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Acta Neuropathologica Communications Jun 2024The relationship between amyloidosis and vasculature in cognitive impairment and Alzheimer's disease (AD) pathogenesis is increasingly acknowledged. We conducted a...
The relationship between amyloidosis and vasculature in cognitive impairment and Alzheimer's disease (AD) pathogenesis is increasingly acknowledged. We conducted a quantitative and topographic assessment of retinal perivascular amyloid plaque (AP) distribution in individuals with both normal and impaired cognition. Using a retrospective dataset of scanning laser ophthalmoscopy fluorescence images from twenty-eight subjects with varying cognitive states, we developed a novel image processing method to examine retinal peri-arteriolar and peri-venular curcumin-positive AP burden. We further correlated retinal perivascular amyloidosis with neuroimaging measures and neurocognitive scores. Our study unveiled that peri-arteriolar AP counts surpassed peri-venular counts throughout the entire cohort (P < 0.0001), irrespective of the primary, secondary, or tertiary vascular branch location, with a notable increase among cognitively impaired individuals. Moreover, secondary branch peri-venular AP count was elevated in the cognitively impaired (P < 0.01). Significantly, peri-venular AP count, particularly in secondary and tertiary venules, exhibited a strong correlation with clinical dementia rating, Montreal cognitive assessment score, hippocampal volume, and white matter hyperintensity count. In conclusion, our exploratory analysis detected greater peri-arteriolar versus peri-venular amyloidosis and a marked elevation of amyloid deposition in secondary branch peri-venular regions among cognitively impaired subjects. These findings underscore the potential feasibility of retinal perivascular amyloid imaging in predicting cognitive decline and AD progression. Larger longitudinal studies encompassing diverse populations and AD-biomarker confirmation are warranted to delineate the temporal-spatial dynamics of retinal perivascular amyloid deposition in cognitive impairment and the AD continuum.
Topics: Humans; Male; Female; Aged; Cognitive Dysfunction; Hippocampus; Atrophy; Amyloidosis; Aged, 80 and over; Retrospective Studies; Middle Aged; Plaque, Amyloid; Retinal Diseases; Retinal Vessels; Ophthalmoscopy
PubMed: 38943220
DOI: 10.1186/s40478-024-01810-2 -
Alzheimer's Research & Therapy Jun 2024Amyloid-β (Aβ) and tau are brain hallmarks of Alzheimer's disease (AD), also present in blood as soluble biomarkers or encapsulated in extracellular vesicles (EVs).... (Comparative Study)
Comparative Study
BACKGROUND
Amyloid-β (Aβ) and tau are brain hallmarks of Alzheimer's disease (AD), also present in blood as soluble biomarkers or encapsulated in extracellular vesicles (EVs). Our goal was to assess how soluble plasma biomarkers of AD pathology correlate with the number and content of EVs.
METHODS
Single-molecule enzyme-linked assays were used to quantify Aβ42/40 and tau in plasma samples and neurally-derived EVs (NDEVs) from a cohort of APOE ε4- (n = 168) and APOE ε4+ (n = 68) cognitively normal individuals and AD patients (n = 55). The ratio of CD56 (Neuronal cell-adhesion molecule) to CD81 signal measured by ELISA-DELFIA was used for the relative quantification of NDEVs in plasma samples.
RESULTS
The soluble plasma Aβ42/40 ratio is decreased in AD patients compared to cognitively normal individuals. The amount and content (Aβ40, Aβ42, tau) of plasma NDEVs were similar between groups. Plasma NDEVs quantity remain consistent with aging and between AD and CN individuals. However, the quantity of soluble biomarkers was negatively correlated to NDEVs number in cognitively normal individuals, while in AD patients, this correlation is lost, suggesting a shift in the mechanism underpinning the production and the release of these biomarkers in pathological conditions.
CONCLUSION
Soluble plasma Aβ42/40 ratio is the most robust biomarker to discriminate between AD patients and CN individuals, as it normalizes for the number of NDEVs. Analysis of NDEVs and their content pointed toward peculiar mechanisms of Aβ release in AD. Further research on independent cohorts can confirm our findings and assess whether plasma Aβ and tau need correction by NDEVs for better AD risk identification in CN populations.
