CSF Alzheimer Disease Biomarkers: Time-Varying Relationships With MCI Symptom Onset and Associations With Age, Sex, and ApoE4.

BACKGROUND AND OBJECTIVES: This study aimed to examine whether baseline CSF measures of Alzheimer disease (AD)-related pathology are associated with the time to onset of mild cognitive impairment (MCI) and whether these associations differ by age, sex, Apolipoprotein E (ApoE4) status, and proximal (≤7 years) vs distal (>7 years) time to symptom onset. METHODS: Measures of amyloid (Aß1-42 and Aß1-40), phospho-tau (ptau181), and total tau (t-tau) were determined from CSF samples obtained at baseline from participants in an ongoing longitudinal project, known as the Biomarkers for Older Controls at Risk for Alzheimer Disease study (BIOCARD) study. The fully automated, Lumipulse G immunoassay was used to analyze the specimens. Cox regression models were used to examine the relationship of baseline biomarker levels with time to symptom onset of MCI and interactions with age, sex, and ApoE allelic status in subjects who progressed from normal cognition to MCI. RESULTS: Analyses included 273 participants from the BIOCARD cohort, who were cognitively normal and predominantly middle-aged at baseline, and have been followed for an average of 16 years (max = 23.6). During follow-up, 94 progressed to MCI (median time to symptom onset = 6.9 years). In Cox regression models, elevated ptau181 and t-tau levels were associated with time to MCI symptom onset if it occurred within 7 years of baseline (HR 1.386 and 1.329; p = 0.009 and 0.017, respectively), while a lower Aß42/Aß40 ratio was associated with symptom onset if it occurred >7 years from baseline (HR 0.596, p = 0.003). There were also significant 3-way CSF × age × sex interactions for ptau181 and Aß42/Aß40, with follow-up analyses indicating that associations between these biomarkers and progression to MCI were stronger among men than among women, but this difference between sexes diminished with increasing age. DISCUSSION: The lengthy follow-up of BIOCARD participants permitted an examination of time-varying associations between CSF AD biomarkers with MCI symptom onset and the influence of sex, baseline age, and ApoE4 genotype on these associations. These factors may inform clinical trial enrollment strategies, or trial duration and outcomes, which may use these measures as surrogate markers of treatment response.

Translational animal models for Alzheimer's disease: An Alzheimer's Association Business Consortium Think Tank.

Over 5 million Americans and 50 million individuals worldwide are living with Alzheimer's disease (AD). The progressive dementia associated with AD currently has no cure. Although clinical trials in patients are ultimately required to find safe and effective drugs, animal models of AD permit the integration of brain pathologies with learning and memory deficits that are the first step in developing these new drugs. The purpose of the Alzheimer's Association Business Consortium Think Tank meeting was to address the unmet need to improve the discovery and successful development of Alzheimer's therapies. We hypothesize that positive responses to new therapies observed in validated models of AD will provide predictive evidence for positive responses to these same therapies in AD patients. To achieve this goal, we convened a meeting of experts to explore the current state of AD animal models, identify knowledge gaps, and recommend actions for development of next-generation models with better predictability. Among our findings, we all recognize that models reflecting only single aspects of AD pathogenesis do not mimic AD. Models or combinations of new models are needed that incorporate genetics with environmental interactions, timing of disease development, heterogeneous mechanisms and pathways, comorbidities, and other pathologies that lead to AD and related dementias. Selection of the best models requires us to address the following: (1) which animal species, strains, and genetic backgrounds are most appropriate; (2) which models permit efficient use throughout the drug development pipeline; (3) the translatability of behavioral-cognitive assays from animals to patients; and (4) how to match potential AD therapeutics with particular models. Best practice guidelines to improve reproducibility also need to be developed for consistent use of these models in different research settings. To enhance translational predictability, we discuss a multi-model evaluation strategy to de-risk the successful transition of pre-clinical drug assets to the clinic.

Correction to: The Toronto cognitive assessment (TorCA): normative data and validation to detect amnestic mild cognitive impairment.

Upon publication of this article [1], it was brought to our attention that one of the 303 participants in the normative study should have been deleted from the database.

The Toronto Cognitive Assessment (TorCA): normative data and validation to detect amnestic mild cognitive impairment.

