Alzheimer's Disease Studies Research Articles

Clinical performance and robustness evaluation of plasma amyloid-β42/40 prescreening.

Further evidence is needed to support the use of plasma amyloid β (Aβ) biomarkers as Alzheimer's disease prescreening tools. This study evaluated the clinical performance and robustness of plasma Aβ42 /Aβ40 for amyloid positivity prescreening. Data were collected from 333 BioFINDER and 121 Alzheimer's Disease Neuroimaging Initiative study participants. Risk and predictive values versus percentile of plasma Aβ42 /Aβ40 evaluated the actionability of plasma Aβ42 /Aβ40 , and simulations modeled the impact of potential uncertainties and biases. Amyloid PET was the brain amyloidosis reference standard. Elecsys plasma Aβ42 /Aβ40 could potentially rule out amyloid pathology in populations with low-to-moderate amyloid positivity prevalence. However, simulations showed small measurement or pre-analytical errors in Aβ42 and/or Aβ40 cause misclassifications, impacting sensitivity or specificity. The minor fold change between amyloid PET positive and negative cases explains the biomarkers low robustness. Implementing plasma Aβ42 /Aβ40 for routine clinical use may pose significant challenges, with misclassification risks. Plasma Aβ42 /Aβ40 ruled out amyloid PET positivity in a setting of low amyloid-positive prevalence. Including (pre-) analytical errors or measurement biases caused misclassifications. Plasma Aβ42 /Aβ40 had a low inherent dynamic range, independent of analytical method. Other blood biomarkers may be easier to implement as robust prescreening tools.

Alleged Fabrication in Alzheimer's Studies Worries Patients, Not Researchers in the Field

Alleged Fabrication in Alzheimer's Studies Worries Patients, Not Researchers in the Field

Tau positron emission tomography in preclinical Alzheimer's disease.

Rates of tau accumulation in cognitively unimpaired older adults are subtle, with magnitude and spatial patterns varying in recent reports. Regional accumulation also likely varies in the degree to which accumulation is amyloid-β-dependent. Thus, there is a need to evaluate the pattern and consistency of tau accumulation across multiple cognitively unimpaired cohorts and how these patterns relate to amyloid burden, in order to design optimal tau end points for clinical trials. Using three large cohorts of cognitively unimpaired older adults, the Anti-Amyloid Treatment in Asymptomatic Alzheimer's and companion study, Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (n = 447), the Alzheimer's Disease Neuroimaging Initiative (n = 420) and the Harvard Aging Brain Study (n = 190), we attempted to identify regions with high rates of tau accumulation and estimate how these rates evolve over a continuous spectrum of baseline amyloid deposition. Optimal combinations of regions, tailored to multiple ranges of baseline amyloid burden as hypothetical clinical trial inclusion criteria, were tested and validated. The inferior temporal cortex, fusiform gyrus and middle temporal cortex had the largest effect sizes of accumulation in both longitudinal cohorts when considered individually. When tau regions of interest were combined to find composite weights to maximize the effect size of tau change over time, both longitudinal studies exhibited a similar pattern-inferior temporal cortex, almost exclusively, was optimal for participants with mildly elevated amyloid β levels. For participants with highly elevated baseline amyloid β levels, combined optimal composite weights were 53% inferior temporal cortex, 31% amygdala and 16% fusiform. At mildly elevated levels of baseline amyloid β, a sample size of 200/group required a treatment effect of 0.40-0.45 (40-45% slowing of tau accumulation) to power an 18-month trial using the optimized composite. Neither a temporal lobe composite nor a global composite reached 80% power with 200/group with an effect size under 0.5. The focus of early tau accumulation on the medial temporal lobe has resulted from the observation that the entorhinal cortex is the initial site to show abnormal levels of tau with age. However, these abnormal levels do not appear to be the result of a high rate of accumulation in the short term, but possibly a more moderate rate occurring early with respect to age. While the entorhinal cortex plays a central role in the early appearance of tau, it may be the inferior temporal cortex that is the critical region for rapid tau accumulation in preclinical Alzheimer's disease.