Topics: Humans; Alzheimer Disease; Extracellular Vesicles; Biomarkers; Female; Male; Amyloid beta-Peptides; Aged; tau Proteins; Peptide Fragments; Aged, 80 and over; Middle Aged; Cohort Studies; Apolipoprotein E4
PubMed: 38943196
DOI: 10.1186/s13195-024-01508-6 -
Acta Neuropathologica Communications Jun 2024
PubMed: 38943188
DOI: 10.1186/s40478-024-01819-7 -
Acta Neuropathologica Communications Jun 2024We quantified and determined for the first time the distribution pattern of the neuropeptide NPFF in the human cerebral cortex and subjacent white matter. To do so, we...
We quantified and determined for the first time the distribution pattern of the neuropeptide NPFF in the human cerebral cortex and subjacent white matter. To do so, we studied n = 9 cases without neurological disorders and n = 22 cases with neurodegenerative diseases, including sporadic amyotrophic lateral sclerosis (ALS, n = 8), Alzheimer's disease (AD, n = 8), Pick's disease (PiD, n = 3), and schizophrenia (n = 3). NPFF-immunopositive cells were located chiefly, but not exclusively, in the superficial white matter and constituted there a subpopulation of white matter interstitial cells (WMIC): Pyramidal-like and multipolar somata predominated in the gyral crowns, whereas bipolar and ovoid somata predominated in the cortex surrounding the sulci. Their sparsely ramified axons were unmyelinated and exhibited NPFF-positive bead-like varicosities. We found significantly fewer NPFF-immunopositive cells in the gray matter of the frontal, cingulate, and superior temporal gyri of both sporadic ALS and late-stage AD patients than in controls, and significantly fewer NPFF-positive cells in the subjacent as well as deep white matter of the frontal gyrus of these patients compared to controls. Notably, the number of NPFF-positive cells was also significantly lower in the hippocampal formation in AD compared to controls. In PiD, NPFF-positive cells were present in significantly lower numbers in the gray and white matter of the cingulate and frontal gyrii in comparison to controls. In schizophrenic patients, lower wNPFF cell counts in the neocortex were significant and global (cingulate, frontal, superior temporal gyrus, medial, and inferior gyri). The precise functions of NPFF-positive cells and their relationship to the superficial corticocortical white matter U-fibers are currently unknown. Here, NPFF immunohistochemistry and expression characterize a previously unrecognized population of cells in the human brain, thereby providing a new entry-point for investigating their physiological and pathophysiological roles.
Topics: Humans; White Matter; Male; Schizophrenia; Female; Cerebral Cortex; Aged; Middle Aged; Neurodegenerative Diseases; Aged, 80 and over; Oligopeptides; Adult; Neurons
PubMed: 38943180
DOI: 10.1186/s40478-024-01792-1 -
BMC Geriatrics Jun 2024Critical wandering occurs when an individual living with dementia leaves a location and is unaware of place or time. Critical wandering incidents are expected to...
BACKGROUND
Critical wandering occurs when an individual living with dementia leaves a location and is unaware of place or time. Critical wandering incidents are expected to increase with the growing prevalence of persons living with dementia worldwide. We investigated the association between demographic, psychopathological, and environmental factors and a history of critical wandering among Medic-Alert subscribers, both with and without dementia.
METHODS
Our retrospective study included data of 25,785 Canadian Medic-Alert subscribers who were aged 40 years or older. We used multivariable logistic regression analysis to examine the associations between a history of critical wandering and dementia status as psychopathological independent variable, controlled by demographic (age, ethnic background, sex at birth, Canadian languages spoken) and environmental (living arrangement, population density) factors.
RESULTS
The overall study sample comprised of mainly older adults (77.4%). Medic-Alert subscribers who were older, male sex at birth, living with dementia, of a minority ethnic group and who did not have proficiency in an official Canadian language had a higher likelihood of a history of critical wandering. Residing in an urban environment, in an institution or with a family member, were environmental factors associated with a higher likelihood of a history of critical wandering.
CONCLUSIONS
People living with dementia experience a higher likelihood of a history of critical wandering compared to those without dementia. Medic-Alert and similar organizations can develop algorithms based on the associated factors that can be used to flag risks of critical wandering. This can inform preventative strategies at the individual and community levels.
