non-AD Cases Research Articles

Non-Alzheimer's amnestic mild cognitive impairment with medial temporal hypometabolism.

The increasing use of Alzheimer's disease (AD) biomarkers has led to the recognition of a subgroup of non-AD amnestic mild cognitive impairment (aMCI) patients who have medial temporal hypometabolism on fluorodeoxyglucose-positron emission tomography (FDG-PET). In this academic memory-clinic-based consecutive series, 16 non-AD aMCI patients and 28 AD controls matched for sex, age, and baseline Mini-Mental State Examination (MMSE) were followed for a median duration of 4.5 years. Our primary outcome was the MMSE decline rate over the subsequent years. We also determined the final diagnosis over time. FDG-PET showed more pronounced medial temporal hypometabolism in non-AD cases and more inferior parietal lobule hypometabolism in AD controls. MMSE decline was slower in non-AD (β=-0.51) than in AD (β=-2.00) patients. Five non-AD cases developed frontotemporal dementia years after symptom onset, and one developed dementia with Lewy bodies. Non-AD aMCI patients with medial temporal hypometabolism show slower cognitive decline. Non-AD aMCI with medial temporal hypometabolism shows slower cognitive decline than AD.FDG-PET revealed distinct metabolic patterns between non-AD aMCI and AD patients.Approximately one-third of non-AD aMCI cases developed frontotemporal dementia.Comprehensive diagnostic biomarkers are crucial for non-AD aMCI characterization.

Lower Prevalence of Asymptomatic Alzheimer's Disease Among Healthy African Americans.

Alzheimer's disease (AD) is believed to be more common in African Americans (AA), but biomarker studies in AA populations are limited. This report represents the largest study to date examining cerebrospinal fluid AD biomarkers in AA individuals. We analyzed 3,006 cerebrospinal fluid samples from controls, AD cases, and non-AD cases, including 495 (16.5%) self-identified black/AA and 2,456 (81.7%) white/European individuals using cutoffs derived from the Alzheimer's Disease Neuroimaging Initiative, and using a data-driven multivariate Gaussian mixture of regressions. Distinct effects of race were found in different groups. Total Tauand phospho181-Tau were lower among AA individuals in all groups (p < 0.0001), and Aβ42 was markedly lower in AA controls compared with white controls (p < 0.0001). Gaussian mixture of regressions modeling of cerebrospinal fluid distributions incorporating adjustments for covariates revealed coefficient estimates for AA race comparable with 2-decade change in age. Using Alzheimer's Disease Neuroimaging Initiative cutoffs, fewer AA controls were classified as biomarker-positive asymptomatic AD (8.0% vs 13.4%). After adjusting for covariates, our Gaussian mixture of regressions model reduced this difference, but continued to predict lower prevalence of asymptomatic AD among AA controls (9.3% vs 13.5%). Although the risk of dementia is higher, data-driven modeling indicates lower frequency of asymptomatic AD in AA controls, suggesting that dementia among AA populations may not be driven by higher rates of AD. ANN NEUROL 2024;96:463-475.

An effectual recommendation model using hybrid learning models for early detection of Alzheimer’s disease

Alzheimer’s disease (AD) is a neurodegenerative disorder that affects millions of individuals worldwide, causing progressive cognitive decline. Early prediction and diagnosis the AD accurately is crucial for effective intervention and treatment. In this study, we propose a comprehensive framework for AD prediction using various techniques, including preprocessing and denoising with Multilayer Perceptron (MLP) and Ant Colony Optimization (ACO), segmentation using U-Net, and classification with Spatial Pyramid Pooling Network (SPPNet). Furthermore, we employ Convolutional Neural Network (CNN) with SPPNet for training and develop a chatbot for recommendation based on MRI data input. The preprocessing and denoising techniques play a vital role in enhancing the quality of the input data. MLP is utilized for preprocessing, where it effectively handles feature extraction and noise reduction. ACO is employed for denoising, optimizing the data to improve the signal-to-noise ratio, and enhancing the overall performance of subsequent stages. For accurate segmentation of brain regions, we employ the U-Net architecture, which has shown remarkable success in medical image segmentation tasks. U-Net effectively identifies the regions of interest, aiding in subsequent classification stages. The classification phase utilizes SPPNet, a deep learning model known for its ability to capture spatial information at multiple scales. SPPNet extracts features from segmented brain regions, enabling robust classification of AD and non-AD cases. To enhance the training process, we employ CNN with SPPNet, leveraging the power of convolutional layers to capture intricate patterns and improve predictive accuracy. The CNN-SPPNet model is trained on a large dataset of MRI scans, enabling it to learn complex representations and make accurate predictions. Hence the proposed work can be integrated with a chatbot that takes MRI data as input and provides recommendations based on the predicted AD probability. Experimental evaluation shows that the combination of preprocessing, denoising, segmentation, and classification offers a comprehensive solution for accurate and efficient AD diagnosis and management.