BACKGROUND: A need exists for easily administered assessment tools to detect mild cognitive changes that are more comprehensive than screening tests but shorter than a neuropsychological battery and that can be administered by physicians, as well as any health care professional or trained assistant in any medical setting. The Toronto Cognitive Assessment (TorCA) was developed to achieve these goals. METHODS: We obtained normative data on the TorCA (n = 303), determined test reliability, developed an iPad version, and validated the TorCA against neuropsychological assessment for detecting amnestic mild cognitive impairment (aMCI) (n = 50/57, aMCI/normal cognition). For the normative study, healthy volunteers were recruited from the Rotman Research Institute registry. For the validation study, the sample was comprised of participants with aMCI or normal cognition based on neuropsychological assessment. Cognitively normal participants were recruited from both healthy volunteers in the normative study sample and the community. RESULTS: The TorCA provides a stable assessment of multiple cognitive domains. The total score correctly classified 79% of participants (sensitivity 80%; specificity 79%). In an exploratory logistic regression analysis, indices of Immediate Verbal Recall, Delayed Verbal and Visual Recall, Visuospatial Function, and Working Memory/Attention/Executive Control, a subset of the domains assessed by the TorCA, correctly classified 92% of participants (sensitivity 92%; specificity 91%). Paper and iPad version scores were equivalent. CONCLUSIONS: The TorCA can improve resource utilization by identifying patients with aMCI who may not require more resource-intensive neuropsychological assessment. Future studies will focus on cross-validating the TorCA for aMCI, and validation for disorders other than aMCI.

The roles of inflammation and immune mechanisms in Alzheimer's disease.

The Alzheimer's Association's Research roundtable met in April 2015 to explore the role of neuroinflammatory mechanisms in the progression of Alzheimer's disease (AD). The ability of innate immune cells, particularly microglia and astrocytes, to mediate neuroinflammation in AD has been implicated as a significant contributor to disease pathogenesis. Adaptive immunity, which plays an important role in responding to injury and some diseases of the central nervous system, may contribute to neuroinflammation in AD as well. Communication between the central and peripheral immune systems may also be important in AD. An increased understanding of the physiology of the innate immune system may aid the identification of new therapeutic targets or mechanisms. The development of predictive animal models and translatable neuroinflammation biomarkers for AD would also facilitate the advancement of novel treatments for innate immunity. Important challenges impeding the advancement of new therapeutic agents and strategies to overcome them were discussed.

Improving Alzheimer's disease phase II clinical trials.

Over the past 30 years, many drugs have been studied as possible treatments for Alzheimer's disease, but only four have demonstrated sufficient efficacy to be approved as treatments, of which three are in the same class. This lack of success has raised questions both in the pharmaceutical industry and academia about the future of Alzheimer's disease therapy. The high cost and low success rate of drug development across many disease areas can be attributed, in large part, to late-stage clinical failures (Schachter and Ramoni, Nat Rev Drug Discov 2007;6:107-8). Thus, identifying in phase II, or preferably phase I, drugs that are likely to fail would have a dramatic impact on the costs associated with developing new drugs. With this in mind, the Alzheimer's Association convened a Research Roundtable on June 23 and 24, 2011, in Washington, DC, bringing together scientists from academia, industry, and government regulatory agencies to discuss strategies for improving the probability of phase II trial results predicting success when considering the go/no-go decision-making process leading to the initiation of phase III.

Accelerating drug discovery for Alzheimer's disease: best practices for preclinical animal studies.

Animal models have contributed significantly to our understanding of the underlying biological mechanisms of Alzheimer's disease (AD). As a result, over 300 interventions have been investigated and reported to mitigate pathological phenotypes or improve behavior in AD animal models or both. To date, however, very few of these findings have resulted in target validation in humans or successful translation to disease-modifying therapies. Challenges in translating preclinical studies to clinical trials include the inability of animal models to recapitulate the human disease, variations in breeding and colony maintenance, lack of standards in design, conduct and analysis of animal trials, and publication bias due to under-reporting of negative results in the scientific literature. The quality of animal model research on novel therapeutics can be improved by bringing the rigor of human clinical trials to animal studies. Research communities in several disease areas have developed recommendations for the conduct and reporting of preclinical studies in order to increase their validity, reproducibility, and predictive value. To address these issues in the AD community, the Alzheimer's Drug Discovery Foundation partnered with Charles River Discovery Services (Morrisville, NC, USA) and Cerebricon Ltd. (Kuopio, Finland) to convene an expert advisory panel of academic, industry, and government scientists to make recommendations on best practices for animal studies testing investigational AD therapies. The panel produced recommendations regarding the measurement, analysis, and reporting of relevant AD targets, th choice of animal model, quality control measures for breeding and colony maintenance, and preclinical animal study design. Major considerations to incorporate into preclinical study design include a priori hypotheses, pharmacokinetics-pharmacodynamics studies prior to proof-of-concept testing, biomarker measurements, sample size determination, and power analysis. The panel also recommended distinguishing between pilot 'exploratory' animal studies and more extensive 'therapeutic' studies to guide interpretation. Finally, the panel proposed infrastructure and resource development, such as the establishment of a public data repository in which both positive animal studies and negative ones could be reported. By promoting best practices, these recommendations can improve the methodological quality and predictive value of AD animal studies and make the translation to human clinical trials more efficient and reliable.

