Search

Background and objectivesThis 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.MethodsMeasures of amyloid (Aβ1-42 and Aβ1-40), 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.ResultsAnalyses 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 Aβ42/Aβ40 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 Aβ42/Aβ40, 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.DiscussionThe 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.

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.

Pulse-chase studies were utilized to demonstrate the effect of beta-secretase cleavage of beta-amyloid precursor protein (APP) in the endoplasmic reticulum/intermediate compartment of NT2N cells. Results obtained demonstrated that the turnover of intracellular APPbeta was slower than the turnover of newly synthesized APP sub(FL), confirming that APPbeta was produced from APP sub(FL) inside NT2N neurons even before secretion.

One of the pathological hallmarks of Alzheimer's disease (AD) is the senile plaque; such plaques are observed in regions of the cerebral cortex and in some other brain regions of patients with AD. In recent years, researchers have identified important biochemical constituents of senile plaques. Among these is the beta-amyloid protein, which seems to be the result of abnormal processing of another protein termed beta-amyloid precursor protein (beta-APP). There is growing evidence that the abnormalities of Alzheimer's disease are not limited to the brain. Although most researchers believe that the amyloid found in senile plaques is produced by local brain cells, it is important to determine which other tissues are manufacturing beta-APP. Using specific antibodies that bind to beta-APP, researchers examined tissue specimens from a wide range of organs and structures from patients with Alzheimer's disease. Beta-APP was found in the pituitary gland and the adrenal gland. It was also found in sensory ganglia, the clusters of sensory cells outside the central nervous system. Within the sensory ganglia, beta-APP was found in both the nerve cells themselves and the so-called ''satellite'' cells which serve auxiliary functions. Curiously, beta-APP was also observed in megakaryocytes, the cells in the bone marrow that serve as the source of platelets circulating in the blood. The antibody reaction with heart muscle and skeletal muscle was equivocal, so it is not clear whether beta-APP is absent from these tissues or present in only small amounts. Beta-APP was not found in liver, spleen, kidney, thyroid gland, lung, tongue, skin, ovary, urinary bladder, or aorta. (Consumer Summary produced by Reliance Medical Information, Inc.)

A study was conducted, by using the smaller peptides, to examine amino acids that are important in regulating the enzyme activity and to determine the smallest peptide sequence with inhibitory effects. The result shows that the exon 9 peptide inhibits gamma-secretase by binding exclusively to the substrate site, affecting substrate binding without perturbing the catalytic site directly.