Interplay between α-, β-, and γ-secretases determines biphasic amyloid-β protein level in the presence of a γ-secretase inhibitor

Unraveling Molecular Targets for Neurodegenerative Diseases Through Caenorhabditis elegans Models

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and prion disease, represent a group of age-related disorders that pose a growing and formidable challenge to global health. Despite decades of extensive research that has uncovered key genetic factors and biochemical pathways, the precise molecular mechanisms underlying these diseases and effective therapeutic strategies remain elusive. Caenorhabditis elegans (C. elegans) has emerged as a powerful model organism for studying NDDs due to its unique biological features such as genetic tractability, conserved molecular pathways, and ease of high-throughput screening. This model provides an exceptional platform for identifying molecular targets associated with NDDs and developing novel therapeutic interventions. This review highlights the critical role of C. elegans in elucidating the complex molecular mechanisms of human NDDs, with a particular focus on recent advancements and its indispensable contributions to the discovery of molecular targets and therapeutic strategies for these NDDs.

Altered synaptic plasticity at hippocampal CA1-CA3 synapses in Alzheimer's disease: integration of amyloid precursor protein intracellular domain and amyloid beta effects into computational models

Alzheimer's disease (AD) is a progressive memory loss and cognitive dysfunction brain disorder brought on by the dysfunctional amyloid precursor protein (APP) processing and clearance of APP peptides. Increased APP levels lead to the production of AD-related peptides including the amyloid APP intracellular domain (AICD) and amyloid beta (Aβ), and consequently modify the intrinsic excitability of the hippocampal CA1 pyramidal neurons, synaptic protein activity, and impair synaptic plasticity at hippocampal CA1-CA3 synapses. The goal of the present study is to build computational models that incorporate the effect of AD-related peptides on CA1 pyramidal neuron and hippocampal synaptic plasticity under the AD conditions and investigate the potential pharmacological treatments that could normalize hippocampal synaptic plasticity and learning in AD. We employ a phenomenological N-methyl-D-aspartate (NMDA) receptor-based voltage-dependent synaptic plasticity model that includes the separate receptor contributions on long-term potentiation (LTP) and long-term depression (LTD) and embed it into the a detailed compartmental model of CA1 pyramidal neuron. Modeling results show that partial blockade of Glu2NB-NMDAR-gated channel restores intrinsic excitability of a CA1 pyramidal neuron and rescues LTP in AICD and Aβ conditions. The model provides insight into the complex interactions in AD pathophysiology and suggests the conditions under which the synchronous activation of a cluster of synaptic inputs targeting the dendritic tree of CA1 pyramidal neuron leads to restored synaptic plasticity.

P2X7 Receptor and Purinergic Signaling: Orchestrating Mitochondrial Dysfunction in Neurodegenerative Diseases

Mitochondrial dysfunction is one of the basic hallmarks of cellular pathology in neurodegenerative diseases. Since the metabolic activity of neurons is highly dependent on energy supply, nerve cells are especially vulnerable to impaired mitochondrial function. Besides providing oxidative phosphorylation, mitochondria are also involved in controlling levels of second messengers such as Ca2+ ions and reactive oxygen species (ROS). Interestingly, the critical role of mitochondria as producers of ROS is closely related to P2XR purinergic receptors, the activity of which is modulated by free radicals. Here, we review the relationships between the purinergic signaling system and affected mitochondrial function. Purinergic signaling regulates numerous vital biological processes in the CNS. The two main purines, ATP and adenosine, act as excitatory and inhibitory neurotransmitters, respectively. Current evidence suggests that purinergic signaling best explains how neuronal activity is related to neuronal electrical activity and energy homeostasis, especially in the development of Alzheimer's and Parkinson's diseases. In this review, we focus on the mechanisms underlying the involvement of the P2RX7 purinoreceptor in triggering mitochondrial dysfunction during the development of neurodegenerative disorders. We also summarize various avenues by which the purine signaling pathway may trigger metabolic dysfunction contributing to neuronal death and the inflammatory activation of glial cells. Finally, we discuss the potential role of the purinergic system in the search for new therapeutic approaches to treat neurodegenerative diseases.

