Alzheimer's Disease Clinical Trials Research Articles

Zinc Therapy in Early Alzheimer's Disease: Safety and Potential Therapeutic Efficacy.

Zinc therapy is normally utilized for treatment of Wilson disease (WD), an inherited condition that is characterized by increased levels of non-ceruloplasmin bound (‘free’) copper in serum and urine. A subset of patients with Alzheimer’s disease (AD) or its prodromal form, known as Mild Cognitive Impairment (MCI), fail to maintain a normal copper metabolic balance and exhibit higher than normal values of non-ceruloplasmin copper. Zinc’s action mechanism involves the induction of intestinal cell metallothionein, which blocks copper absorption from the intestinal tract, thus restoring physiological levels of non-ceruloplasmin copper in the body. On this basis, it is employed in WD. Zinc therapy has shown potential beneficial effects in preliminary AD clinical trials, even though the studies have missed their primary endpoints, since they have study design and other important weaknesses. Nevertheless, in the studied AD patients, zinc effectively decreased non-ceruloplasmin copper levels and showed potential for improved cognitive performances with no major side effects. This review discusses zinc therapy safety and the potential therapeutic effects that might be expected on a subset of individuals showing both cognitive complaints and signs of copper imbalance.

The Iron Chelator Deferiprone Improves the Phenotype in a Mouse Model of Tauopathy.

Abnormally hyperphosphorylated tau is a defining pathological feature of tauopathies, such as Alzheimer's disease (AD), and accumulating evidence suggests a role for iron in mediating tau pathology that may lead to cognitive decline in these conditions. The metal chelator deferiprone (DFP), which has a high affinity for iron, is currently in clinical trials for AD and Parkinson's disease. However, the effect of DFP on tau pathology remains underexplored. We aimed to investigate the impact of chronic DFP treatment on tau pathology using a well-characterized mouse model of tauopathy (rTg(tauP301L)4510). Animals were treated daily with DFP (100 mg/kg) via oral gavage for 16 weeks. After 14 weeks, mice were tested in the Y-maze, open field, Morris water maze, and rotorod. At the end of the study, brain tissue was collected to examine metal levels (using inductively coupled plasma-mass spectrometry) and for western blot analysis of DFP on tau and iron associated pathways. DFP significantly reduced anxiety-like behavior, and revealed a trend toward improved cognitive function. This was accompanied by a decrease in brain iron levels and sarkosyl-insoluble tau. Our data also showed downregulation of the tau kinases glycogen synthase kinase 3β and cyclin dependent kinase-5 in DFP treated mice and an increase in the methylation of the catalytic subunit of protein phosphatase 2A. These data support the hypothesis that suggests that iron plays a neurotoxic role in tauopathies and may be a potential therapeutic target for this class of disorders.

Training the Workforce to Conduct Embedded Pragmatic Clinical Trials to Improve Care for People Living with Dementia and Their Caregivers.

The National Institute on Aging IMbedded Pragmatic Alzheimer's Disease and Alzheimer's Disease-Related Dementias Clinical Trials (IMPACT) Collaboratory serves as a national resource for the conduct of embedded pragmatic clinical trials to improve the care of people living with dementia (PLWD) in partnership with the healthcare systems that serve them. Inherent in this objective is the need to train and support a cadre of investigators prepared to conduct this work now and in the future. The Training Core of the IMPACT Collaboratory supports the training of investigators to become experts in this field through three objectives: (1) curricula development and dissemination; (2) network generation and navigation; and (3) a career development award program. The innovative approach of the Training Core will require developing content and providing training experiences that recognize the unique challenges of research at the intersection of health systems, pragmatic trials, and PLWD and their caregivers. Ultimately, we seek to build the nation's capacity to conduct research that bridges the gaps between efficacy studies to effectiveness research to implementation science. Although foundational resources in the methods of each of these areas are already available, few actually focus on pragmatic trials embedded within healthcare systems that focus on PLWD. To bring new interventions for PLWD from efficacy to widespread implementation, researchers must build diffusability, adaptability, heterogeneity, and scalability into the design of the intervention. In achieving these objectives, the Training Core will utilize the network of investigators, institutions, and stakeholders represented in the IMPACT Collaboratory. J Am Geriatr Soc 68:S21-S27, 2020.

