Marker Of Neurodegenerative Diseases Research Articles

Cerebrospinal fluid proteomic profile of frailty: Results from the PROLIPHYC cohort.

Frailty is a clinical state reflecting a decrease in physiological reserve capacities, known to affect numerous biological pathways and is associated with health issues, including neurodegenerative diseases. However, how global protein expression is affected in the central nervous system in frail subject remains underexplored. In this post hoc cross-sectional biomarker analysis, we included 90 adults (52-85 years) suspected of normal pressure hydrocephalus (NPH) and presenting with markers of neurodegenerative diseases. We investigated the human proteomic profile of cerebrospinal fluid associated with frailty defined by an established cumulated frailty index (FI, average = 0.32), not enriched for neurology clinical features. Using a label-free quantitative proteomic approach, we identified and quantified 999 proteins of which 13 were positively associated with frailty. Pathway analysis with the top positively frailty-associated proteins revealed enrichment for proteins related to inflammation and immune response. Among the 60 proteins negatively associated with frailty, functional pathways enriched included neurogenesis, synaptogenesis and neuronal guidance. We constructed a frailty prediction model using ridge regression with 932 standardized proteins. Our results showed that the "proteomic model" could become an equivalent predictor of FI in order to study chronological age. This study represents the first comprehensive exploration of the proteomic profile of frailty within cerebrospinal fluid. It sheds light on the physiopathology of frailty, particularly highlighting processes of neuroinflammation and inhibition of neurogenesis. Our findings unveil a range of biological mechanisms that are dysregulated in frailty, in NPH subjects at risk of neurodegenerative impairment, offering new perspectives on frailty phenotyping and prediction.

Alzheimer’s and neurodegenerative disease biomarkers in blood predict brain atrophy and cognitive decline

BackgroundAlthough blood-based biomarkers have been identified as cost-effective and scalable alternatives to PET and CSF markers of neurodegenerative disease, little is known about how these biomarkers predict future brain atrophy and cognitive decline in cognitively unimpaired individuals. Using data from the Baltimore Longitudinal Study of Aging (BLSA), we examined whether plasma biomarkers of Alzheimer’s disease (AD) pathology (amyloid-β [Aβ42/40], phosphorylated tau [pTau-181]), astrogliosis (glial fibrillary acidic protein [GFAP]), and neuronal injury (neurofilament light chain [NfL]) were associated with longitudinal brain volume loss and cognitive decline. Additionally, we determined whether sex, APOEε4 status, and plasma amyloid-β status modified these associations.MethodsPlasma biomarkers were measured using Quanterix SIMOA assays. Regional brain volumes were measured by 3T MRI, and a battery of neuropsychological tests assessed five cognitive domains. Linear mixed effects models adjusted for demographic factors, kidney function, and intracranial volume (MRI analyses) were completed to relate baseline plasma biomarkers to baseline and longitudinal brain volume and cognitive performance.ResultsBrain volume analyses included 622 participants (mean age ± SD: 70.9 ± 10.2) with an average of 3.3 MRI scans over 4.7 years. Cognitive performance analyses included 674 participants (mean age ± SD: 71.2 ± 10.0) with an average of 3.9 cognitive assessments over 5.7 years. Higher baseline pTau-181 was associated with steeper declines in total gray matter volume and steeper regional declines in several medial temporal regions, whereas higher baseline GFAP was associated with greater longitudinal increases in ventricular volume. Baseline Aβ42/40 and NfL levels were not associated with changes in brain volume. Lower baseline Aβ42/40 (higher Aβ burden) was associated with a faster decline in verbal memory and visuospatial performance, whereas higher baseline GFAP was associated with a faster decline in verbal fluency. Results were generally consistent across sex and APOEε4 status. However, the associations of higher pTau-181 with increasing ventricular volume and memory declines were significantly stronger among individuals with higher Aβ burden, as was the association of higher GFAP with memory decline.ConclusionsAmong cognitively unimpaired older adults, plasma biomarkers of AD pathology (pTau-181) and astrogliosis (GFAP), but not neuronal injury (NfL), serve as markers of future brain atrophy and cognitive decline.