Importance of CSF-based Aβ clearance with age in humans increases with declining efficacy of blood-brain barrier/proteolytic pathways

The kinetics of amyloid beta turnover within human brain is still poorly understood. We previously found a dramatic decline in the turnover of Aβ peptides in normal aging. It was not known if brain interstitial fluid/cerebrospinal fluid (ISF/CSF) fluid exchange, CSF turnover, blood-brain barrier function or proteolysis were affected by aging or the presence of β amyloid plaques. Here, we describe a non-steady state physiological model developed to decouple CSF fluid transport from other processes. Kinetic parameters were estimated using: (1) MRI-derived brain volumes, (2) stable isotope labeling kinetics (SILK) of amyloid-β peptide (Aβ), and (3) lumbar CSF Aβ concentration during SILK. Here we show that changes in blood-brain barrier transport and/or proteolysis were largely responsible for the age-related decline in Aβ turnover rates. CSF-based clearance declined modestly in normal aging but became increasingly important due to the slowing of other processes. The magnitude of CSF-based clearance was also lower than that due to blood-brain barrier function plus proteolysis. These results suggest important roles for blood-brain barrier transport and proteolytic degradation of Aβ in the development Alzheimer’s Disease in humans.

To understand if brain interstitial fluid/cerebrospinal fluid (ISF/CSF) exchange, CSF turnover, blood-brain barrier function or proteolysis were affected by aging or the presence of β amyloid plaques, Elbert et al. develop a non-steady state physiological model using MRI-derived brain volumes, stable isotope labeling kinetics of Aβ, and lumbar CSF Aβ concentration. Their model suggests an important role for blood-brain barrier transport and proteolytic degradation of Aβ in the development Alzheimer’s Disease in humans.

Modeling Neurotransmission: Computational Tools to Investigate Neurological Disorders

The investigation of synaptic functions remains one of the most fascinating challenges in the field of neuroscience and a large number of experimental methods have been tuned to dissect the mechanisms taking part in the neurotransmission process. Furthermore, the understanding of the insights of neurological disorders originating from alterations in neurotransmission often requires the development of (i) animal models of pathologies, (ii) invasive tools and (iii) targeted pharmacological approaches. In the last decades, additional tools to explore neurological diseases have been provided to the scientific community. A wide range of computational models in fact have been developed to explore the alterations of the mechanisms involved in neurotransmission following the emergence of neurological pathologies. Here, we review some of the advancements in the development of computational methods employed to investigate neuronal circuits with a particular focus on the application to the most diffuse neurological disorders.

Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain

Despite the acceleration of knowledge and data accumulation in neuroscience over the last years, the highly prevalent neurodegenerative disease of AD remains a growing problem. Alzheimer's Disease (AD) is the most common cause of dementia and represents the most prevalent neurodegenerative disease. For AD, disease-modifying treatments are presently lacking, and the understanding of disease mechanisms continues to be incomplete. In the present review, we discuss candidate contributing factors leading to AD, and evaluate novel computational brain simulation methods to further disentangle their potential roles. We first present an overview of existing computational models for AD that aim to provide a mechanistic understanding of the disease. Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain (www.thevirtualbrain.org), an open-source, multiscale, whole-brain simulation neuroinformatics platform. Finally, we discuss how this methodological approach may contribute to the understanding, improved diagnostics, and treatment optimization of AD.

