Cerebrospinal Fluid Beta-amyloid Research Articles

Neuroimaging correlates of Alzheimer's disease biomarker concentrations in a racially diverse high-risk cohort of middle-aged adults.

In this study, we investigated biomarkers in a midlife, racially diverse, at-risk cohort to facilitate early identification and intervention. We examined neuroimaging measures, including resting state functional magnetic resonance imaging (fMRI), white matter hyperintensity vo (WMH), and hippocampal volumes, alongside cerebrospinal fluid (CSF) markers. Our data set included 76 cognitively unimpaired, middle-aged, Black Americans (N=29, F/M=17/12) and Non-Hispanic White (N=47, F/M=27/20) individuals. We compared cerebrospinal fluid phosphorylated tau141 and amyloid beta (Aβ)42 to fMRI default mode network (DMN) subnetwork connectivity, WMH volumes, and hippocampal volumes. Results revealed a significant race × Aβ42 interaction in Black Americans: lower Aβ42 was associated with reduced DMN connectivity and increased WMH volumes regions but not in non-Hispanic White individuals. Our findings suggest that precuneus DMN connectivity and temporal WMHs may be linked to Alzheimer's disease risk pathology during middle age, particularly in Black Americans. Cerebrospinal fluid (CSF) amyloid beta (Aβ)42 relates to precuneus functional connectivity in Black, but not White, Americans. Higher white matter hyperintensity volume relates to lower CSF Aβ42 in Black Americans. Precuneus may be a hub for early Alzheimer's disease pathology changes detected by functional connectivity.

Alzheimer's disease genetic pathways impact cerebrospinal fluid biomarkers and imaging endophenotypes in non-demented individuals.

Unraveling how Alzheimer's disease (AD) genetic risk is related to neuropathological heterogeneity, and whether this occurs through specific biological pathways, is a key step toward precision medicine. We computed pathway-specific genetic risk scores (GRSs) in non-demented individuals and investigated how AD risk variants predict cerebrospinal fluid (CSF) and imaging biomarkers reflecting AD pathology, cardiovascular, white matter integrity, and brain connectivity. CSF amyloidbeta and phosphorylated tau were related to most GRSs. Inflammatory pathways were associated with cerebrovascular disease, whereas quantitative measures of white matter lesion and microstructure integrity were predicted by clearance and migration pathways. Functional connectivity alterations were related to genetic variants involved in signal transduction and synaptic communication. This study reveals distinct genetic risk profiles in association with specific pathophysiological aspects in predementia stages of AD, unraveling the biological substrates of the heterogeneity of AD-associated endophenotypes and promoting a step forward in disease understanding and development of personalized therapies. Polygenic risk for Alzheimer's disease encompasses six biological pathways that can be quantified with pathway-specific genetic risk scores, and differentially relate to cerebrospinal fluid and imaging biomarkers. Inflammatory pathways are mostly related to cerebrovascular burden. White matter health is associated with pathways of clearance and membrane integrity, whereas functional connectivity measures are related to signal transduction and synaptic communication pathways.

CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease.

We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.

Association analyses of apolipoprotein E genotypes and cognitive performance in patients with Parkinson’s disease

BackgroundCognitive impairment is a common non-motor symptom of Parkinson’s disease (PD). The apolipoprotein E (APOE) ε4 genotype increases the risk of Alzheimer’s disease (AD). However, the effect of APOEε4 on cognitive function of PD patients remains unclear. In this study, we aimed to understand whether and how carrying APOEε4 affects cognitive performance in patients with early-stage and advanced PD.MethodsA total of 119 Chinese early-stage PD patients were recruited. Movement Disorder Society Unified Parkinson’s Disease Rating Scale, Hamilton anxiety scale, Hamilton depression scale, non-motor symptoms scale, Mini-mental State Examination, Montreal Cognitive Assessment, and Fazekas scale were evaluated. APOE genotypes were determined by polymerase chain reactions and direct sequencing. Demographic and clinical information of 521 early-stage and 262 advanced PD patients were obtained from Parkinson’s Progression Marker Initiative (PPMI).ResultsNo significant difference in cognitive performance was found between ApoEε4 carriers and non-carriers in early-stage PD patients from our cohort and PPMI. The cerebrospinal fluid (CSF) Amyloid Beta 42 (Aβ42) level was significantly lower in ApoEε4 carrier than non-carriers in early-stage PD patients from PPMI. In advanced PD patients from PPMI, the BJLOT, HVLT retention and SDMT scores seem to be lower in ApoEε4 carriers without reach the statistical significance.ConclusionsAPOEε4 carriage does not affect the cognitive performance of early-stage PD patients. However, it may promote the decline of CSF Aβ42 level and the associated amyloidopathy, which is likely to further contribute to the cognitive dysfunction of PD patients in the advanced stage.

