Recent developments in Alzheimer's disease therapeutics

Alzheimer's disease is a devastating neurological disorder that affects more than 37 million people worldwide. The economic burden of Alzheimer's disease is massive; in the United States alone, the estimated direct and indirect annual cost of patient care is at least $100 billion. Current FDA-approved drugs for Alzheimer's disease do not prevent or reverse the disease, and provide only modest symptomatic benefits. Driven by the clear unmet medical need and a growing understanding of the molecular pathophysiology of Alzheimer's disease, the number of agents in development has increased dramatically in recent years. Truly *disease-modifying' therapies that target the underlying mechanisms of Alzheimer's disease have now reached late stages of human clinical trials. Primary targets include beta-amyloid, whose presence and accumulation in the brain is thought to contribute to the development of Alzheimer's disease, and tau protein which, when hyperphosphorylated, results in the self-assembly of tangles of paired helical filaments also believed to be involved in the pathogenesis of Alzheimer's disease. In this review, we briefly discuss the current status of Alzheimer's disease therapies under study, as well the scientific context in which they have been developed

Bayesian latent time joint mixed-effects model of progression in the Alzheimer's Disease Neuroimaging Initiative.

IntroductionWe characterize long-term disease dynamics from cognitively healthy to dementia using data from the Alzheimer's Disease Neuroimaging Initiative.MethodsWe apply a latent time joint mixed-effects model to 16 cognitive, functional, biomarker, and imaging outcomes in Alzheimer's Disease Neuroimaging Initiative. Markov chain Monte Carlo methods are used for estimation and inference.ResultsWe find good concordance between latent time and diagnosis. Change in amyloid positron emission tomography shows a moderate correlation with change in cerebrospinal fluid tau (ρ = 0.310) and phosphorylated tau (ρ = 0.294) and weaker correlation with amyloid-β 42 (ρ = 0.176). In comparison to amyloid positron emission tomography, change in volumetric magnetic resonance imaging summaries is more strongly correlated with cognitive measures (e.g., ρ = 0.731 for ventricles and Alzheimer's Disease Assessment Scale). The average disease trends are consistent with the amyloid cascade hypothesis.DiscussionThe latent time joint mixed-effects model can (1) uncover long-term disease trends; (2) estimate the sequence of pathological abnormalities; and (3) provide subject-specific prognostic estimates of the time until onset of symptoms

Predicting the course of Alzheimer's progression.

Alzheimer's disease is the most common neurodegenerative disease and is characterized by the accumulation of amyloid-beta peptides leading to the formation of plaques and tau protein tangles in brain. These neuropathological features precede cognitive impairment and Alzheimer's dementia by many years. To better understand and predict the course of disease from early-stage asymptomatic to late-stage dementia, it is critical to study the patterns of progression of multiple markers. In particular, we aim to predict the likely future course of progression for individuals given only a single observation of their markers. Improved individual-level prediction may lead to improved clinical care and clinical trials. We propose a two-stage approach to modeling and predicting measures of cognition, function, brain imaging, fluid biomarkers, and diagnosis of individuals using multiple domains simultaneously. In the first stage, joint (or multivariate) mixed-effects models are used to simultaneously model multiple markers over time. In the second stage, random forests are used to predict categorical diagnoses (cognitively normal, mild cognitive impairment, or dementia) from predictions of continuous markers based on the first-stage model. The combination of the two models allows one to leverage their key strengths in order to obtain improved accuracy. We characterize the predictive accuracy of this two-stage approach using data from the Alzheimer's Disease Neuroimaging Initiative. The two-stage approach using a single joint mixed-effects model for all continuous outcomes yields better diagnostic classification accuracy compared to using separate univariate mixed-effects models for each of the continuous outcomes. Overall prediction accuracy above 80% was achieved over a period of 2.5 years. The results further indicate that overall accuracy is improved when markers from multiple assessment domains, such as cognition, function, and brain imaging, are used in the prediction algorithm as compared to the use of markers from a single domain only

