Brain communications最新文献

This scientific commentary refers to 'Integrating genome-wide association studies and transcriptomics prioritizes drug targets for meningioma', by Liao et al. (https://doi.org/10.1093/braincomms/fcaf053).

Alzheimer's disease and related dementias have a multifactorial aetiology and heterogeneous biology. The current study aims to identify different biological signatures in a deeply phenotyped memory clinic patient population. In this cross-sectional study, we analysed 49 pre-specified proteins using a multiplex antibody-based suspension bead array in 278 CSF samples from the real-world research database and biobank at the Karolinska University Hospital Memory Clinic, Solna, Sweden. Patients with a clinical diagnosis of subjective cognitive decline (N = 151), mild cognitive impairment (N = 61), Alzheimer's disease (N = 47), or other diagnoses (N = 19; vascular dementias, alcohol-related dementia, unspecified dementias, or other amnesias) were included. Principal component analyses were performed, and resulting principal components (PCs) were tested for associations with clinical variables and Alzheimer's disease biomarkers (CSF biomarkers beta-amyloid 42, beta-amyloid 42/40, phosphorylated tau 181, phosphorylated tau 181/beta-amyloid 42). PC 1 (explaining 52% of the variance between patients) was associated with the clinical Alzheimer's disease CSF biomarkers beta-amyloid 42, phosphorylated tau 181, and total tau but not with Alzheimer's disease-related neurodegeneration imaging markers, cognitive performance, or clinical diagnosis. PC 2 (explaining 9% of the variance) displayed an inflammatory profile with high contributions of chitinase 3 like 1 (CHI3L1) and triggering receptor expressed on myeloid cells 2 (TREM2) and significant correlation to CSF free light chain kappa. In contrast to PC 1, PC 3 (explaining 5% of the variance) showed associations with all the clinical Alzheimer's disease CSF biomarkers, the imaging markers, cognitive impairment and clinical diagnosis. Serpin family A member 3 (SERPINA3), chitinase 1 (CHIT1), and neuronal pentraxin 2 (NPTX2) contributed most to PC 3. PC 4 (explaining 4% of the variance) exhibited an inflammatory profile distinct from PC 2, with the largest contributions from TREM2, leucine-rich alpha-2-glycoprotein 1 (LRG1) and complement C9. The component was associated with peripheral inflammation. We found that CSF protein profiles in a memory clinic cohort reflect molecular differences across diagnostic groups. Our results emphasize that real-world memory clinic patients can have different ongoing biological processes despite receiving the same diagnosis. In the future, this information could be utilized to identify patient endotypes and uncover precision biomarkers and novel therapeutic targets.

Early hearing intervention in children with congenital hearing loss is critical for improving auditory development, speech recognition and both expressive and receptive language, which translates into better educational outcomes and quality of life. In children receiving hearing aids or cochlear implants, both adaptive and potentially maladaptive neural reorganization can mitigate higher-level functions that impact reading. The focus of the present study was to dissect the neural underpinnings of the reading networks in children with cochlear implants and assess how these networks mediate the reading ability in children with cochlear implants. Cortical activity was obtained using naturalistic stimuli from 75 children (50 cochlear implant recipients, aged 7-17, and 25 age-matched children with typical hearing) using functional near-infrared spectroscopy. Assessment of basic reading skill was completed using the Reading Inventory and Scholastic Evaluation. We computed directed functional connectivity of the haemodynamic activity in reading-associated anterior and posterior brain regions using the time-frequency causality estimation method known as temporal partial directed coherence. The influence of the cochlear implant-related clinical measures on reading outcome and the extent to which neural connectivity mediated these effects were examined using structural equation modelling. Our findings reveal that the timing of intervention (e.g. age of first cochlear implants, age of first hearing aid) in children with cochlear implants significantly influenced their reading ability. Furthermore, reading-related processes (word recognition and decoding, vocabulary, morphology and sentence processing) were substantially mediated by the directed functional connectivity within reading-related neural circuits. Notably, the impact of these effects differed across various reading skills. Hearing age, defined as the age at which a participant received adequate access to sound, and age of initial implantation emerged as robust predictors of reading proficiency. The current study is one of the first to identify the influence of neural characteristics on reading outcomes for children with cochlear implants. The findings emphasize the importance of the duration of deafness and early intervention for enhancing outcomes and strengthening neural network connections. However, the neural evidence further suggested that such positive influences cannot fully offset the detrimental impact of early auditory deprivation. Consequently, additional, perhaps more specialized, interventions might be necessary to maximize the benefits of early prosthetic hearing intervention.