Selecting Outcomes to Ensure Pragmatic Trials Are Relevant to People Living with Dementia.

Outcome measures for embedded pragmatic clinical trials (ePCTs) should reflect the lived experience of people living with dementia (PLWD) and their caregivers, yet patient- and caregiver-reported outcomes (PCROs) are rarely available in large clinical and administrative data sources. Although pragmatic methods may lead to use of existing administrative data rather than new data collected directly from PLWD, interventions are truly impactful only when they change outcomes prioritized by PLWD and their caregivers. The Patient- and Caregiver-Reported Outcomes Core (PCRO Core) of the IMbedded Pragmatic Alzheimer's Disease (AD) and AD-Related Dementias Clinical Trials (IMPACT) Collaboratory aims to promote optimal use of outcomes relevant to PLWD and their caregivers in pragmatic trials. The PCRO Core will address key scientific challenges limiting outcome measurement, such as gaps in existing measures, methodologic constraints, and burdensome data capture. PCRO Core investigators will create a searchable library of AD/AD-related dementias (ADRD) clinical outcome measures, including measures in existing data sources with potential for AD/ADRD ePCTs, and will support best practices in measure development, including pragmatic adaptation of PCROs. Working together with other Cores and Teams within the IMPACT Collaboratory, the PCRO Core will support investigators to select from existing outcome measures, and to innovate in methods for measurement and data capture. In the future, the work of the IMPACT Collaboratory may galvanize broader embedded use of outcomes that matter to PLWD and their care partners in large health systems. J Am Geriatr Soc 68:S55-S61, 2020.

Using Healthcare Data in Embedded Pragmatic Clinical Trials among People Living with Dementia and Their Caregivers: State of the Art.

Embedded pragmatic clinical trials (ePCTs) are embedded in healthcare systems as well as their data environments. For people living with dementia (PLWD), settings of care can be different from the general population and involve additional people whose information is also important. The ePCT designs have the opportunity to leverage data that becomes available through the normal delivery of care. They may be particularly valuable in Alzheimer's disease and Alzheimer's disease-related dementia (AD/ADRD), given the complexity of case identification and the diversity of care settings. Grounded in the objectives of the Data and Technical Core of the newly established National Institute on Aging Imbedded Pragmatic Alzheimer's Disease and AD-Related Dementias Clinical Trials Collaboratory (IMPACT Collaboratory), this article summarizes the state of the art in using existing data sources (eg, Medicare claims, electronic health records) in AD/ADRD ePCTs and approaches to integrating them in real-world settings. J Am Geriatr Soc 68:S49-S54, 2020.

Dissemination and Implementation of Evidence-Based Dementia Care Using Embedded Pragmatic Trials.

There are many nonpharmacologic interventions tested in randomized clinical trials that demonstrate significant benefits for people living with Alzheimer's disease (AD) and AD-related dementia, their care partners, or professional care providers. Nevertheless, with few exceptions, proven interventions have not been translated for delivery in real-world settings, such as home care, primary care, hospitals, community-based services, adult day services, assisted living, nursing homes, or other healthcare systems (HCSs). Using embedded pragmatic clinical trial (ePCT) methods is one approach that can facilitate dissemination and implementation (D&I) of dementia care interventions. The science of D&I can inform the integration of evidence-based dementia care in HCSs by offering theoretical frameworks that capture field complexities and guiding evaluation of implementation processes. Also, D&I science can suggest evidence-based strategies for implementing dementia care in HCSs. Although D&I considerations can inform each stage of dementia care intervention development, it is particularly critical when designing ePCTs. This article examines fundamental considerations for implementing dementia-specific interventions in HCSs and how best to prepare for successful dissemination upstream in the context of ePCTs, thereby illustrating the critical role of the D&I Core of the National Institute on Aging Imbedded Pragmatic Alzheimer's Disease and AD-Related Dementias Clinical Trials Collaboratory. The scientific premise of the D&I Core is that having the "end" in mind, upfront in the design and testing of dementia care programs, can lead to decision-making that optimizes the ultimate goal of wide-scale D&I of evidence-based dementia care programs in HCSs. J Am Geriatr Soc 68:S28-S36, 2020.

