Higher-order spectral analysis of spontaneous speech signals in Alzheimer’s disease

An early and accurate diagnosis of Alzheimer’s disease (AD) has been progressively attracting more attention in recent years. One of the main problems of AD is the loss of language skills. This paper presents a computational framework for classifying AD patients compared to healthy control subjects using information from spontaneous speech signals. Spontaneous speech data are obtained from 30 AD patients and 30 healthy controls. Because of the nonlinear and dynamic nature of speech signals, higher order spectral features (specifically bispectrum) were used for analysis. Four classifiers (k-Nearest Neighbor, Support Vector Machine, Naïve Bayes and Decision tree) were used to classify subjects into three different levels of AD and healthy group based on their performance in terms of the HOS-based features. Ten-fold cross-validation method was used to test the reliability of the classifier results. The results showed that the proposed method had a good potential in AD diagnosis. The proposed method was also able to diagnose the earliest stage of AD with high accuracy. The method has the great advantage of being non-invasive, cost-effective, and associated with no side effects. Therefore, the proposed method can be a spontaneous speech directed test for pre-clinical evaluation of AD diagnosis.     

A predictive microarray-based biomarker for early detection of Alzheimer’s disease intended for clinical diagnostic application

Abstract

Objective: Microarray-based signatures for clinical application are often plagued by processing variability or batch effects that compromise the robustness of the test performance.

Methods: A splice variant array-based signature for early detection of Alzheimer’s disease (AD) was developed using 315 AD or normal subjects processed in three disparate microarray batches.

Results: A modified top scoring pair classifier using the signature, is robust to batch effects and outperforms other common classifiers, with sensitivity and specificity of 88.3% (95% CI:81.2%, 93.4%) and 88.9% (95% CI:65.3%, 98.6%), respectively, on an independent cohort.

Conclusions: This splice-variant array-based signature shows promise for clinical diagnostic use in AD.     

Discovery of novel PDE9A inhibitors with antioxidant activities for treatment of Alzheimer’s disease

Phosphodiesterase-9 (PDE9) is a promising target for treatment of Alzheimer’s disease (AD). To discover multifunctional anti-AD agents with capability of PDE9 inhibition and antioxidant activity, a series of novel pyrazolopyrimidinone derivatives, coupling with the pharmacophore of antioxidants such as ferulic and lipolic acids have been designed with the assistance of molecular docking and dynamics simulations. Twelve out of 14 synthesised compounds inhibited PDE9A with IC₅₀ below 200?nM, and showed good antioxidant capacities in the ORAC assay. Compound 1h, the most promising multifunctional anti-AD agent, had IC₅₀ of 56?nM against PDE9A and good antioxidant ability (ORAC (trolox)?=?3.3). The selectivity of 1h over other PDEs was acceptable. In addition, 1h showed no cytotoxicity to human neuroblastoma SH-SY5Y cells. The analysis on structure-activity relationship (SAR) and binding modes of the compounds may provide insight into further modification.     

Advances in developing novel therapeutic strategies for Alzheimer’s disease

Alzheimer’s Disease (AD), the most prevalent neurodegenerative disease of aging, affects one in eight older Americans. Nearly all drug treatments tested for AD today have failed to show any efficacy. There is a great need for therapies to prevent and/or slow the progression of AD. The major challenge in AD drug development is lack of clarity about the mechanisms underlying AD pathogenesis and pathophysiology. Several studies support the notion that AD is a multifactorial disease. While there is abundant evidence that amyloid plays a role in AD pathogenesis, other mechanisms have been implicated in AD such as tangle formation and spread, dysregulated protein degradation pathways, neuroinflammation, and loss of support by neurotrophic factors. Therefore, current paradigms of AD drug design have been shifted from single target approach (primarily amyloid-centric) to developing drugs targeted at multiple disease aspects, and from treating AD at later stages of disease progression to focusing on preventive strategies at early stages of disease development. Here, we summarize current strategies and new trends of AD drug development, including pre-clinical and clinical trials that target different aspects of disease (mechanism-based versus non-mechanism based, e.g. symptomatic treatments, lifestyle modifications and risk factor management).     