Power and Sample Size for Longitudinal Models in R -- The longpower Package and Shiny App

Longitudinal studies are ubiquitous in medical and clinical research. Sample size computations are critical to ensure that these studies are sufficiently powered to provide reliable and valid inferences. There are several methodologies for calculating sample sizes for longitudinal studies that depend on many considerations including the study design features, outcome type and distribution, and proposed analytical methods. We briefly review the literature and describe sample size formulas for continuous longitudinal data. We then apply the methods using example studies comparing treatment versus control groups in randomized trials assessing treatment effect on clinical outcomes. We also introduce a Shiny app that we developed to assist researchers with obtaining required sample sizes for longitudinal studies by allowing users to enter required pilot estimates. For Alzheimer's studies, the app can estimate required pilot parameters using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Illustrative examples are used to demonstrate how the package and app can be used to generate sample size and power curves. The package and app are designed to help researchers easily assess the operating characteristics of study designs for Alzheimer's clinical trials and other research studies with longitudinal continuous outcomes. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu).

Estimating the longitudinal trajectory of cognitive function measurement using short-term data with different disease stages: Application in Alzheimer's disease.

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by a gradual decline in cognitive function over a few decades. The Mini-Mental State Examination (MMSE) is a widely used measure for evaluating global cognitive functioning. Characterizing the longitudinal trajectory of the MMSE in the population of interest is important to detect AD onset for preventive intervention. In this study, we formulate a new class of longitudinal trajectory modeling for MMSE from short-term individual data based on an ordinary differential equation. The proposed method models the relationship between individual decline speed of MMSE and the average MMSE using the fractional polynomial function model and subsequently estimates the longitudinal trajectory of MMSE by solving the ordinary differential equation for the estimated model. The appropriate model for trajectory estimation is selected based on the proposed criterion for quantifying the goodness of trajectory fit. The accuracy of the trajectory estimation of the proposed method was demonstrated via simulation studies. The proposed method was successfully applied to MMSE data from the Japanese Alzheimer's Disease Neuroimaging Initiative study.

Predicting Amyloid Positivity in Cognitively Unimpaired Older Adults: A Machine Learning Approach Using A4 Data.

To develop and test the performance of the Positive Aβ Risk Score (PARS) for prediction of β-amyloid (Aβ) positivity in cognitively unimpaired individuals for use in clinical research. Detecting Aβ positivity is essential for identifying at-risk individuals who are candidates for early intervention with amyloid targeted treatments. We used data from 4,134 cognitively normal individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study. The sample was divided into training and test sets. A modified version of AutoScore, a machine learning-based software tool, was used to develop a scoring system using the training set. Three risk scores were developed using candidate predictors in various combinations from the following categories: demographics (age, sex, education, race, family history, body mass index, marital status, and ethnicity), subjective measures (Alzheimer's Disease Cooperative Study Activities of Daily Living-Prevention Instrument, Geriatric Depression Scale, and Memory Complaint Questionnaire), objective measures (free recall, Mini-Mental State Examination, immediate recall, digit symbol substitution, and delayed logical memory scores), and APOE4 status. Performance of the risk scores was evaluated in the independent test set. PARS model 1 included age, body mass index (BMI), and family history and had an area under the curve (AUC) of 0.60 (95% CI 0.57-0.64). PARS model 2 included free recall in addition to the PARS model 1 variables and had an AUC of 0.61 (0.58-0.64). PARS model 3, which consisted of age, BMI, and APOE4 information, had an AUC of 0.73 (0.70-0.76). PARS model 3 showed the highest, but still moderate, performance metrics in comparison with other models with sensitivity of 72.0% (67.6%-76.4%), specificity of 62.1% (58.8%-65.4%), accuracy of 65.3% (62.7%-68.0%), and positive predictive value of 48.1% (44.1%-52.1%). PARS models are a set of simple and practical risk scores that may improve our ability to identify individuals more likely to be amyloid positive. The models can potentially be used to enrich trials and serve as a screening step in research settings. This approach can be followed by the use of additional variables for the development of improved risk scores. This study provides Class II evidence that in cognitively unimpaired individuals PARS models predict Aβ positivity with moderate accuracy.

