Biomarkers in Alzheimer's disease: a review

c-Triadem: A constrained, explainable deep learning model to identify novel biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder that requires early diagnosis for effective management. However, issues with currently available diagnostic biomarkers preclude early diagnosis, necessitating the development of alternative biomarkers and methods, such as blood-based diagnostics. We propose c-Triadem (constrained triple-input Alzheimer's disease model), a novel deep neural network to identify potential blood-based biomarkers for AD and predict mild cognitive impairment (MCI) and AD with high accuracy. The model utilizes genotyping data, gene expression data, and clinical information to predict the disease status of participants, i.e., cognitively normal (CN), MCI, or AD. The nodes of the neural network represent genes and their related pathways, and the edges represent known relationships among the genes and pathways. Simulated data validation further highlights the robustness of key features identified by SHapley Additive exPlanations (SHAP). We trained the model with blood genotyping data, microarray, and clinical features from the Alzheimer's Neuroimaging Disease Initiative (ADNI). We demonstrate that our model's performance is superior to previous models with an AUC of 97% and accuracy of 89%. We then identified the most influential genes and clinical features for prediction using SHapley Additive exPlanations (SHAP). Our SHAP analysis shows that CASP9, LCK, and SDC3 SNPs and PINK1, ATG5, and ubiquitin (UBB, UBC) expression have a higher impact on model performance. Our model has facilitated the identification of potential blood-based genetic markers of DNA damage response and mitophagy in affected regions of the brain. The model can be used for detection and biomarker identification in other related dementias.

c-Triadem: A constrained, explainable deep learning model to identify novel biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder that requires early diagnosis for effective management. However, issues with currently available diagnostic biomarkers preclude early diagnosis, necessitating the development of alternative biomarkers and methods, such as blood-based diagnostics. We propose c-Triadem (constrained triple-input Alzheimer's disease model), a novel deep neural network to identify potential blood-based biomarkers for AD and predict mild cognitive impairment (MCI) and AD with high accuracy. The model utilizes genotyping data, gene expression data, and clinical information to predict the disease status of participants, i.e., cognitively normal (CN), MCI, or AD. The nodes of the neural network represent genes and their related pathways, and the edges represent known relationships among the genes and pathways. We trained the model with blood genotyping data, microarray, and clinical features from the Alzheimer's Neuroimaging Disease Initiative (ADNI). We demonstrate that our model's performance is superior to previous models with an AUC of 97% and accuracy of 89%. We then identified the most influential genes and clinical features for prediction using SHapley Additive exPlanations (SHAP). Our SHAP analysis shows that CASP9, LCK, and SDC3 SNPs and PINK1, ATG5, and ubiquitin (UBB, UBC) expression have a higher impact on model performance. Our model has facilitated the identification of potential blood-based genetic markers of DNA damage response and mitophagy in affected regions of the brain. The model can be used for detection and biomarker identification in other related dementias.

Reelin links Apolipoprotein E4, Tau, and Amyloid-β in Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder that affects the cerebral cortex and hippocampus, and is characterised by progressive cognitive decline and memory loss. A recent report of a patient carrying a novel gain-of-function variant of RELN (H3447R, termed RELN-COLBOS) who developed resilience against presenilin-linked autosomal-dominant AD (ADAD) has generated enormous interest. The RELN-COLBOS variant enhances interactions with the apolipoprotein E receptor 2 (ApoER2) and very-low-density lipoprotein receptor (VLDLR), which are associated with delayed AD onset and progression. These findings were validated in a transgenic mouse model. Reelin is involved in neurodevelopment, neurogenesis, and neuronal plasticity. The evidence accumulated thus far has demonstrated that the Reelin pathway links apolipoprotein E4 (ApoE4), amyloid-β (Aβ), and tubulin-associated unit (Tau), which are key proteins that have been implicated in AD pathogenesis. Reelin and key components of the Reelin pathway have been highlighted as potential therapeutic targets and biomarkers for AD.

