New and emerging treatments for Alzheimer's disease

Signature-based approaches for informed drug repurposing: targeting CNS disorders

CNS disorders, and in particular psychiatric illnesses, lack definitive disease-altering therapeutics. The limited understanding of the mechanisms driving these illnesses with the slow pace and high cost of drug development exacerbates this issue. For these reasons, drug repurposing - both a less expensive and time-efficient practice compared to de novo drug development - has been a promising strategy to overcome the paucity of treatments available for these debilitating disorders. While empirical drug-repurposing has been a routine practice in clinical psychiatry, innovative, informed, and cost-effective repurposing efforts using big data ("omics") have been designed to characterize drugs by structural and transcriptomic signatures. These strategies, in conjunction with ontological integration, provide an important opportunity to address knowledge-based challenges associated with drug development for CNS disorders. In this review, we discuss various signature-based in silico approaches to drug repurposing, its integration with multiple omics platforms, and how this data can be used for clinically relevant, evidence-based drug repurposing. These tools provide an exciting translational avenue to merge omics-based drug discovery platforms with patient-specific disease signatures, ultimately facilitating the identification of new therapies for numerous psychiatric disorders.

The prodrug of 7,8-dihydroxyflavone development and therapeutic efficacy for treating Alzheimer's disease

The BDNF mimetic compound 7,8-dihydroxyflavone (7,8-DHF), a potent small molecular TrkB agonist, displays prominent therapeutic efficacy against Alzheimer's disease (AD). However, 7,8-DHF has only modest oral bioavailability and a moderate pharmacokinetic (PK) profile. To alleviate these preclinical obstacles, we used a prodrug strategy for elevating 7,8-DHF oral bioavailability and brain exposure, and found that the optimal prodrug R13 has favorable properties and dose-dependently reverses the cognitive defects in an AD mouse model. We synthesized a large number of 7,8-DHF derivatives via ester or carbamate group modification on the catechol ring in the parent compound. Using in vitro absorption, distribution, metabolism, and excretion assays, combined with in vivo PK studies, we identified a prodrug, R13, that prominently up-regulates 7,8-DHF PK profiles. Chronic oral administration of R13 activated TrkB signaling and prevented Aβ deposition in 5XFAD AD mice, inhibiting the pathological cleavage of APP and Tau by AEP. Moreover, R13 inhibited the loss of hippocampal synapses and ameliorated memory deficits in a dose-dependent manner. These results suggest that the prodrug R13 is an optimal therapeutic agent for treating AD.

Currents of memory: recent progress, translational challenges, and ethical considerations in fornix deep brain stimulation trials for Alzheimer's disease

The serendipitous discovery of triggered autobiographical memories and eventual memory improvement in an obese patient who received fornix deep brain stimulation in 2008 paved the way for several phase I and phase II clinical trials focused on the safety and efficacy of this potential intervention for people with Alzheimer's disease. In this article, we summarize clinical trials and case reports on fornix deep brain stimulation for Alzheimer's disease and review experiments on animal models evaluating the physiological or behavioral effects of this intervention. Based on information from these reports and studies, we identify potential translational challenges of this approach and determine practical and ethical considerations for clinical trials, focusing on issues regarding selection criteria, trial design, and outcome evaluation. Based on initial results suggesting greater benefit for those with milder disease stage, we find it essential that participant expectations are carefully managed to avoid treatment disenchantment and/or frustration from participants and caregivers. Finally, we urge for collaboration between centers to establish proper clinical standards and to promote better trial results comparison.