Predictors of who Serves as an Alzheimer's Disease Research Participant's Study Partner and the Impact of their Relationship on Study Partners' Reports on Participants.

Background: Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD) research typically requires participants to enroll with a "study partner" (SP). Little is known about what predicts who steps into the SP role or whether the SP's relationship to the participant affects their reports of disease severity.Methods: Health and Retirement Study data (HRS), collected prior to the Aging, Demographics and Memory Study (ADAMS), was used to identify sociocultural factors that predict who serves as a SP in ADAMS. SP-reported outcomes were compared between three types of participant-SP relationships: spousal, adult child, and other.Results: Spouses (35%) and adult children (39%) were similarly likely to serve as SPs. Factors predicting who served differed. In multivariable analyses, adult children rated participants less impaired than spouses on measures of memory, judgment, and organizational abilities (p < .05). Conclusions: The participant-SP relationship has independent effects on the SP's reports of the severity of cognitive impairments.

Simulated Electroconvulsive Therapy: A Novel Approach to a Control Group in Clinical Trials.

Agitation is the most common behavioral symptom of Alzheimer disease (AD) affecting approximately 40% to 60% of the AD population, yet there are no Food and Drug Administration-approved therapies for the myriad of behavioral or psychological symptoms of dementia. There is growing evidence from naturalistic studies that electroconvulsive therapy (ECT) is a safe and effective treatment for agitation in AD patients who are refractory to pharmacotherapy and behavioral interventions. Despite the existing evidence, ECT remains underused because of stigma, lack of education, and concerns regarding adverse cognitive effects. Randomized controlled clinical trials of ECT are an opportunity to provide high-quality evidence of ECT as a safe and efficacious treatment for agitation in the AD population. We describe the methods for the Electroconvulsive Therapy in Alzheimer's Dementia study, which uses a novel, simulated ECT (S-ECT) control group to conduct a single-blind efficacy study of ECT for the treatment of agitation and aggression in individuals with moderate to severe AD. We discuss the rationale, study design, methodology, ethical and practical challenges, and management strategies in using an S-ECT group as the comparator arm in this randomized controlled trial of ECT in AD-related treatment refractory agitation and aggression. Validation of the safety and efficacy of ECT in patients with advanced AD with refractory agitation and aggression is necessary. This can be accomplished through creative formulation of S-ECT groups that effectively maintain the blind while providing scientific integrity.

Associations of Stages of Objective Memory Impairment With Amyloid PET and Structural MRI: The A4 Study.

Background and ObjectivesThe goal of this work was to investigate the neuroimaging correlates of the Stages of Objective Memory Impairment (SOMI) system operationalized with the Free and Cued Selective Reminding Test (FCSRT), a widely used episodic memory measure.MethodsThe FCSRT begins with a study phase in which items (e.g., grapes) are identified in response to unique semantic cues (e.g., fruit) that are used in the test phase to prompt recall of items not retrieved by free recall. There are 3 test trials of the 16 items (maximum 48). Data from 4,484 cognitively unimpaired participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) study were used. All participants had amyloid PET imaging, and a subset of 1,262 β-amyloid (Aβ)–positive had structural MRIs. We compared the Aβ mean cortical standardized uptake value ratio (SUVR) and volumetric measures of hippocampus, parahippocampal gyrus, entorhinal cortex, and inferior temporal cortex between the 5 SOMI stages.ResultsParticipants had a mean age of 71.3 (SD 4.6) years; 40.6% were male; and 34.6% were APOE ε4 positive. Half had no memory impairment; the other half had retrieval deficits, storage limitations, or both. Analysis of covariance in the entire sample while controlling for age, sex, education, and APOE ε4 showed that individuals in higher SOMI stages had higher global amyloid SUVR (p < 0.001). Both SOMI-4 and -3 subgroups had higher amyloid SUVR than SOMI-0 and SOMI-1 subgroups. Individuals in higher SOMI stages had smaller hippocampal volume (p = 0.003), entorhinal cortex (p < 0.05), and inferior temporal lobes (p < 0.05), but there was no difference between parahippocampal gyrus volume of different SOMI stages. Pairwise comparison of SOMI subgroups showed that the SOMI-4, -3, and -2 subgroups had smaller hippocampal volume than the SOMI-0 and -1 subgroup. The SOMI-4 subgroup had significantly smaller entorhinal cortex and smaller inferior temporal lobe compared to all other groups.DiscussionPresence of Alzheimer disease pathology is closely related to memory impairment according to SOMI stages in the cognitively unimpaired sample of A4. Results from structural MRIs suggest that memory storage impairment (SOMI-3 and -4) is present when there is widespread medial temporal lobe atrophy.Trial Registration InformationClinicalTrials.gov identifier: NCT02008357.Classification of EvidenceThis study provides Class I evidence that, in normal older individuals, higher stages of memory impairment assessed with FCSRT were associated with higher amyloid imaging burden and lower volume of hippocampus, entorhinal cortex, and inferior temporal lobes.