Prediction of Normal Tissue Complication Probability (NTCP) After Radiation Therapy Using Imaging and Molecular Biomarkers and Multivariate Modelling

The aim of this study was to design a predictive radiobiological model of normal brain tissue in low-grade glioma following radiotherapy based on imaging and molecular biomarkers. Fifteen patients with primary brain tumors prospectively participated in this study and underwent radiation therapy. Magnetic resonance imaging (MRI) was obtained from the patients, including T1- and T2-weighted imaging and diffusion tensor imaging (DTI), and a generalized equivalent dose (gEUD) was calculated. The radiobiological model of the normal tissue complication probability (NTCP) was performed using the variables gEUD; axial diffusivity (AD) and radial diffusivity (RD) of the corpus callosum; and serum protein S100B by univariate and multivariate logistic regression XLIIIrd Sir Peter Freyer Memorial Lecture and Surgical Symposium (2018). Changes in AD, RD, and S100B from baseline up to the 6 months after treatment had an increasing trend and were significant in some time points (P-value < 0.05). The model resulting from RD changes in the 6 months after treatment was significantly more predictable of necrosis than other univariate models. The bivariate model combining RD changes in Gy40 dose-volume and gEUD, as well as the trivariate model obtained using gEUD, RD, and S100B, had a higher predictive value among multivariate models at the sixth month of the treatment. Changes in RD diffusion indices and in serum protein S100B value were used in the early-delayed stage as reliable biomarkers for predicting late-delayed damage (necrosis) caused by radiation in the corpus callosum. Current findings could pave the way for intervention therapies to delay the severity of damage to white matter structures, minimize cognitive impairment, and improve the quality of life of patients with low-grade glioma.

Developing Biomarkers for the Skin: Biomarkers for the Diagnosis and Prediction of Treatment Outcomes of Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by memory decline and cognitive impairment. Research on biomarkers can aid in early diagnosis, monitoring disease progression, evaluating treatment efficacy, and advancing fundamental research. We conducted a cross-sectional longitudinal study to see if there is an association between AD patients and age-matched healthy controls for their physiologic skin characteristics, such as pH, hydration, transepidermal water loss (TEWL), elasticity, microcirculation, and ApoE genotyping. The study used the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating-Sum of the Boxes (CDR-SB) scales as references to quantify the presence of disease, if any. Our findings demonstrate that AD patients have a dominantly neutral pH, greater skin hydration, and less elasticity compared to the control subjects. At baseline, the tortuous capillary percentage negatively correlated with MMSE scores in AD patients. However, AD patients who carry the ApoE E4 allele and exhibit a high percentage of tortuous capillaries and capillary tortuous numbers have shown better treatment outcomes at six months. Therefore, we believe that physiologic skin testing is a rapid and effective way to screen, monitor progression, and ultimately guide the most appropriate treatment for AD patients.

Biomarkers: Role and Scope in Neurological Disorders

Neurological disorders pose a great threat to social health and are a major cause for mortality and morbidity. Effective drug development complemented with the improved drug therapy has made considerable progress towards easing symptoms associated with neurological illnesses, yet poor diagnosis and imprecise understanding of these disorders has led to imperfect treatment options. The scenario is complicated by the inability to extrapolate results of cell culture studies and transgenic models to clinical applications which has stagnated the process of improving drug therapy. In this context, the development of biomarkers has been viewed as beneficial to easing various pathological complications. A biomarker is measured and evaluated in order to gauge the physiological process or a pathological progression of a disease and such a marker can also indicate the clinical or pharmacological response to a therapeutic intervention. The development and identification of biomarkers for neurological disorders involves several issues including the complexity of the brain, unresolved discrepant data from experimental and clinical studies, poor clinical diagnostics, lack of functional endpoints, and high cost and complexity of techniques yet research in the area of biomarkers is highly desired. The present work describes existing biomarkers for various neurological disorders, provides support for the idea that biomarker development may ease our understanding underlying pathophysiology of these disorders and help to design and explore therapeutic targets for effective intervention.

Near-Infrared Fluorescent Probes as Imaging and Theranostic Modalities for Amyloid-Beta and Tau Aggregates in Alzheimer's Disease

A person suspected of having Alzheimer's disease (AD) is clinically diagnosed for the presence of principal biomarkers, especially misfolded amyloid-beta (Aβ) and tau proteins in the brain regions. Existing radiotracer diagnostic tools, such as PET imaging, are expensive and have limited availability for primary patient screening and pre-clinical animal studies. To change the status quo, small-molecular near-infrared (NIR) probes have been rapidly developed, which may serve as an inexpensive, handy imaging tool to comprehend the dynamics of pathogenic progression in AD and assess therapeutic efficacy in vivo. This Perspective summarizes the biochemistry of Aβ and tau proteins and then focuses on structurally diverse NIR probes with coverages of their spectroscopic properties, binding affinity toward Aβ and tau species, and theranostic effectiveness. With the summarized information and perspective discussions, we hope that this paper may serve as a guiding tool for designing novel in vivo imaging fluoroprobes with theranostic capabilities in the future.