Microtubule stabilising peptides rescue tau phenotypes in-vivo

The microtubule cytoskeleton is a highly dynamic, filamentous network underpinning cellular structure and function. In Alzheimer's disease, the microtubule cytoskeleton is compromised, leading to neuronal dysfunction and eventually cell death. There are currently no disease-modifying therapies to slow down or halt disease progression. However, microtubule stabilisation is a promising therapeutic strategy that is being explored. We previously investigated the disease-modifying potential of a microtubule-stabilising peptide NAP (NAPVSIPQ) in a well-established Drosophila model of tauopathy characterised by microtubule breakdown and axonal transport deficits. NAP prevented as well as reversed these phenotypes even after they had become established. In this study, we investigate the neuroprotective capabilities of an analogous peptide SAL (SALLRSIPA). We found that SAL mimicked NAP's protective effects, by preventing axonal transport disruption and improving behavioural deficits, suggesting both NAP and SAL may act via a common mechanism. Both peptides contain a putative 'SIP' (Ser-Ile-Pro) domain that is important for interactions with microtubule end-binding proteins. Our data suggests this domain may be central to the microtubule stabilising function of both peptides and the mechanism by which they rescue phenotypes in this model of tauopathy. Our observations support microtubule stabilisation as a promising disease-modifying therapeutic strategy for tauopathies like Alzheimer's disease.

A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer's Disease Diagnosis

Background:

Recent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer’s disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust.

Objectives:

This study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts.

Methods:

Our study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis.

Results:

Gene and pathway level models performed similarly to each other and to a model based on demographic information only.

Conclusions:

Any potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach.

Alzheimer disease research in the 21st century: past and current failures, new perspectives and funding priorities

Much of Alzheimer disease (AD) research has been traditionally based on the use of animals, which have been extensively applied in an effort to both improve our understanding of the pathophysiological mechanisms of the disease and to test novel therapeutic approaches. However, decades of such research have not effectively translated into substantial therapeutic success for human patients. Here we critically discuss these issues in order to determine how existing human-based methods can be applied to study AD pathology and develop novel therapeutics. These methods, which include patient-derived cells, computational analysis and models, together with large-scale epidemiological studies represent novel and exciting tools to enhance and forward AD research. In particular, these methods are helping advance AD research by contributing multifactorial and multidimensional perspectives, especially considering the crucial role played by lifestyle risk factors in the determination of AD risk. In addition to research techniques, we also consider related pitfalls and flaws in the current research funding system. Conversely, we identify encouraging new trends in research and government policy. In light of these new research directions, we provide recommendations regarding prioritization of research funding. The goal of this document is to stimulate scientific and public discussion on the need to explore new avenues in AD research, considering outcome and ethics as core principles to reliably judge traditional research efforts and eventually undertake new research strategies.

Blood metabolite markers of neocortical amyloid-β burden: discovery and enrichment using candidate proteins

We believe this is the first study to investigate associations between blood metabolites and neocortical amyloid burden (NAB) in the search for a blood-based biomarker for Alzheimer's disease (AD). Further, we present the first multi-modal analysis of blood markers in this field. We used blood plasma samples from 91 subjects enrolled in the University of California, San Francisco Alzheimer's Disease Research Centre. Non-targeted metabolomic analysis was used to look for associations with NAB using both single and multiple metabolic feature models. Five metabolic features identified subjects with high NAB, with 72% accuracy. We were able to putatively identify four metabolites from this panel and improve the model further by adding fibrinogen gamma chain protein measures (accuracy=79%). One of the five metabolic features was studied in the Alzheimer's Disease Neuroimaging Initiative cohort, but results were inconclusive. If replicated in larger, independent studies, these metabolic features and proteins could form the basis of a blood test with potential for enrichment of amyloid pathology in anti-amyloid trials.

Blood Protein Markers of Neocortical Amyloid-β Burden: A Candidate Study Using SOMAscan Technology

BACKGROUND

Four previously reported studies have tested for association of blood proteins with neocortical amyloid-β burden (NAB). If shown to be robust, these proteins could have utility as a blood test for enrichment in clinical trials of Alzheimer's disease (AD) therapeutics.

OBJECTIVE

This study aimed to investigate whether previously identified blood proteins also show evidence for association with NAB in serum samples from the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL). The study considers candidate proteins seen in cohorts other than AIBL and candidates previously discovered in the AIBL cohort.