Nitrooxidative Stress and Neuroinflammation Caused by Air Pollutants Are Associated with the Biological Markers of Neurodegenerative Diseases.

Millions of people around the world are exposed to air pollutants, such as particulate matter 2.5 (PM2.5) and ozone (O3). Such exposure usually does not exclude these two types of pollutants and their harmful effects could be additive or synergistic. O3 is a highly oxidizing gas that reacts with the cellular environment just as PM2.5, triggering nitrooxidative damage. Once nitrooxidative stress overcomes the endogenous antioxidant system, an acute neuroinflammatory process is generated, and once it becomes chronic, it favors the formation of neurodegenerative disease markers. The presence of these markers becomes potentially dangerous in people who have a genetic predisposition and are at a higher risk of developing neurodegenerative diseases such as Alzheimer's and Parkinson's. Our experimental approach for nitrooxidative damage and neuroinflammation caused by air pollutants has focused on the exposure of rats to O3 in an isolated chamber. The hippocampus is the most studied brain structure because of its neuronal connectivity network with the olfactory epithelium, its weak antioxidant defense, and its fundamental roll in cognitive processes. However, other brain structures may exhibit a different degree of damage upon exposure to O3 and PM2.5, making their involvement an important factor in developing other CNS diseases. The age spectrum for augmented sensibility to air pollutants seems to mostly affect the pre-postnatal (autism spectrum) period and the elderly (neurodegenerative). Thus, a new approach could be the estimation of the damage caused by PM2.5 and O3 through a controlled exposure paradigm to determine the extent of damage caused by both pollutants.

Impaired 24-h activity patterns are associated with an increased risk of Alzheimer’s disease, Parkinson’s disease, and cognitive decline

BackgroundSleep-wake regulating circuits are affected during prodromal stages in the pathological progression of both Alzheimer’s disease (AD) and Parkinson’s disease (PD), and this disturbance can be measured passively using wearable devices. Our objective was to determine whether accelerometer-based measures of 24-h activity are associated with subsequent development of AD, PD, and cognitive decline.MethodsThis study obtained UK Biobank data from 82,829 individuals with wrist-worn accelerometer data aged 40 to 79 years with a mean (± SD) follow-up of 6.8 (± 0.9) years. Outcomes were accelerometer-derived measures of 24-h activity (derived by cosinor, nonparametric, and functional principal component methods), incident AD and PD diagnosis (obtained through hospitalization or primary care records), and prospective longitudinal cognitive testing.ResultsOne hundred eighty-seven individuals progressed to AD and 265 to PD. Interdaily stability (a measure of regularity, hazard ratio [HR] per SD increase 1.25, 95% confidence interval [CI] 1.05–1.48), diurnal amplitude (HR 0.79, CI 0.65–0.96), mesor (mean activity; HR 0.77, CI 0.59–0.998), and activity during most active 10 h (HR 0.75, CI 0.61–0.94), were associated with risk of AD. Diurnal amplitude (HR 0.28, CI 0.23–0.34), mesor (HR 0.13, CI 0.10–0.16), activity during least active 5 h (HR 0.24, CI 0.08–0.69), and activity during most active 10 h (HR 0.20, CI 0.16–0.25) were associated with risk of PD. Several measures were additionally predictive of longitudinal cognitive test performance.ConclusionsIn this community-based longitudinal study, accelerometer-derived metrics were associated with elevated risk of AD, PD, and accelerated cognitive decline. These findings suggest 24-h rhythm integrity, as measured by affordable, non-invasive wearable devices, may serve as a scalable early marker of neurodegenerative disease.