P2X7 Receptors Amplify CNS Damage in Neurodegenerative Diseases

ATP is a (co)transmitter and signaling molecule in the CNS. It acts at a multitude of ligand-gated cationic channels termed P2X to induce rapid depolarization of the cell membrane. Within this receptor-channel family, the P2X7 receptor (R) allows the transmembrane fluxes of Na⁺, Ca²⁺, and K⁺, but also allows the slow permeation of larger organic molecules. This is supposed to cause necrosis by excessive Ca²⁺ influx, as well as depletion of intracellular ions and metabolites. Cell death may also occur by apoptosis due to the activation of the caspase enzymatic cascade. Because P2X7Rs are localized in the CNS preferentially on microglia, but also at a lower density on neuroglia (astrocytes, oligodendrocytes) the stimulation of this receptor leads to the release of neurodegeneration-inducing bioactive molecules such as pro-inflammatory cytokines, chemokines, proteases, reactive oxygen and nitrogen molecules, and the excitotoxic glutamate/ATP. Various neurodegenerative reactions of the brain/spinal cord following acute harmful events (mechanical CNS damage, ischemia, status epilepticus) or chronic neurodegenerative diseases (neuropathic pain, Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, amyotrophic lateral sclerosis) lead to a massive release of ATP via the leaky plasma membrane of neural tissue. This causes cellular damage superimposed on the original consequences of neurodegeneration. Hence, blood-brain-barrier permeable pharmacological antagonists of P2X7Rs with excellent bioavailability are possible therapeutic agents for these diseases. The aim of this review article is to summarize our present state of knowledge on the involvement of P2X7R-mediated events in neurodegenerative illnesses endangering especially the life quality and duration of the aged human population.

Mathematical Models to Shed Light on Amyloid-Beta and Tau Protein Dependent Pathologies in Alzheimer's Disease

The number of patients suffering from dementia due to Alzheimer's disease (AD) is constantly rising worldwide. This has accordingly resulted in huge burdens on the health systems and involved families. Lack of profound understanding of neural networking in normal brain and their interruption in AD makes the treatment of this neurodegenerative multifaceted disease a challenging issue. In recent years, mathematical and computational methods have paved the way towards a better understanding of the brain functional connectivity. Thus, much attention has been paid to this matter from both basic science researchers and clinicians with an interdisciplinary approach to determine what is not functioning properly in AD patients and how this malfunctioning can be addressed. In this review, a number of AD-related articles and well-studied pathophysiologic topics (e.g., amyloid-beta, neurofibrillary tangles, Ca²⁺ dysregulation, and synaptic plasticity alterations) has been literally surveyed from a computational and systems biology point of view. The neural networks were discussed from biological and mathematical point of views and their alterations in recent findings were further highlighted. Application of the graph theoretical analysis in the brain imaging was reviewed, depicting the relations between brain structure and function, without diving into mathematical details. Moreover, differential rate equations were briefly articulated, emphasizing the potential use of these equations in simplifying complex processes in relevance to pathologies of AD. Comprehensive insights were given into the AD progression from neural networks perspective, which may lead us towards potential strategies for early diagnosis and effective treatment of AD.

Emerging Signal Regulating Potential of Genistein Against Alzheimer's Disease: A Promising Molecule of Interest

Alzheimer’s disease (AD) is a progressive, irreversible brain disorder characterized by pathological aggregation of the amyloid-β peptide (Aβ) and tau protein; both of these are toxic to neurons. Currently, natural products are regarded as an alternative approach to discover novel multipotent drugs against AD. Dietary soy isoflavone genistein is one of the examples of such agents that occurs naturally and is known to exert a number of beneficial health effects. It has been observed that genistein has the capacity to improve the impairments triggered by Aβ and also it possesses the antioxidant potential to scavenge the AD-mediated generation of free radicals. Furthermore, genistein can interact directly with the targeted signaling proteins and also can stabilize their activity to combat AD. In order to advance the development of AD treatment, a better comprehension of the direct interactions of target proteins and genistein might prove beneficial. Therefore, this article focuses on the therapeutic effects and molecular targets of genistein, which has been found to target directly the Aβ and tau to control the intracellular signaling pathways responsible for neurons death in the AD brain.