METHODS

Our study used the SOMAscan platform for protein quantification in blood serum. Linear and logistic regressions were used to model continuous NAB and dichotomized NAB respectively using single proteins as a predictor. Multiple protein models were built using stepwise regression techniques and support vectors machines. Age and APOEɛ4 carriage were used as covariates for all analysis.

RESULTS

Of the 41 proteins previously reported, 15 AIBL candidates and 20 non-AIBL candidates were available for testing. Of these candidates, pancreatic polypeptide (PPY) and IgM showed a significant association with NAB. Notably, IgM was found to associate with continuous NAB across cognitively normal control subjects.

CONCLUSIONS

We have further demonstrated the association of PPY and IgM with NAB, despite technical differences between studies. There are several reasons for a lack of significance for the other candidates including platform differences and the use of serum rather than plasma samples. To investigate the possibility of technical differences causing lack of replication, further studies are required.

Evaluating disease-modifying agents: a simulation framework for Alzheimer's disease

BACKGROUND

Considerable advances have been made in modeling Alzheimer's disease (AD), with a move towards individual-level rather than cohort models and simulations that consider multiple dimensions when evaluating disease severity. However, the possibility that disease-modifying agents (DMAs) may emerge requires an update of existing modeling frameworks.

OBJECTIVES

The aim of this study was to develop a simulation allowing for economic evaluation of DMAs in AD.

METHODS

The model was developed based on a previously published, well-validated, discrete event simulation which measures disease severity on the basis of cognition, behaviour, and function, and captures the interrelated changes in these measures for individuals. The updated model adds one more domain, patient dependence, in addition to cognition, behaviour, and function to better characterize disease severity. Furthermore, the model was modified to have greater flexibility in assessing the impact of various important assumptions, such as the long-term effectiveness of DMAs and their impact on survival, on model outcomes. A validation analysis was performed to examine how well the model predicted change in disease severity among patients not receiving DMA treatment by comparing model results to those observed in two recent phase III clinical trials of bapineuzumab. In addition, various hypothetical scenarios were tested to demonstrate the improved features of the model.

RESULTS

Validation results show that the model closely predicts the mean changes in disease severity over 18 months. Results from different hypothetical scenarios show that the model allows for credible assessment of those major uncertainties surrounding the long-term effectiveness of DMAs, including the potential impact of improved survival with DMA treatment. They also indicate that varying these assumptions could have a major impact on the value of DMAs.

CONCLUSIONS

The updated economic model has good predictive power, but validation against longer-term outcomes is still needed. Our analyses also demonstrate the importance of designing a model with sufficient flexibility such that the model allows for assessment of the impact of key sources of uncertainty on the value of DMAs.

Potential applications of magnetic particles to detect and treat Alzheimer's disease

Nanotechnology is an exciting and promising scientific discipline. At the nanoscale, a material displays novel physical properties that offer many new and beneficial products and applications. In particular, magnetic nanoparticles - a core/shell nanoparticle - present considerable diagnostic and therapeutic potentials, and superparamagnetic iron oxide nanoparticles (SPIONs) are considered promising theranostic tools. Alzheimer's disease (AD) is a neurodegenerative disorder that predominantly affects people over 65 years of age. The disease is characterized by the presence of extracellular plaques in the brain which are formed by interwoven fibrils composed of variants of the β-amyloid peptide. Medication can temporarily retard worsening of symptoms, but only in the first stages of the disease; early detection is thus of crucial importance. This minireview covers the progress made in research on the use of magnetic nanoparticles for ex vivo and/or in vivo detection and diagnosis of AD by means of magnetic resonance imaging (MRI), or to label peptides and fibrils. Of particular importance is the use of these nanoparticles to detect AD biomarkers in biological fluids. A description is given of the bio-barcode amplification assay using functionalized magnetic particles, as well as the use of such nanoparticles as a system for inhibiting or delaying the assembly of peptide monomers into oligomers and fibrils. Lastly, a brief overview is given of possible future lines of research in this.