Topics: Humans; Male; Female; Retrospective Studies; Aged; Dementia; Aged, 80 and over; Middle Aged; Wandering Behavior; Adult; Risk Factors; Canada
PubMed: 38943089
DOI: 10.1186/s12877-024-05162-3 -
Scientific Reports Jun 2024While there are currently over 40 replicated genes with mapped risk alleles for Late Onset Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still...
While there are currently over 40 replicated genes with mapped risk alleles for Late Onset Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest driver of risk, with odds ratios for neuropathologically confirmed E44 carriers exceeding 30 (95% confidence interval 16.59-58.75). We sought to address whether the APOE E4 haplotype modifies expression globally through networks of expression to increase LOAD risk. We have used the Human Brainome data to build expression networks comparing APOE E4 carriers to non-carriers using scalable mixed-datatypes Bayesian network (BN) modeling. We have found that VGF had the greatest explanatory weight. High expression of VGF is a protective signal, even on the background of APOE E4 alleles. LOAD risk signals, considering an APOE background, include high levels of SPECC1L, HLA-DRA and RANBP3L. Our findings nominate several new transcripts, taking a combined approach to network building including known LOAD risk loci.
Topics: Humans; Alzheimer Disease; Genetic Predisposition to Disease; Apolipoprotein E4; HLA-DR alpha-Chains; Female; Male; Aged; Adaptor Proteins, Signal Transducing; Alleles; Haplotypes; Bayes Theorem; Risk Factors; Nuclear Proteins; Aged, 80 and over
PubMed: 38942763
DOI: 10.1038/s41598-024-65010-7 -
Radiography (London, England : 1995) Jun 2024Alzheimer's disease (AD), the most common cause of dementia, presents a global health crisis with its prevalence expected to triple worldwide by 2050, emphasizing the...
INTRODUCTION
Alzheimer's disease (AD), the most common cause of dementia, presents a global health crisis with its prevalence expected to triple worldwide by 2050, emphasizing the urgent need for early diagnosis to delay progression and improve patient quality of life. Our project aims to detect AD in its early phase by identifying subtle neuroanatomical changes with Radiomics features, offering a more accurate diagnosis.
METHODS
The AssemblyNet segmentation model was used to analyze brain changes by employing anonymized T1 MRI scans from 416 patients. For each segmented label we extracted Radiomic features. After preprocessing of Radiomic features we trained four models, Gradient Booster, Random Forest, Support Vector Classifier, and XGBoost, in a 70%/20%/10% train, validation and test split. All models were hyperparameter tuned with GridSearch, Cross validation and evaluated with accuracy on the test data.
RESULTS
208 T1-weighted MRI scans were segmented, with 132 segmentation labels per patient, 1130 Radiomic features per segmentation, totalling in over 31 million features. For all four models we achieved accuracies between 0.71 and 0.86, and the machine learning model with highest accuracy were XGBoost, achieving an accuracy at 0.86 on the segmentation of the left inferior lateral ventricle.
CONCLUSION
Our study's use of segmentation on T1-weighted MRI scans resulted promising accuracies for early AD diagnosis with the machine learning model XGBoost, peaking at 0.86 accuracy. Future research should aim to expand datasets and refine methodologies for broader applicability.
IMPLICATION FOR PRACTICE
Implementing Radiomics for early AD detection using T1-weighted MRI scans could substantially improve diagnostic accuracy, enabling earlier interventions that may delay disease progression and improve outcomes, thereby requiring radiographers to adopt more advanced imaging techniques and analysis tools, as well as additional training to effectively interpret complex Radiomic data.
PubMed: 38942647
DOI: 10.1016/j.radi.2024.06.016 -
Aging Jun 2024Down Syndrome (DS) is a common genetic disorder characterized by an extra copy of chromosome 21, leading to dysregulation of various metabolic pathways. Oxidative stress...