A panel of four decreased serum microRNAs as a novel biomarker for early Parkinson’s disease

Context: Sensitive, non-invasive biomarkers that facilitate Parkinson’s disease (PD) detection and stage assignment are currently unavailable.

Objective: The objective of this study is to investigate the potential of circulating microRNAs (miRNAs) as novel biomarkers for PD.

Materials and methods: Solexa sequencing technology and quantitative real-time PCR were applied to screen and verify altered serum miRNAs in PD patients.

Results: Serum miR-141, miR-214, miR-146b-5p, and miR-193a-3p were decreased significantly in PD patients compared with controls. Furthermore, the 4-miRNA panel enabled the differentiation of HY stage 1 and 2 PD patients from controls.

Discussion and conclusion: The four serum miRNAs may represent novel biomarkers for the early detection of PD.     

A standard model of Alzheimer’s disease?

ABSTRACT

The recent Research Framework proposed by the US National Institute on Aging and the Alzheimer’s Association (NIA-AA) recommends that Alzheimer’s disease be defined by its specific biology rather than by non-specific neurodegenerative and syndromal features. By affirming markers of abnormal Aβ and tau proteins as the essential pathobiological signature of Alzheimer’s disease, the Framework tacitly reinforces the amyloid (Aβ) cascade as the leading theory of Alzheimer pathogenesis. In light of recent evidence that the cascade is driven by the misfolding and templated aggregation of Aβ and tau, we believe that an empirically grounded Standard Model of Alzheimer’s pathogenesis is within reach. A Standard Model can clarify and consolidate existing information, contextualize risk factors and the complex disease phenotype, identify testable hypotheses for future research, and pave the most direct path to effective prevention and treatment.     

Mathematical model on Alzheimer’s disease

Background

Alzheimer disease (AD) is a progressive neurodegenerative disease that destroys memory and cognitive skills. AD is characterized by the presence of two types of neuropathological hallmarks: extracellular plaques consisting of amyloid β-peptides and intracellular neurofibrillary tangles of hyperphosphorylated tau proteins. The disease affects 5 million people in the United States and 44 million world-wide. Currently there is no drug that can cure, stop or even slow the progression of the disease. If no cure is found, by 2050 the number of alzheimer’s patients in the U.S. will reach 15 million and the cost of caring for them will exceed $ 1 trillion annually.

Results

The present paper develops a mathematical model of AD that includes neurons, astrocytes, microglias and peripheral macrophages, as well as amyloid β aggregation and hyperphosphorylated tau proteins. The model is represented by a system of partial differential equations. The model is used to simulate the effect of drugs that either failed in clinical trials, or are currently in clinical trials.

Conclusions

Based on these simulations it is suggested that combined therapy with TNF- α inhibitor and anti amyloid β could yield significant efficacy in slowing the progression of AD.

     

New approaches for the treatment of Alzheimer’s disease

Alzheimer’s disease (AD) is the most prevalent chronic neurodegenerative disease. Current approved therapies are symptomatic treatments having some effect on cognitive function. Therapies that target β-amyloid (Aβ) have been the focus of efforts to develop a disease modification treatment for AD but these approaches have failed to show any clinical benefit so far. Beyond the ‘Aβ hypothesis’, there are a number of newer approaches to treat AD with neuroinflammation emerging as a very active area of research based on risk gene analysis. This short review will summarize approved drug therapies, recent clinical trials and new approaches for the treatment of AD.     