Statistical Considerations for Embedded Pragmatic Clinical Trials in People Living with Dementia.

There is overwhelming need for nonpharmacological interventions to improve the health and well-being of people living with dementia (PLWD). The National Institute on Aging Imbedded Pragmatic Alzheimer's Disease (AD) and AD-Related Dementias Clinical Trials (IMPACT) Collaboratory supports clinical trials of such interventions embedded in healthcare systems. The embedded pragmatic clinical trial (ePCT) is ideally suited to testing the effectiveness of complex interventions in vulnerable populations at the point of care. These trials, however, are complex to conduct and interpret, and face challenges in efficiency (i.e., statistical power) and reproducibility. In addition, trials conducted among PLWD present specific statistical challenges, including difficulty in outcomes ascertainment from PLWD, necessitating reliance on reports by caregivers, and heterogeneity in measurements across different settings or populations. These and other challenges undercut the reliability of measurement, the feasibility of capturing outcomes using pragmatic designs, and the ability to validly estimate interventions' effectiveness in real-world settings. To address these challenges, the IMPACT Collaboratory has convened a Design and Statistics Core, the goals of which are: to support the design and conduct of ePCTs directed toward PLWD and their caregivers; to develop guidance for conducting embedded trials in this population; and to educate quantitative and clinical scientists in the design, conduct, and analysis of these trials. In this article, we discuss some of the contemporary methodological challenges in this area and develop a set of research priorities the Design and Statistics Core will undertake to meet these goals. J Am Geriatr Soc 68:S68-S73, 2020.

Achieving Health Equity in Embedded Pragmatic Trials for People Living with Dementia and Their Family Caregivers.

Embedded pragmatic clinical trials (ePCTs) advance research on Alzheimer's disease/Alzheimer's disease and related dementias (AD/ADRD) in real-world contexts; however, health equity issues have not yet been fully considered, assessed, or integrated into ePCT designs. Health disparity populations may not be well represented in ePCTs without special efforts to identify and successfully recruit sites of care that serve larger numbers of these populations. The National Institute on Aging (NIA) Imbedded Pragmatic Alzheimer's disease (AD) and AD-Related Dementias (AD/ADRD) Clinical Trials (IMPACT) Collaboratory's Health Equity Team will contribute to the overall mission of the collaboratory by developing and implementing strategies to address health equity in the conduct of ePCTs and ensure the collaboratory is a national resource for all Americans with dementia. As a first step toward meeting these goals, this article reviews what is currently known about the inclusion of health disparities populations of people living with dementia (PLWD) and their caregivers in ePCTs, highlights unique challenges related to health equity in the conduct of ePCTs, and suggests priority areas in the design and implementation of ePCTs to increase the awareness and avoidance of pitfalls that may perpetuate and magnify healthcare disparities. J Am Geriatr Soc 68:S8-S13, 2020.

Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on 18F-Florbetapir PET Using ADNI Data.

Cortical amyloid quantification on PET by using the standardized uptake value ratio is valuable for research studies and clinical trials in Alzheimer disease. However, it is resource intensive, requiring co-registered MR imaging data and specialized segmentation software. We investigated the use of deep learning to automatically quantify standardized uptake value ratio and used this for classification. Using the Alzheimer's Disease Neuroimaging Initiative dataset, we identified 2582 18F-florbetapir PET scans, which were separated into positive and negative cases by using a standardized uptake value ratio threshold of 1.1. We trained convolutional neural networks (ResNet-50 and ResNet-152) to predict standardized uptake value ratio and classify amyloid status. We assessed performance based on network depth, number of PET input slices, and use of ImageNet pretraining. We also assessed human performance with 3 readers in a subset of 100 randomly selected cases. We have found that 48% of cases were amyloid positive. The best performance was seen for ResNet-50 by using regression before classification, 3 input PET slices, and pretraining, with a standardized uptake value ratio root-mean-square error of 0.054, corresponding to 95.1% correct amyloid status prediction. Using more than 3 slices did not improve performance, but ImageNet initialization did. The best trained network was more accurate than humans (96% versus a mean of 88%, respectively). Deep learning algorithms can estimate standardized uptake value ratio and use this to classify 18F-florbetapir PET scans. Such methods have promise to automate this laborious calculation, enabling quantitative measurements rapidly and in settings without extensive image processing manpower and expertise.

