Assessment of Preanalytical Cerebrospinal Fluid Handling and Storage Factors on Measurement of Aß1-42, Aß1-40, and pTau181 Using an Automated Chemiluminescent Platform.

BACKGROUND: Standardizing cerebrospinal fluid (CSF) laboratory protocols will improve the reliability and availability of clinical biomarker testing required for prescription of novel Alzheimer disease (AD) therapies. This study evaluated several preanalytical handling and storage factors common to ß-amyloid1-42 (Aß1-42), ß-amyloid1-40 (Aß1-40), and phosphorylated tau (pTau181) concentrations including storage at different temperatures, extended cap contact, various mixing methods, and multiple freeze-thaw cycles. METHODS: Aß1-42, Aß1-40, and pTau181 concentrations were measured using LUMIPULSE G1200 automated assays. Samples were collected in polypropylene tubes of various volumes. Sample cap-contact was evaluated by storing samples in upright and inverted positions at either 4°C for 1 week or -80°C for 1 month. To assess mixing methods, samples were freeze-thawed and mixed by inversion, vortex, horizontal roller, or unmixed prior to assay sampling. The impact of successive freeze-thaw cycles was assessed through freezing, thawing, and analyzing CSF samples. RESULTS: Short-term storage at 4°C did not affect Aß1-42, Aß1-40, or pTau181 measurements in any tube type. Tube cap contact affected Aß1-42 in 2.5 mL tubes and pTau181 levels in 10 mL tubes. No difference was observed between mixing methods. After 4 freeze-thaw cycles, Aß1-42 significantly decreased but Aß1-40 remained unchanged. Utilizing the Aß1-42/Aß1-40 ratio, Aß1-42 values normalized, maintaining ratio values within ±5% of baseline measurements. CONCLUSIONS: Storage of CSF at 4°C for 1 week or -80°C for 1 month did not significantly affect Aß1-42, Aß1-40, pTau181, or associated ratio measurements. Tube cap-contact impacted pTau181 and pTau181/Aß1-42 values in larger tubes. Mixing methods are equivalent. The Aß1-42/Aß1-40 ratio compensates for freeze-thaw variability up to 4 cycles.

Assessment of the Correlation and Diagnostic Accuracy between Cerebrospinal Fluid and Plasma Alzheimer's Disease Biomarkers: A Comparison of the Lumipulse and Simoa Platforms.

We compared the clinical and analytical performance of Alzheimer's disease (AD) plasma biomarkers measured using the single-molecule array (Simoa) and Lumipulse platforms. We quantified the plasma levels of amyloid beta 42 (Aß42), Aß40, phosphorylated tau (Ptau181), and total tau biomarkers in 81 patients with mild cognitive impairment (MCI), 30 with AD, and 16 with non-AD dementia. We found a strong correlation between the Simoa and Lumipulse methods. Concerning the clinical diagnosis, Simoa Ptau181/Aß42 (AUC 0.739, 95% CI 0.592-0.887) and Lumipulse Aß42 and Ptau181/Aß42 (AUC 0.735, 95% CI 0.589-0.882 and AUC 0.733, 95% CI 0.567-0.900) had the highest discriminating power. However, their power was significantly lower than that of CSF Aß42/Aß40, as measured by Lumipulse (AUC 0.879, 95% CI 0.766-0.992). Simoa Ptau181 and Lumipulse Ptau181/Aß42 were the markers most consistent with the CSF Aß42/Aß40 status (AUC 0.801, 95% CI 0.712-0.890 vs. AUC 0.870, 95% CI 0.806-0.934, respectively) at the ≥2.127 and ≥0.084 cut-offs, respectively. The performance of the Simoa and Lumipulse plasma AD assays is weaker than that of CSF AD biomarkers. At present, the analysed AD plasma biomarkers may be useful for screening to reduce the number of lumbar punctures in the clinical setting.

[Assessment of the significance of dilated perivascular spaces and nocture arterial hypertension in the development of Alzheimer's disease]. / Otsenka znacheniya rasshirennykh perivaskulyarnykh prostranstv i nochnoi arterial'noi gipertenzii v razvitii bolezni Al'tsgeimera.