The glymphatic system may play a central role in cognitive impairment associated with Parkinson's disease, but its relationship with regional cortical atrophy is not fully explored. To explore associations among glymphatic dysfunction, regional cortical degeneration and cognitive impairment in Parkinson's disease participants, we evaluated 51 participants with documented Parkinson's disease (28 men; age, 61.65 ± 8.27 years) and 30 age- and sex-matched normal controls (11 men; age, 59.2 ± 5.90 years) who underwent 3.0-T MRI of the brain, including high-resolution T1-weighted imaging and diffusion-tensor imaging along the perivascular space as a surrogate for glymphatic flow. Cortical grey matter volume was segmented automatically based on three-dimensional T1-weighted sequences. Cognitive function was assessed by Mini-Mental State Examination. The relationship between glymphatic dysfunction, cognitive decline and regional cortical degeneration was explored. The participants with Parkinson's disease revealed lower diffusion-tensor imaging along the perivascular space (1.45 ± 0.17 versus 1.64 ± 0.17, P < 0.0001) as compared with normal controls, indicating disturbed glymphatic flow. Glymphatic dysfunction was associated with cognitive scores (r = 0.54, P = 0.003). Diffusion-tensor imaging along the perivascular space values were positively associated with the volume of specific cortical regions (all P-values <0.05) including the temporal pole, posterior orbital gyrus, orbital part of the inferior frontal gyrus, frontal operculum, central operculum and anterior cingulate gyrus. Mediation analysis within the Parkinson's disease participants indicated that the relationship between glymphatic dysfunction and cognitive scores was partially mediated by the integrity of orbital part of the inferior frontal gyrus and anterior cingulate gyrus. Glymphatic dysfunction is associated with cognitive decline in Parkinson's disease, whereas the distribution of regional cortical degeneration may constitute the link between glymphatic dysfunction and cognitive impairment.

Multiple sclerosis is an inflammatory demyelinating condition of the central nervous system affecting approximately 1 million people in the USA. Although standard structural MRI techniques are now the main imaging modality for multiple sclerosis diagnosis and management, they are yet to provide information regarding the metabolic profile of the disease. Ultra-high field 7T MRI systems have provided gains in signal-to-noise ratio (SNR) and spatial resolution for structural MRI as well as larger chemical shifts leading to improvements in specialized imaging sequences, such as nuclear Overhauser effect (NOE) imaging, that can evaluate macromolecular metabolite composition. In this work, NOE images were acquired on a cohort of multiple sclerosis and healthy control subjects to spatially map differences in their lipid metabolites as a result of NOE effects. NOE image data were acquired on a total of 25 subjects {15 multiple sclerosis subjects [10 females, 5 males (21-70 years)] and 10 healthy controls [5 females, 5 males (23-71 years)]} on a 7T MRI system with a frequency offset range of -5 to 5 ppm. A five-pool Lorentzian line fitting model was utilized to fit and quantitatively compare direct saturation (DS), magnetization transfer (MT), amide proton transfer (APT), amine, and relayed NOE (rNOE) and used as a comparison to conventional T₁ maps. Grey and white matter tissues were segmented using the T₁ maps, while the lesion tissue was segmented manually. Correlations between disease duration and lesion load were performed to investigate any existing relationship to image contrast. The primary findings of this work include statistically significant decreases in the rNOE pool for the normal-appearing white matter (NAWM) (11.4% decrease) and normal-appearing grey matter (NAGM) (10.6% decrease) in multiple sclerosis subjects compared to healthy controls. Additionally, a significant decrease in the amine pool was also observed for NAWM (15.3% decrease) in multiple sclerosis subjects compared to healthy controls. Changes in multiple sclerosis lesion contrast were also observed for several pools (DS, amine, and rNOE). Decreases in both the rNOE and amine pools suggest that in multiple sclerosis, there are diffuse decreases in mobile lipids, such as those found in neuronal cell bodies, as well as a decrease in proteins with amine groups. Furthermore, these measurable contrast changes were not detected in the corresponding T₁ maps. NOE imaging can provide complementary metabolic information to conventional MRI methods. Future studies will focus on utilizing this technique for longitudinal tracking of disease progression and investigating similar demyelinating diseases.