Best Practices to Maximize the Use and Reuse of Quantitative and Systems Pharmacology Models: Recommendations From the United Kingdom Quantitative and Systems Pharmacology Network

The lack of standardization in the way that quantitative and systems pharmacology (QSP) models are developed, tested, and documented hinders their reproducibility, reusability, and expansion or reduction to alternative contexts. This in turn undermines the potential impact of QSP in academic, industrial, and regulatory frameworks. This article presents a minimum set of recommendations from the UK Quantitative and Systems Pharmacology Network (UK QSP Network) to guide QSP practitioners seeking to maximize their impact, and stakeholders considering the use of QSP models in their environment.

Quantitative Systems Pharmacology Model for Alzheimer Disease Indicates Targeting Sphingolipid Dysregulation as Potential Treatment Option

Alzheimer disease (AD) is a devastating neurodegenerative disorder with high unmet medical need. Drug development is hampered by limited understanding of the disease and its driving factors. Quantitative Systems Pharmacology (QSP) modeling provides a comprehensive quantitative framework to evaluate the relevance of biological mechanisms in the context of disease and to predict the efficacy of novel treatments. Here, we report a QSP model for AD with a particular focus on investigating the relevance of dysregulation of cholesterol and sphingolipids. We show that our model captures the modulation of several biomarkers in subjects with AD, as well as the response to pharmacological interventions. We evaluate the impact of targeting the sphingosine-1-phosphate 5 receptor (S1PR5) as a potential novel treatment option for AD, and model predictions increase our confidence in this novel disease pathway. Future applications for the QSP model are in validation of further targets and identification of potential treatment response biomarkers.

Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease (Review)

Alzheimer's disease (AD) is a complex and multifactorial disease. In order to understand the genetic influence in the progression of AD, and to identify novel pharmaceutical agents and their associated targets, the present study discusses computational modeling and biomarker evaluation approaches. Based on mechanistic signaling pathway approaches, various computational models, including biochemical and morphological models, are discussed to explore the strategies that may be used to target AD treatment. Different biomarkers are interpreted on the basis of morphological and functional features of amyloid β plaques and unstable microtubule‑associated tau protein, which is involved in neurodegeneration. Furthermore, imaging and cerebrospinal fluids are also considered to be key methods in the identification of novel markers for AD. In conclusion, the present study reviews various biochemical and morphological computational models and biomarkers to interpret novel targets and agonists for the treatment of AD. This review also highlights several therapeutic targets and their associated signaling pathways in AD, which may have potential to be used in the development of novel pharmacological agents for the treatment of patients with AD. Computational modeling approaches may aid the quest for the development of AD treatments with enhanced therapeutic efficacy and reduced toxicity.

Dietary lipophilic iron alters amyloidogenesis and microglial morphology in Alzheimer's disease knock-in APP mice

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized pathologically by amyloid beta (Aβ) deposition, microgliosis, and iron dyshomeostasis. Increased labile iron due to homeostatic dysregulation is believed to facilitate amyloidogenesis. Free iron is incorporated into aggregating amyloid peptides during Aβ plaque formation and increases potential for oxidative stress surrounding plaques. The goal of this work was to observe how brain iron levels temporally influence Aβ plaque formation, plaque iron concentration, and microgliosis. We fed humanized APP^NL-F and APP^NL-G-F knock-in mice lipophilic iron compound 3,5,5-trimethylhexanoyl ferrocene (TMHF) and iron deficient diets for twelve months. TMHF elevated brain iron by 22% and iron deficiency decreased brain iron 21% relative to control diet. Increasing brain iron with TMHF accelerated plaque formation, increased Aβ staining, and increased senile morphology of amyloid plaques. Increased brain iron was associated with increased plaque-iron loading and microglial iron inclusions. TMHF decreased IBA1+ microglia branch length while increasing roundness indicative of microglial activation. This body of work suggests that increasing mouse brain iron with TMHF potentiates a more human-like Alzheimer's disease phenotype with iron integration into Aβ plaques and associated microgliosis.