OBJECTIVE: To study the severity and localization of dilated perivascular spaces (DPVS), the levels of protein markers of amyloidosis and neurodegeneration in the cerebrospinal fluid (CSF) at different daily blood pressure (BP) profiles in patients with Alzheimer's disease (AD) and other types of cognitive impairment. MATERIAL AND METHODS: A total of 119 people, aged 53 to 92 years, including 55 patients with AD, 27 patients with vascular cognitive disorders (VCD), 19 patients with frontotemporal degeneration (FTD). All patients underwent BP monitoring for 24 hours using a standard oscillometric measurement method, lumbar puncture to assess Aß-42 and Aß-40 amyloid protein, total and phosphorylated tau protein in the CSF, magnetic resonance imaging tomography of the brain with subsequent assessment of the severity of expansion and localization of DPVS according to the G.M. Potter scale. RESULTS: In 58.3% of patients with AD, there is no adequate reduction in BP at night in comparison with patients with VCD (p<0.05). A significant degree of expansion of the DPVS turned out to be most typical for patients with AD: grade 3 was detected in 45.7% of patients, and the maximum, grade 4, was detected in 13.4%. At the same time, DPVSs were significantly more often detected in the group of subjects with insufficient reduction in diastolic BP (DBP) at night. A strong inverse correlation was established between the level of Aß-42 in the CSF and the variability of DBP at night (r= -0.92; p<0.05). The decrease in the level of Aß-42 in AD, especially at the prodromal stage, is directly related to the low variability of DBP at night, which is more characteristic of an insufficient decrease or increase in BP during night sleep. CONCLUSION: Patients with AD were characterized by an insufficient decrease in BP at night, which is associated with the severity and degree of maximum expansion of the DPVS. A decrease in the level of Aß-42 amyloid protein in the CSF strongly correlates with the variability of DBP at night.

New plasma LC-MS/MS assays for the quantitation of beta-amyloid peptides and identification of apolipoprotein E proteoforms for Alzheimer's disease risk assessment.

Early detection of Alzheimer's disease (AD) represents an unmet clinical need. Beta-amyloid (Aß) plays an important role in AD pathology, and the Aß42/40 peptide ratio is a good indicator for amyloid deposition. In addition, variants of the apolipoprotein E (APOE) gene are associated with variable AD risk. Here, we describe the development and validation of high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays for plasma Aß40 and Aß42 quantitation, as well as apolipoprotein E (ApoE) proteotype determination as a surrogate for APOE genotype. Aß40 and Aß42 were simultaneously immunoprecipitated from plasma, proteolytically digested, and quantitated by LC-MS/MS. ApoE proteotype status was qualitatively assessed by targeting tryptic peptides from the ApoE2, ApoE3, and ApoE4 proteoforms. Both assays were validated according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. Within-run precision was 1.8%-4.2% (Aß40), 1.9%-7.2% (Aß42), and 2.6%-8.3% (Aß42/40 ratio). Between-run precision was 3.5%-5.9% (Aß40), 3.8%-8.0% (Aß42), and 3.3%-8.7% (Aß42/40 ratio). Both Aß40 and Aß42 were linear from 10 to 2500 pg/mL. Identified ApoE proteotypes had 100% concordance with APOE genotypes. We have developed a precise, accurate, and sensitive high-throughput LC-MS/MS assay for plasma Aß40, Aß42, and proteoforms of ApoE.

Insights from Turkey's big data: unraveling the preventability, pathogenesis, and risk management of Alzheimer's disease (AD).

Extensive research into dementia has more recently honed in on several key areas. These areas include the advancement of techniques such as the accumulation of amyloid-ß and tau proteins, the monitoring of cerebral hypometabolism rates etc. The primary objective of this study is to explore the intricate interplay between Alzheimer's disease (AD)-other dementias (D) and various chronic illnesses in terms of time, intensity, and connectivity. In this context, we retrospectively examined data of 149,786 individuals aged 65 and above who received diagnoses of AD and D in the year 2020. At first, logistic regression (LR) analysis has been made with "sex", "age" and "foreigner" (citizenship status) independent variables for AD and D. The LR models shows that while "sex" and "age" variables have a small rate on the risk of developing AD/D, it is detected that being a foreigner increase the risk of AD and D as 69.8% and 88.5% respectively. Besides, the LR models have middle-level success prediction rate for both of the two dependent variables. Additionally, we used the parallel coordinates graphs method within the R Studio to visualize their relationships and connections. The findings of this investigation strongly suggest that AD/D don't stand as isolated conditions, but rather stem from intricate interactions and progressive processes involving diverse chronic diseases over time. Notably, ailments including hypertension, coronary artery disease, diabetes, hyperlipidemia, and psychological disorders, contribute substantially to the emergence of both AD and D. This study highlights that the fight against AD/D can only be possible with next-generation prophylactic interventions that can predict and manage risks. Such an approach holds the potential to potentially lower AD and dementia to levels that are amenable to treatment.