Developing a global strategy to prevent Alzheimer's disease: Leon Thal Symposium 2010.

The fourth Leon Thal Symposium (LTS2010) was convened in Toulouse, France, on November 3, 2010. This symposium reviewed design parameters that are necessary to develop comprehensive national databases on healthy aging. Such datasets offer the potential to serve as the foundation for a systems-approach to solve the dual public health problems of: (1) early detection of people who are at elevated risk for Alzheimer's disease, and (2) the development of interventions to delay onset of, or prevent, late-life dementia. The symposium considered three interrelated components of a National Database for Longitudinal Studies on Healthy Aging as follows: (a) a registry of healthy aging adults; (b) refined computer-based assessments for data gathering, including assessments of behavioral/memory changes associated with aging that are appropriate for broad use in nonexpert settings; and (c) high performance computing/supercomputer-based approaches for health data modeling and mining.

Developing a national strategy to prevent dementia: Leon Thal Symposium 2009.

Among the major impediments to the design of clinical trials for the prevention of Alzheimer's disease (AD), the most critical is the lack of validated biomarkers, assessment tools, and algorithms that would facilitate identification of asymptomatic individuals with elevated risk who might be recruited as study volunteers. Thus, the Leon Thal Symposium 2009 (LTS'09), on October 27-28, 2009 in Las Vegas, Nevada, was convened to explore strategies to surmount the barriers in designing a multisite, comparative study to evaluate and validate various approaches for detecting and selecting asymptomatic people at risk for cognitive disorders/dementia. The deliberations of LTS'09 included presentations and reviews of different approaches (algorithms, biomarkers, or measures) for identifying asymptomatic individuals at elevated risk for AD who would be candidates for longitudinal or prevention studies. The key nested recommendations of LTS'09 included: (1) establishment of a National Database for Longitudinal Studies as a shared research core resource; (2) launch of a large collaborative study that will compare multiple screening approaches and biomarkers to determine the best method for identifying asymptomatic people at risk for AD; (3) initiation of a Global Database that extends the concept of the National Database for Longitudinal Studies for longitudinal studies beyond the United States; and (4) development of an educational campaign that will address public misconceptions about AD and promote healthy brain aging.

A roadmap for the prevention of dementia II: Leon Thal Symposium 2008.

This document proposes an array of recommendations for a National Plan of Action to accelerate the discovery and development of therapies to delay or prevent the onset of disabling symptoms of Alzheimer's disease. A number of key scientific and public-policy needs identified in this document will be incorporated by the Alzheimer Study Group into a broader National Alzheimer's Strategic Plan, which will be presented to the 111th Congress and the Obama administration in March 2009. The Alzheimer's Strategic Plan is expected to include additional recommendations for governance, family support, healthcare, and delivery of social services.

Mechanism of gamma-secretase cleavage activation: is gamma-secretase regulated through autoinhibition involving the presenilin-1 exon 9 loop?

Maturation of gamma-secretase requires an endoproteolytic cleavage in presenilin-1 (PS1) within a peptide loop encoded by exon 9 of the corresponding gene. Deletion of the loop has been demonstrated to cause familial Alzheimer's disease. A synthetic peptide corresponding to the loop sequence was found to inhibit gamma-secretase in a cell-free enzymatic assay with an IC(50) of 2.1 microM, a value similar to the K(m) (3.5 microM) for the substrate C100. Truncation at either end, single amino acid substitutions at certain residues, sequence reversal, or randomization reduced its potency. Similar results were also observed in a cell-based assay using HEK293 cells expressing APP. In contrast to small-molecule gamma-secretase inhibitors, kinetic inhibition studies demonstrated competitive inhibition of gamma-secretase by the exon 9 peptide. Consistent with this finding, inhibitor cross-competition kinetics indicated noncompetitive binding between the exon 9 peptide and L685458, a transition-state analogue presumably binding at the catalytic site, and ligand competition binding experiments revealed no competition between L685458 and the exon 9 peptide. These data are consistent with the proposed gamma-secretase mechanism involving separate substrate-binding and catalytic sites and binding of the exon 9 peptide at the substrate-binding site, but not the catalytic site of gamma-secretase. NMR analyses demonstrated the presence of a loop structure with a beta-turn in the middle of the exon 9 peptide and a loose alpha-helical conformation for the rest of the peptide. Such a structure supports the hypothesis that this exon 9 peptide can adopt a distinct conformation, one that is compact enough to occupy the putative substrate-binding site without necessarily interfering with binding of small molecule inhibitors at other sites on gamma-secretase. We hypothesize that gamma-secretase cleavage activation may be a result of a cleavage-induced conformational change that relieves the inhibitory effect of the intact exon 9 loop occupying the substrate-binding site on the immature enzyme. It is possible that the DeltaE9 mutation causes Alzheimer's disease because cleavage activation of gamma-secretase is no longer necessary, alleviating constraints on Abeta formation.