Intra and inter-regional functional connectivity of the human brain due to Task-Evoked fMRI Data classification through CNN & LSTM

Background and purposeOlfaction is an early marker of neurodegenerative disease. Standard olfactory function is essential due to the importance of olfaction in human life. The psychophysical evaluation assesses the olfactory function commonly. It is patient-reported, and results rely on the patient's answers and collaboration. However, methodological difficulties attributed to the psychophysical evaluation of olfactory-related cerebral areas led to limited assessment of olfactory function in the human brain. Materials and MethodsThe current study utilized clustering approaches to assess olfactory function in fMRI data and used brain activity to parcellate the brain with homogeneous properties. Deep neural network architecture based on ResNet convolutional neural networks (CNN) and Long Short-Term Model (LSTM) designed to classify healthy with olfactory disorders subjects. ResultsThe fMRI result obtained by k-means unsupervised machine learning model was within the expected outcome and similar to those found with the conn toolbox in detecting active areas. There was no significant difference between the means of subjects and every subject. Proposing a CRNN deep learning model to classify fMRI data in two different healthy and with olfactory disorders groups leads to an accuracy score of 97 %. ConclusionsThe K-means unsupervised algorithm can detect the active regions in the brain and analyze olfactory function. Classification results prove the CNN-LSTM architecture using ResNet provides the best accuracy score in olfactory fMRI data. It is the first attempt conducted on olfactory fMRI data in detail until now.

The role of Mild Behavioral Impairment in a future era of Alzheimer’s disease modifying treatments

Early clinical risk markers of neurodegenerative diseases, such as Alzheimer’s disease (AD), can be considered fundamental in a new era with novel disease modifying treatments on the horizon. Mild Behavioral Impairment (MBI) is a diagnostic construct defined by the later-life emergence of persistent neuropsychiatric symptoms (e.g. apathy, anxiety, depression, amongst others) displayed by older adults, with the aim to identify individuals at increased risk of future dementia. According to established MBI criteria the syndrome can co-occur with mild cognitive impairment due to a neurodegenerative disease or even precede it, and in fact, MBI is most meaningful when reported in conjunction with cognitive status, as MBI-associated risk is moderated by cognitive status. MBI symptomatology has been reported prevalent among older adults, as well as in patients with early stages of neurodegenerative disease. Symptoms of MBI are further associated with several clinically negative outcomes, such as a reduced quality of life, increased caregiver burden and earlier institutionalization. In support of the MBI construct, several previous reports have demonstrated MBI to be predictive of future cognitive decline, dementia, or AD. The construct is also related to AD biomarkers including beta-amyloid, tau, and cerebral atrophy. Intriguingly, an earlier study indicates that MBI even can precede memory deficits in its association with early tau deposition in cognitively unimpaired elderly with confirmed amyloid-beta pathology, strengthening its position as an early marker of dementing biochemical processes. Despite this growing evidence of being both prevalent and an early prognostic marker, MBI is still only given diminutive consideration in contemporary clinical diagnostic criteria for AD. Perhaps so since the added value of MBI in such criteria has rarely been investigated. Consequently, cognitively unimpaired subjects with positive MBI and AD biomarker status face the risk of not being eligible for a future disease modifying AD treatment since they formally do not fulfill AD diagnostic criteria. Hence, studies exploring the added value of MBI in clinical diagnostic criteria for neurocognitive disorders are prompted.

Polypathologic Associations with Gray Matter Atrophy in Neurodegenerative Disease.

Mixed pathologies are common in neurodegenerative disease; however, antemortem imaging rarely captures copathologic effects on brain atrophy due to a lack of validated biomarkers for non-Alzheimer's pathologies. We leveraged a dataset comprising antemortem MRI and postmortem histopathology to assess polypathologic associations with atrophy in a clinically heterogeneous sample of 125 human dementia patients (41 female, 84 male) with T1-weighted MRI ≤ 5 years before death and postmortem ordinal ratings of amyloid-[Formula: see text], tau, TDP-43, and [Formula: see text]-synuclein. Regional volumes were related to pathology using linear mixed-effects models; approximately 25% of data were held out for testing. We contrasted a polypathologic model comprising independent factors for each proteinopathy with two alternatives: a model that attributed atrophy entirely to the protein(s) associated with the patient's primary diagnosis and a protein-agnostic model based on the sum of ordinal scores for all pathology types. Model fits were evaluated using log-likelihood and correlations between observed and fitted volume scores. Additionally, we performed exploratory analyses relating atrophy to gliosis, neuronal loss, and angiopathy. The polypathologic model provided superior fits in the training and testing datasets. Tau, TDP-43, and [Formula: see text]-synuclein burden were inversely associated with regional volumes, but amyloid-[Formula: see text] was not. Gliosis and neuronal loss explained residual variance in and mediated the effects of tau, TDP-43, and [Formula: see text]-synuclein on atrophy. Regional brain atrophy reflects not only the primary molecular pathology but also co-occurring proteinopathies; inflammatory immune responses may independently contribute to degeneration. Our findings underscore the importance of antemortem biomarkers for detecting mixed pathology.