Reversal of Calcium Dysregulation as Potential Approach for Treating Alzheimer's Disease.

Despite decades of research and effort, there is still no effective disease-modifying treatment for Alzheimer's Disease (AD). Most of the recent AD clinical trials were targeting amyloid pathway, but all these trials failed. Although amyloid pathology is a hallmark and defining feature of AD, targeting the amyloid pathway has been very challenging due to low efficacy and serious side effects. Alternative approaches or mechanisms for our understanding of the major cause of memory loss in AD need to be considered as potential therapeutic targets. Increasing studies suggest that Ca2+ dysregulation in AD plays an important role in AD pathology and is associated with other AD abnormalities, such as excessive inflammation, increased ROS, impaired autophagy, neurodegeneration, synapse, and cognitive dysfunction. Ca2+ dysregulation in cytosolic space, Endoplasmic Reticulum (ER) and mitochondria have been reported in the context of various AD models. Drugs or strategies, to correct the Ca2+ dysregulation in AD, have been demonstrated to be promising as an approach for the treatment of AD in preclinical models. This review will discuss the mechanisms of Ca2+ dysregulation in AD and associated pathology and discuss potential approaches or strategies to develop novel drugs for the treatment of AD by targeting Ca2+ dysregulation.

Collagen hydrogel confinement of Amyloid-β (Aβ) accelerates aggregation and reduces cytotoxic effects

Alzheimer's disease (AD) is the most common form of dementia and is associated with the accumulation of amyloid-β (Aβ), a peptide whose aggregation has been associated with neurotoxicity. Drugs targeting Aβ have shown great promise in 2D in vitro models and mouse models, yet preclinical and clinical trials for AD have been highly disappointing. We propose that current in vitro culture systems for discovering and developing AD drugs have significant limitations; specifically, that Aβ aggregation is vastly different in these 2D cultures carried out on flat plastic or glass substrates vs. in a 3D environment, such as brain tissue, where Aβ confinement alters aggregation kinetics and thermodynamics. In this work, we identified attenuation of Aβ cytotoxicity in 3D hydrogel culture compared to 2D cell culture. We investigated Aβ structure and aggregation in solution vs. hydrogel using Transmission Electron Microscopy (TEM), Fluorescence Correlation Spectroscopy (FCS), and Thioflavin T (ThT) assays. Our results reveal that the equilibrium is shifted to stable extended β-sheet (ThT positive) aggregates in hydrogels and away from the relatively unstable/unstructured presumed toxic oligomeric Aβ species in solution. Volume exclusion imparted by hydrogel confinement stabilizes unfolded, presumably toxic species, promoting stable extended β-sheet fibrils. Statement of SignificanceAlzheimer's disease (AD) is a devastating disease and has been studied for over 100 years. Yet, no cure exists and only 5 prescription drugs are FDA-approved to temporarily treat the AD symptoms of declining brain functions related to thinking and memory. Why don't we have more effective treatments to cure AD or relieve AD symptoms? We propose that current culture methods based upon cells cultured on flat, stiff substrates have significant limitations for discovering and developing AD drugs. This study provides strong evidence that AD drugs should be tested in 3D culture systems as a step along the development pathway towards new, more effective drugs to treat AD.

Identification of novel candidate autoantibodies in Alzheimer's disease.