Regression analysis of additive hazards model with sparse longitudinal covariates.

Additive hazards model is often used to complement the proportional hazards model in the analysis of failure time data. Statistical inference of additive hazards model with time-dependent longitudinal covariates requires the availability of the whole trajectory of the longitudinal process, which is not realistic in practice. The commonly used last value carried forward approach for intermittently observed longitudinal covariates can induce biased parameter estimation. The more principled joint modeling of the longitudinal process and failure time data imposes strong modeling assumptions, which is difficult to verify. In this paper, we propose methods that weigh the distance between the observational time of longitudinal covariates and the failure time, resulting in unbiased regression coefficient estimation. We establish the consistency and asymptotic normality of the proposed estimators. Simulation studies provide numerical support for the theoretical findings. Data from an Alzheimer's study illustrate the practical utility of the methodology.

Functional hybrid factor regression model for handling heterogeneity in imaging studies.

This paper develops a functional hybrid factor regression modelling framework to handle the heterogeneity of many large-scale imaging studies, such as the Alzheimer's disease neuroimaging initiative study. Despite the numerous successes of those imaging studies, such heterogeneity may be caused by the differences in study environment, population, design, protocols or other hidden factors, and it has posed major challenges in integrative analysis of imaging data collected from multicentres or multistudies. We propose both estimation and inference procedures for estimating unknown parameters and detecting unknown factors under our new model. The asymptotic properties of both estimation and inference procedures are systematically investigated. The finite-sample performance of our proposed procedures is assessed by using Monte Carlo simulations and a real data example on hippocampal surface data from the Alzheimer's disease study.

Effects of Subcortical Atrophy and Alzheimer's Pathology on Cognition in Elderly Type 2 Diabetes: The Alzheimer's Disease Neuroimaging Initiative Study.

BackgroundSubcortical atrophy and increased cerebral β-amyloid and tau deposition are linked to cognitive decline in type 2 diabetes. However, whether and how subcortical atrophy is related to Alzheimer’s pathology in diabetes remains unclear. This study therefore aimed to investigate subcortical structural alterations induced by diabetes and the relationship between subcortical alteration, Alzheimer’s pathology and cognition.MethodsParticipants were 150 patients with type 2 diabetes and 598 propensity score-matched controls without diabetes from the Alzheimer’s Disease Neuroimaging Initiative. All subjects underwent cognitive assessments, magnetic resonance imaging (MRI), and apolipoprotein E (ApoE) genotyping, with a subset that underwent amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) assays to determine cerebral β-amyloid deposition (n = 337) and CSF p-tau (n = 433). Subcortical structures were clustered into five modules based on Pearson’s correlation coefficients of volumes across all subjects: the ventricular system, the corpus callosum, the limbic system, the diencephalon, and the striatum. Using structural equation modeling (SEM), we investigated the relationships among type 2 diabetes, subcortical structural alterations, and AD pathology.ResultsCompared with the controls, the diabetic patients had significant reductions in the diencephalon and limbic system volumes; moreover, patients with longer disease duration (>6 years) had more severe volume deficit in the diencephalon. SEM suggested that type 2 diabetes, age, and the ApoE ε4 allele (ApoE-ε4) can affect cognition via reduced subcortical structure volumes (total effect: age > ApoE-ε4 > type 2 diabetes). Among them, age and ApoE-ε4 strongly contributed to AD pathology, while type 2 diabetes neither directly nor indirectly affected AD biomarkers.ConclusionOur study suggested the subcortical atrophy mediated the association of type 2 diabetes and cognitive decline. Although both type 2 diabetes and AD are correlated with subcortical neurodegeneration, type 2 diabetes have no direct or indirect effect on the cerebral amyloid deposition and CSF p-tau.