Precise prediction of cerebrospinal fluid amyloid beta protein for early Alzheimer's disease detection using multimodal data.

Alzheimer's disease (AD) constitutes a neurodegenerative disorder marked by a progressive decline in cognitive function and memory capacity. The accurate diagnosis of this condition predominantly relies on cerebrospinal fluid (CSF) markers, notwithstanding the associated burdens of pain and substantial financial costs endured by patients. This study encompasses subjects exhibiting varying degrees of cognitive impairment, encompassing individuals with subjective cognitive decline, mild cognitive impairment, and dementia, constituting a total sample size of 82 participants. The primary objective of this investigation is to explore the relationships among brain atrophy measurements derived from magnetic resonance imaging, atypical electroencephalography (EEG) patterns, behavioral assessment scales, and amyloid β-protein (Aβ) indicators. The findings of this research reveal that individuals displaying reduced Aβ1-42/Aβ-40 levels exhibit significant atrophy in the frontotemporal lobe, alongside irregularities in various parameters related to EEG frequency characteristics, signal complexity, inter-regional information exchange, and microstates. The study additionally endeavors to estimate Aβ1-42/Aβ-40 content through the application of a random forest algorithm, amalgamating structural data, electrophysiological features, and clinical scales, achieving a remarkable predictive precision of 91.6%. In summary, this study proposes a cost-effective methodology for acquiring CSF markers, thereby offering a valuable tool for the early detection of AD.

Cerebrospinal fluid soluble insulin receptor levels in Alzheimer's disease.

Brain insulin resistance and deficiency is a consistent feature of Alzheimer's disease (AD). Insulin resistance can be mediated by the surface expression of the insulin receptor (IR). Cleavage of the IR generates the soluble IR (sIR). We measured the levels of sIR present in cerebrospinal fluid (CSF) from individuals along the AD diagnostic spectrum from two cohorts: Seattle (n=58) and the Consortium for the Early Identification of Alzheimer's Disease-Quebec (CIMA-Q; n=61). We further investigated the brain cellular contribution for sIR using human cell lines. CSF sIR levels were not statistically different in AD. CSF sIR and amyloid beta (Aβ)42 and Aβ40 levels significantly correlated as well as CSF sIR and cognition in the CIMA-Q cohort. Human neurons expressing the amyloid precursor protein "Swedish" mutation generated significantly greater sIR and human astrocytes were also able to release sIR in response to both an inflammatory and insulin stimulus. These data support further investigation into the generation and role of sIR in AD. Cerebrospinal fluid (CSF) soluble insulin receptor (sIR) levels positively correlate with amyloid beta (Aβ)42 and Aβ40.CSF sIR levels negatively correlate with cognitive performance (Montreal Cognitive Assessment score).CSF sIR levels in humans remain similar across Alzheimer's disease diagnostic groups.Neurons derived from humans with the "Swedish" mutation in which Aβ42 is increased generate increased levels of sIR.Human astrocytes can also produce sIR and generation is stimulated by tumor necrosis factor α and insulin.

Neuropathological changes associated with aberrant cerebrospinal fluid p-tau181 and Aβ42 in Alzheimer’s disease and other neurodegenerative diseases