Synthesis and evaluation of novel benzothiazole derivatives based on the bithiophene structure as potential radiotracers for β-amyloid plaques in Alzheimer’s disease

In this study, six novel benzothiazole derivatives based on the bithiophene structure were developed as potential β-amyloid probes. In vitro binding studies using Aβ aggregates showed that all of them demonstrated high binding affinities with K_i values ranged from 0.11 to 4.64 nM. In vitro fluorescent staining results showed that these compounds can intensely stained Aβ plaques within brain sections of APP/PS1 transgenic mice, animal model for AD. Two radioiodinated compounds [¹²⁵I]-2-(5′-iodo-2,2′-bithiophen-5-yl)-6-methoxybenzo[d]thiazole [¹²⁵I]10 and [¹²⁵I]-2-(2,2′-bithiophen-5-yl)-6-iodobenzo[d]thiazole [¹²⁵I]13 were successfully prepared through an iododestannylation reaction. Furthermore, in vitro autoradiography of the AD model mice brain sections showed that both [¹²⁵I]10 and [¹²⁵I]13 labeled the Aβ plaques specifically with low background. In vivo biodistribution studies in normal mice indicated that [¹²⁵I]13 exhibited high brain uptake (3.42% ID/g at 2 min) and rapid clearance from the brain (0.53% ID/g at 60 min), while [¹²⁵I]10 showed lower brain uptake (0.87% ID/g at 2 min). In conclusion, these preliminary results of this study suggest that the novel radioiodinated benzothiazole derivative [¹²⁵I]13 may be a candidate as an in vivo imaging agent for detecting β-amyloid plaques in the brain of AD patients.     

A brief overview of amyloids and Alzheimer’s disease

Amyloid fibrils are self-assembled fibrous protein aggregates that are associated with a number of presently incurable diseases such as Alzheimer’s and Parkinson’s disease. Millions of people worldwide suffer from amyloid diseases. This review summarizes the unique cross-β structure of amyloid fibrils, morphological variations, the kinetics of amyloid fibril formation, and the cytotoxic effects of these fibrils and oligomers. Alzheimer’s disease is also explored as an example of an amyloid disease to show the various approaches to treat these amyloid diseases. Finally, this review investigates the nanotechnological and biological applications of amyloid fibrils; as well as a summary of the typical biological pathways involved in the disposal of amyloid fibrils and their precursors.     

Discovery of novel 2,5-dihydroxyterephthalamide derivatives as multifunctional agents for the treatment of Alzheimer’s disease

A series of 2,5-dihydroxyterephthalamide derivatives were designed, synthesized and evaluated as multifunctional agents for the treatment of Alzheimer’s disease. In vitro assays demonstrated that most of the derivatives exhibited good multifunctional activities. Among them, compound 9d showed the best inhibitory activity against both RatAChE and EeAChE (IC₅₀?=?0.56?μM and 5.12?μM, respectively). Moreover, 9d exhibited excellent inhibitory effects on self-induced Aβ_1–42 aggregation (IC₅₀?=?3.05?μM) and Cu²⁺-induced Aβ_1–42 aggregation (71.7% at 25.0?μM), and displayed significant disaggregation ability to self- and Cu²⁺-induced Aβ_1–42 aggregation fibrils (75.2% and 77.2% at 25.0?μM, respectively). Furthermore, 9d also showed biometal chelating abilities, antioxidant activity, anti-neuroinflammatory activities and appropriate BBB permeability. These multifunctional properties highlight 9d as promising candidate for further studies directed to the development of novel drugs against AD.     

Above-ground biomass estimation based on NPP time-series − A novel approach for biomass estimation in semi-arid Kazakhstan

Biomass is a sensitive indicator of environmental change and ecological functioning. Quantification of biomass is essential to identify and monitor those areas threatened by degradation and desertification. This is especially important in arid and semi-arid environments. However, robust techniques to monitor carbon stocks over large areas and through time are still missing. The major objective of the presented study is to develop a novel approach for biomass estimation in semi-arid environments using remote-sensing based Net Primary Productivity (NPP) data.The developed methodical concept aims at derivation of above-ground grass and shrub biomass for natural environments. It is based on NPP time-series and plants’ relative growth rates. Fractional cover data provide information about grass and shrub coverage. The developed approach has been applied to three study areas in Kazakhstan, in which field data were collected for validation.Biomass maps were derived that show the spatial distribution of grass and shrub biomass. Validation revealed a moderate correlation (R = 0.68) with field data for grass biomass. For shrub biomass, a high correlation (R = 0.83) is retrieved when fractional cover information from field observations is used.The presented novel approach for biomass estimation is based on remote sensing derived NPP time-series and is thus potentially transferable in space and time. This is a great advantage compared to commonly applied empirical relationships. The presented concept can be adapted to be applied to other vegetation communities. Providing the necessary data about fractional vegetation cover is available, the method will allow for repeated and large-area biomass estimation for natural semi-arid environments as needed for observing changes in biomass and support sustainable land management.     