Saponins and flavonoids from Bacopa floribunda plant extract exhibit antioxidant and anti-inflammatory effects on amyloid beta 1-42-induced Alzheimer's disease in BALB/c mice

Ethnopharmacological relevanceBacopa floribunda (BF), a locally available plant has been employed traditionally as memory enhancer in Southwestern, Nigeria. It has been utilized in traditional and Ayurvedic medicine as brain tonic for enhancing memory, anti-aging and forestalling series of psychological disorders. However, there is a dearth of scientific information on the mechanism(s) of action of important phytochemicals from BF extract on dementia. Aim of the studyAlzheimer's disease, the commonest form of dementia has been postulated to triple by 2050 as a result of increase in life expectancy. This study therefore assessed and compared the possible mechanism(s) of action of flavonoids and saponins from BF on Amyloid beta (Aβ1-42)-induced dementia in male BALB/c mice. Materials and methodsEighty (80) healthy BALB/c mice divided into 10 groups (n = 8) were given a single bilateral ICV injection of Aβ1-42 or normal saline. Graded doses of Saponins and flavonoids (50, 100 and 200 mg/kg) were used as treatment for 21 days. Hippocampal homogenates were assayed for the levels of antioxidants, oxidative stress and neuroinflammatory markers. In vitro antioxidant activity of flavonoids and saponins were equally assessed using standard procedures. The extent of microglial activation was quantified through immunohistochemistry procedure. ResultsAβ1-42 successfully caused a spike in hippocampal levels of MDA, IL1β, TNF-α including MPO levels and invariably decreased antioxidant activities. Likewise an increase in reactive microglia (microgliosis) was observed. However, crude saponins and flavonoids from BF were able to suppress microgliosis, oxidative stress and neuroinflammation induced by Aβ1- 42 and were observed to be more effective at higher doses of saponins (100 mg/kg and 200 mg/kg) and flavonoid (100 mg/kg). ConclusionsPhytochemicals from BF efficiently exhibited dose dependent alleviation of some symptoms associated with Alzheimer's disease.

The neuroinflammatory marker sTNFR2 relates to worse cognition and tau in women across the Alzheimer's disease spectrum.

IntroductionDespite women showing greater Alzheimer's disease (AD) prevalence, tau burden, and immune/neuroinflammatory response, whether neuroinflammation impacts cognition differently in women versus men and the biological basis of this impact remain unknown. We examined sex differences in how cerebrospinal fluid (CSF) neuroinflammation relates to cognition across the aging–mild cognitive impairment (MCI)–AD continuum and the mediating role of phosphorylated tau (p‐tau) versus other AD biomarkers.MethodsParticipants included 284 individuals from the Alzheimer's Disease Neuroimaging Initiative study. CSF neuroinflammatory markers included interleukin‐6, tumor necrosis factor α, soluble tumor necrosis factor receptor 2 (sTNFR2), and chitinase‐3‐like protein 1. AD biomarkers were CSF p‐tau181 and amyloid beta1‐42 levels and magnetic resonance imaging measures of hippocampal and white matter hyperintensity volumes.ResultsWe found a sex‐by‐sTNFR2 interaction on Mini‐Mental State Examination and Clinical Dementia Rating‐Sum of Boxes. Higher levels of sTNFR2 related to poorer cognition in women only. Among biomarkers, only p‐tau181 eliminated the female‐specific relationships between neuroinflammation and cognition.DiscussionWomen may be more susceptible than men to the adverse effects of sTNFR2 on cognition with a potential etiological link with tau to these effects.