Genome-wide association study and polygenic risk scores of retinal thickness across the cognitive continuum: data from the NORFACE cohort

BackgroundSeveral studies have reported a relationship between retinal thickness and dementia. Therefore, optical coherence tomography (OCT) has been proposed as an early diagnosis method for Alzheimer’s disease (AD). In this study, we performed a genome-wide association study (GWAS) aimed at identifying genes associated with retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GCIPL) thickness assessed by OCT and exploring the relationships between the spectrum of cognitive decline (including AD and non-AD cases) and retinal thickness.MethodsRNFL and GCIPL thickness at the macula were determined using two different OCT devices (Triton and Maestro). These determinations were tested for association with common single nucleotide polymorphism (SNPs) using adjusted linear regression models and combined using meta-analysis methods. Polygenic risk scores (PRSs) for retinal thickness and AD were generated.ResultsSeveral genetic loci affecting retinal thickness were identified across the genome in accordance with previous reports. The genetic overlap between retinal thickness and dementia, however, was weak and limited to the GCIPL layer; only those observable with all-type dementia cases were considered.ConclusionsOur study does not support the existence of a genetic link between dementia and retinal thickness.

Advancing spinal cord injury care through non-invasive autonomic dysreflexia detection with AI

This paper presents an AI-powered solution for detecting and monitoring Autonomic Dysreflexia (AD) in individuals with spinal cord injuries. Current AD detection methods are limited, lacking non-invasive monitoring systems. We propose a model that combines skin nerve activity (SKNA) signals with a deep neural network (DNN) architecture to overcome this limitation. The DNN is trained on a meticulously curated dataset obtained through controlled colorectal distension, inducing AD events in rats with spinal cord surgery above the T6 level. The proposed system achieves an impressive average classification accuracy of 93.9% ± 2.5%, ensuring accurate AD identification with high precision (95.2% ± 2.1%). It demonstrates a balanced performance with an average F1 score of 94.4% ± 1.8%, indicating a harmonious balance between precision and recall. Additionally, the system exhibits a low average false-negative rate of 4.8% ± 1.6%, minimizing the misclassification of non-AD cases. The robustness and generalizability of the system are validated on unseen data, maintaining high accuracy, F1 score, and a low false-negative rate. This AI-powered solution represents a significant advancement in non-invasive, real-time AD monitoring, with the potential to improve patient outcomes and enhance AD management in individuals with spinal cord injuries. This research contributes a promising solution to the critical healthcare challenge of AD detection and monitoring.

CSF p-tau205: a biomarker of tau pathology in Alzheimer’s disease

Post-mortem staging of Alzheimer’s disease (AD) neurofibrillary pathology is commonly performed by immunohistochemistry using AT8 antibody for phosphorylated tau (p-tau) at positions 202/205. Thus, quantification of p-tau205 and p-tau202 in cerebrospinal fluid (CSF) should be more reflective of neurofibrillary tangles in AD than other p-tau epitopes. We developed two novel Simoa immunoassays for CSF p-tau205 and p-tau202 and measured these phosphorylations in three independent cohorts encompassing the AD continuum, non-AD cases and cognitively unimpaired participants: a discovery cohort (n = 47), an unselected clinical cohort (n = 212) and a research cohort well-characterized by fluid and imaging biomarkers (n = 262). CSF p-tau205 increased progressively across the AD continuum, while CSF p-tau202 was increased only in AD and amyloid (Aβ) and tau pathology positive (A+T+) cases (P < 0.01). In A+ cases, CSF p-tau205 and p-tau202 showed stronger associations with tau-PET (rSp205 = 0.67, rSp202 = 0.45) than Aβ-PET (rSp205 = 0.40, rSp202 = 0.09). CSF p-tau205 increased gradually across tau-PET Braak stages (P < 0.01), whereas p-tau202 only increased in Braak V–VI (P < 0.0001). Both showed stronger regional associations with tau-PET than with Aβ-PET, and CSF p-tau205 was significantly associated with Braak V–VI tau-PET regions. When assessing the contribution of Aβ and tau pathologies (indexed by PET) to CSF p-tau205 and p-tau202 variance, tau pathology was found to be the most prominent contributor in both cases (CSF p-tau205: R2 = 69.7%; CSF p-tau202: R2 = 85.6%) Both biomarkers associated with brain atrophy measurements globally (rSp205 = − 0.36, rSp202 = − 0.33) and regionally, and correlated with cognition (rSp205 = − 0.38/− 0.40, rSp202 = − 0.20/− 0.29). In conclusion, we report the first high-throughput CSF p-tau205 immunoassay for the in vivo quantification of tau pathology in AD, and a potentially cost-effective alternative to tau-PET in clinical settings and clinical trials.