How donanemab data address the coverage with evidence development questions.

The Centers for Medicare & Medicaid Services (CMS) established a class-based National Coverage Determination (NCD) for monoclonal antibodies directed against amyloid for Alzheimer's disease (AD) with patient access through Coverage with Evidence Development (CED) based on three questions. This review, focused on donanemab, answers each of these CED questions with quality evidence. TRAILBLAZER-ALZ registration trials are presented with supporting literature and real-world data to answer CED questions for donanemab. TRAILBLAZER-ALZ registration trials demonstrated that donanemab significantly slowed cognitive and functional decline in amyloid-positive early symptomatic AD participants, and lowered their risk of disease progression while key safety risks occurred primarily within the first 6 months and then declined. Donanemab meaningfully improved health outcomes with a manageable safety profile in an early symptomatic AD population, representative of Medicare populations across diverse practice settings. The donanemab data provide the necessary level of evidence for CMS to open a reconsideration of their NCD. HIGHLIGHTS: Donanemab meaningfully improved outcomes in trial participants with early symptomatic Alzheimer's disease. Comorbidities in trial participants were consistent with the Medicare population. Co-medications in trial participants were consistent with the Medicare population. Risks associated with treatment tended to occur in the first 6 months. Risks of amyloid-related imaging abnormalities were managed with careful observation and magnetic resonance imaging monitoring.

Beyond CSF and Neuroimaging Assessment: Evaluating Plasma miR-145-5p as a Potential Biomarker for Mild Cognitive Impairment and Alzheimer's Disease.

Alzheimer's disease (AD) is the most common cause of dementia. New strategies for the early detection of MCI and sporadic AD are crucial for developing effective treatment options. Current techniques used for diagnosis of AD are invasive and/or expensive, so they are not suitable for population screening. Cerebrospinal fluid (CSF) biomarkers such as amyloid ß1-42 (Aß1-42), total tau (T-tau), and phosphorylated tau181 (P-tau181) levels are core biomarkers for early diagnosis of AD. Several studies have proposed the use of blood-circulating microRNAs (miRNAs) as potential novel early biomarkers for AD. We therefore applied a novel approach to identify blood-circulating miRNAs associated with CSF biomarkers and explored the potential of these miRNAs as biomarkers of AD. In total, 112 subjects consisting of 28 dementia due to AD cases, 63 MCI due to AD cases, and 21 cognitively healthy controls were included. We identified seven Aß1-42-associated plasma miRNAs, six P-tau181-associated plasma miRNAs, and nine Aß1-42-associated serum miRNAs. These miRNAs were involved in AD-relevant biological processes, such as PI3K/AKT signaling. Based on this signaling pathway, we constructed an miRNA-gene target network, wherein miR-145-5p has been identified as a hub. Furthermore, we showed that miR-145-5p performs best in the prediction of both AD and MCI. Moreover, miR-145-5p also improved the prediction performance of the mini-mental state examination (MMSE) score. The performance of this miRNA was validated using different datasets including an RT-qPCR dataset from plasma samples of 23 MCI cases and 30 age-matched controls. These findings indicate that blood-circulating miRNAs that are associated with CSF biomarkers levels and specifically plasma miR-145-5p alone or combined with the MMSE score can potentially be used as noninvasive biomarkers for AD or MCI screening in the general population, although studies in other AD cohorts are necessary for further validation.

Association between neuropsychological assessment and amyloid status in a clinical setting.