Cell type-specific Alzheimer's disease polygenic risk scores are associated with distinct disease processes in preclinical Alzheimer's disease.

Conventional polygenic risk score (PRS) summarizes genetic risk throughout the genome and lacks biological specificity. Here, leveraging human brain single nucleus RNA sequencing (sNuc-Seq) data, we introduce a new method to capture cell-type specific Alzheimer's disease (AD) PRS, and implicate different cell types in distinct disease processes in preclinical AD. Cognitively unimpaired (CU) older adults of European descent who participated in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) study screening PET were included in this study. Cortical amyloid-β burden (Aβ) was quantified as cortical composite SUVR from the florbetapir PET. Screening cognition was measured with Preclinical Alzheimer Cognitive Composite (PACC). We defined cell type-specific genes as genes expressed higher in a given cell type (FDR<0.05) compared to other cell types in a published human neocortex sNucSeq study, for eight major cell types identified from the same study. Published AD genome-wide association study results were processed with PRS-CS to infer posterior effect size of each genetic variant, and we derived cell type-specific ADPRS by weighted summation and standardization of the genetic risk of AD localized to cell type-specific genes. We excluded the APOE region from ADPRS, and adjusted for APOE ε4, ε2, age, sex, and the first three genotype principal components in all analyses. In CU older adults from the A4 screen data (n=2961; 71.3±4.8 years old), microglia-specific ADPRS had the strongest association with higher Aβ (beta=0.018, p=2.0×10-8 ), while neuron-specific ADPRSs showed weaker associations (Figure 1A). By contrast, excitatory neuron-specific ADPRS had the strongest association with lower PACC (additionally adjusted for years of education; beta=-0.16, p=1.0×10-4 ; Figure 1B), and this association remained significant even after adjusting for Aβ (beta=-0.14, p=6.1×10-4 ). The excitatory neuron-specific ADPRS was negatively associated with years of education (beta=-0.12, p=0.018), suggesting a shared heritability between neuron-specific AD risk and lower cognitive reserve. These results further implicate microglia in fibrillar Aβ accumulation and support the neuronal role in cognitive reserve. Cell type-specific ADPRSs derived using our novel method demonstrate specific relationships with AD pathology and cognition, and may improve power to predict progression during the preclinical stages of AD.

Exploring older adults' experiences using technology during a viral pandemic

BackgroundOlder adults are at greater risk for morbidity and mortality associated with COVID‐19. Spatial distancing and sequestering practices are recommended to limit viral exposure. Older adults adopting these practices are at increased risk of social isolation and adverse health outcomes. Remote technologies offer various platforms for satisfying socialization and healthcare needs while sequestering. Understanding how older adults are using technology has implications for wellbeing during a pandemic.MethodResearchers attempted to contact all participants enrolled in the University of Kentucky Alzheimer's Disease Research Center longitudinal study via telephone to survey technology use (n = 706). Participants were contacted directly, except for demented participants, whose primary caregivers were contacted to respond on their behalf, when possible. Participants and caregivers gave their assent verbally to complete the voluntary survey, the procedures of which were approved by the IRB. The surveys consisted of validated instruments to gauge the extent of use of and comfort with technology. Spearman correlations, chi‐square tests, and t‐tests were used to explore data.ResultUltimately, 384 participants were reached and 332 consented to participate. Most reported reliable home internet access (91.5%) and some internet use (90.6%). Recent feelings of loneliness were not related to any technology‐related variables (all ps > 0.29) other than decreasing with greater willingness to use telehealth (Rho = ‐0.11, p = 0.06). Those who reported a lack of comfort with technology (n = 76) were less likely to text messaging (67% vs 78%) and social media (56% vs 69%), ps ≤ 0.06, but felt socially connected using technology at similar levels (82% vs 75%), p = 0.22. Nearly 70% of this group reported they would use technology more with training. Across all participants, willingness to use telehealth was not related to frequency of frustration with tech (Rho = 0, p = 0.99).ConclusionThe results suggest that some older adults’ use of technology is limited by familiarity. Lack of familiarity does not appear to create a barrier to using telehealth nor does frustration with technology appear to limit telehealth use. The findings have implications for supporting older adults sequestered during a pandemic but potentially more broadly.