Accumulated failures in Alzheimer's disease (AD) clinical trials have highlighted an urgent need to identify additional biomarkers involved in AD. Recently, mounting evidence reported that autoantibodies are ubiquitous in human sera. However, it is unknown whether autoantibodies are upregulated in amyloid-tau biomarker-confirmed AD. A total of 40 subjects with mild dementia (Clinical Dementia Rating=1) were stratified into AD (n=16) and non-AD (n=24) groups according to their cerebrospinal fluid levels of tau and Aβ42 . Their sera were collected and analyzed using a microarray containing>1600 potential human autoantigens. Autoantibodies that were present exclusively in the AD group were identified and selected using the penetrance-based fold change method with the following criteria: penetrance fold change(AD) ≥2, frequency(AD) ≥15% and frequency(non-AD) =0%. All controls and samples passed the quality control criteria and were further used for biomarker analysis. Six autoantibodies with elevated responses to the following autoantigens were found exclusively in the AD group: nucleosome assembly protein 1-like 3 (31.3%, 5/16 subjects) and microtubule-associated protein 4, pantothenic acid kinase 3, phosphoinositide-3-kinase regulatory subunit 1, protein tyrosine phosphatase type IVA member 1 and SRY (sex-determining region Y)-box 15 (all 18.8%, 3/16 subjects). Although some identified autoantigens are linked to AD and cognitive dysfunction, the increased autoantibody levels have not been reported in AD. Autoantibodies may provide deeper insights into the pathogenesis of AD and serve as diagnostic biomarkers; their corresponding antigens can be further studied to assess their potential as therapeutic targets.

Initiation of symptomatic medication in Alzheimer's disease clinical trials: Hypothetical versus treatment policy approach.

In clinical trials in populations with mild cognitive impairment, it is common for participants to initiate concurrent symptomatic medications for Alzheimer's disease after randomization to the experimental therapy. One strategy for addressing this occurrence is to exclude any observations that occur after the concurrent medication is initiated. The rationale for this approach is that these observations might reflect a symptomatic benefit of the concurrent medication that would adversely bias efficacy estimates for an effective experimental therapy. We interrogate the assumptions underlying such an approach by estimating the effect of newly prescribed concurrent medications in an observational study, the Alzheimer's Disease Neuroimaging Initiative.

Structural Brain Magnetic Resonance Imaging to Rule Out Comorbid Pathology in the Assessment of Alzheimer's Disease Dementia: Findings from the Ontario Neurodegenerative Disease Research Initiative (ONDRI) Study and Clinical Trials Over the Past 10 Years.

Background/Objective:Structural brain magnetic resonance imaging (MRI) is not mandatory in Alzheimer’s disease (AD) research or clinical guidelines. We aimed to explore the use of structural brain MRI in AD/mild cognitive impairment (MCI) trials over the past 10 years and determine the frequency with which inclusion of standardized structural MRI acquisitions detects comorbid vascular and non-vascular pathologies.Methods:We systematically searched ClinicalTrials.gov for AD clinical trials to determine their neuroimaging criteria and then used data from an AD/MCI cohort who underwent standardized MRI protocols, to determine type and incidence of clinically relevant comorbid pathologies.Results:Of 210 AD clinical trials, 105 (50%) included structural brain imaging in their eligibility criteria. Only 58 (27.6%) required MRI. 16,479 of 53,755 (30.7%) AD participants were in trials requiring MRI. In the observational AD/MCI cohort, 141 patients met clinical criteria; 22 (15.6%) had relevant MRI findings, of which 15 (10.6%) were exclusionary for the study.Discussion:In AD clinical trials over the last 10 years, over two-thirds of participants could have been enrolled without brain MRI and half without even a brain CT. In a study sample, relevant comorbid pathology was found in 15% of participants, despite careful screening. Standardized structural MRI should be incorporated into NIA-AA diagnostic guidelines (when available) and research frameworks routinely to reduce diagnostic heterogeneity.

Sex and gender differences in Alzheimer's disease: current challenges and implications for clinical practice: Position paper of the Dementia and Cognitive Disorders Panel of the European Academy of Neurology.