Early intervention and adding effective doses of EGb761 like Ginkgo extract slow down dementia progression: insights to the neurovascular unit.

Dementia is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and functional deterioration. Pharmacological interventions play a crucial role in managing dementia symptoms and potentially slowing down disease progression. This study aimed to investigate the impact of pharmacological interventions, including acetylcholinesterase inhibitors (AChEIs), memantine, and Gingko extract, on the progression of dementia, with a specific focus on mild cognitive impairment (MCI), Alzheimer's disease (AD), and non-Alzheimer dementias. A total of 547 participants out of 3,547 cases in a specific dataset followed by the same author, including healthy controls, individuals with MCI, AD, and non-Alzheimer dementias, were included in this study. The follow-up duration was up to 211 months, allowing for a minimum 3 visits comprehensive assessment of disease progression. The treatment approaches included AChEIs, memantine, and combination therapy, with variations in the starting time for these treatments based on the dementia type. The use of AChEIs and memantine showed efficacy in improving cognitive function and overall function in individuals with MCI, AD, and non-AD dementias. Combination therapy EGb761 like Gingko extract with AChEIs and/or Memantine demonstrated a slower progression compared to AChEIs alone in individuals with prodromal dementia (MCI) and AD. The starting time for memantine and combination therapy was earlier in non-AD dementia cases compared to AD dementia cases and prodromal dementia. Pharmacological interventions, particularly the use of AChEIs and memantine, can have a positive impact on cognitive function and overall function in individuals with dementia. The combination of AChEIs with EGb761 like Gingko extract may provide additional benefits in slowing down disease progression in AD cases. Early recognition and accurate classification of MCI subtypes are crucial, and the use of EGb761 like Gingko extract is recommended for symptomatic treatment. Future personalized risk predictions based on biomarker constellations may further enhance the multi-target treatment approaches of MCI and different dementia types.

Factors affecting progression of non-Alzheimer dementia: a retrospective analysis with long-term follow-up.

Non-Alzheimer's dementias, including vascular dementia (VaD), frontotemporal dementia (FTD), Lewy body dementia (LBD), and Parkinson's disease dementia (PDD), possess unique characteristics and prognostic factors that remain poorly understood. This study aims to investigate the temporal course of these subtypes and identify the impact of functional, neuropsychiatric, and comorbid medical conditions on prognosis. Additionally, the relationship between hippocampal atrophy, white matter intensities, and disease progression will be examined, along with the identification of key covariates influencing slow or fast progression in non-Alzheimer's dementias. A total of 196 patients with non-Alzheimer's dementias who underwent at least three comprehensive evaluations were included, with proportions of VaD, FTD, LBD, and PDD being 50, 19.39, 19.90, and 10.71%, respectively. Patient demographics, comorbidities, neuropsychiatric and neuroimaging parameters, and global evaluation were analyzed using appropriate statistical methods. The study followed patients for a mean duration of 62.57 ± 33.45 months (ranging from 11 to 198 months). The results from three different visits for each non-AD dementia case demonstrated significant differences in various measures across visits, including functional capacity (BDLAS), cognition (MMSE), and other neuropsychological tests. Notably, certain genotypes and hippocampal atrophy grades were more prevalent in specific subtypes. The results indicate that Fazekas grading and hippocampal atrophy were significant predictors of disease progression, while epilepsy, extrapyramidal symptoms, thyroid dysfunction, coronary artery disease, diabetes mellitus, hypertension, stroke, hyperlipidemia, sleep disorders, smoking, and family history of dementia were not significant predictors. BDLAS and EDLAS scores at the first and second visits showed significant associations with disease progression, while scores at the third visit did not. Group-based trajectory analysis revealed that non-AD cases separated into two reliable subgroups with slow/fast prognosis, showing high reliability (Entropy = 0.790, 51.8 vs. 48.2%). This study provides valuable insights into the temporal course and prognostic factors of non-Alzheimer's dementias. The findings underscore the importance of considering functional, neuropsychological, and comorbid medical conditions in understanding disease progression. The significant associations between hippocampal atrophy, white matter intensities, and prognosis highlight potential avenues for further research and therapeutic interventions.