Exosomes: a novel therapeutic target for Alzheimer's disease?

Extracellular exosomes are formed inside the cytoplasm of cells in compartments known as multivesicular bodies. Thus, exosomes contain cytoplasmic content. Multivesicular bodies fuse with the plasma membrane and release exosomes into the extracellular environment. Comprehensive research suggests that exosomes act as both inflammatory intermediaries and critical inducers of oxidative stress to drive progression of Alzheimer's disease. An important role of exosomes in Alzheimer's disease includes the formation of neurofibrillary tangles and beta-amyloid production, clearance, and accumulation. In addition, exosomes are involved in neuroinflammation and oxidative stress, which both act as triggers for beta-amyloid pathogenesis and tau hyperphosphorylation. Further, it has been shown that exosomes are strongly associated with beta-amyloid clearance. Thus, effective measures for regulating exosome metabolism may be novel drug targets for Alzheimer's disease.

A toolbox for discrete modelling of cell signalling dynamics

We present a library of network motifs for the development of complex and realistic biological network models using the BioModelAnalyzer, and demonstrate their wider value by using them to construct a model of the cell cycle.

A Translational Systems Pharmacology Model for Aβ Kinetics in Mouse, Monkey, and Human

A mechanistic model of amyloid beta production, degradation, and distribution was constructed for mouse, monkey, and human, calibrated and externally verified across multiple datasets. Simulations of single‐dose avagacestat treatment demonstrate that the Aβ₄₂ brain inhibition may exceed that in cerebrospinal fluid (CSF). The dose that achieves 50% CSF Aβ₄₀ inhibition for humans (both healthy and with Alzheimer's disease (AD)) is about 1 mpk, one order of magnitude lower than for mouse (10 mpk), mainly because of differences in pharmacokinetics. The predicted maximal percent of brain Aβ₄₂ inhibition after single‐dose avagacestat is higher for AD subjects (about 60%) than for healthy individuals (about 45%). The probability of achieving a normal physiological level for Aβ₄₂ in brain (1 nM) during multiple avagacestat dosing can be increased by using a dosing regimen that achieves higher exposure. The proposed model allows prediction of brain pharmacodynamics for different species given differing dosing regimens.

The Impact of Mathematical Modeling in Understanding the Mechanisms Underlying Neurodegeneration: Evolving Dimensions and Future Directions

Neurodegenerative diseases are a heterogeneous group of disorders that are characterized by the progressive dysfunction and loss of neurons. Here, we distil and discuss the current state of modeling in the area of neurodegeneration, and objectively compare the gaps between existing clinical knowledge and the mechanistic understanding of the major pathological processes implicated in neurodegenerative disorders. We also discuss new directions in the field of neurodegeneration that hold potential for furthering therapeutic interventions and strategies.

Kinase Inhibition Leads to Hormesis in a Dual Phosphorylation-Dephosphorylation Cycle

Many antimicrobial and anti-tumour drugs elicit hormetic responses characterised by low-dose stimulation and high-dose inhibition. While this can have profound consequences for human health, with low drug concentrations actually stimulating pathogen or tumour growth, the mechanistic understanding behind such responses is still lacking. We propose a novel, simple but general mechanism that could give rise to hormesis in systems where an inhibitor acts on an enzyme. At its core is one of the basic building blocks in intracellular signalling, the dual phosphorylation-dephosphorylation motif, found in diverse regulatory processes including control of cell proliferation and programmed cell death. Our analytically-derived conditions for observing hormesis provide clues as to why this mechanism has not been previously identified. Current mathematical models regularly make simplifying assumptions that lack empirical support but inadvertently preclude the observation of hormesis. In addition, due to the inherent population heterogeneities, the presence of hormesis is likely to be masked in empirical population-level studies. Therefore, examining hormetic responses at single-cell level coupled with improved mathematical models could substantially enhance detection and mechanistic understanding of hormesis.