Alzheimer's disease (AD) is characterized by high heterogeneity in disease manifestation, progression and risk factors. High phenotypic variability is currently regarded as one of the largest hurdles in early diagnosis and in the design of clinical trials; there is therefore great interest in identifying factors driving variability that can be used for patient stratification. In addition to genetic and lifestyle factors, the individual's sex and gender are emerging as crucial drivers of phenotypic variability. Evidence exists on sex and gender differences in the rate of cognitive deterioration and brain atrophy, and in the effect of risk factors as well as in the patterns of diagnostic biomarkers. Such evidence might be of high relevance and requires attention in clinical practice and clinical trials. However, sex and gender differences are currently seldom appreciated; importantly, consideration of sex and gender differences is not currently a focus in the design and analysis of clinical trials for AD. The objective of this position paper is (i) to provide an overview of known sex and gender differences that might have implications for clinical practice, (ii) to identify the most important knowledge gaps in the field (with a special regard to clinical trials) and (iii) to provide conclusions for future studies. This scientific statement is endorsed by the European Academy of Neurology.

Clinical Trials in Alzheimer's Disease: A Hurdle in the Path of Remedy.

Human clinical trials seek to ameliorate the disease states and symptomatic progression of illnesses that, as of yet, are largely untreatable according to clinical standards. Ideally, clinical trials test “disease-modifying drugs,” i.e., therapeutic agents that specifically modify pathological features or molecular bases of the disease and would presumably have a large impact on disease progression. In the case of Alzheimer's disease (AD), however, this approach appears to have stalled progress in the successful development of clinically useful therapies. For the last 25 years, clinical trials involving AD have centered on beta-amyloid (Aβ) and the Aβ hypothesis of AD progression and pathology. According to this hypothesis, the progression of AD begins following an accumulation of Aβ peptide, leading to eventual synapse loss and neuronal cell death: the true overriding pathological feature of AD. Clinical trials arising from the Aβ hypothesis target causal steps in the pathway in order to reduce the formation of Aβ or enhance clearance, and though agents have been successful in this aim, they remain unsuccessful in rescuing cognitive function or slowing cognitive decline. As such, further use of resources in the development of treatment options for AD that target Aβ, its precursors, or its products should be reevaluated. The purpose of this review was to give an overview of how human clinical trials are conducted in the USA and to assess the results of recent failed trials involving AD, the majority of which were based on the Aβ hypothesis. Based on these current findings, it is suggested that lowering Aβ is an unproven strategy, and it may be time to refocus on other targets for the treatment of this disease including pathological forms of tau.

Machine Learning Predictive Models Can Improve Efficacy of Clinical Trials for Alzheimer's Disease.

The ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e., placebo arm) and also would be responsive to the therapeutic intervention being studied (i.e., drug arm). One strategy to boost the power of trials is to enroll individuals who are more likely to progress targeted using data-driven predictive models. To investigate if machine learning (ML) models can effectively predict clinical disease progression (cognitive decline) in mild-to-moderate AD patients during the timeframe of a phase III clinical trial. Data from 202 participants with a diagnosis of AD at baseline from the Alzheimer's Disease Neuroimaging Initiative (ADNI) was used to train ML classifiers that can differentiate between individuals who had declining cognitive function (DC) and individuals with stable cognitive function (SC). DC was defined as any downward change in the Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-cog) score over 12 months of follow-up. SC was defined by the absence of decline in ADAS-cog. Trained models were applied to data from 77 participants from the placebo arm of the phase III trial of Semagacestat (LFAN study) to identify subgroups of SC versus DC. Only 74.8% of ADNI participants and 63.6% of LFAN participants had cognitive decline after one year of follow up. K-nearest neighbors (kNN) classifier had an accuracy of 68.3%, sensitivity of 80.1%, and specificity of 33.3% for identifying decliners in ADNI (training sample). In LFAN (validation sample), the model showed an overall accuracy of 61.3%, sensitivity of 65.5%, and specificity of 47.0% in identifying decliners at the 12 months of follow-up. The model had a positive predictive value of 80.8%, which was 17.2% more than the base prevalence of decliners. Machine learning predictive models can be effectively used to boost the power of clinical trials by reducing the sample size.