Pathogenic variants in the Longitudinal Early-onset Alzheimer's Disease Study cohort.

One goal of the Longitudinal Early-onset Alzheimer's Disease Study (LEADS) is to investigate the genetic etiology of early onset (40-64 years) cognitive impairment. Toward this goal, LEADS participants are screened for known pathogenic variants. LEADS amyloid-positive early-onset Alzheimer's disease (EOAD) or negative early-onset non-AD (EOnonAD) cases were whole exome sequenced (N=299). Pathogenic variant frequency in APP, PSEN1, PSEN2, GRN, MAPT, and C9ORF72 was assessed for EOAD and EOnonAD. Gene burden testing was performed in cases compared to similar-age cognitively normal controls in the Parkinson's Progression Markers Initiative (PPMI) study. Previously reported pathogenic variants in the six genes were identified in 1.35% of EOAD (3/223) and 6.58% of EOnonAD (5/76). No genes showed enrichment for carriers of rare functional variants in LEADS cases. Results suggest that LEADS is enriched for novel genetic causative variants, as previously reported variants are not observed in most cases. Sequencing identified eight cognitively impaired pathogenic variant carriers. Pathogenic variants were identified in PSEN1, GRN, MAPT, and C9ORF72. Rare variants were not enriched in APP, PSEN1/2, GRN, and MAPT. The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) is a key resource for early-onset Alzheimer's genetic research.

A Novel Serum-Based Diagnosis of Alzheimer's Disease Using an Advanced Phage-Based Biochip.

55 million people worldwide suffer from Alzheimer's disease (AD). A definitive diagnosis of AD is made postmortem after a neuropathological examination of the brain. There is an urgent need for an innovative, noninvasive methodology that allows for an early and reliable diagnosis. Several engineered phages that recognized Aβ-autoantibodies present in the sera of AD patients are previously identified. Here, novel phages are tested for their ability to accurately discriminate AD sera using immunophage-polymerase chain reaction in a miniatured biochip. It is found that five of the six phages analyzed discriminate between healthy controls and AD patients. Further, by combining the response of two phages, non-AD and severe AD cases are identified with 100% accuracy and mild-to-moderate cases with 90% accuracy. While the number of cases used here are relatively small and can be confirmed in larger cohorts, this first-of-a-kind system represents an innovative methodology with the potential of having a major impact in the AD field: from a clinical perspective, it can aid physicians in making an accurate AD diagnosis; from a research perspective, it can be used as a surrogate for AD clinical trials.

Immunogenicity of MultiTEP platform technology-based Tau vaccine in non-human primates

Pathological forms of Tau protein are directly associated with neurodegeneration and correlate with Alzheimer’s Disease (AD) symptoms, progression, and severity. Previously, using various mouse models of Tauopathies and AD, we have demonstrated the immunogenicity and efficacy of the MultiTEP-based adjuvanted vaccine targeting the phosphatase activating domain (PAD) of Tau, AV-1980R/A. Here, we analyzed its immunogenicity in non-human primates (NHP), the closest phylogenic relatives to humans with a similar immune system, to initiate the transition of this vaccine into clinical trials. We have demonstrated that AV-1980R/A is highly immunogenic in these NHPs, activating a broad but unique to each monkey repertoire of MultiTEP-specific T helper (Th) cells that, in turn, activate B cells specific to PAD. The resulting anti-PAD IgG antibodies recognize pathological Tau tangles and Tau-positive neuritis in AD case brain sections with no staining in control non-AD cases. These published data and efficacy results support the AV-1980R/A vaccine progression to first-in-human clinical trials.