Down Syndrome (DS) is a common genetic disorder characterized by an extra copy of chromosome 21, leading to dysregulation of various metabolic pathways. Oxidative stress in DS is associated with neurodevelopmental defects, neuronal dysfunction, and a dementia onset resembling Alzheimer's disease. Additionally, chronic oxidative stress contributes to cardiovascular diseases and certain cancers prevalent in DS individuals. This study investigates the impact of ageing on oxidative stress and liver fibrosis using a DS murine model (Ts2Cje mice). Our results show that DS mice show increased liver oxidative stress and impaired antioxidant defenses, as evidenced by reduced glutathione levels and increased lipid peroxidation. Therefore, DS liver exhibits an altered inflammatory response and mitochondrial fitness as we showed by assaying the expression of HMOX1, CLPP, and the heat shock proteins Hsp90 and Hsp60. DS liver also displays dysregulated lipid metabolism, indicated by altered expression of PPARα, PPARγ, FATP5, and CTP2. Consistently, these changes might contribute to non-alcoholic fatty liver disease development, a condition characterized by liver fat accumulation. Consistently, histological analysis of DS liver reveals increased fibrosis and steatosis, as showed by Col1a1 increased expression, indicative of potential progression to liver cirrhosis. Therefore, our findings suggest an increased risk of liver pathologies in DS individuals, particularly when combined with the higher prevalence of obesity and metabolic dysfunctions in DS patients. These results shed a light on the liver's role in DS-associated pathologies and suggest potential therapeutic strategies targeting oxidative stress and lipid metabolism to prevent or mitigate liver-related complications in DS individuals.
PubMed: 38942607
DOI: 10.18632/aging.205970 -
Brain Research Jun 2024Oxidative stress plays a pivotal role in various neurological disorders, encompassing both neurodegenerative diseases such as Alzheimer's and Parkinson's, and mood...
Oxidative stress plays a pivotal role in various neurological disorders, encompassing both neurodegenerative diseases such as Alzheimer's and Parkinson's, and mood disorders like depression. The balance between the generation of reactive oxygen species (ROS) and the cell's antioxidant defenses, when disrupted, can lead to neuronal damage and neurologic dysfunction. In this study, we focused on the pathogenic role of oxidative stress in various neurologic disease models in vitro and investigated the neuroprotective capabilities of some novel bicyclic γ-butyrolactone compounds, with particular emphasis on the compound designated as 'bd'. Our investigation leveraged the HT22 and SH-SY5Y cells to model oxidative stress induced by HO or corticosterone (CORT), common triggers of neuronal damage in neurodegenerative and mood disorders. We discovered that compound bd robustly reduced ROS production and suppressed neuronal apoptosis, suggesting its potential in treating a wider array of neurological conditions influenced by oxidative stress. In conclusion, our research underscores the importance of addressing oxidative stress in the context of diverse neurological disorders. The identification of compound bd as a neuroprotective agent with potential efficacy against ROS-induced apoptosis in neural cells opens new horizons for therapeutic development, offering hope for patients suffering from neurodegenerative diseases, depression, and other stress-related neurological conditions.
PubMed: 38942352
DOI: 10.1016/j.brainres.2024.149099 -
NeuroImage Jun 2024The prediction of Alzheimer's disease (AD) progression from its early stages is a research priority. In this context, the use of Artificial Intelligence (AI) in AD has...
BACKGROUND
The prediction of Alzheimer's disease (AD) progression from its early stages is a research priority. In this context, the use of Artificial Intelligence (AI) in AD has experienced a notable surge in recent years. However, existing investigations predominantly concentrate on distinguishing clinical phenotypes through cross-sectional approaches. This study aims to investigate the potential of modeling additional dimensions of the disease, such as variations in brain metabolism assessed via [F]-fluorodeoxyglucose positron emission tomography (FDG-PET), and utilize this information to identify patients with mild cognitive impairment (MCI) who will progress to dementia (pMCI).
METHODS
We analyzed data from 1,617 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had undergone at least one FDG-PET scan. We identified the brain regions with the most significant hypometabolism in AD and used Deep Learning (DL) models to predict future changes in brain metabolism. The best-performing model was then adapted under a multi-task learning framework to identify pMCI individuals. Finally, this model underwent further analysis using eXplainable AI (XAI) techniques.
RESULTS
Our results confirm a strong association between hypometabolism, disease progression, and cognitive decline. Furthermore, we demonstrated that integrating data on changes in brain metabolism during training enhanced the models' ability to detect pMCI individuals (sensitivity=88.4%, specificity=86.9%). Lastly, the application of XAI techniques enabled us to delve into the brain regions with the most significant impact on model predictions, highlighting the importance of the hippocampus, cingulate cortex, and some subcortical structures.
CONCLUSION
This study introduces a novel dimension to predictive modeling in AD, emphasizing the importance of projecting variations in brain metabolism under a multi-task learning paradigm.
PubMed: 38942101
DOI: 10.1016/j.neuroimage.2024.120695