Neurologic Effects of SARS-CoV-2 Transmitted among Dogs.

SARS-CoV-2 induces illness and death in humans by causing systemic infections. Evidence suggests that SARS-CoV-2 can induce brain pathology in humans and other hosts. In this study, we used a canine transmission model to examine histopathologic changes in the brains of dogs infected with SARS-CoV-2. We observed substantial brain pathology in SARS-CoV-2-infected dogs, particularly involving blood-brain barrier damage resembling small vessel disease, including changes in tight junction proteins, reduced laminin levels, and decreased pericyte coverage. Furthermore, we detected phosphorylated tau, a marker of neurodegenerative disease, indicating a potential link between SARS-CoV-2-associated small vessel disease and neurodegeneration. Our findings of degenerative changes in the dog brain during SARS-CoV-2 infection emphasize the potential for transmission to other hosts and induction of similar signs and symptoms. The dynamic brain changes in dogs highlight that even asymptomatic individuals infected with SARS-CoV-2 may develop neuropathologic changes in the brain.

Lithium Cholesterol Sulfate: A Novel and Potential Drug for Treating Alzheimer's Disease and Autism Spectrum Disorder.

Recent studies have shown that lithium treatment can reduce symptoms of Alzheimer's disease (AD) and Autism Spectrum Disorder (ASD). However, the present lithium salts clinically available have serious short-term and long-term side effects which requires frequent monitoring of blood chemistry and plasma lithium levels so as to avoid toxicity. Consequently, there is a demand for a safer and more effective lithium formulation to treat these diseases. Hence, we firstly synthesized lithium cholesterol sulfate (LiCS) and compared its pharmacological effects with that of lithium chloride (LiCl) and sodium cholesterol sulfate (NaCS) on markers of neurodegenerative disease in cell cultures. LiCS was more potent than LiCl in increasing inhibitory GSK3β (Ser9) phosphorylation (pGSK3β) in both CHO and SH-SY5Y cells. These agents dose-dependently increased pGSK3β, starting at 10 µM for LiCS and 60µM for LiCl and maximally by approximately 100% at 60 µM for LiCS and 1.25 mM for LiCl, without altering total GSK3β levels. In HEK293/tau cells, LiCS reduced tau (Thr231) phosphorylation (ptau) starting at 10 µM and maximally by 63% at 40 µM without altering total tau levels, but ptau levels were not altered by LiCl at any dose between 60 µM and 1.25 mM. In BV2 cells, LiCS and LiCl decreased LPS-induced TNFα levels, starting at 20 µM for LiCS and 5 mM for LiCl, and maximally by approximately 30% at 80 µM for LiCS and 20 mM for LiCl. NaCS at any dose between 5 and 90 µM did not alter pGSK3β, ptau or LPS-induced TNFα. LiCS may become a new drug with good pharmacological potential for the treatment of neurodegenerative disorders such as AD and ASD by allowing lithium to more readily access intracellular pathological processes.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration.

Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification. We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition. CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration. These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation. Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Toolkit to Examine Lifelike Language (TELL): An app to capture speech and language markers of neurodegeneration.