Development and internal validation of a prognostic model for 15-year risk of Alzheimer dementia in primary care patients.

The exploitation of routinely collected clinical health information is warranted to optimize the case detection and diagnostic workout of Alzheimer's disease (AD). We aimed to derive an AD prediction score based on routinely collected primary care data. We built a cohort selecting 199,978 primary care patients 60 + part of the Health Search Database between January 2002 and 2009, followed up until 2019 to detect incident AD cases. The cohort was randomly divided into a derivation and validation sub-cohort. To identify AD and non-AD cases, we applied a clinical algorithm that involved two clinicians. According to a nested case-control design, AD cases were matched with up to 10 controls based on age, sex, calendar period, and follow-up duration. Using the derivation sub-cohort, 32 potential AD predictors (sociodemographic, clinical, drug-related, etc.) were tested in a logistic regression and selected to build a prediction model. The predictive performance of this model was tested on the validation sub-cohort by mean of explained variation, calibration, and discrimination measurements. We identified 3223 AD cases. The presence of memory disorders, hallucinations, anxiety, and depression and the use of NSAIDs were associated with future AD. The combination of the predictors allowed the production of a predictive score that showed an explained variation (pseudo-R2) for AD occurrence of 13.4%, good calibration parameters, and an area under the curve of 0.73 (95% CI: 0.71-0.75). In accordance with this model, 7% of patients presented with a high-risk score for developing AD over 15years. An automated risk score for AD based on routinely collected clinical data is a promising tool for the early case detection and timely management of patients by the general practitioners.

Plasma biomarkers for Alzheimer\u2019s Disease in relation to neuropathology and cognitive change

Plasma biomarkers related to amyloid, tau, and neurodegeneration (ATN) show great promise for identifying these pathological features of Alzheimer’s Disease (AD) as shown by recent clinical studies and selected autopsy studies. We have evaluated ATN plasma biomarkers in a series of 312 well-characterized longitudinally followed research subjects with plasma available within 5 years or less before autopsy and examined these biomarkers in relation to a spectrum of AD and related pathologies. Plasma Aβ42, Aβ40, total Tau, P-tau181, P-tau231 and neurofilament light (NfL) were measured using Single molecule array (Simoa) assays. Neuropathological findings were assessed using standard research protocols. Comparing plasma biomarkers with pathology diagnoses and ratings, we found that P-tau181 (AUC = 0.856) and P-tau231 (AUC = 0.773) showed the strongest overall sensitivity and specificity for AD neuropathological change (ADNC). Plasma P-tau231 showed increases at earlier ADNC stages than other biomarkers. Plasma Aβ42/40 was decreased in relation to amyloid and AD pathology, with modest diagnostic accuracy (AUC = 0.601). NfL was increased in non-AD cases and in a subset of those with ADNC. Plasma biomarkers did not show changes in Lewy body disease (LBD), hippocampal sclerosis of aging (HS) or limbic-predominant age-related TDP-43 encephalopathy (LATE) unless ADNC was present. Higher levels of P-tau181, 231 and NfL predicted faster cognitive decline, as early as 10 years prior to autopsy, even among people with normal cognition or mild cognitive impairment. These results support plasma P-tau181 and 231 as diagnostic biomarkers related to ADNC that also can help to predict future cognitive decline, even in predementia stages. Although NfL was not consistently increased in plasma in AD and shows increases in several neurological disorders, it had utility to predict cognitive decline. Plasma Aβ42/40 as measured in this study was a relatively weak predictor of amyloid pathology, and different assay methods may be needed to improve on this. Additional plasma biomarkers are needed to detect the presence and impact of LBD and LATE pathology.

Neurodegeneration and Astrogliosis in the Human CA1 Hippocampal Subfield Are Related to hsp90ab1 and bag3 in Alzheimer's Disease.