A joint model for multivariate longitudinal and survival data to discover the conversion to Alzheimer's disease.

Alzheimer's disease (AD) is an incurable and progressive disease that starts from mild cognitive impairment and deteriorates over time. Examining the effects of patients' longitudinal cognitive decline on time to conversion to AD and obtaining a reliable diagnostic model are therefore critical to the evaluation of AD prognosis and early treatment. Previous studies either assess patients' cognitive impairment through a single cognitive test or assume it changes linearly across time, thereby leading to an incomplete measure of cognitive decline or overlooking the subtle trajectory pattern of patients' cognitive impairment. This study develops a new joint model to address these shortcomings. First, a dynamic factor analysis model is adopted to characterize cognitive impairment through multiple cognitive measures in a comprehensive manner. Second, a spline-based random coefficient model is proposed to reveal possibly nonlinear trajectories of patients' cognitive decline. Finally, a proportional hazard model is considered to examine the effects of time-invariant markers and time-variant cognitive impairment on AD hazards. A Bayesian approach coupled with spline approximation techniques and MCMC methods is developed to conduct statistical inference. The application of the proposed method to the Alzheimer's Disease Neuroimaging Initiative study provides new insights into the prevention of AD and shows a high prediction capacity of the proposed method.

Differences Between Plasma and Cerebrospinal Fluid Glial Fibrillary Acidic Protein Levels Across the Alzheimer Disease Continuum

Glial fibrillary acidic protein (GFAP) is a marker of reactive astrogliosis that increases in the cerebrospinal fluid (CSF) and blood of individuals with Alzheimer disease (AD). However, it is not known whether there are differences in blood GFAP levels across the entire AD continuum and whether its performance is similar to that of CSF GFAP. To evaluate plasma GFAP levels throughout the entire AD continuum, from preclinical AD to AD dementia, compared with CSF GFAP. This observational, cross-sectional study collected data from July 29, 2014, to January 31, 2020, from 3 centers. The Translational Biomarkers in Aging and Dementia (TRIAD) cohort (Montreal, Canada) included individuals in the entire AD continuum. Results were confirmed in the Alzheimer's and Families (ALFA+) study (Barcelona, Spain), which included individuals with preclinical AD, and the BioCogBank Paris Lariboisière cohort (Paris, France), which included individuals with symptomatic AD. Plasma and CSF GFAP levels measured with a Simoa assay were the main outcome. Other measurements included levels of CSF amyloid-β 42/40 (Aβ42/40), phosphorylated tau181 (p-tau181), neurofilament light (NfL), Chitinase-3-like protein 1 (YKL40), and soluble triggering receptor expressed on myeloid cells 2 (sTREM2) and levels of plasma p-tau181 and NfL. Results of amyloid positron emission tomography (PET) were available in TRIAD and ALFA+, and results of tau PET were available in TRIAD. A total of 300 TRIAD participants (177 women [59.0%]; mean [SD] age, 64.6 [17.6] years), 384 ALFA+ participants (234 women [60.9%]; mean [SD] age, 61.1 [4.7] years), and 187 BioCogBank Paris Lariboisière participants (116 women [62.0%]; mean [SD] age, 69.9 [9.2] years) were included. Plasma GFAP levels were significantly higher in individuals with preclinical AD in comparison with cognitively unimpaired (CU) Aβ-negative individuals (TRIAD: Aβ-negative mean [SD], 185.1 [93.5] pg/mL, Aβ-positive mean [SD], 285.0 [142.6] pg/mL; ALFA+: Aβ-negative mean [SD], 121.9 [42.4] pg/mL, Aβ-positive mean [SD], 169.9 [78.5] pg/mL). Plasma GFAP levels were also higher among individuals in symptomatic stages of the AD continuum (TRIAD: CU Aβ-positive mean [SD], 285.0 [142.6] pg/mL, mild cognitive impairment [MCI] Aβ-positive mean [SD], 332.5 [153.6] pg/mL; AD mean [SD], 388.1 [152.8] pg/mL vs CU Aβ-negative mean [SD], 185.1 [93.5] pg/mL; Paris: MCI Aβ-positive, mean [SD], 368.6 [158.5] pg/mL; AD dementia, mean [SD], 376.4 [179.6] pg/mL vs CU Aβ-negative mean [SD], 161.2 [67.1] pg/mL). Plasma GFAP magnitude changes were consistently higher than those of CSF GFAP. Plasma GFAP more accurately discriminated Aβ-positive from Aβ-negative individuals than CSF GFAP (area under the curve for plasma GFAP, 0.69-0.86; area under the curve for CSF GFAP, 0.59-0.76). Moreover, plasma GFAP levels were positively associated with tau pathology only among individuals with concomitant Aβ pathology. This study suggests that plasma GFAP is a sensitive biomarker for detecting and tracking reactive astrogliosis and Aβ pathology even among individuals in the early stages of AD.