Recent studies suggest that increased cerebrospinal fluid (CSF) phospho-tau is associated with brain amyloid pathology rather than the tau pathology. However, confirmation using gold standard neuropathological assessments remains limited. This study aimed to determine background pathologies associated with aberrant CSF p-tau181 and amyloid-beta 1–42 (Aβ42) in Alzheimer’s disease (AD) and other neurodegenerative diseases. We retrospectively studied all patients with antemortem CSF and postmortem neuropathologic data at our institution. Comprehensive neuropathologic assessments were conducted for all patients, including Thal phase, Braak NFT stage, and CERAD score for AD. CSF concentrations of p-tau181 and Aβ42 were compared between AD neuropathological scores at autopsy by one-way ANOVA stratified by other pathologies. A total of 127 patients with AD (n = 22), Lewy body disease (n = 26), primary tauopathies (n = 30), TDP-43 proteinopathy (n = 16), and other diseases (n = 33) were included. The age at lumbar puncture was 76.3 ± 9.1 years, 40.8% were female, and median time from lumbar puncture to autopsy was 637 (175–1625) days. While Braak NFT 0–II was prevalent without amyloid pathology, Braak NFT ≥IV was observed exclusively in patients with amyloid pathology. Stratified analyses showed that CSF p-tau181 was slightly but significantly higher in patients with high Thal phase or CERAD score even in those with Braak NFT 0–II at autopsy. In patients with amyloid pathology, CSF p-tau181 was significantly and more profoundly elevated in those with Braak NFT ≥III at autopsy. CSF Aβ42 was lower in patients with high amyloid pathological scores. However, 34% with Thal ≤ 2 and 38% with CERAD ≤ sparse also showed decreased Aβ42. Progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) were overrepresented in this group. These results neuropathologically confirmed previous studies that CSF p-tau181 levels were slightly elevated with amyloid pathology alone and were even higher with tau pathology, and that CSFAβ42 can be decreased in PSP/CBD.

CSF protein ratios with enhanced potential to reflect Alzheimer’s disease pathology and neurodegeneration

BackgroundAmyloid and tau aggregates are considered to cause neurodegeneration and consequently cognitive decline in individuals with Alzheimer’s disease (AD). Here, we explore the potential of cerebrospinal fluid (CSF) proteins to reflect AD pathology and cognitive decline, aiming to identify potential biomarkers for monitoring outcomes of disease-modifying therapies targeting these aggregates.MethodWe used a multiplex antibody-based suspension bead array to measure the levels of 49 proteins in CSF from the Swedish GEDOC memory clinic cohort at the Karolinska University Hospital. The cohort comprised 148 amyloid- and tau-negative individuals (A-T-) and 65 amyloid- and tau-positive individuals (A+T+). An independent sample set of 26 A-T- and 26 A+T+ individuals from the Amsterdam Dementia Cohort was used for validation. The measured proteins were clustered based on their correlation to CSF amyloid beta peptides, tau and NfL levels. Further, we used support vector machine modelling to identify protein pairs, matched based on their cluster origin, that reflect AD pathology and cognitive decline with improved performance compared to single proteins.ResultsThe protein-clustering revealed 11 proteins strongly correlated to t-tau and p-tau (tau-associated group), including mainly synaptic proteins previously found elevated in AD such as NRGN, GAP43 and SNCB. Another 16 proteins showed predominant correlation with Aβ42 (amyloid-associated group), including PTPRN2, NCAN and CHL1. Support vector machine modelling revealed that proteins from the two groups combined in pairs discriminated A-T- from A+T+ individuals with higher accuracy compared to single proteins, as well as compared to protein pairs composed of proteins originating from the same group. Moreover, combining the proteins from different groups in ratios (tau-associated protein/amyloid-associated protein) significantly increased their correlation to cognitive decline measured with cognitive scores. The results were validated in an independent cohort.ConclusionsCombining brain-derived proteins in pairs largely enhanced their capacity to discriminate between AD pathology-affected and unaffected individuals and increased their correlation to cognitive decline, potentially due to adjustment of inter-individual variability. With these results, we highlight the potential of protein pairs to monitor neurodegeneration and thereby possibly the efficacy of AD disease-modifying therapies.

Does Physical Exercise Modify the Pathophysiology of Alzheimer's Disease in Older Persons?

Physical exercise is well known for its benefits on brain health. However, the mechanisms through which these benefits occur remain discussed, especially in the context of cognitive conditions such as Alzheimer's disease. The present short review summarizes the findings of interventional studies that examined the effects of exercise training on the specific and non-specific biomarkers of Alzheimer's disease. Controlled exercise intervention studies published in the English language were selected if they assessed the effects of a physical exercise intervention of at least 2 weeks in middle-aged or older adults on one of the following biomarkers measured either in the brain, the cerebrospinal fluid or the blood: beta-amyloid, tau, neurofilament light chain, and glial fibrillary acidic protein. Overall, there was no strong evidence of significant effects of exercise interventions on any of the selected biomarkers. However, in specific populations, such as women with obesity, pre-diabetes, or depression, favorable changes in blood beta-amyloid concentrations were reported. Further benefits on cerebrospinal fluid beta-amyloid were also demonstrated in APOE-ε4 allele carriers with Alzheimer's disease. In conclusion, the current evidence suggests that physical exercise does not modulate the pathophysiology of Alzheimer's disease in the overall population of middle-aged and older adults. Nonetheless, some specific populations, such as women with metabolic disorders and Alzheimer's disease patients with APOE-ε4 genotype, seem to be favorably affected. Further studies, including long follow-ups, large sample sizes, and concomitantly assessing the effects of other factors such as sedentary behavior and diet, are required to bring further evidence to the field.