Automated speech and language analysis (ASLA) is a promising approach for capturing early markers of neurodegenerative diseases. However, its potential remains underexploited in research and translational settings, partly due to the lack of a unified tool for data collection, encryption, processing, download, and visualization. Here we introduce the Toolkit to Examine Lifelike Language (TELL) v.1.0.0, a web-based app designed to bridge such a gap. First, we outline general aspects of its development. Second, we list the steps to access and use the app. Third, we specify its data collection protocol, including a linguistic profile survey and 11 audio recording tasks. Fourth, we describe the outputs the app generates for researchers (downloadable files) and for clinicians (real-time metrics). Fifth, we survey published findings obtained through its tasks and metrics. Sixth, we refer to TELL's current limitations and prospects for expansion. Overall, with its current and planned features, TELL aims to facilitate ASLA for research and clinical aims in the neurodegeneration arena. A demo version can be accessed here: https://demo.sci.tellapp.org/ .

SYVN1 attenuates ferroptosis and alleviates spinal cord ischemia–reperfusion injury in rats by regulating the HMGB1/NRF2/HO-1 axis

BackgroundThe ferroptosis of neurons is an important pathological mechanism of spinal cord ischemia reperfusion injury (SCIRI). Previous studies showed that synoviolin 1 (SYVN1) is a good prognostic marker of neurodegenerative diseases, but its mechanism is still unclear. This study aims to explore the role of SYVN1 in the ferroptosis of neurons and to clarify its internal mechanism. MethodsRat primary spinal cord neurons were treated with oxygen-glucose deprivation (OGD) for 1, 4 or 8 h, and then cell viability, ROS and MDA levels, glutathione peroxidase (GSH-Px) activity, and the expression of ferroptosis-related proteins GPX4, FTH1 and PTGS2 were detected. OGD/R-induced neurons were transfected with pcDNA-SYVN1 or si-HMGB1, and then cell functions were detected. Transmission electron microscope (TEM) was used to detect cell ferroptosis. The interplay between SYVN1 and high mobility group box 1 (HMGB1) was confirmed with Co-immunoprecipitation (Co-IP) assay. The stability of HMGB1 was measured by ubiquitination assay. Also, cells were treated with pcDNA-SYVN1 or together with ubiquitination inhibitor MG132, as well as treated with pcDNA-SYVN1 and pcDNA-HMGB1 or together with NRF2 activator dimethyl fumarate (DMF), and then Western blotting was used to detect the expression of HMGB1, nuclear NRF2 and HO-1 proteins. In addition, SD rats were occluded left common carotid artery and aortic arch to establish a SCIRI rat model. And rats were injected intrathecal with adenovirus-mediated SYVN1 overexpression vector (Ad-SYVN1, 2 μL, virus titer 5 × 1013 transduction unit [TU]/mL) to overexpress SYVN1. The motion function of rats was quantified using the Basso Rat Scale (BMS) for Locomotion. The ferroptosis and the number of neurons in the spinal cord tissue of rats were detected. ResultsSYVN1 overexpression inhibited ferroptosis of SCIRI rats and OGD/R-treated primary spinal cord neurons, and down-regulated the expression of HMGB1. In terms of mechanism, the binding of SYVN1 and HMGB1 promoted the ubiquitination and degradation of HMGB1, and negatively regulated the expression of HMGB1. Moreover, under OGD/R conditions, MG132 treatment or HMGB1 overexpression eliminated the inhibitory effect of SYVN1 overexpression on the ferroptosis of neurons and the activation of the NRF2/HO-1 pathway, and DMF treatment abolished the inhibition of HMGB1 overexpression on the NRF2/HO-1 pathway. Finally, in vivo experiments showed that SYVN1 overexpression could alleviate the spinal cord ischemia–reperfusion injury in rats by down-regulating HMGB1 and promoting the activation of the NRF2/HO-1 pathway. ConclusionSYVN1 regulates ferroptosis through the HMGB1/NRF2/HO-1 axis to prevent spinal cord ischemia–reperfusion injury.