Hormesis is a highly controversial and poorly understood phenomenon. It describes the idea that an inhibitor molecule, like an anti-cancer or anti-microbial drug, can inadvertently stimulate cell growth instead of suppressing it. This can have a profound effect on human health leading to failures in clinical treatments. Therefore, getting at the mechanistic basis of hormesis is critical for drug development and clinical practice, however molecular mechanisms underpinning hormesis remain poorly understood. In this paper we use a mathematical model to propose a simple and yet general mechanism that could explain why we find hormesis so widely in living systems. In particular, we discover that hormesis is present within a fundamental structure that forms a basic building block of many intracellular signalling pathways found in diverse processes including control of cell reproduction and programmed cell death. The benefits of our study are two-fold. Having simple molecular understanding of the causes of hormetic responses can greatly improve the design of new drug compounds that avoid such responses. Moreover, due to the fundamental nature of the newly proposed mechanism, our findings have a potential broad applicability to both anti-cancer and anti-microbial drugs.

Decrease in catalytic capacity of γ-secretase can facilitate pathogenesis in sporadic and Familial Alzheimer's disease

BACKGROUND

Alzheimer's disease can be a result of an age-induced disparity between increase in cellular metabolism of Aβ peptides and decrease in maximal activity of a membrane-embedded protease γ-secretase.

RESULTS

We compared activity of WT γ-secretase with the activity of 6 FAD mutants in its presenilin-1 component and 5 FAD mutants in Aβ-part of its APP substrate (Familial Alzheimer's disease). All 11 FAD mutations show linear correlation between the decrease in maximal activity and the clinically observed age-of-onset and age-of-death. Biphasic-inhibitors showed that a higher ratio between physiological Aβ-production and the maximal activity of γ-secretase can be observed in cells that can facilitate pathogenic changes in Aβ-products. For example, Aβ production in cells with WT γ-secretase is at 11% of its maximal activity, with delta-exon-9 mutant at 26%, while with M139V mutant is at 28% of the maximal activity. In the same conditions, G384A mutant is fully saturated and at its maximal activity. Similarly, Aβ production in cells with γ-secretase complex carrying Aph1AL component is 12% of its maximal activity, while in cells with Aph1B complex is 26% of its maximal activity. Similar to the cell-based studies, clinical studies of biphasic dose-response in plasma samples of 54 healthy individuals showed variable ratios between physiological Aβ production and the maximal activity of γ-secretase.

CONCLUSIONS

The increase in the ratio between physiological Aβ production and maximal activity of γ-secretase can be an early sign of pathogenic processes in enzyme-based, cell-based, and clinical studies of sporadic and Familiar Alzheimer's disease.

CNS amyloid-β, soluble APP-α and -β kinetics during BACE inhibition

BACE, a β-secretase, is an attractive potential disease-modifying therapeutic strategy for Alzheimer's disease (AD) as it results directly in the decrease of amyloid precursor protein (APP) processing through the β-secretase pathway and a lowering of CNS amyloid-β (Aβ) levels. The interaction of the β-secretase and α-secretase pathway-mediated processing of APP in the rhesus monkey (nonhuman primate; NHP) CNS is not understood. We hypothesized that CNS inhibition of BACE would result in decreased newly generated Aβ and soluble APPβ (sAPPβ), with increased newly generated sAPPα. A stable isotope labeling kinetics experiment in NHPs was performed with a (13)C6-leucine infusion protocol to evaluate effects of BACE inhibition on CNS APP processing by measuring the kinetics of sAPPα, sAPPβ, and Aβ in CSF. Each NHP received a low, medium, or high dose of MBI-5 (BACE inhibitor) or vehicle in a four-way crossover design. CSF sAPPα, sAPPβ, and Aβ were measured by ELISA and newly incorporated label following immunoprecipitation and liquid chromatography-mass spectrometry. Concentrations, kinetics, and amount of newly generated APP fragments were calculated. sAPPβ and sAPPα kinetics were similar, but both significantly slower than Aβ. BACE inhibition resulted in decreased labeled sAPPβ and Aβ in CSF, without observable changes in labeled CSF sAPPα. ELISA concentrations of sAPPβ and Aβ both decreased and sAPPα increased. sAPPα increased by ELISA, with no difference by labeled sAPPα kinetics indicating increases in product may be due to APP shunting from the β-secretase to the α-secretase pathway. These results provide a quantitative understanding of pharmacodynamic effects of BACE inhibition on NHP CNS, which can inform about target development.