Long-term intensive training has enabled world class gymnasts to attain exceptional skill levels, inducing notable neuroplastic changes in their brains. Previous studies have identified optimized brain modularity related to long-term intensive training based on resting-state functional MRI, which is associated with higher efficiency in motor and cognitive functions. However, most studies assumed that functional topological networks remain static during the scans, neglecting the inherent dynamic changes over time. This study applied a multilayer network model to identify the effect of long-term intensive training on dynamic functional network properties in gymnasts. The imaging data were collected from 13 gymnasts and 14 age- and gender-matched non-athlete controls. We first construct dynamic functional connectivity matrices for each subject to capture the temporal information underlying these brain signals. Then, we applied a multilayer community detection approach to analyse how brain regions form modules and how this modularity changes over time. Graph theoretical parameters, including flexibility, promiscuity, cohesion and disjointedness, were estimated to characterize the dynamic properties of functional networks across global, network, and nodal levels in the gymnasts. The gymnasts showed significantly lower flexibility, cohesion and disjointedness at the global level than the controls. Then, we observed lower flexibility and cohesion in the auditory, dorsal attention, sensorimotor, subcortical, cingulo-opercular and default mode networks in the gymnasts than in the controls. Furthermore, these gymnasts showed decreased flexibility and cohesion in several regions associated with motor function. Together, we found brain functional neuroplasticity related to long-term intensive training, primarily characterized by decreased flexibility of brain dynamics in the gymnasts, which provided new insights into brain reorganization in motor skill learning.

This scientific commentary refers to 'Retinal microstructure and microvasculature in association with brain amyloid burden', by Egle et al. (https://doi.org/10.1093/braincomms/fcaf013).

Spontaneous electroencephalography (EEG) measurements have demonstrated putative variations in the neural connectivity of subjects with autism spectrum disorder, as compared to neurotypical individuals. However, the exact nature of these connectivity differences has remained unknown, a question that we now address. Resting-state, eyes-open EEG data were recorded over 20 min from a cohort of 13 males aged 3-5 years with autism spectrum disorder, and nine neurotypical individuals as a control group. We use time-localized, phase-based methods of data analysis, including wavelet phase coherence and dynamical Bayesian inference. Several 3 min signal segments were analysed to evaluate the reproducibility of the proposed measures. In the autism spectrum disorder cohort, we demonstrate a significant (P < 0.05) reduction in functional connectivity strength across all frontal probe pairs. In addition, the percentage of time during which frontal regions were coupled was significantly reduced in the autism spectrum disorder group compared to the control group. These changes remained consistent across repeated measurements. To further validate the findings, an additional resting-state EEG dataset (eyes open and closed) from 67 individuals with autism spectrum disorder and 66 control group individuals (male, 5-15 years) was assessed. The functional connectivity results demonstrated a reduction in theta and alpha connectivity on a local, but not global, level. No association was found with age. The connectivity differences observed suggest the potential of theta and alpha connectivity as biomarkers for autism spectrum disorder. Additionally, the robustness to amplitude perturbations of the methods proposed here makes them particularly suitable for the clinical assessment of autism spectrum disorder and of the efficacy of therapeutic interventions.

Transcranial direct current stimulation shows promise as a non-invasive therapeutic method for patients with focal drug-resistant epilepsy. However, there is considerable variability in individual responses to transcranial direct current stimulation, and the factors influencing treatment effectiveness in targeted regions are not well understood. We aimed to assess how the extent and depth of the epileptogenic zone and associated networks impact patient responses to transcranial direct current stimulation therapy. We conducted a retrospective analysis of stereoelectroencephalography data from 23 patients participating in a personalized multichannel transcranial direct current stimulation protocol. We evaluated the extent and depth of the epileptogenic zone network, propagation zone network, and the combined network of the entire epileptogenic and propagation zones, correlating these factors with clinical response measured by the reduction in seizure frequency following repeated transcranial direct current stimulation sessions. Among the patients, 10 (43.5%) were classified as responders (R), experiencing a significant (>50%) decrease in seizure frequency, while 13 were non-responders, showing minimal improvement or increased seizure frequency. Importantly, we found a significant positive correlation between the extent of the epileptogenic zone network and changes in seizure frequency. A smaller epileptogenic zone network extent was associated with better transcranial direct current stimulation efficacy, with responders demonstrating a significantly smaller epileptogenic and propagation zones compared with non-responders. Additionally, non-responders tended to have a significantly deeper epileptogenic zone network compared with responders. Our results highlight the significant impact of the extent and depth of the epileptogenic zone network on transcranial direct current stimulation efficacy in patients with refractory focal epilepsy. Responders typically exhibited a smaller and shallower epileptogenic zone network compared with non-responders. These findings suggest that utilizing individualized epileptogenic zone network characteristics could help refine patient selection for personalized transcranial direct current stimulation protocols, potentially improving therapeutic outcomes.