Orientational changes of white matter fibers in Alzheimer's disease and amnestic mild cognitive impairment

White matter abnormalities represent early neuropathological events in neurodegenerative diseases such as Alzheimer's disease (AD), investigating these white matter alterations would likely provide valuable insights into pathological changes over the course of AD. Using a novel mathematical framework called "Director Field Analysis" (DFA), we investigated the geometric microstructural properties (i.e., splay, bend, twist, and total distortion) in the orientation of white matter fibers in AD, amnestic mild cognitive impairment (aMCI), and cognitively normal (CN) individuals from the Alzheimer's Disease Neuroimaging Initiative 2 database. Results revealed that AD patients had extensive orientational changes in the bilateral anterior thalamic radiation, corticospinal tract, inferior and superior longitudinal fasciculus, inferior fronto-occipital fasciculus, and uncinate fasciculus in comparison with CN. We postulate that these orientational changes of white matter fibers may be partially caused by the expansion of lateral ventricle, white matter atrophy, and gray matter atrophy in AD. In contrast, aMCI individuals showed subtle orientational changes in the left inferior longitudinal fasciculus and right uncinate fasciculus, which showed a significant association with the cognitive performance, suggesting that these regions may be preferential vulnerable to breakdown by neurodegenerative brain disorders, thereby resulting in the patients' cognitive impairment. To our knowledge, this article is the first to examine geometric microstructural changes in the orientation of white matter fibers in AD and aMCI. Our findings demonstrate that the orientational information of white matter fibers could provide novel insight into the underlying biological and pathological changes in AD and aMCI.

Kinetics and computational analysis of cholinesterase inhibition by REVERC3, a bisdemethoxycurcumin-rich Curcuma longa extract: Relevance to the treatment of Alzheimer's disease

Objectives: Cholinesterase inhibition is a common strategy to treat Alzheimer’s disease. In this study, we have investigated the cholinesterase inhibitory effects of a first-of-its-kind turmeric extract (REVERC3) having enriched content of bisdemethoxycurcumin as major active curcuminoid. Methods: The inhibition studies were performed using Ellman’s colorimetric assay. The kinetics of acetylcholinesterase and butyrylcholinesterase was determined in the presence of REVERC3 using the Lineweaver–Burk double reciprocal plots. Furthermore, we used AutoDock tools to predict the binding of bisdemethoxycurcumin with the active sites of cholinesterases. Results: REVERC3 showed 4.8- and 5.39-fold higher inhibitory potential of acetylcholinesterase and butyrylcholinesterase with IC50 values of 29.08 and 33.59 µg/mL, respectively, compared to the regular turmeric extract. The mode of binding of REVERC3 was competitive in the case of acetylcholinesterase while it was uncompetitive for the inhibition of butyrylcholinesterase. Docking analysis revealed that bisdemethoxycurcumin, the major constituent of REVERC3, has different preferences of binding in the active sites of acetylcholinesterase and butyrylcholinesterase. However, the best binding pose predictions are in line with the experimental binding mode of the cholinesterases. Conclusion: These results indicate that bisdemethoxycurcumin-enriched turmeric extract could improve the cholinergic functions via dual inhibition of cholinesterases. However, the predominant role of bisdemethoxycurcumin in REVERC3 must be further validated using preclinical studies and clinical trials.

A Bayesian hierarchical change point model with parameter constraints

Alzheimer's disease is the leading cause of dementia among adults aged 65 or above. Alzheimer's disease is characterized by a change point signaling a sudden and prolonged acceleration in cognitive decline. The timing of this change point is of clinical interest because it can be used to establish optimal treatment regimens and schedules. Here, we present a Bayesian hierarchical change point model with a parameter constraint to characterize the rate and timing of cognitive decline among Alzheimer's disease patients. We allow each patient to have a unique random intercept, random slope before the change point, random change point time, and random slope after the change point. The difference in slope before and after a change point is constrained to be nonpositive, and its parameter space is partitioned into a null region (representing normal aging) and a rejection region (representing accelerated decline). Using the change point time, the estimated slope difference, and the threshold of the null region, we are able to (1) distinguish normal aging patients from those with accelerated cognitive decline, (2) characterize the rate and timing for patients experiencing cognitive decline, and (3) predict personalized risk of progression to dementia due to Alzheimer's disease. We apply the approach to data from the Religious Orders Study, a national cohort study of aging Catholic nuns, priests, and lay brothers.