The mechanism of gamma-secretase: multiple inhibitor binding sites for transition state analogs and small molecule inhibitors.

Transition state analogs pepstatin methylester (PME) and L685458 have been shown to inhibit gamma-secretase non-competitively (Tian, G., Sobotka-Briner, C., Zysk, J., Liu, X., Birr, C., Sylvester, M. A., Edwards, P. D., Scott, C. W., and Greenberg, B. D. (2002) J. Biol. Chem. 277, 31499-31505). This unusual kinetics suggests physical separation of the sites for substrate binding and catalysis with binding of the transition state analogs to the catalytic site and not to the substrate binding site. Methods of inhibitor cross-competition kinetics and competition ligand binding were utilized to address whether non-transition state small molecule inhibitors, which also display non-competitive inhibition of gamma-secretase, inhibit the enzyme by binding to the catalytic site as well. Inhibitor cross-competition kinetics indicated competitive binding between the transition state analogs PME and L685458 and between small molecules arylsulfonamides and benzodiazepines, but non-competitive binding between the transition state analogs and the small molecule inhibitors. These results were indicative of two inhibitor binding sites, one for transition state analogs and the other for non-transition state small molecule inhibitors. The presence of two inhibitor binding sites for two different classes of inhibitors was corroborated by results from competition ligand binding using [3H]L685458 as the radioligand. Although L685458 and PME displaced the radioligand at the same concentrations as for enzyme inhibition, arylsulfonamides and benzodiazepines did not displace the radioligand at their Ki values, a result consistent with the presence of two inhibitor binding sites. These findings provide useful insights into the catalytic and regulatory mechanisms of gamma-secretase that may facilitate the design of novel gamma-secretase inhibitors.

Linear non-competitive inhibition of solubilized human gamma-secretase by pepstatin A methylester, L685458, sulfonamides, and benzodiazepines.

Cerebral deposition of amyloid beta-protein (A beta) is believed to play a key role in the pathogenesis of Alzheimer's disease. Because A beta is produced from the processing of amyloid beta-protein precursor (APP) by beta- and gamma-secretases, these enzymes are considered important therapeutic targets for identification of drugs to treat Alzheimer's disease. Unlike beta-secretase, which is a monomeric aspartyl protease, gamma-secretase activity resides as part of a membrane-bound, high molecular weight, macromolecular complex. Pepstatin and L685458 are among several structural classes of gamma-secretase inhibitors identified so far. These compounds possess a hydroxyethylene dipeptide isostere of aspartyl protease transition state analogs, suggesting gamma-secretase may be an aspartyl protease. However, the mechanism of inhibition of gamma-secretase by pepstatin and L685458 has not been elucidated. In this study, we report that pepstatin A methylester and L685458 unexpectedly displayed linear non-competitive inhibition of gamma-secretase. Sulfonamides and benzodiazepines, which do not resemble transition state analogs of aspartyl proteases, also displayed potent, non-competitive inhibition of gamma-secretase. Models to rationalize how transition state analogs inhibit their targets by non-competitive inhibition are discussed.

Proteolysis of chimeric beta-amyloid precursor proteins containing the Notch transmembrane domain yields amyloid beta-like peptides.

gamma-Secretase is an unusual intramembranous protease that has been reported to cleave the beta-amyloid precursor protein (APP) near the middle of its transmembrane domain (TMD) but cleave Notch near the cytoplasmic end of its TMD. To ascertain whether the TMD sequence of the substrate determines where gamma-secretase cleaves and whether the region just before the TMD participates in recognition by the enzyme, we expressed chimeric human APP molecules containing either the TMD or pre-TMD regions of Notch or other transmembrane proteins. APP chimeras bearing either the Notch or the amyloid precursor-like protein-2 TMD released similar amounts of approximately 4-kDa amyloid beta-peptide (Abeta)-like peptides as did intact APP. Mass spectrometry revealed that the principal Abeta-like peptide ended at residue 40, indicating cleavage at the middle of the Notch TMD in the chimera. Generation of Abeta-like peptides was significantly decreased when the APP TMD was replaced by those of SREBP-1 or human epithelial growth factor receptor 3. Replacement of the APP pre-TMD region (Abeta 10-28) with that of SREBP-1 increased generation of Abeta-like peptides, while those of human epithelial growth factor receptor 3 or amyloid precursor-like protein-2 decreased it. We conclude that gamma-secretase can cleave near the middle of the Notch TMD, that Abeta-like peptides may arise during Notch processing, and that the pre-TMD sequence of the substrate influences recognition or binding by the enzyme.