Alzheimer’s disease (AD), the most prevalent neurodegenerative disorder, is characterized by executive dysfunction and memory impairment mediated by the accumulation of extracellular amyloid-β peptide (Aβ) and intracellular hyperphosphorylated tau protein. The hippocampus (HIPP) is essential for memory formation and is involved in early stages of disease. In fact, hippocampal atrophy is used as an early biomarker of neuronal injury and to evaluate disease progression. It is not yet well-understood whether changes in hippocampal volume are due to neuronal or glial loss. The aim of the study was to assess hippocampal atrophy and/or gliosis using unbiased stereological quantification and to obtain hippocampal proteomic profiles related to neurodegeneration and gliosis. Hippocampal volume measurement, stereological quantification of NeuN-, Iba-1- and GFAP-positive cells, and sequential window acquisition of all theoretical mass spectrometry (SWATH-MS) analysis were performed in AD and non-AD cases. Reduced hippocampal volume was identified using the Cavalieri probe, particularly in the CA1 region, where it correlated with neuronal loss and astrogliosis. A total of 102 downregulated and 47 upregulated proteins were identified in the SWATH-MS analysis after restrictive filtering based on an FC > 1.5 and p value < 0.01. The Hsp90 family of chaperones, particularly BAG3 and HSP90AB1, are closely related to astrocytes, indicating a possible role in degrading Aβ and tau through chaperone-mediated autophagy.

Tau seeds are widespread in the brain at the earliest stages of Alzheimer's disease-related changes.

Alzheimer's disease (AD) is pathologically characterized by the systematic spread of 3R/4R tau species with progressing disease. Current imaging and CSF in-vivo assessments of tau are thought to reflect more mature tangle neuropathology. However, earlier oligomeric tau species are indicated to have greater neurotoxicity than mature forms and it is largely unknown how tau seeds correlate with histological indicators of AD. Furthermore, tau co-pathology is thought to influence features and progression of other neurodegenerative diseases including Lewy body disease (LBD); yet reliable measurements of tau seeds in such diseases remains an unmet need. Here, we use tau real-time quaking-induced conversion (RT-QuIC) assays to directly measure bioactive tau seeds in brain samples across a spectrum of neurodegenerative diseases to determine tau seeding activities at different stages of AD related changes. Tau RT-QuIC exploits the seeded polymerization growth mechanism of tau filaments, with sensitivities in the low fM range, allowing quantitation of disease-associated aggregates with unprecedented sensitivity and selectivity. Tau RT-QuIC assays were used to quantitate tau seeds in mid-frontal lobe brain tissue from 64 cases including subjects with neuropathologically confirmed AD (n=15), Parkinson's disease (n=7), multiple system atrophy (n=6), LBD (n=14), frontotemporal lobar degeneration (n=4), progressive supranuclear palsy (n=6), corticobasal degeneration (n=2), early Alzheimer's changes (Braak I-III) (n=7), and controls (n=3). All cases had Braak tau staging and frontal lobes were immunohistochemically stained for tau with NFT1. 3R/4R tau seeding activity is typically 100-1000-fold higher in cases with a primary AD diagnosis compared to controls, 4R tauopathies, and synucleinopathies, consistent with our prior observations. Seeding activity positively correlated with Braak tau stage, a histological measure of tau accumulation, with increased tau seeding activities at higher Braak stages. Tau seeds are detectable in the frontal lobe even at Braak I, a stage at which frontal lobe lacks histologically visible tau deposits. Ultrasensitive RT-QuIC assays detect tau seeds at the earliest stages of disease processes, prior to histopathological evidence of more mature tau accumulations and can indicate co-occurrence of tau pathology in non-AD cases. Tau seeding activity correlates with overall Braak tau stage, raising the possibility of quantitative value of tau RT-QuIC assays.

Associations of Fully Automated CSF and Novel Plasma Biomarkers With Alzheimer Disease Neuropathology at Autopsy.