Targeted Mass Spectrometry Suggests Beta-Synuclein as Synaptic Blood Marker in Alzheimer's Disease.

Synaptic degeneration is a major hallmark of Alzheimer's disease (AD) and the best pathological correlate of cognitive dysfunction. Synaptic markers are therefore a highly desired read-out for patient diagnosis and possible follow-up in clinical trials. Several synaptic markers for AD are described in cerebrospinal fluid (CSF), but studies in blood have failed so far. Using quantitative mass spectrometry (IP-MS, MRM) we observed increased concentrations of the presynaptic protein beta-synuclein (βSyn) in CSF and blood of AD patients (n = 64, p < 0.01) and confirmed this finding in two validation cohorts (AD: n = 40 and n = 49, controls: n = 44 and n = 25). βSyn was already increased in patients with mild cognitive impairment (p < 0.01) and was also markedly increased in Creutzfeldt-Jakob disease (CJD; n = 25, p < 0.001) but not behavioral variant frontotemporal dementia (n = 16), dementia with Lewy bodies/Parkinson's disease dementia (n = 13), Parkinson's disease (n = 25), or amyotrophic lateral sclerosis (n = 30). The diagnostic sensitivity and specificity for CJD versus other neurodegenerative diseases was ≥96%. These findings suggest βSyn as a candidate blood marker for synaptic degeneration that might be used in clinical AD trials and patient follow-up as part of the recently suggested ATN biomarker panel. It can also serve in the differential diagnosis of CJD.

Pathogenic Aβ generation in familial Alzheimer's disease: novel mechanistic insights and therapeutic implications.

Neurotoxic amyloid-β peptide (Aβ) 42/43 species generated by β-secretase and γ-secretase from the β-amyloid precursor protein (APP) are believed to trigger Alzheimer's disease (AD). Relative increases of these species due to mutations in APP and presenilin/γ-secretase are associated with the vast majority of early onset familial AD cases. Important breakthroughs have recently been made in elucidating the mechanism(s) of these mutations, showing that altered substrate interactions and substrate-enzyme complex stabilities are underlying their pathogenic Aβ generation. Moreover, first structures of γ-secretase in complex with APP and Notch1 substrates allow insight into how substrate cleavage could be initiated and further progress has been made in the mechanistic understanding of γ-secretase modulators, advanced Aβ-lowering drugs. These insights could be exploited for future AD clinical trials.

Using practice effects for targeted trials or sub-group analysis in Alzheimer's disease: How practice effects predict change over time.

ObjectiveTo describe the presence of practice effects in persons with Alzheimer disease (AD) or mild cognitive impairment (MCI) and to evaluate how practice effects affect cognitive progression and the outcome of clinical trials.MethodsUsing data from a meta-database consisting of 18 studies including participants from the Alzheimer disease Cooperative Study (ADCS) and the Alzheimer Disease Neuroimaging Initiative (ADNI) with ADAS-Cog11 as the primary outcome, we defined practice effects based on the improvement in the first two ADAS-Cog11 scores and then estimated the presence of practice effects and compared the cognitive progression between participants with and without practice effects. The robustness of practice effects was investigated using CDR SB, an outcome independent the definition itself. Furthermore, we evaluated how practice effects can affect sample size estimation.ResultsThe overall percent of practice effects for AD participants was 39.0% and 53.3% for MCI participants. For AD studies, the mean change from baseline to 2 years was 12.8 points for the non-practice effects group vs 7.4 for the practice effects group; whereas for MCI studies, it was 4.1 for non-practice effects group vs 0.2 for the practice effects group. AD participants without practice effects progressed 0.9 points faster than those with practice effects over a period of 2 years in CDR-SB; whereas for MCI participants, the difference is 0.7 points. The sample sizes can be different by over 35% when estimated based on participants with/without practice effects.ConclusionPractice effects were prevalent and robust in persons with AD or MCI and affected the cognitive progression and sample size estimation. Planning of future AD or MCI clinical trials should account for practice effects to avoid underpower or considers target trials or stratification analysis based on practice effects.