neurology, psychiatry, neuropsychology and infectious diseases, helping to disentangle the various factors contributing to cognitive complaints and deficits in people with HIV. While the advent of cART has contributed to slowing the progression of cognitive deficits in people with HIV and reducing the prevalence of HIV-associated dementia, NCI persists at a significant rate. Adjuvant stimulating or neuroprotective pharmacological agents have shown some potential benefits. Despite promising outcomes, studies on cognitive neurorehabilitation of HIV-related NCI remain sparse and limited in terms of methodological aspects. The access to cognitive neurorehabilitation is also restricted, in particular at the global scale. Novel technology bears a significant potential for restoring cognitive function in people with HIV, affording high degrees of standardization and personalization, along with opportunities for telerehabilitation. Entertaining serious video game environments with immersive graphics can further promote patient motivation, training adherence and impact on everyday life, as indicated by a growing body of evidence, including in seropositive children and older individuals in Africa. Upon validation of technology-assisted cognitive neurorehabilitation for HIV-related NCI in large-scale randomized controlled trials with state-of-the-art methodology, these approaches will promote socio-professional reintegration and quality of life of people with HIV.

Our editor discusses re-organizing her lab's data storage to facilitate sharing and archiving data. She also advertises the 'Brain Communications' early career researcher paper prize for the first author of a paper published in the journal in 2024-please send nominations!

Predicting risk of future dementia is essential for primary prevention strategies, particularly in the era of novel immunotherapies. However, few studies have developed population-level prediction models using existing routine healthcare data. In this longitudinal retrospective cohort study, we predicted incident dementia using primary and secondary care health records at 5, 10 and 13 years in 144 113 Scottish older adults who were dementia-free prior to 1st April 2009. Gradient-boosting (XGBoost) prediction models were trained on two feature subsets: data-driven (using all 171 extracted variables) and clinically supervised (22 curated variables). We used a random-stratified internal validation set to rank top predictors in each model, assessing performance stratified by age and socioeconomic deprivation. Predictions were stratified into 10 equally sized risk deciles and ranked by response rate. Over 13 years of follow-up, 11 143 (8%) patients developed dementia. The data-driven models achieved marginally better precision-recall area-under-the-curve scores of 0.18, 0.26 and 0.30 compared to clinically supervised models with scores of 0.17, 0.27 and 0.29 for incident dementia at 5, 10 and 13 years, respectively. The clinically supervised model achieved comparable specificity 0.88 [95% confidence interval (CI) 0.87-0.88] and sensitivity (0.55, 95% CI 0.53-0.57) to the data-driven model for prediction at 13 years. The most important model features were age, deprivation and frailty, measured by a modified electronic frailty index excluding known cognitive deficits. Model precision was consistent across socioeconomic deprivation quintiles but lower in younger-onset (<70 years) dementia cases. At 13 years, dementia was diagnosed in 32% of the population classified as highest risk with 40% of individuals in this group below the age of 80. Personalized estimates of future dementia risk from routinely collected healthcare data could influence risk factor modification and help to target brain imaging and novel immunotherapies in selected individuals with pre-symptomatic disease.