Diagnosing Alzheimer's disease: Which dementia screening test to use in elderly Puerto Ricans with mild cognitive impairment and early Alzheimer's disease?

Typically, Alzheimer's disease (AD) diagnosis is not made at its earliest period, for instance, at mild cognitive impairment (MCI) and early AD (E-AD). Our study aims to demonstrate a correlation between the screening tools, including the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Clinical Dementia Rating (CDR), and the biological biomarkers in the cerebrospinal fluid (CSF) amyloid beta 1-42 (Aβ42), phosphorylated tau (p-tau) proteins and total tau (t-tau)/Aβ42 ratio in Puerto Ricans>55 years old with MCI and E-AD. We evaluated 30 participants, including demographics, memory scales, and CSF biomarkers. Twenty-eight CSF biomarkers (Aβ42, p-tau protein, and t-tau/Aβ42 ratio) were analyzed using the Meso Scale Discovery Platform (MSD). Associations between memory scales (MoCA, MMSE, CDR) and CSF markers were performed using Spearman rho correlation. Our study revealed a statistical association favoring a direct relationship between MMSE and MoCA with t-tau/Aβ42 ratio in CSF (P=0.022, P=0.035, respectively). We found a trend toward significance with an inverse relationship with MMSE and Aβ42 (P=0.069) and a direct relationship with MMSE and p-tau (P=0.098). MMSE and MoCA screening tests were identified with a statistically significant association with the CSF biomarkers, specifically t-tau/Aβ42 ratio, in elderly Puerto Ricans with MCI and E-AD. Puerto Ricans>55 years old with MCI and E-AD could be screened confidently with MMSE and MoCA for a higher likelihood of earlier detection and, thus, initiation of disease-modifying treatment and prompt non-pharmacological interventions.

Serum Bile Acids Improve Prediction of Alzheimer's Progression in a Sex-Dependent Manner.

Sex disparities in serum bile acid (BA) levels and Alzheimer's disease (AD) prevalence have been established. However, the precise link between changes in serum BAs and AD development remains elusive. Here, authors quantitatively determined 33 serum BAs and 58 BA features in 4219 samples collected from 1180 participants from the Alzheimer's Disease Neuroimaging Initiative. The findings revealed that these BA features exhibited significant correlations with clinical stages, encompassing cognitively normal (CN), early and late mild cognitive impairment, and AD, as well as cognitive performance. Importantly, these associations are more pronounced in men than women. Among participants with progressive disease stages (n=660), BAs underwent early changes in men, occurring before AD. By incorporating BA features into diagnostic and predictive models, positive enhancements are achieved for all models. The area under the receiver operating characteristic curve improved from 0.78 to 0.91 for men and from 0.76 to 0.83 for women for the differentiation of CN and AD. Additionally, the key findings are validated in a subset of participants (n=578) with cerebrospinal fluid amyloid-beta and tau levels. These findings underscore the role of BAs in AD progression, offering potential improvements in the accuracy of AD prediction.

Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity.Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

Decline in proper name retrieval during story recall is associated with Alzheimer’s disease CSF biomarkers in cognitively unimpaired individuals