OBJECTIVE: Large research cohorts show robust associations between neuropsychological tests and Alzheimer's disease (AD) biomarkers, but studies in clinical settings are limited. The increasing availability of AD biomarkers to the practicing clinician makes it important to understand the relationship between comprehensive clinical neuropsychological assessment and biomarker status. This study examined concordance between practicing clinical neuropsychologists' diagnostic impressions and AD biomarker status in patients seen at an outpatient medical center, with a secondary aim of defining the characteristics of discordant cases. METHOD: Participants (N = 79) seen for clinical neuropsychological assessment who subsequently underwent lumbar puncture or amyloid positron emission tomography imaging were identified via retrospective chart review. Concordance between clinical neuropsychological diagnosis (non-AD, indeterminate, possible/probable AD) and AD biomarker status (negative, indeterminate, positive) was determined. Individual test score data were used to examine between-group differences based on amyloid status. RESULTS: AD biomarker positive and negative patients did not differ on individual neuropsychological tests after correcting for multiple comparisons, though the small number of AD biomarker indeterminate individuals performed better than biomarker positive patients. However, there was 76.7% concordance between neuropsychologists' diagnostic impressions and AD biomarker status (88% sensitivity and 55% specificity of neuropsychological assessment in detecting AD biomarker status). AD biomarker negative patients diagnosed as possible/probable AD (discordant) versus non-AD (concordant) had significantly lower Neuropsychological Assessment Battery Story Delayed Recall, higher Wechsler Adult Intelligence Scale-Fourth Edition Coding, and higher Trail-Making A (i.e., an amnestic memory profile). CONCLUSIONS: Comprehensive neuropsychological assessment showed modest concordance with AD biomarker status in patients seen in an outpatient medical center for routine clinical care. Low specificity for the clinical diagnosis of AD could be explained by the multiplicity of etiologies that cause memory impairment (i.e., TAR DNA-binding protein 43, suspected non-AD pathology). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Cost-effectiveness comparison between blood biomarkers and conventional tests in Alzheimer's disease diagnosis.

Dementia management has evolved with drugs such as lecanemab, shifting management from palliative care to early diagnosis and intervention. However, the administration of these drugs presents challenges owing to the invasiveness, high cost and limited availability of amyloid-PET and cerebrospinal fluid tests for guiding drug administration. Our manuscript explores the potential of less invasive blood biomarkers as a diagnostic method, with a cost-effectiveness analysis and a comparison with traditional tests. Our findings suggest that blood biomarkers are a cost-effective alternative, but with lower accuracy, indicating the need for multiple specific biomarkers for precision. This underscores the importance of future research on new blood biomarkers and their clinical efficacy.

Cognitive Reserve in Parkinson's Disease without Dementia: ß-Amyloid and Metabolic Assessment.

BACKGROUND: Cognitive reserve (CR) is the mismatch between preserved cognition and neuropathological damage. Amyloidopathy in Parkinson's disease (PD) could be associated with faster progression to dementia, but the putative protective effect of CR is unknown. OBJECTIVES: To evaluate the effect of CR on ß-amyloid burden and brain metabolism in non-demented PD subjects. METHODS: Participants with PD (n = 53) underwent a clinical evaluation, [18 F]-fluorodeoxyglucose and [18 F]-flutemetamol positron emission tomography magnetic resonances, and were classified according to CR. The metabolic pattern of 16 controls was compared to PD subjects. RESULTS: The PD subjects showed hypometabolism mainly in the bilateral posterior cortex. Superior-CR subjects (n = 22) exhibited better cognitive performance, increased amyloid burden, and higher metabolism in several right hemisphere areas compared to low-medium-CR subjects (n = 31). CONCLUSIONS: Higher CR in non-demented PD is associated with better cognitive performance, which might reduce vulnerability to the effect of ß-amyloid. Whether superior CR leads to protection against metabolic deterioration, and predominantly right hemisphere involvement, deserves further exploration.

Stochastic model of Alzheimer's disease progression using two-state Markov chains.

In 2016, Hao and Friedman developed a deterministic model of Alzheimer's disease progression using a system of partial differential equations. This model describes the general behavior of the disease, however, it does not incorporate the molecular and cellular stochasticity intrinsic to the underlying disease processes. Here we extend the Hao and Friedman model by modeling each event in disease progression as a stochastic Markov process. This model identifies stochasticity in disease progression, as well as changes to the mean dynamics of key agents. We find that the pace of neuron death increases whereas the production of the two key measures of progression, Tau and Amyloid beta proteins, decelerates when stochasticity is incorporated into the model. These results suggest that the non-constant reactions and time-steps have a significant effect on the overall progression of the disease.