ObjectiveTo study CSF biomarkers of Alzheimer disease (AD) analyzed by fully automated Elecsys immunoassays compared to neuropathologic gold standards and to compare their accuracy to plasma phosphorylated tau (p-tau181) measured with a novel single molecule array method.MethodsWe studied antemortem Elecsys-derived CSF biomarkers in 45 individuals who underwent standardized postmortem assessments of AD and non-AD neuropathologic changes at autopsy. In a subset of 26 participants, we also analyzed antemortem levels of plasma p-tau181 and neurofilament light (NfL). Reference biomarker values were obtained from 146 amyloid-PET–negative healthy controls (HC).ResultsAll CSF biomarkers clearly distinguished pathology-confirmed AD dementia (n = 27) from HC (area under the curve [AUC] 0.86–1.00). CSF total tau (t-tau), p-tau181, and their ratios with β-amyloid1-42 (Aβ1-42) also accurately distinguished pathology-confirmed AD from non-AD dementia (n = 8; AUC 0.94–0.97). In pathology-specific analyses, intermediate to high Thal amyloid phases were best detected by CSF Aβ1-42 (AUC [95% confidence interval] 0.91 [0.81–1]), while intermediate to high scores for Consortium to Establish a Registry for Alzheimer's Disease neuritic plaques and Braak tau stages were best detected by CSF p-tau181 (AUC 0.89 [0.79–0.99] and 0.88 [0.77–0.99], respectively). Optimal Elecsys biomarker cutoffs were derived at 1,097, 229, and 19 pg/mL for Aβ1-42, t-tau, and p-tau181. In the plasma subsample, both plasma p-tau181 (AUC 0.91 [0.86–0.96]) and NfL (AUC 0.93 [0.87–0.99]) accurately distinguished those with pathology-confirmed AD (n = 14) from HC. However, only p-tau181 distinguished AD from non-AD dementia cases (n = 4; AUC 0.96 [0.88–1.00]) and showed a similar, although weaker, pathologic specificity for neuritic plaques (AUC 0.75 [0.52–0.98]) and Braak stage (AUC 0.71 [0.44–0.98]) as CSF p-tau181.ConclusionElecsys-derived CSF biomarkers detect AD neuropathologic changes with very high discriminative accuracy in vivo. Preliminary findings support the use of plasma p-tau181 as an easily accessible and scalable biomarker of AD pathology.Classification of EvidenceThis study provides Class II evidence that fully automated CSF t-tau and p-tau181 measurements discriminate between autopsy-confirmed AD and other dementias.

Variation in the concentration and regional distribution of magnetic nanoparticles in human brains, with and without Alzheimer\u2019s disease, from the UK

The presence of magnetic nanoparticles (MNPs) in the human brain was attributed until recently to endogenous formation; associated with a putative navigational sense, or with pathological mishandling of brain iron within senile plaques. Conversely, an exogenous, high-temperature source of brain MNPs has been newly identified, based on their variable sizes/concentrations, rounded shapes/surface crystallites, and co-association with non-physiological metals (e.g., platinum, cobalt). Here, we examined the concentration and regional distribution of brain magnetite/maghemite, by magnetic remanence measurements of 147 samples of fresh/frozen tissues, from Alzheimer’s disease (AD) and pathologically-unremarkable brains (80–98 years at death) from the Manchester Brain Bank (MBB), UK. The magnetite/maghemite concentrations varied between individual cases, and different brain regions, with no significant difference between the AD and non-AD cases. Similarly, all the elderly MBB brains contain varying concentrations of non-physiological metals (e.g. lead, cerium), suggesting universal incursion of environmentally-sourced particles, likely across the geriatric blood–brain barrier (BBB). Cerebellar Manchester samples contained significantly lower (~ 9×) ferrimagnetic content compared with those from a young (29 years ave.), neurologically-damaged Mexico City cohort. Investigation of younger, variably-exposed cohorts, prior to loss of BBB integrity, seems essential to understand early brain impacts of exposure to exogenous magnetite/maghemite and other metal-rich pollution particles.

Maturation of neuronal AD-tau pathology involves site-specific phosphorylation of cytoplasmic and synaptic tau preceding conformational change and fibril formation

In Alzheimer's disease (AD), tau-protein undergoes a multi-step process involving the transition from a natively unfolded monomer to large, aggregated structures such as neurofibrillary tangles (NFTs). However, it is not yet clear which events initiate the early preclinical phase of AD tauopathy and whether they have impact on the propagation of tau pathology in later disease stages. To address this question, we analyzed the distribution of tau species phosphorylated at T231, S396/S404 and S202/T205, conformationally modified at the MC1 epitope and fibrillary tau detected by the Gallyas method (Gallyas-tau), in the brains of 15 symptomatic and 20 asymptomatic cases with AD pathology as well as of 19 nonAD cases. As initial tau lesions, we identified phosphorylated-T231-tau diffusely distributed within the somatodendritic compartment (IC-tau) and phosphorylated-S396/pS404-tau in axonal lesions of the white matter and in the neuropil (IN-tau). The subcellular localization of pT231-tau in the cell body and pS396/pS404-tau in the presynapse was confirmed in hP301L mutant Drosophila larvae. Phosphorylated-S202/T205-tau, MC1-tau and Gallyas-tau were negative for these lesions. IC- and IN-tau were observed in all analyzed regions of the human brain, including early affected regions in nonAD cases (entorhinal cortex) and late affected regions in symptomatic AD cases (cerebellum), indicating that tau pathology initiation follows similar processes when propagating into previously unaffected regions. Furthermore, a sequence of AD-related maturation of tau-aggregates was observed, initiated by the appearance of IC- and IN-tau, followed by the formation of pretangles exhibiting pT231-tau, pS396/pS404-tau and pS202/pT205-tau, then by MC1-conformational tau, and, finally, by the formation of Gallyas-positive NFTs. Since cases classified as nonAD [Braak NFT stages < I (including a-1b)] already showed IC- and IN-tau, our findings suggest that these lesions are a prerequisite for the development of AD.