Lessons from a BACE1 inhibitor trial: off-site but not off base

Alzheimer's disease (AD) is characterized by formation of neuritic plaque primarily composed of a small filamentous protein called amyloid-β peptide (Aβ). The rate-limiting step in the production of Aβ is the processing of Aβ precursor protein (APP) by β-site APP-cleaving enzyme (BACE1). Hence, BACE1 activity plausibly plays a rate-limiting role in the generation of potentially toxic Aβ within brain and the development of AD, thereby making it an interesting drug target. A phase II trial of the promising LY2886721 inhibitor of BACE1 was suspended in June 2013 by Eli Lilly and Co., due to possible liver toxicity. This outcome was apparently a surprise to the study's team, particularly since BACE1 knockout mice and mice treated with the drug did not show such liver toxicity. Lilly proposed that the problem was not due to LY2886721 anti-BACE1 activity. We offer an alternative hypothesis, whereby anti-BACE1 activity may induce apparent hepatotoxicity through inhibiting BACE1's processing of β-galactoside α-2,6-sialyltransferase I (STGal6 I). In knockout mice, paralogues, such as BACE2 or cathepsin D, could partially compensate. Furthermore, the short duration of animal studies and short lifespan of study animals could mask effects that would require several decades to accumulate in humans. Inhibition of hepatic BACE1 activity in middle-aged humans would produce effects not detectable in mice. We present a testable model to explain the off-target effects of LY2886721 and highlight more broadly that so-called off-target drug effects might actually represent off-site effects that are not necessarily off-target. Consideration of this concept in forthcoming drug design, screening, and testing programs may prevent such failures in the future.

Network-based biomarkers in Alzheimer's disease: review and future directions

By 2050 it is estimated that the number of worldwide Alzheimer's disease (AD) patients will quadruple from the current number of 36 million people. To date, no single test, prior to postmortem examination, can confirm that a person suffers from AD. Therefore, there is a strong need for accurate and sensitive tools for the early diagnoses of AD. The complex etiology and multiple pathogenesis of AD call for a system-level understanding of the currently available biomarkers and the study of new biomarkers via network-based modeling of heterogeneous data types. In this review, we summarize recent research on the study of AD as a connectivity syndrome. We argue that a network-based approach in biomarker discovery will provide key insights to fully understand the network degeneration hypothesis (disease starts in specific network areas and progressively spreads to connected areas of the initial loci-networks) with a potential impact for early diagnosis and disease-modifying treatments. We introduce a new framework for the quantitative study of biomarkers that can help shorten the transition between academic research and clinical diagnosis in AD.

Loss of the neuroprotective factor Sphingosine 1-phosphate early in Alzheimer's disease pathogenesis

Background

The greatest genetic risk factor for late-onset Alzheimer's disease (AD) is the ϵ4 allele of Apolipoprotein E (ApoE). ApoE regulates secretion of the potent neuroprotective signaling lipid Sphingosine 1-phosphate (S1P). S1P is derived by phosphorylation of sphingosine, catalysed by sphingosine kinases 1 and 2 (SphK1 and 2), and SphK1 positively regulates glutamate secretion and synaptic strength in hippocampal neurons. S1P and its receptor family have been subject to intense pharmacological interest in recent years, following approval of the immunomodulatory drug Fingolimod, an S1P mimetic, for relapsing multiple sclerosis.

Results

We quantified S1P levels in six brain regions that are differentially affected by AD pathology, in a cohort of 34 post-mortem brains, divided into four groups based on Braak neurofibrillary tangle staging. S1P declined with increasing Braak stage, and this was most pronounced in brain regions most heavily affected by AD pathology. The S1P/sphingosine ratio was 66% and 64% lower in Braak stage III/IV hippocampus (p = 0.010) and inferior temporal cortex (p = 0.014), respectively, compared to controls. In accordance with this change, both SphK1 and SphK2 activity declined with increasing Braak pathology in the hippocampus (p = 0.032 and 0.047, respectively). S1P/sphingosine ratio was 2.5-fold higher in hippocampus of ApoE2 carriers compared to ApoE4 carriers, and multivariate regression showed a significant association between APOE genotype and hippocampal S1P/sphingosine (p = 0.0495), suggesting a new link between APOE genotype and pre-disposition to AD.