Abeta, oxidative stress in Alzheimer disease: evidence based on proteomics studies

The initiation and progression of Alzheimer disease (AD) is a complex process not yet fully understood. While many hypotheses have been provided as to the cause of the disease, the exact mechanisms remain elusive and difficult to verify. Proteomic applications in disease models of AD have provided valuable insights into the molecular basis of this disorder, demonstrating that on a protein level, disease progression impacts numerous cellular processes such as energy production, cellular structure, signal transduction, synaptic function, mitochondrial function, cell cycle progression, and proteasome function. Each of these cellular functions contributes to the overall health of the cell, and the dysregulation of one or more could contribute to the pathology and clinical presentation in AD. In this review, foci reside primarily on the amyloid β-peptide (Aβ) induced oxidative stress hypothesis and the proteomic studies that have been conducted by our laboratory and others that contribute to the overall understanding of this devastating neurodegenerative disease.

The progression towards Alzheimer's disease described as a bistable switch arising from the positive loop between amyloids and Ca(2+)

Alzheimer's disease is a progressive neurodegenerative disorder affecting millions of people. It is characterized by the slow deposition of cerebral amyloid-β peptides in the brain and by dysregulations in neuronal Ca(2+) homeostasis. Numerous experimental studies have revealed the existence of a feed-forward loop wherein amyloids-β disturb neuronal Ca(2+) levels, which in turn affect the production of amyloids. Here, we formalize this positive loop in a minimal, qualitative model and show that it exhibits bistability. Thus, a stable steady state characterized by low levels of Ca(2+) and amyloids, corresponding to a healthy situation, coexists with another 'pathological state' where the levels of both compounds are high. The onset of the disease corresponds to the switch from the lower steady state to the higher one induced by a large-enough perturbation in either the metabolism of amyloids or the homeostasis of intracellular Ca(2+). Numerical simulations of the model reproduce a variety of experimental observations about the disease, as its irreversible character, the threshold-like transition to a severe pathology after the slow accumulation of symptoms, the effect of presenilins, the so-called 'prion-like' autocatalytic behaviour of amyloids and the inherent random character of the apparition of the disease that is well known for the sporadic form. The model thus provides a conceptual framework that could be useful when developing therapeutic protocols to slow down the progression of Alzheimer's disease.

Plasma amyloid beta measurements - a desired but elusive Alzheimer's disease biomarker

Cerebrospinal fluid and positron emission tomography biomarkers accurately predict an underlying Alzheimer's disease (AD) pathology; however, they represent either invasive or expensive diagnostic tools. Therefore, a blood-based biomarker like plasma amyloid beta (Aβ) that could correlate with the underlying AD pathology and serve as a prognostic biomarker or an AD screening strategy is urgently needed as a cost-effective and non-invasive diagnostic tool. In this paper we review the demographic, biologic, genetic and technical aspects that affect plasma Aβ levels. Findings of cross-sectional and longitudinal studies of plasma Aβ, including autosomal dominant AD cases, sporadic AD cases, Down syndrome cases and population studies, are also discussed. Finally, we review the association between cerebrovascular disease and Aβ plasma levels and the responses observed in clinical trials. Based on our review of the current literature on plasma Aβ, we conclude that further clinical research and assay development are needed before measures of plasma Aβ can be interpreted so they can be applied as trait, risk or state biomarkers for AD.