Discovery of Umibecestat (CNP520): A Potent, Selective, and Efficacious β-Secretase (BACE1) Inhibitor for the Prevention of Alzheimer's Disease.

After identification of lead compound 6, 5-amino-1,4-oxazine BACE1 inhibitors were optimized in order to improve potency, brain penetration, and metabolic stability. Insertion of a methyl and a trifluoromethyl group at the 6-position of the 5-amino-1,4-oxazine led to 8 (NB-360), an inhibitor with a pKa of 7.1, a very low P-glycoprotein efflux ratio, and excellent pharmacological profile, enabling high central nervous system penetration and exposure. Fur color changes observed with NB-360 in efficacy studies in preclinical animal models triggered further optimization of the series. Herein, we describe the steps leading to the discovery of 3-chloro-5-trifluoromethyl-pyridine-2-carboxylic acid [6-((3R,6R)-5-amino-3,6-dimethyl-6-trifluoromethyl-3,6-dihydro-2H-[1,4]oxazin-3-yl)-5-fluoro-pyridin-2-yl]amide 15 (CNP520, umibecestat), an inhibitor with superior BACE1/BACE2 selectivity and pharmacokinetics. CNP520 reduced significantly Aβ levels in mice and rats in acute and chronic treatment regimens without any side effects and thus qualified for Alzheimer's disease prevention studies in the clinic.

Advanced Nanoparticular Approaches to Combat Alzheimer's Disease.

Alzheimer's disease (AD) is a neurological disease that affects many of the world's rapidly ageing population. In the etiology of Alzheimer's disease (AD), the involvement of amyloid β (Aβ) plaque accumulation and oxidative stress in the brain have important roles. Various drugs have been proposed to prevent and treat AD, but delivering these therapeutic agents to the brain is difficult. Over the last decade, nanoparticle-mediated drug delivery represents one promising strategy to increase the CNS penetration of several therapeutic moieties successfully. Different nanocarriers are being investigated to treat and diagnose AD. NTDDS (nanotechnology-based drug delivery systems) can be used in various methods to improve patient compliance and treatment outcomes. However, literature analysis revealed that clinical activities, such as NTDDS application in Alzheimer's disease research lag behind despite extensive research. This review gives an account of the BBB and discusses the literature on some drugs, which are successfully encapsulated as nanoparticles for a future therapeutic approach. It also emphasizes the current clinical studies for Alzheimer's disease therapy.