AbstractBackgroundRemembering names of people and places is a common problem in aging that is exacerbated in Alzheimer’s disease (AD). Because retrieval of proper names (PNs) has been associated with brain regions affected by AD (anterior and medial temporal lobe), PN retrieval may be an especially sensitive measure of early AD pathology. Extending results of a previous study from WRAP (Mueller et al., 2020), this study examined associations between cerebrospinal fluid (CSF) AD biomarkers and longitudinal delayed story recall PN retrieval.MethodParticipants were from the BIOCARD study, a cohort of late‐middle aged adults enriched for parental history of AD. Participants were cognitively unimpaired at baseline with longitudinal item‐level data from the Logical Memory (LM; WMS‐R) Story A recall (N = 218; M(SD) baseline age = 58(9); M(SD) follow‐up = 4.1(2.9) years). CSF amyloid beta (Ab42/40) and phosphorylated tau181 (p‐tau181) were measured using automated electrochemiluminescence assays; AD biomarker abnormality (+) was determined using the bottom quartile for Ab42/40 and the top quartile for p‐tau181. We calculated total Story A PNs (range 0‐4) and total score (0‐25). We performed longitudinal linear mixed effects (LME) models examining the interaction between time (LM age, centered) and last available Ab42/40 and/or p‐tau181 status as predictors of PNs and total recall (subject‐specific random intercepts).ResultOf the 218 participants included, forty‐nine (22.4%) were Ab42/40+, 60 (27.5%) were p‐tau181+, and the remainder were A‐/T‐ (Table 1). In LME models, CSF‐Ab42/40+*age was not a significant predictor of either outcome. The p‐tau181+*age interaction showed significantly greater annual decline in PNs in the p‐tau181+ group than the p‐tau181‐ group (interaction beta = ‐.01, p = .02; simple slope estimate p‐tau181‐ = .002, p‐tau181+ = ‐.01) (Table 2, Fig.1). Interaction patterns were weaker yet similar for total recall. In follow‐up analyses, 15 participants who converted to MCI or dementia were removed and results remained unchanged. In an exploratory model combining biomarker statuses, the Ab42/40+/p‐tau181+*age interaction was non‐significant.ConclusionAs in the WRAP study, these results from BIOCARD indicate that PN recall is more sensitive to preclinical change than the traditional story recall total score metric; results also indicate that decline is greatest in those with elevated CSF p‐tau. Future directions should include replication in other longitudinal cohorts.

Which cortical regions affect the prediction of cerebrospinal fluid amyloid beta from PET images by novel residual neural network (ArcheD)

AbstractBackgroundAmyloid‐β (Aβ) aggregation, as a biological hallmark of Alzheimer’s disease (AD), is a key component of biological classification of AD in the AT(N) framework. This research aimed to develop a new deep learning model for predicting Aβ cerebrospinal fluid (CSF) measures from amyloid PET scans and explore which cortical regions are most important contributors in the model’s prediction.MethodWe developed a Residual Network model (ArcheD) to predict Aβ CSF from amyloid PET images, and trained it on 1,870 PET scans from the Alzheimer’s Disease Neuroimaging Initiative. We registered PET scans to MNI152 template and used the Neuromorphometrics atlas to derive cortical gray matter (GM) regions. We extracted brain regions’ contributions to model decision‐making by guided backpropagation, and visualized these contributions as relevance heatmaps. We used bootstrapping, Welch’s t‐test and FDR correction in testing significance of brain regions’ relevance to predictions in the whole cohort, and separately in clinical diagnostic classes of AD, mild cognitive impairment (MCI), and cognitively normal (CN) cases.ResultArcheD showed high accuracy in predicting Aβ CSF (r = 0.81; p<0.00001). According to the relevance analysis for all samples (n = 1,390) temporal (mean 0.106; 95%CI [0.105, 0.108]) and parietal (0.105; 95%CI [0.104, 0.107]) lobes were the most important GM regions for the model decision‐making. Occipital (0.098; 95%CI [0.098, 0.100]) and frontal lobes (0.091; 95%CI [0.089, 0.92]) showed noticeably fewer relevance values. Based on between‐classes comparison, these regions contribute significantly more to CSF prediction in AD and MCI individuals compared to CN (p<0.05). Analysis of 49 smaller regions showed an almost 7‐fold difference between the most and least contributing regions.ConclusionWe developed a deep residual neural network model that predicted Aβ CSF from amyloid PET scans with high accuracy, and found that temporal and parietal lobes have the highest influence on Aβ CSF predictions. In the next step, we will validate the model in independent data and aim to develop the model further for clinical use.