Beta to theta power ratio in EEG periodic components as a potential biomarker in mild cognitive impairment and Alzheimer’s dementia

BackgroundAlzheimer’s dementia (AD) is associated with electroencephalography (EEG) abnormalities including in the power ratio of beta to theta frequencies. EEG studies in mild cognitive impairment (MCI) have been less consistent in identifying such abnormalities. One potential reason is not excluding the EEG aperiodic components, which are less associated with cognition than the periodic components. Here, we investigate whether aperiodic and periodic EEG components are disrupted differently in AD or MCI vs. healthy control (HC) individuals and whether a periodic based beta/theta ratio differentiates better MCI from AD and HC groups than a ratio based on the full spectrum.MethodsData were collected from 44 HC (mean age (SD) = 69.1 (5.3)), 114 MCI (mean age (SD) = 72.2 (7.5)), and 41 AD (mean age (SD) = 75.7 (6.5)) participants. Aperiodic and periodic components and full spectrum EEG were compared among the three groups. Receiver operating characteristic curves obtained via logistic regression classifications were used to distinguish the groups. Last, we explored the relationships between cognitive performance and the beta/theta ratios based on the full or periodic spectrum.ResultsAperiodic EEG components did not differ among the three groups. In contrast, AD participants showed an increase in full spectrum and periodic relative powers for delta, theta, and gamma and a decrease for beta when compared to HC or MCI participants. As predicted, MCI group differed from HC participants on the periodic based beta/theta ratio (Bonferroni corrected p-value = 0.036) measured over the occipital region. Classifiers based on beta/theta power ratio in EEG periodic components distinguished AD from HC and MCI participants, and outperformed classifiers based on beta/theta power ratio in full spectrum EEG. Beta/theta ratios were comparable in their association with cognition.ConclusionsIn contrast to a full spectrum EEG analysis, a periodic-based analysis shows that MCI individuals are different on beta/theta ratio when compared to healthy individuals. Focusing on periodic components in EEG studies with or without other biological markers of neurodegenerative diseases could result in more reliable findings to separate MCI from healthy aging, which would be valuable for designing preventative interventions.

Neuronal exosomes as a new signaling system

Every year more and more works are devoted to the study of neuronal exosomes. The potential of exosomes as diagnostic markers for neurodegenerative diseases has been significantly explored., and similar marker search patterns have been adopted for the study of psychiatric pathologies. The fundamentals of exosome biogenesis in different cell types have been elucidated., the physiological significance of exosomes is being actively studied., and many aspects of signaling with their participation are being elucidated. At the same time., data have been accumulated pointing to the role of exosomal signaling as an important element of interneuronal communication. Do we have enough evidence to call exosomes a new non-canonical neurotransmitter in the brain? This discussion work is devoted to answering this question., in which the author presents to the scientific community the concept of the possible role of brain exosomes as a signaling system.

Influence of mild cognitive impairment and body mass index on white matter integrity assessed by diffusion tensor imaging.

Mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease, is characterized by decreased memory and cognition, which are linked to degenerative changes in the brain. To assess whether white matter (WM) integrity is compromised in MCI, we collected diffusion-weighted images from 60 healthy older adults (OA) (69.16 ± 0.7) and 20 older adults with amnestic MCI (72.45 ± 1.9). WM integrity differences were examined using Tract-Based Spatial Statistics (TBSS). We hypothesized that those with MCI would have diminished WM integrity relative to OA. In a whole-brain comparison, those with MCI showed higher axial diffusivity in the splenium (SCC) and body of the corpus callosum (BCC), superior corona radiata (SCR), and the retrolenticular part of the internal capsule (RLIC) (p's < .05 TFCE-corrected). Additionally, significant between-group connectivity differences were observed using probabilistic tractography between the SCC, chosen from the TBSS results, and forceps major and minor (p-value's < .05). To further relate a physical health indicator to WM alterations, linear regression showed significant interactions between cognitive status and body mass index (BMI) on diffusivity outcome measures from probabilistic tractography (p-value-'s < .05). Additionally, we examined the association between relational memory, BMI, and WM integrity. WM integrity was positively associated with relational memory performance. These findings suggest that these regions may be more sensitive to early markers of neurodegenerative disease and health behaviors, suggesting that modifiable lifestyle factors may affect white matter integrity.

Revisiting the effects of exercise on cerebral neurovascular functions in rats using multimodal assessment techniques.