Conclusions

This study demonstrates loss of S1P and sphingosine kinase activity early in AD pathogenesis, and prior to AD diagnosis. Our findings establish a rationale for further exploring S1P receptor pharmacology in the context of AD therapy.

Phenotypic screens targeting neurodegenerative diseases

Neurodegenerative diseases affect millions of people worldwide, and the incidences increase as the population ages. Disease-modifying therapy that prevents or slows disease progression is still lacking, making neurodegenerative diseases an area of high unmet medical need. Target-based drug discovery for disease-modifying agents has been ongoing for many years, without much success due to incomplete understanding of the molecular mechanisms underlying neurodegeneration. Phenotypic screening, starting with a disease-relevant phenotype to screen for compounds that change the outcome of biological pathways rather than activities at certain specific targets, offers an alternative approach to find small molecules or targets that modulate the key characteristics of neurodegeneration. Phenotypic screens that focus on amelioration of disease-specific toxins, protection of neurons from degeneration, or promotion of neuroregeneration could be potential fertile grounds for discovering therapeutic agents for neurodegenerative diseases. In this review, we will summarize the progress of compound screening using these phenotypic-based strategies for this area, with a highlight on unique considerations for disease models, assays, and screening methodologies. We will further provide our perspectives on how best to use phenotypic screening to develop drug leads for neurodegenerative diseases.

Neurotrophic and neuroprotective actions of (-)- and (+)-phenserine, candidate drugs for Alzheimer's disease

Neuronal dysfunction and demise together with a reduction in neurogenesis are cardinal features of Alzheimer’s disease (AD) induced by a combination of oxidative stress, toxic amyloid-β peptide (Aβ) and a loss of trophic factor support. Amelioration of these was assessed with the Aβ lowering AD experimental drugs (+)-phenserine and (−)-phenserine in neuronal cultures, and actions in mice were evaluated with (+)-phenserine. Both experimental drugs together with the metabolite N1-norphenserine induced neurotrophic actions in human SH-SY5Y cells that were mediated by the protein kinase C (PKC) and extracellular signal–regulated kinases (ERK) pathways, were evident in cells expressing amyloid precursor protein Swedish mutation (APP_SWE), and retained in the presence of Aβ and oxidative stress challenge. (+)-Phenserine, together with its (−) enantiomer as well as its N1- and N8-norphenserine and N1,N8-bisnorphenserine metabolites, likewise provided neuroprotective activity against oxidative stress and glutamate toxicity via the PKC and ERK pathways. These neurotrophic and neuroprotective actions were evident in primary cultures of subventricular zone (SVZ) neural progenitor cells, whose neurosphere size and survival were augmented by (+)-phenserine. Translation of these effects in vivo was assessed in wild type and AD APPswe transgenic (Tg2576) mice by doublecortin (DCX) immunohistochemical analysis of neurogenesis in the SVZ, which was significantly elevated by 16 day systemic (+)-phenserine treatment, in the presence of a (+)-phenserine-induced elevation in brain- derived neurotrophic factor (BDNF).

Unique and universal barriers: hospice care for aging adults with intellectual disability

As life expectancy of people with intellectual disability (ID) has increased, there has been a concurrent increase in age-related illnesses and conditions similar to that of the general population. These circumstances result in people with ID dying from typical life-ending conditions, and thus, they require similar end-of-life services such as palliative and hospice care. Although there are notable barriers to hospice for all, people with ID face additional challenges in accessing the benefits of these services. This article presents a review of the literature on these issues, underscoring the multiple challenges and the importance of a more collaborative approach between hospice and palliative care workers with people with ID, their families, and other important stakeholders.