Heme oxygenase-1 protects against Alzheimer’s amyloid-β1-42 induced toxicity via carbon monoxide production

Heme oxygenase-1 (HO-1), an inducible enzyme up-regulated in Alzheimer‟s disease (AD), catabolises heme to biliverdin, Fe2+ and carbon monoxide (CO). CO can protect neurones from oxidative stress-induced apoptosis by inhibiting Kv2.1 channels, which mediate cellular K+ efflux as an early step in the apoptotic cascade. Since apoptosis contributes to the neuronal loss associated with amyloid β peptide (Aβ) toxicity in AD, we investigated the protective effects of HO-1 and CO against Aβ1-42 toxicity in SH-SY5Y cells, employing cells stably transfected with empty vector or expressing the cellular prion protein, PrPc, and rat primary hippocampal neurons. Aβ1-42 (containing protofibrils) caused a concentrationdependent decrease in cell viability, attributable at least in part to induction of apoptosis, with the PrPc expressing cells showing greater susceptibility to Aβ1-42 toxicity. Pharmacological induction or genetic over-expression of HO-1 significantly ameliorated the effects of Aβ1-42. The CO-donor CORM-2 protected cells against Aβ1-42 toxicity in a concentration-dependent manner. Electrophysiological studies revealed no differences in the outward current pre- and post-Aβ1-42 treatment suggesting that K+ channel activity is unaffected in these cells. Instead, Aβ toxicity was reduced by the L-type Ca2+ channel blocker nifedipine, and by the CaMKKII inhibitor, STO-609. Aβ also activated the downstream kinase, AMP-dependent protein kinase (AMPK). CO prevented this activation of AMPK. Our findings indicate that HO-1 protects against Aβ toxicity via production of CO. Protection does not arise from inhibition of apoptosis-associated K+ efflux, but rather by inhibition of AMPK activation, which has been recently implicated in the toxic effects of Aβ. These data provide a novel, beneficial effect of CO which adds to its growing potential as a therapeutic agent.

The nutritional and clinical significance of lipid rafts

Purpose of review Lipid rafts are potentially modifiable by diet, particularly (but not exclusively) by dietary fatty acids. This review examines the potential for dietary modification of raft structure and function in the immune system, brain and retinal tissue, the gut, and in cancer cells. Recent findings In-vitro and ex-vivo studies suggest that dietary n-3 polyunsaturated fatty acids (PUFAs) may exert immunosuppressive and anticancer effects through changes in lipid raft organization. In addition, gangliosides and cholesterol may modulate lipid raft organization in a number of tissues, and recent work has highlighted sphingolipids in membrane microdomains as potential targets for inhibition of tumor growth. The roles of fatty acids and gangliosides, especially in relation to lipid rafts, in cognitive development, age-related cognitive decline, psychiatric disorders, and Alzheimer’s disease are poorly understood and require further investigation. The roles of lipid rafts in cancer, in microbial pathogenesis, and in insulin resistance are starting to emerge, and indicate compelling evidence for the growing importance of membrane microdomains in health and disease. Summary In-vitro and animal studies show that n-3 PUFAs, cholesterol, and gangliosides modulate the structure and composition of lipid rafts, potentially influencing a wide range of biological processes, including immune function, neuronal signaling, cancer cell growth, entry of pathogens through the gut barrier, and insulin resistance in metabolic disorders. The physiological, clinical, and nutritional relevance of these observations remains to be determined.