Category Switching Test: A Brief Amyloid-ß-Sensitive Assessment Tool for Mild Cognitive Impairment.

The Category Switching Test (CaST) is a verbal fluency test with active semantic category switching. This study aimed to explore the association between CaST performance and brain amyloid-ß (Aß) burden in patients with mild cognitive impairment (MCI) and the neurofunctional mechanisms. A total of 112 participants with MCI underwent Florbetapir positron emission tomography, resting-state functional magnetic resonance imaging, and a neuropsychological test battery. The high Aß burden group had worse CaST performance than the low-burden group. CaST score and left middle temporal gyrus fractional amplitude of low-frequency fluctuations (fALFF) related inversely to the global Florbetapir standardized uptake value rate. Functional connectivity between the left middle temporal gyrus and frontal lobe decreased widely and correlated with CaST score in the high Aß burden group. Thus, CaST score and left middle temporal gyrus fALFF were valuable in discriminating high Aß burden. CaST might be useful in screening for MCI with high Aß burden.

Impact of simulated reduced injected dose on the assessment of amyloid PET scans.

PURPOSE: To investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [18F]flutemetamol and [18F]florbetaben. METHODS: Cognitively impaired and unimpaired individuals (N = 250, 36% Aß-positive) were included and injected with [18F]flutemetamol (N = 175) or [18F]florbetaben (N = 75). PET scans were acquired in list-mode (90-110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aß-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aß- and Aß + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated. RESULTS: At 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [18F]flutemetamol and [18F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aß- from Aß + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers. CONCLUSION: This proof-of-concept study showed that for both [18F]flutemetamol and [18F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.

Associations of sleep duration and daytime sleepiness with plasma amyloid beta and cognitive performance in cognitively unimpaired, middle-aged and older African Americans.

STUDY OBJECTIVES: Given the established racial disparities in both sleep health and dementia risk for African American populations, we assess cross-sectional and longitudinal associations of self-report sleep duration (SRSD) and daytime sleepiness with plasma amyloid beta (Aß) and cognition in an African American (AA) cohort. METHODS: In a cognitively unimpaired sample drawn from the African Americans Fighting Alzheimer's in Midlife (AA-FAiM) study, data on SRSD, Epworth Sleepiness Scale, demographics, and cognitive performance were analyzed. Aß40, Aß42, and the Aß42/40 ratio were quantified from plasma samples. Cross-sectional analyses explored associations between baseline predictors and outcome measures. Linear mixed-effect regression models estimated associations of SRSD and daytime sleepiness with plasma Aß and cognitive performance levels and change over time. RESULTS: One hundred and forty-seven participants comprised the cross-sectional sample. Baseline age was 63.2 ±â€…8.51 years. 69.6% self-identified as female. SRSD was 6.4 ±â€…1.1 hours and 22.4% reported excessive daytime sleepiness. The longitudinal dataset included 57 participants. In fully adjusted models, neither SRSD nor daytime sleepiness is associated with cross-sectional or longitudinal Aß. Associations with level and trajectory of cognitive test performance varied by measure of sleep health. CONCLUSIONS: SRSD was below National Sleep Foundation recommendations and daytime sleepiness was prevalent in this cohort. In the absence of observed associations with plasma Aß, poorer self-reported sleep health broadly predicted poorer cognitive function but not accelerated decline. Future research is necessary to understand and address modifiable sleep mechanisms as they relate to cognitive aging in AA at disproportionate risk for dementia. CLINICAL TRIAL INFORMATION: Not applicable.

Efficacy assessment of an active tau immunotherapy in Alzheimer's disease patients with amyloid and tau pathology: a post hoc analysis of the "ADAMANT" randomised, placebo-controlled, double-blind, multi-centre, phase 2 clinical trial.