Physical activity in the form of aerobic exercise has many beneficial effects on brain function. Here, we aim to revisit the effects of exercise on brain morphology and neurovascular organization using a rat running model. Electrocorticography (ECoG) was integrated with laser speckle contrast imaging (LSCI) and applied to simultaneously detect CSD propagation and the corresponding neurovascular function. In addition, blood oxygenation level-dependent (BOLD) signal in fMRI was used to observe cerebral utilization of oxygen. Results showed significant decrease in somatosensory evoked potentials (SSEPs) and deceleration of CSD propagation in the EXE group. Western blot results in the EXE group showed significant increases in BDNF, GFAP, and NeuN levels and significant decreases in neurodegenerative disease markers. Decreases in SSEP and CSD parameters may result from exercise-induced increases in cerebrovascular system function and increases in the stability and buffering of extracellular ion concentrations and cortical excitability.

Functional connectivity and mild behavioral impairment in dementia-free elderly.

Mild behavioral impairment (MBI) is a syndrome that uses later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a group at high risk for incident dementia. MBI is associated with neurodegenerative disease markers in advance of syndromic dementia. Functional connectivity (FC) correlates of MBI are understudied and could provide further insights into mechanisms early in the disease course. We used resting-state functional magnetic resonance imaging (rs-fMRI) to test the hypothesis that FC within the default mode network (DMN) and salience network (SN) of persons with MBI (MBI+) is reduced, relative to those without (MBI-). From two harmonized dementia-free cohort studies, using a score of ≥6 on the MBI Checklist to define MBI status, 32 MBI+ and 63 MBI- individuals were identified (mean age: 71.7 years; 54.7% female). Seed-based connectivity analysis was implemented in each MBI group using the CONN fMRI toolbox (v20.b), with the posterior cingulate cortex (PCC) as the seed region within the DMN and anterior cingulate cortex (ACC) as the seed within the SN. The average time series from the PCC and ACC were used to determine FC with other regions within the DMN (medial prefrontal cortex, lateral inferior parietal cortex) and SN (anterior insula, supramarginal gyrus, rostral prefrontal cortex), respectively. Age, sex, years of education, and Montreal Cognitive Assessment scores were included as model covariates. The false discovery rate approach was used to correct for multiple comparisons, with a p-value of .05 considered significant. For the DMN, MBI+ individuals exhibited reduced FC between the PCC and the medial prefrontal cortex, compared to MBI-. For the SN, MBI+ individuals exhibited reduced FC between the ACC and left anterior insula. MBI in dementia-free older adults is associated with reduced FC in networks known to be disrupted in dementia. Our results complement the evidence linking MBI with Alzheimer's disease biomarkers. Resting-state functional magnetic resonance imaging was completed in 95 dementia-free persons from FAVR and COMPASS-ND studies.Participants were stratified by informant-rated Mild Behavioral Impairment Checklist (MBI-C) score, ≥6 for MBI+.MBI+ participants showed reduced functional connectivity (FC) within the default mode network and salience network.These FC changes are consistent with those seen in early-stage Alzheimer's disease.MBI may help identify persons with early-stage neurodegenerative disease.

Late-life Onset Psychosis-like Symptoms Assessed in the Mild Behavioral Impairment Framework are Associated Impaired Performance on the Stroop Task

Late-life onset psychosis and milder delusion-like ideation are known risk factors for cognitive decline and dementia. The Mild Behavioural Impairment (MBI) framework was developed to capture specific psychotic-like symptoms relevant to dementia prognosis in older adults. This study aims to investigate the cognitive deficits associated with MBI-psychosis and their implications for understanding the underlying mechanisms and potential treatment targets. The study recruited participants between November 2021 and July 2022 from the PROTECT study registry. Participants completed the Cambridge Gambling Task, Stroop, Trail Making, Paired Associates Learning, Verbal Reasoning, Digit Span and Self-Ordered Search. Psychotic symptom status was assessed using the Mild Behavioural Impairment Checklist (MBI-C), with participants categorized as MBI-psychosis if they or their study partner reported any psychotic symptoms. Out of 2,111 eligible participants invited, 417 consented to participate. There were no significant differences in age, sex, education level, or mental health history between the MBI-psychosis and No Psychosis groups. Participants with MBI-psychosis exhibited significantly worse performance on the Stroop task (p=0.0002, Cohen’s d=0.37) compared to those without psychosis. There was also some evidence of impairment in verbal reasoning, though it did not reach significance after Bonferroni correction. No significant differences were found on other cognitive measures. This cross-sectional study provides insight into the cognitive deficits associated with MBI-psychosis. The finding of impaired Stroop task performance in individuals with MBI-psychosis is noteworthy, as this deficit is commonly observed in earlier-life major psychotic disorders. Further research is needed to explore the neural underpinnings of these deficits and to determine whether they represent early markers of neurodegenerative disease or other factors.