Neuroinflammation and its modulation by flavonoids

There is increasing evidence to suggest that neuroinflammatory processes contribute to the cascade of events that lead to the progressive neuronal damage observed in neurodegenerative disorders such as Parkinson’s disease and Alzheimer’s disease. Therefore, treatment regimes aimed at modulating neuroinflammatory processes may act to slow the progression of these debilitating brain disorders. Recently, a group of dietary polyphenols known as flavonoids have been shown to exert neuroprotective effects in vivo and in neuronal cell models. In this review we discuss the evidence relating to the modulation of neuroinflammation by flavonoids. We highlight the evidence which suggests their mechanism of action involves: 1) attenuation of the release of cytokines, such as interleukin-1β (IL-1β) and tumor necrosis factor-alpha (TNF-α); 2) an inhibitory action against inducible nitric oxide synthase (iNOS) induction and subsequent nitric oxide (NO•) production; 3) inhibition of the activation of NADPH oxidase and subsequent reactive oxygen species generation; 4) a capacity to down-regulate the activity of pro-inflammatory transcription factors such as nuclear factor-κB (NF-κB); and 5) the potential to modulate signalling pathways such as mitogen-activated protein kinase (MAPK) cascade. We also consider the potential of these dietary compounds to represent novel therapeutic agents by considering their metabolism in the body and their ability to access the brain via the blood brain barrier. Finally, we discuss future areas of study which are necessary before dietary flavonoids can be established as therapeutic agents against neuroinflammation.

Amyloid formation: interface influence

The causes of pathological conditions such as Alzheimer’s and Parkinson’s diseases are becoming better understood. Proteins that misfold from their native structure to form aggregates of β-sheet fibrils — termed amyloid — are known1,2 to be implicated in these ‘amyloid diseases’. Understanding the early steps of fibril formation is critical, and the conditions, mechanism and kinetics of protein and peptide aggregation are being widely investigated through a variety of in vitro studies. Kinetic aspects of the dispersion of the protein or peptide in solution are thought to influence the fibrillization process by mass-transfer effects. In addition, mixing also leads to shear forces, which can influence fibril growth by perturbing the equilibrium between the isolated and aggregated proteins, causing existing fibrils to fragment and create new nuclei3. Writing in the Journal of the American Chemical Society, David Talaga and co-workers have now highlighted4 an additional factor that can influence the fibrillization of amyloid-forming proteins — the presence of hydrophobic interfaces.

Modulation of neuroinflammation by dietary flavonoids

There is increasing evidence to suggest neuroinflammatory processes contribute to the cascade of events that lead to the progressive neuronal damage observed in neurodegenerative disorders such as Parkinson’s disease and Alzheimer’s disease. The molecular mechanisms underlying such neurodegenerative processes are rather complex and involve modulation of the mitogen-activated protein kinase (MAPK) and NF-κB pathways leading to the generation of nitric oxide (NO). Such a small molecule may diffuse to the neighbouring neurons and trigger neuronal death through the inhibition of mitochondrial respiration and increases in the reactive oxygen and nitrogen species. Recently, attention has focused on the neuroprotective effects of flavonoids which have been effective in protecting against both age-related cognitive and motor decline in vivo. Although, the precise mechanisms by which flavonoids may exert their neuroprotective effects remain unclear, accumulating evidence suggest that they may exert their neuroprotective effects through the modulation of the MAP Kinase and PI3 Kinase signaling pathways. The aim of the present chapter is to highlight the potential neuroprotective role of dietary flavonoids in terms of their ability to modulate neuroinflammation in the central nervous system. We will provide an outline of the role glial cells play in neuroinflammation and describe the involvement of inflammatory mediators, produced by glia, in the cascade of events leading to neuronal degeneration. We will then present the evidence that flavonoids may modulate neuroinflammation by inhibiting the production of these inflammatory agents and summarise their potential mechanisms of action.