BACKGROUND: Tau pathology correlates with and predicts clinical decline in Alzheimer's disease. Approved tau-targeted therapies are not available. METHODS: ADAMANT, a 24-month randomised, placebo-controlled, parallel-group, double-blinded, multicenter, Phase 2 clinical trial (EudraCT2015-000630-30, NCT02579252) enrolled 196 participants with Alzheimer's disease; 119 are included in this post-hoc subgroup analysis. AADvac1, active immunotherapy against pathological tau protein. A machine learning model predicted likely Amyloid+Tau+ participants from baseline MRI. STATISTICAL METHODS: MMRM for change from baseline in cognition, function, and neurodegeneration; linear regression for associations between antibody response and endpoints. RESULTS: The prediction model achieved PPV of 97.7% for amyloid, 96.2% for tau. 119 participants in the full analysis set (70 treatment and 49 placebo) were classified as A+T+. A trend for CDR-SB 104-week change (estimated marginal means [emm] = -0.99 points, 95% CI [-2.13, 0.13], p = 0.0825]) and ADCS-MCI-ADL (emm = 3.82 points, CI [-0.29, 7.92], p = 0.0679) in favour of the treatment group was seen. Reduction was seen in plasma NF-L (emm = -0.15 log pg/mL, CI [-0.27, -0.03], p = 0.0139). Higher antibody response to AADvac1 was related to slowing of decline on CDR-SB (rho = -0.10, CI [-0.21, 0.01], p = 0.0376) and ADL (rho = 0.15, CI [0.03, 0.27], p = 0.0201), and related to slower brain atrophy (rho = 0.18-0.35, p < 0.05 for temporal volume, whole cortex, and right and left hippocampus). CONCLUSIONS: In the subgroup of ML imputed or CSF identified A+T+, AADvac1 slowed AD-related decline in an antibody-dependent manner. Larger anti-tau trials are warranted. FUNDING: AXON Neuroscience SE.

Montreal Cognitive Assessment in Mild Cognitive Impairment: Relationship with Cerebrospinal Fluid Biomarkers and Conversion to Dementia.

BACKGROUND: Mild cognitive impairment (MCI) is considered a prodromal state of dementia. Abnormal values of cerebrospinal fluid Alzheimer's disease biomarkers (CSF-AD-b) have been associated with a higher risk of conversion to dementia (due to Alzheimer's disease), but studies evaluating the ability of Montreal Cognitive Assessment (MoCA) in this task are lacking. OBJECTIVE: This study aims to investigate the relationship between MoCA and CSF-AD-b, as well as the ability of those tools to predict conversion to dementia. METHODS: Taking advantage of our MCI cohort with biological characterization on longitudinal follow-up (180 patients followed for 62.6 months during which 41.3% converted), we computed MoCA and MMSE z-scores, using Portuguese normative data. The performance in MoCA z-score was correlated with CSF-AD-b and the relative time to conversion and risk according to baseline characteristics were analyzed using Kaplan-Meier analysis and Cox regression models. RESULTS: MoCA z-scores were correlated with Aß42 (p = 0.026), t-tau (p = 0.033), and p-tau (p = 0.01). Impaired MMSE (p < 0.001) and MoCA z-scores (p = 0.019), decreased Aß42 (p < 0.001) and increased t-tau (p < 0.001) and p-tau (p < 0.001) were associated with shorter estimated time of conversion. Aß42 (p < 0.001) and MMSE z-scores (p = 0.029) were independent predictors of conversion. For those with at least 9 years of education, MoCA z-score (p = 0.004) (but not MMSE) was an independent predictor of conversion as well as Aß42. CONCLUSIONS: This study confirms the role of CSF-AD-b, namely Aß42, in predicting conversion from MCI to dementia and suggests the utility of MoCA in predicting conversion in highly educated subjects, supporting its use in the evaluation of MCI patients.

MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum.

Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniques can detect complex patterns in MRI data and have potential for noninvasive characterization of ATN status. Purpose To use deep learning to predict PET-determined ATN biomarker status using MRI and readily available diagnostic data. Materials and Methods MRI and PET data were retrospectively collected from the Alzheimer's Disease Imaging Initiative. PET scans were paired with MRI scans acquired within 30 days, from August 2005 to September 2020. Pairs were randomly split into subsets as follows: 70% for training, 10% for validation, and 20% for final testing. A bimodal Gaussian mixture model was used to threshold PET scans into positive and negative labels. MRI data were fed into a convolutional neural network to generate imaging features. These features were combined in a logistic regression model with patient demographics, APOE gene status, cognitive scores, hippocampal volumes, and clinical diagnoses to classify each ATN biomarker component as positive or negative. Area under the receiver operating characteristic curve (AUC) analysis was used for model evaluation. Feature importance was derived from model coefficients and gradients. Results There were 2099 amyloid (mean patient age, 75 years ± 10 [SD]; 1110 male), 557 tau (mean patient age, 75 years ± 7; 280 male), and 2768 FDG PET (mean patient age, 75 years ± 7; 1645 male) and MRI pairs. Model AUCs for the test set were as follows: amyloid, 0.79 (95% CI: 0.74, 0.83); tau, 0.73 (95% CI: 0.58, 0.86); and neurodegeneration, 0.86 (95% CI: 0.83, 0.89). Within the networks, high gradients were present in key temporal, parietal, frontal, and occipital cortical regions. Model coefficients for cognitive scores, hippocampal volumes, and APOE status were highest. Conclusion A deep learning algorithm predicted each component of PET-determined ATN status with acceptable to excellent efficacy using MRI and other available diagnostic data. © RSNA, 2023 Supplemental material is available for this article.

Reconceptualization of the Erlangen Score for the Assessment of Dementia Risk: The ERlangen Score.

BACKGROUND: The established Erlangen Score (ES) for the interpretation of cerebrospinal fluid (CSF) biomarkers in the diagnostics of Alzheimer's disease (AD) uses markers of amyloidopathy and tauopathy, equally weighted to form an easy-interpretable ordinal scale. However, these biomarkers are not equally predictive for AD. OBJECTIVE: The higher weighting of the Aß42/Aß40 ratio, as a reconceptualized ERlangen Score (ERS), was tested for advantages in diagnostic performance. METHODS: Non-demented subjects (N = 154) with a mean follow up of 5 years were assigned to a group ranging from 0 to 4 in ES or ERS. Psychometric trajectories and dementia risk were assessed. RESULTS: The distribution of subjects between ES and ERS among the groups differed considerably, as grouping allocated 32 subjects to ES group 2, but only 2 to ERS group 2. The discriminative accuracy between the ES (AUC 73.2%, 95% CI [64.2, 82.2]) and ERS (AUC 72.0%, 95% CI [63.1, 81.0]) for dementia risk showed no significant difference. Without consideration of the Aß42/Aß40 ratio in ES grouping, the optimal cut-off of the ES shifted to ≥2. CONCLUSIONS: The ERS showed advantages over the ES in test interpretation with comparable overall test performance, as fewer cases were allocated to the intermediate risk group. The established cut-off of ≥2 can be maintained for the ERS, whereas it must be adjusted for the ES when determining the Aß42/Aß40 ratio.

Biomarkers and Risk Assessment of Alzheimer's Disease in Low- and Middle-Income Countries.

Dementia is a chronic syndrome which is common among the elderly and is associated with significant morbidity and mortality for patients and their caregivers. Alzheimer's disease (AD), the most common form of clinical dementia, is biologically characterized by the deposition of amyloid-ß plaques and neurofibrillary tangles in the brain. The onset of AD begins decades before manifestation of symptoms and clinical diagnosis, underlining the need to shift from clinical diagnosis of AD to a more objective diagnosis using biomarkers. Having performed a literature search of original articles and reviews on PubMed and Google Scholar, we present this review detailing the existing biomarkers and risk assessment tools for AD. The prevalence of dementia in low- and middle-income countries (LMICs) is predicted to increase over the next couple of years. Thus, we aimed to identify potential biomarkers that may be appropriate for use in LMICs, considering the following factors: sensitivity, specificity, invasiveness, and affordability of the biomarkers. We also explored risk assessment tools and the potential use of artificial intelligence/machine learning solutions for diagnosing, assessing risks, and monitoring the progression of AD in low-resource settings. Routine use of AD biomarkers has yet to gain sufficient ground in clinical settings. Therefore, clinical diagnosis of AD will remain the mainstay in LMICs for the foreseeable future. Efforts should be made towards the development of low-cost, easily administered risk assessment tools to identify individuals who are at risk of AD in the population. We recommend that stakeholders invest in education, research and development targeted towards effective risk assessment and management.