Disease Delineation for Multiple Sclerosis, Friedreich Ataxia, and Healthy Controls Using Supervised Machine Learning on Speech Acoustics.

Neurodegenerative disease often affects speech. Speech acoustics can be used as objective clinical markers of pathology. Previous investigations of pathological speech have primarily compared controls with one specific condition and excluded comorbidities. We broaden the utility of speech markers by examining how multiple acoustic features can delineate diseases. We used supervised machine learning with gradient boosting (CatBoost) to delineate healthy speech from speech of people with multiple sclerosis or Friedreich ataxia. Participants performed a diadochokinetic task where they repeated alternating syllables. We subjected 74 spectral and temporal prosodic features from the speech recordings to machine learning. Results showed that Friedreich ataxia, multiple sclerosis and healthy controls were all identified with high accuracy (over 82%). Twenty-one acoustic features were strong markers of neurodegenerative diseases, falling under the categories of spectral qualia, spectral power, and speech rate. We demonstrated that speech markers can delineate neurodegenerative diseases and distinguish healthy speech from pathological speech with high accuracy. Findings emphasize the importance of examining speech outcomes when assessing indicators of neurodegenerative disease. We propose large-scale initiatives to broaden the scope for differentiating other neurological diseases and affective disorders.

A novel episodic memory test optimized for smart phone high‐frequency assessments

AbstractBackgroundDecline in episodic memory is a strong marker of neurodegenerative diseases, making it an important target for cognitive assessment. We present a new remote, repeatable, and brief assessment of episodic memory and visual short‐term memory (VSTM) for smart phone deployment. We evaluated this task for sensitivity to age and established cognitive measures of memory and attention.MethodThe task consists of a learning phase where participants see a sequence of items, then are asked to replicate the item order and location by dragging and dropping these items on‐screen. A recall phase follows a minimum 12‐hour delay, with replication of the earlier response. Each session takes less than 2 minutes. The first phase supplies metrics of spatial and order precision VSTM, with the second phase characterising long‐term episodic memory.Experiment 1 (n = 133) compares the task with CANTAB assessments of visuospatial memory. In Experiment 2 (n = 80) the novel task was repeated twice daily for a week, alongside momentary mood ratings, and a more comprehensive battery of CANTAB tasks at baseline.In Experiment 1, multiple regression and dominance analyses explore the independent and shared variance of measures in explaining age. In Experiment 2, clustering and multivariate autoregressive models outline differences in timeseries relationships between mood and memory, and age.ResultExperiment 1 revealed that CANTAB measures and novel spatial and order metrics were correlated with age (r = .20 to r = .37, adjusted P = &lt;.05). Multiple regression showed models with CANTAB Paired Associate Learning (PAL) score, and delayed novel spatial metrics were significantly predictive of age (t = ‐4.08, 3.17, p &lt;.005). The dominance analysis revealed novel immediate precision overlapped with existing measures in predicting Age, while delayed precision had more unique variance (4.6% vs 0.62% unique sample variance explained in Age, accounting for PAL).Experiment 2 characterised variance in individual learning curves over time and differing autoregressive processes associated with age and CANTAB measures.ConclusionWe present a brief novel episodic memory task that can be deployed remotely, with delayed spatial precision significantly predictive of healthy Ageing. Additionally, we show this test’s suitability as a repeated assessment, compatible with high‐frequency study designs in older populations.