Synthesis and evaluation of multi-target-directed ligands for the treatment of Alzheimer’s disease based on the fusion of donepezil and melatonin

A novel series of compounds obtained by fusing the acetylcholinesterase (AChE) inhibitor donepezil and the antioxidant melatonin were designed as multi-target-directed ligands for the treatment of Alzheimer’s disease (AD). In vitro assay indicated that most of the target compounds exhibited a significant ability to inhibit acetylcholinesterase (eeAChE and hAChE), butyrylcholinesterase (eqBuChE and hBuChE), and β-amyloid (Aβ) aggregation, and to act as potential antioxidants and biometal chelators. Especially, 4u displayed a good inhibition of AChE (IC₅₀ value of 193 nM for eeAChE and 273 nM for hAChE), strong inhibition of BuChE (IC₅₀ value of 73 nM for eqBuChE and 56 nM for hBuChE), moderate inhibition of Aβ aggregation (56.3% at 20 μM) and good antioxidant activity (3.28 trolox equivalent by ORAC assay). Molecular modeling studies in combination with kinetic analysis revealed that 4u was a mixed-type inhibitor, binding simultaneously to catalytic anionic site (CAS) and the peripheral anionic site (PAS) of AChE. In addition, 4u could chelate metal ions, reduce PC12 cells death induced by oxidative stress and penetrate the blood–brain barrier (BBB). Taken together, these results strongly indicated the hybridization approach is an efficient strategy to identify novel scaffolds with desired bioactivities, and further optimization of 4u may be helpful to develop more potent lead compound for AD treatment.     

Design,synthesis and evaluation of pyrazolopyrimidinone derivatives as novel PDE9A inhibitors for treatment of Alzheimer’s disease

Phosphodiesterase-9 (PDE9) is a promising target for the treatment of Alzheimer’s disease (AD). To discover efficient PDE9 inhibitors with good metabolic stability and solubility, a series of novel pyrazolopyrimidinone derivatives have been designed with the assistance of molecular docking and dynamics simulations. All the fourteen synthesized compounds gave excellent inhibition ratio against PDE9 at 10 nM. Compound 1k with the IC₅₀ of 2.0 nM against PDE9, showed good metabolic stability (t_1/2 of 57 min) in the RLM as well as good solubility (195 mg/L). The analysis on binding modes of targeted compounds may provide insight for further structural modification.     

Integrative computational evaluation of genetic markers for Alzheimer’s disease

Recent studies have reported hundreds of genes linked to Alzheimer’s Disease (AD). However, many of these candidate genes may be not identified in different studies when analyses were replicated. Moreover, results could be controversial. Here, we proposed a computational workflow to curate and evaluate AD related genes. The method integrates large scale literature knowledge data and gene expression data that were acquired from postmortem human brain regions (AD case/control: 31/32 and 22/8). Pathway Enrichment, Sub-Network Enrichment, and Gene-Gene Interaction analysis were conducted to study the pathogenic profile of the candidate genes, with 4 metrics proposed and validated for each gene. By using our approach, a scalable AD genetic database was developed, including AD related genes, pathways, diseases and info of supporting references. The AD case/control classification supported the effectiveness of the 4 proposed metrics, which successfully identified 21 well-studied AD genes (i.g. TGFB1, CTNNB1, APP, IL1B, PSEN1, PTGS2, IL6, VEGFA, SOD1, AKT1, CDK5, TNF, GSK3B, TP53, CCL2, BDNF, NGF, IGF1, SIRT1, AGER and TLR) and highlighted one recently reported AD gene (i.g. ITGB1). The computational biology approach and the AD database developed in this study provide a valuable resource which may facilitate the understanding of the AD genetic profile.     