The AT(N) framework for Alzheimer\u27s disease in adults with Down syndrome

The National Institute on Aging in conjunction with the Alzheimer\u27s Association (NIA-AA) recently proposed a biological framework for defining the Alzheimer\u27s disease (AD) continuum. This new framework is based upon the key AD biomarkers (amyloid, tau, neurodegeneration, AT[N]) instead of clinical symptoms and represents the latest understanding that the pathological processes underlying AD begin decades before the manifestation of symptoms. By using these same biomarkers, individuals with Down syndrome (DS), who are genetically predisposed to developing AD, can also be placed more precisely along the AD continuum. The A/T(N) framework is therefore thought to provide an objective manner by which to select and enrich samples for clinical trials. This new framework is highly flexible and allows the addition of newly confirmed AD biomarkers into the existing AT(N) groups. As biomarkers for other pathological processes are validated, they can also be added to the AT(N) classification scheme, which will allow for better characterization and staging of AD in DS. These biological classifications can then be merged with clinical staging for an examination of factors that impact the biological and clinical progression of the disease. Here, we leverage previously published guidelines for the AT(N) framework to generate such a plan for AD among adults with DS

Osteoblastic and Vascular Endothelial Niches, Their Control on Normal Hematopoietic Stem Cells, and Their Consequences on the Development of Leukemia

Stem cell self-renewal is regulated by intrinsic mechanisms and extrinsic signals mediated via specialized microenvironments called “niches.” The best-characterized stem cell is the hematopoietic stem cell (HSC). Self-renewal and differentiation ability of HSC are regulated by two major elements: endosteal and vascular regulatory elements. The osteoblastic niche localized at the inner surface of the bone cavity might serve as a reservoir for long-term HSC storage in a quiescent state. Whereas the vascular niche, which consists of sinusoidal endothelial cell lining blood vessel, provides an environment for short-term HSC proliferation and differentiation. Both niches act together to maintain hematopoietic homeostasis. In this paper, we provide some principles applying to the hematopoietic niches, which will be useful in the study and understanding of other stem cell niches. We will discuss altered microenvironment signaling leading to myeloid lineage disease. And finally, we will review some data on the development of acute myeloid leukemia from a subpopulation called leukemia-initiating cells (LIC), and we will discuss on the emerging evidences supporting the influence of the microenvironment on chemotherapy resistance

Evolutionary concept analysis of health seeking behavior in nursing: A systematic review

Background: Although the research in health seeking behavior has been evolving, its concept remains ambiguous. Concept clarification, as a central basis of developing knowledge, plays an undeniable role in the formation of nursing sciences. As the initial step toward the development of theories and theoretical models, concept analysis is broadly used through which the goals can be used and tested. The aim of this study was to report an analysis of the concept of "health seeking behavior". Method: Employing a rigorous evolutionary concept analysis approach, the concept of health seeking behavior was examined for its implications, use, and significance in the discipline of nursing between 2000 and 2012. After applying inclusion and exclusion criteria, a total of 40 articles and 3 books were selected for the final analysis. Results: The definition of attributes, antecedents, and consequences of health seeking behavior was performed through concept analysis. Core attributes (interactional, processing, intellectual, active, decision making based and measurable) were studied. The antecedents of concept were categorized as social, cultural, economic, disease pattern and issues related to health services. Health-seeking behavior resulted in health promotion and disease risk reduction. In addition, it led to predicting the future probable burden of the diseases, facilitation of the health status, early diagnosis, complete and effective treatment, and complication control. Conclusion: Health-seeking behavior, as a multi-dimensional concept, relies on time and context. An awareness of health-seeking behavior attributes antecedents and consequences results in promoting the status, importance and application of this concept in the nursing profession. �© 2015 Poortaghi et al

Effect of drought stress on growth, proline and antioxidant enzyme activities of upland rice

Responses of eight upland rice (Oryza sativa L.) varieties subjected to different drought levels were investigated in laboratory to evaluate eight local upland rice varieties against five drought levels (0, -2, -4, -6, and -8 bars) at germination and early seedling growth stage of plant development. Data were analyzed statistically for growth parameters; shoot length, root length, and dry matter yield, and biochemical parameters; proline and antioxidant enzymes activity (catalase, superoxide dismutase and peroxidase), were measured. Experiment units were arranged factorial completely randomized design with four replications. The drought-tolerant variety, Pulot Wangi tolerated PEG at the highest drought level (-8 bar) and showed no significantly difference relation to control. However, drought-sensitive variety, Kusam was markedly affected even at the lowest drought level used. Concomitantly, the activity of antioxidant enzymes catalase, peroxidase and superoxide dismutase in the drought-tolerant varieties increased markedly during drought stress, while decreased by drought stress in the drought sensitive variety. Consequently, this led to a marked difference in the accumulation of proline in the upland rice varieties. It may be concluded that the activities of antioxidant enzymes and proline accumulation were associated with the dry mass production and consequently with the drought tolerance of the upland rice varieties