Regulation of NF-κB activity in astrocytes: effects of flavonoids at dietary-relevant concentrations

Neuroinflammation plays an important role in the progression of neurodegenerative disorders such as Alzheimer’s disease and Parkinson’s disease. Sustained activation of nuclear transcription factor κB (NF-κB) is thought to play an important role in the pathogenesis of neurodegenerative disorders. Flavonoids have been shown to possess antioxidant and anti-inflammatory properties and we investigated whether flavonoids, at submicromolar concentrations relevant to their bioavailability from the diet, were able to modulate NF-κB signalling in astrocytes. Using luciferase reporter assays, we found that tumour necrosis factor (TNFα, 150 ng/ml) increased NF-κB-mediated transcription in primary cultures of mouse cortical astrocytes, which was abolished on co-transfection of a dominant-negative IκBα construct. In addition, TNFα increased nuclear localisation of p65 as shown by immunocytochemistry. To investigate potential flavonoid modulation of NF-κB activity, astrocytes were treated with flavonoids from different classes; flavan-3-ols ((−)-epicatechin and (+)-catechin), flavones (luteolin and chrysin), a flavonol (kaempferol) or the flavanones (naringenin and hesperetin) at dietary-relevant concentrations (0.1–1 μM) for 18 h. None of the flavonoids modulated constitutive or TNFα-induced NF-κB activity. Therefore, we conclude that NF-κB signalling in astrocytes is not a major target for flavonoids.

Neural correlates of true and false memory in mild cognitive impairment

The goal of this research was to investigate the changes in neural processing in mild cognitive impairment. We measured phase synchrony, amplitudes, and event-related potentials in veridical and false memory to determine whether these differed in participants with mild cognitive impairment compared with typical, age-matched controls. Empirical mode decomposition phase locking analysis was used to assess synchrony, which is the first time this analysis technique has been applied in a complex cognitive task such as memory processing. The technique allowed assessment of changes in frontal and parietal cortex connectivity over time during a memory task, without a priori selection of frequency ranges, which has been shown previously to influence synchrony detection. Phase synchrony differed significantly in its timing and degree between participant groups in the theta and alpha frequency ranges. Timing differences suggested greater dependence on gist memory in the presence of mild cognitive impairment. The group with mild cognitive impairment had significantly more frontal theta phase locking than the controls in the absence of a significant behavioural difference in the task, providing new evidence for compensatory processing in the former group. Both groups showed greater frontal phase locking during false than true memory, suggesting increased searching when no actual memory trace was found. Significant inter-group differences in frontal alpha phase locking provided support for a role for lower and upper alpha oscillations in memory processing. Finally, fronto-parietal interaction was significantly reduced in the group with mild cognitive impairment, supporting the notion that mild cognitive impairment could represent an early stage in Alzheimer’s disease, which has been described as a ‘disconnection syndrome’.

Curcumin protects organotypic hippocampal slice cultures 4 from Ab1–42 -induced synaptic toxicity

Increasing evidence demonstrates that beta-amyloid (Ab) is toxic to synapses, resulting in the progressive dismantling of neuronal circuits. Counteract the synaptotoxic effects of Ab could be particularly relevant for providing effective treatments for Alzheimer’s disease (AD). Curcumin was recently reported to improve learning and memory in animal models of AD. Little is currently known about the specific mechanisms by which Ab affects neuronal excitability and curcumin ameliorates synaptic transmission in the hippocampus. Organotypic hippocampal slice cultures exposed to Ab1–42 were used to study the neuroprotective effects of curcumin through a spectral analysis of multi-electrode array (MEA) recordings of spontaneous neuronal activity. Curcumin counteracted both deleterious effects of Ab; the initial synaptic dysfunction and the later neuronal death. The analysis of MEA recordings of spontaneous neuronal activity showed an attenuation of signal propagation induced by Ab before cell death and curcumin-induced alterations to local field potential (LFP) phase coherence. Curcumin-mediated attenuation of Ab-induced synaptic dysfunction involved regulation of synaptic proteins, namely phospho-CaMKII and phosphosynapsin I. Taken together, our results expand the neuroprotective role of curcumin to a synaptic level. The identification of these mechanisms underlying the effects of curcumin may lead to new targets for future therapies for AD.