Which cortical regions affect the prediction of cerebrospinal fluid amyloid beta from PET images by novel residual neural network (ArcheD)

AbstractBackgroundAmyloid‐ß (Aß) aggregation, as a biological hallmark of Alzheimer’s disease (AD), is a key component of biological classification of AD in the AT(N) framework. This research aimed to develop a new deep learning model for predicting Aß cerebrospinal fluid (CSF) measures from amyloid PET scans and explore which cortical regions are most important contributors in the model’s prediction.MethodWe developed a Residual Network model (ArcheD) to predict Aß CSF from amyloid PET images, and trained it on 1,870 PET scans from the Alzheimer’s Disease Neuroimaging Initiative. We registered PET scans to MNI152 template and used the Neuromorphometrics atlas to derive cortical gray matter (GM) regions. We extracted brain regions’ contributions to model decision‐making by guided backpropagation, and visualized these contributions as relevance heatmaps. We used bootstrapping, Welch’s t‐test and FDR correction in testing significance of brain regions’ relevance to predictions in the whole cohort, and separately in clinical diagnostic classes of AD, mild cognitive impairment (MCI), and cognitively normal (CN) cases.ResultArcheD showed high accuracy in predicting Aß CSF (r = 0.81; p<0.00001). According to the relevance analysis for all samples (n = 1,390) temporal (mean 0.106; 95%CI [0.105, 0.108]) and parietal (0.105; 95%CI [0.104, 0.107]) lobes were the most important GM regions for the model decision‐making. Occipital (0.098; 95%CI [0.098, 0.100]) and frontal lobes (0.091; 95%CI [0.089, 0.92]) showed noticeably fewer relevance values. Based on between‐classes comparison, these regions contribute significantly more to CSF prediction in AD and MCI individuals compared to CN (p<0.05). Analysis of 49 smaller regions showed an almost 7‐fold difference between the most and least contributing regions.ConclusionWe developed a deep residual neural network model that predicted Aß CSF from amyloid PET scans with high accuracy, and found that temporal and parietal lobes have the highest influence on Aß CSF predictions. In the next step, we will validate the model in independent data and aim to develop the model further for clinical use.

Agreement of cerebrospinal fluid biomarkers and amyloid-PET in a multicenter study.

Core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers have shown incomplete agreement with amyloid-positron emission tomography (PET). Our goal was to analyze the agreement between AD CSF biomarkers and amyloid-PET in a multicenter study. Retrospective multicenter study (5 centers). Participants who underwent both CSF biomarkers and amyloid-PET scan within 18months were included. Clinical diagnoses were made according to latest diagnostic criteria by the attending clinicians. CSF Amyloid Beta1-42 (Aβ1-42, A), phosphorliated tau 181 (pTau181, T) and total tau (tTau, N) biomarkers were considered normal (-) or abnormal ( +) according to cutoffs of each center. Amyloid-PET was visually classified as positive/negative. Agreement between CSF biomarkers and amyloid-PET was analyzed by overall percent agreement (OPA). 236 participants were included (mean age 67.9years (SD 9.1), MMSE score 24.5 (SD 4.1)). Diagnoses were mild cognitive impairment or dementia due to AD (49%), Lewy body dementia (22%), frontotemporal dementia (10%) and others (19%). Mean time between tests was 5.1months (SD 4.1). OPA between single CSF biomarkers and amyloid-PET was 74% for Aβ1-42, 75% for pTau181, 73% for tTau. The use of biomarker ratios improved OPA: 87% for Aβ1-42/Aβ1-40 (n = 155), 88% for pTau181/Aβ1-42 (n = 94) and 82% for tTau/Aβ1-42 (n = 160). A + T + N + cases showed the highest agreement between CSF biomarkers and amyloid-PET (96%), followed by A-T-N- cases (89%). Aβ1-42/Aβ1-40 was a better marker of cerebral amyloid deposition, as identified by amyloid tracers, than Aβ1-42 alone. Combined biomarkers in CSF predicted amyloid-PET result better than single biomarkers.