A comment on Warburg’s early understanding of biocatalysis

The early history of biochemistry was characterized by changing moods. The discovery of cell free fermentation (1897) led to the optimistic belief that all life processes were carried out by intracellular enzymes, being definite proteins with special catalytic properties. But, the persistent failure to isolate pure enzymes raised doubts. When Otto Warburg found cell respiration to be a membrane-bound iron catalysis (1914), he renewed the old position that biocatalysis was caused by surface forces and ferments could be heavy metal ions adsorbed on colloidal membrane carriers. This alternative view became popular when Warburg started his research in photosynthesis and explained his peculiar “photolyte” model. Neither the suggestion of surface-active colloidal ferments, nor the idea of “photolyte” stood the test of time and have now been rejected, but their history is of importance to how concepts evolve and die.     

Evolution of Alzheimer’s disease pathogenesis conception

Alzheimer’s disease (AD) is a neurodegenerative disorder that becomes a cause of dementia during atrophic brain changes. There are two distinguished forms of AD: familial early-onset form (FAD, approximately 5% of all cases, develops before age 65, most commonly 40–50) and sporadic late-onset form (SAD, approximately 95% of all cases, develops after 65). Identification of genetic determinants of FAD development and evidence of amyloid-beta peptide’s (Aβ) neurotoxicity as a central event in the cascade of pathological processes significantly expanded the conception of molecular and genetic mechanisms of the disease. However, the question of whether or not the accumulation of Aβ is the triggering factor of more widespread SAD remains open. There are a growing number of arguments for Aβ overproduction being the secondary, concomitant event of AD pathological processes: synaptic failure, hyperphosphorylation of tau protein, neuroinflammation, neuronal loss, and cognitive decline. As one of triggering risk factors of AD development, mitochondrial dysfunction is considered, with the decrease in ATP synthesis and oxidative stress becoming the consequences. However, the specific molecular and genetic mechanisms of AD remain unclear. This is caused by the lack of relevant animal models for studying mechanisms of the disease and objective estimation of pathogenically justified methods of AD prevention and treatment.     

The study of Alzheimer’s disease biomarkers

Alzheimer’s disease (AD) is by far the most common dementing illness of late life and is increasing with the ever-growing number of older adults, in particular, in developed countries. The disease is often referred to as the “Long-Goodbye” because the person with the illness slowly becomes lost to everyone a long time before the body finally gives out. Being able to detect AD earlier on during the course of the disease offers better prospects for the future, for AD individuals, their families and friends as well as on the economy, as a whole. Unfortunately, such a detection technique is not yet, available. However, there are a number of promising biological markers (biomarkers) that correlate well with clinical cognitive tests of individuals and/or postmortem histopathological manifestations of the disease, especially when at least two markers are used for the diagnosis. Biosensors are tools that combine a biochemical binding element to a signal conversion unit and are already being used in the study of some AD biomarkers. However, their use in clinical diagnosis remains a challenge. Introduction of nanotechnology leading to nanobiosensors has several potential advantages over other clinical and/or existing analytical tools, including increased assay speed, flexibility, reduced cost of diagnostic testing, potential to deliver molecular diagnostic tools to family general practitioners, and other health care systems. Even more important, nano-based assays have the potential to detect target proteins at attomolar concentration level. They are, therefore, being increasingly exploited for the detection of early metabolic changes associated with diseases. Because brain damage is irreversible, the use of nanotechnology is particularly important in AD and other neurodegenerative disorders. Nanosensors can also facilitate and enable pointofcare-testing (POCT). This article reviews the basic biochemical processes that lead to AD pathology, current biomarkers for AD, and the current role of nanosensor technology for the study of AD biomarkers. Furthermore, it discusses the huge potential of nanosensing to deliver new molecular diagnostic strategies to AD research.