The effects of flavonoid and other polyphenol consumption on cognitive performance: A systematic research review of human experimental and epidemiological studies

Literature reviews suggest flavonoids, a sub-class of polyphenols, are beneficial for cognition. This is the first review examining the effect of consumption of all polyphenol groups on cognitive function. Inclusion criteria were polyphenol vs. control interventions and epidemiological studies with an objective measure of cognitive function. Participants were healthy or mildly cognitively impaired adults. Studies were excluded if clinical assessment or diagnosis of Alzheimer’s disease, dementia, or cognitive impairment was the sole measure of cognitive function, or if the polyphenol was present with potentially confounding compounds such as caffeine (e.g. tea studies) or Ginkgo Biloba. 28 studies were identified; 4 berry juice studies, 4 cocoa studies, 13 isoflavone supplement studies, 3 other supplement studies, and 4 epidemiological surveys. Overall, 16 studies reported cognitive benefits following polyphenol consumption. Evidence suggests that consuming additional polyphenols in the diet can lead to cognitive benefits, however, the observed effects were small. Declarative memory and particularly spatial memory appear most sensitive to polyphenol consumption and effects may differ depending on polyphenol source. Polyphenol berry fruit juice consumption was most beneficial for immediate verbal memory, whereas isoflavone based interventions were associated with significant improvements for delayed spatial memory and executive function. Comparison between studies was hampered by methodological inconsistencies. Hence, there was no clear evidence for an association between cognitive outcomes and polyphenol dose response, duration of intervention, or population studied. In conclusion, however, the findings do imply that polyphenol consumption has potential to benefit cognition both acutely and chronically.

Advanced feature selection methods in multinominal dementia classification from structural MRI data

Recent studies showed that features extracted from brain MRIs can well discriminate Alzheimer’s disease from Mild Cognitive Impairment. This study provides an algorithm that sequentially applies advanced feature selection methods for findings the best subset of features in terms of binary classification accuracy. The classifiers that provided the highest accuracies, have been then used for solving a multi-class problem by the one-versus-one strategy. Although several approaches based on Regions of Interest (ROIs) extraction exist, the prediction power of features has not yet investigated by comparing filter and wrapper techniques. The findings of this work suggest that (i) the IntraCranial Volume (ICV) normalization can lead to overfitting and worst the accuracy prediction of test set and (ii) the combined use of a Random Forest-based filter with a Support Vector Machines-based wrapper, improves accuracy of binary classification.

Towards the computer-aided diagnosis of dementia based on the geometric and network connectivity of structural MRI data

We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.

Interactions between lipid-free apolipoprotein-AI and a lipopeptide incorporating the RGDS cell adhesion motif

The interaction of a designed bioactive lipopeptide C16-GGGRGDS, comprising a hexadecyl lipid chain attached to a functional heptapeptide, with the lipid-free apoliprotein, Apo-AI, is examined. This apolipoprotein is a major component of high density lipoprotein and it is involved in lipid metabolism and may serve as a biomarker for cardiovascular disease and Alzheimers’ disease. We find via isothermal titration calorimetry that binding between the lipopeptide and Apo-AI occurs up to a saturation condition, just above equimolar for a 10.7 μM concentration of Apo-AI. A similar value is obtained from circular dichroism spectroscopy, which probes the reduction in α-helical secondary structure of Apo-AI upon addition of C16-GGGRGDS. Electron microscopy images show a persistence of fibrillar structures due to self-assembly of C16-GGGRGDS in mixtures with Apo-AI above the saturation binding condition. A small fraction of spheroidal or possibly “nanodisc” structures was observed. Small-angle X-ray scattering (SAXS) data for Apo-AI can be fitted using a published crystal structure of the Apo-AI dimer. The SAXS data for the lipopeptide/ Apo-AI mixtures above the saturation binding conditions can be fitted to the contribution from fibrillar structures coexisting with flat discs corresponding to Apo-AI/lipopeptide aggregates.

An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI

In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer’s Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy controlsized or Alzheimer’s Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer’s Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state of the art classifiers is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer’s Disease, or even further the understand of how Alzheimer’s Disease affects the hippocampus.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.