Value of a Panel of 6 Serum Biomarkers to Differentiate Between Healthy Controls and Mild Cognitive Impairment Due to Alzheimer Disease.

There is considerable evidence suggesting that inflammatory responses may be involved in the neurodegenerative cascade of Alzheimer disease (AD). Blood-based biomarker analysis of inflammatory markers indicative of dementia could serve as a minimally invasive and easy-to-administer diagnostic tool in primary care. The authors quantified 6 markers (brain-derived neurotrophic factor, insulin-like growth factor 1, vascular endothelial growth factor, transforming growth factor-beta type 1, monocyte chemoattractant protein 1, and interleukin-18) in blood serum of 68 healthy blood donors (controls), 42 patients with AD at the dementia stage, 55 patients with AD at the stage of mild cognitive impairment (MCI-AD), and 25 patients with MCI non-AD. All patients have been fully characterized, including AD biomarker analyses in cerebrospinal fluid. Data were analyzed in an algorithm that was trained, validated, and then used for dichotomous classification of unknown data into data sets suspicious and not suspicious of AD. Using this algorithm, 47 of 55 MCI-AD (85.5%) and 20 of 25 MCI non-AD (80%) cases were classified as suspicious of AD. This panel of 6 markers in blood serum may indicate underlying neurodegenerative processes in patients with AD at the MCI stage. The authors assume that a deranged equilibrium of neuroprotective and inflammatory processes is an overall major cause for neurodegeneration and cognitive decline.

Abnormalities of DYRK1A-Cytoskeleton Complexes in the Blood Cells as Potential Biomarkers of Alzheimer's Disease.

Background:DYRK1A is implicated in mental retardation and Alzheimer’s disease (AD) dementia of Down syndrome (DS) individuals. The protein is associated with cytoskeleton and altered expression has been shown to impair the cytoskeletal network via dosage effect.Objective:Our original observations of marked reduction of cytoskeletal proteins associated with DYRK1A in brains and lymphoblastoid cell lines from DS and AD prompted an investigation whether cytoskeleton abnormalities could potentially be used as biomarkers of AD.Methods:Our assay relied on quantification of co-immunoprecipitated cytoskeletal proteins with DYRK1A (co-IP assay) and analysis of the profile of G- and F-actin fractions obtained by high-speed centrifugations (spin-down assay).Results:In co-IP assay, both DS and AD samples displayed reduced abundance of associated cytoskeletal proteins. In spin-down assay, G-actin fractions of controls displayed two closely spaced bands of actin in SDS-PAGE; while in AD and DS, only the upper band of the doublet was present. In both assays, alterations of actin cytoskeleton were present in DS, sporadic and familial AD cases, and in asymptomatic persons who later progressed to confirmed AD, but not in non-AD donors. In blind testing involving six AD and six controls, the above tests positively identified ten cases. Analysis of blood samples revealed the diversity of mild cognitive impairment (MCI) cases regarding the presence of the AD biomarker allowing distinction between likely prodromal AD and non-AD MCI cases.Conclusions:Both brain tissue and lymphocytes from DS and AD displayed similar semi-quantitative and qualitative alterations of actin cytoskeleton. Their specificity for AD-type dementia and the presence before clinical onset of the disease make them suitable biomarker candidates for early and definite diagnosis of AD. The presence of alterations in peripheral tissue points to systemic underlying mechanisms and suggests that early dysfunction of cytoskeleton may be a predisposing factor in the development of AD.