Cognitive Profile in Parkinson’s Disease Dementia Patients with Low versus Normal Cerebrospinal Fluid Amyloid Beta

Introduction: In patients with Parkinson’s disease (PD), low cerebrospinal fluid (CSF) amyloid beta 1-42 (Ab42) at baseline is the most consistent CSF biomarker as a risk factor for developing dementia. Low CSF Ab42 is, however, a typical hallmark of Alzheimer’s disease (AD). Hence, low CSF Ab42 in patients with PD may indicate presence of comorbid AD pathology and may predict a more AD-like cognitive profile when they develop dementia. Our study aimed to investigate if low CSF Ab42 at baseline is associated with a more AD-like cognitive profile in PD patients with dementia. Methods: In a prospectively followed-up, population-based cohort of newly diagnosed PD patients, we compared the cognitive profile of dementia in those with a low CSF Ab42 level at baseline with that of patients who had normal levels at the time when they developed dementia. Four different cognitive domain z-scores (memory, attention, executive, visuospatial) were calculated. Patients were subdivided into three tertiles or categorized dichotomously based on the baseline CSF Ab42 levels as measured by electrochemiluminescence and ELISA. Results: During 10-year follow-up, 37 patients met the inclusion criteria. Memory domain composite z-scores, memory subtest z-scores, and the difference between long-delay free recall versus recognition scores were not significantly different between the groups. Composite z-scores of visuospatial functions significantly differed between the tertiles, which was not significant after Bonferroni correction. In the dichotomous group analysis, z-scores of visuospatial functions significantly differed between the two groups. The other cognitive domain z-scores were not significantly different. Conclusions: In patients with PD dementia, low CSF Ab42 level at baseline is not associated with a specific cognitive profile.

Alzheimer's disease and epilepsy: shared neuropathology guides current and future treatment strategies.

Epilepsy is a cause of profound disability in patients with Alzheimer's disease (AD). The risk of being diagnosed with AD increases the risk for epilepsy, and in parallel, a history of epilepsy increases the likelihood of the development of AD. This bi-directional relationship may be due to underlying shared pathophysiologic hallmarks, including decreased cerebrospinal fluid amyloid beta 42 (Aβ42), increased hyperphosphorylated tau protein, and hippocampal hyperexcitability. Additionally, there are practical treatment considerations in patients with co-morbid AD and epilepsy-namely, there is a higher risk of seizures associated with medications commonly prescribed for Alzheimer's disease patients, including antidepressants and antipsychotics such as trazodone, serotonin norepinephrine reuptake inhibitors (SNRIs), and first-generation neuroleptics. Anti-amyloid antibodies like aducanumab and lecanemab present new and unique considerations in patients with co-morbid AD and epilepsy given the risk of seizures associated with amyloid-related imaging abnormalities (ARIA) seen with this drug class. Finally, we identify and detail five active studies, including two clinical trials of levetiracetam in the respective treatment of cognition and neuropsychiatric features of AD, a study characterizing the prevalence of epilepsy in AD via prolonged EEG monitoring, a study characterizing AD biomarkers in late-onset epilepsy, and a study evaluating hyperexcitability in AD. These ongoing trials may guide future clinical decision-making and the development of novel therapeutics.

Exploring the links among peripheral immunity, biomarkers, cognition, and neuroimaging in Alzheimer's disease.

We analyzed relationships among peripheral immunity markers, cognition, Alzheimer's disease (AD)-related biomarkers, and neuroimaging to understand peripheral immunity involvement in AD. Peripheral immunity markers were assessed in AD, non-AD neurodegenerative disorders, and controls, examining their connections with cognition, AD-related biomarkers, and neuroimaging using multiple regression models. The study included 1579 participants. Higher levels of white blood cell, neutrophil, monocyte, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and lower lymphocyte-to-monocyte ratio (LMR) were associated with cognitive decline and more severe anxiety and depression. The impact of lower LMR, lymphocyte count, and higher NLR on cognitive decline is mediated through cerebrospinal fluid amyloid beta (Aβ) levels. Additionally, increased PLR, NLR, and SII were associated with brain atrophy and hippocampal Aβ deposition (amyloid positron emission tomography). Peripheral immunity markers offer a non-invasive and cost-effective means of studying AD-related pathophysiological changes, providing valuable insights into its pathogenesis and treatment. Peripheral immunity markers linked to cognitive decline and anxiety/depression.Low LMR, LYM, and high NLR linked to reduced CSF Aβ, impacting cognition.High PLR, NLR, SII associated with brain atrophy and hippocampal Aβ deposition.

Cerebrospinal fluid amyloid beta with amyloid positron emission tomography concordance rates in a heterogeneous group of patients including late-onset psychotic disorders: a retrospective cross-sectional study.

Cerebrospinal fluid amyloid beta with amyloid positron emission tomography concordance rates in a heterogeneous group of patients including late-onset psychotic disorders: a retrospective cross-sectional study.