Statistical Methodology for Multiclass Classifications: Applications to Dementia

Alzheimer's disease (AD) is a common, devastating disease which carries a heavy economic burden. Accelerated efforts to identify presymptomatic stages of AD and biomarkers to classify the disease are urgent needs. Currently, no biomarkers can perfectly discriminate individuals into multiple disease categories of AD (no cognitive impairment, mild cognitive impairment, and dementia). Although many biomarkers for diagnosis and their various features are being studied, we lack advanced statistical methods which can fully utilize biomarkers to classify AD accurately, thereby facilitating evaluation of putative markers both alone and in combination. In this paper, we propose two approaches: 1) a forward addition procedure in which we adapt an additive logistic regression model to the setting for disease with ordered multiple categories. Using this approach, we select and combine multiple cross-sectional biomarkers to improve diagnostic accuracy, and 2) a method by extending the Neyman-Pearson Lemma to the ordered three disease categories to construct optimal cutoff points to distinguish multiple disease categories. We evaluate the robustness of the proposed model using a simulation study. Then we apply these two methods to data from the Religious Orders Study to examine the feasibility of combining biomarkers, and compare the diagnostic accuracy between the proposed methods and existing methods including model-based methods (ordinal logistic regression and quadratic discriminant analysis), a tree-based method CART, and the Youden index method. The two proposed methods facilitate evaluations of biomarkers for conditions with graded, rather than binary, classifications. The evaluation of the performance of different approaches provides guidance of how to choose approaches to address research questions.

Mulberry Fruit Cultivar 'Chiang Mai' Prevents Beta-Amyloid Toxicity in PC12 Neuronal Cells and in a Drosophila Model of Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia, characterized by chronic neuron loss and cognitive problems. Aggregated amyloid beta (Aβ) peptides, a product of cleaved amyloid precursor protein (APP) by beta-secretase 1 (BACE-1), have been indicated for the progressive pathogenesis of AD. Currently, screening for anti-AD compounds in foodstuffs is increasing, with promising results. Hence, the purpose of this study was to investigate the extraction conditions, phytochemical contents, and anti-AD properties, targeting Aβ peptides of Morus cf. nigra 'Chiang Mai' (MNCM) both in vitro and in vivo. Data showed that the aqueous extract of MNCM contained high amounts of cyanidin, keracyanin, and kuromanin as anthocyanidin and anthocyanins. The extract also strongly inhibited cholinesterases and BACE-1 in vitro. Moreover, MNCM extract prevented Aβ-induced neurotoxicity and promoted neurite outgrowth in neuronal cells. Interestingly, MNCM extract reduced Aβ1-42 peptides and improved locomotory coordination of Drosophila co-expressing human APP and BACE-1, specifically in the brain. These findings suggest that MNCM may be useful as an AD preventive agent by targeting Aβ formation.

Comparative Kinetics of Acetyl- and Butyryl-Cholinesterase Inhibition by Green Tea Catechins|Relevance to the Symptomatic Treatment of Alzheimer's Disease

Alzheimer’s disease (AD) is characterised by the apoptosis of cholinergic neurons and the consequent attenuation of acetylcholine mediated neurotransmission, resulting in neurodegeneration. Acetyl-cholinesterase (AChE) and butyryl-cholinesterase (BuChE) are attractive therapeutic targets in the treatment of AD since inhibition of these enzymes can be used to restore synaptic concentrations of acetylcholine. Whilst inhibitors for these enzymes such as galantamine and rivastigmine have been approved for use, none are able to halt the progression of AD and are responsible for the production of troublesome side-effects. Efficacious cholinesterase inhibitors have been isolated from natural plant-based compounds with many demonstrating additional benefits beyond cholinesterase inhibition, such as antioxidation and anti-inflammation, which are key parts of AD pathology. In this study, five natural flavan-3-ol (catechin) compounds: ((-)-epicatechin (EC), catechin, (-)-epicatechin-3-gallate (ECG),) (-)-epigallocatechin (EGC), (-)-epigallocatechin-3-gallate (EGCG), isolated from green tea, were screened for their cholinesterase inhibitory activity using the Ellman assay. The kinetics of inhibition was determined using reciprocal Lineweaver-Burk plots. EGCG was the only compound found to produce statistically significant, competitive inhibition, of both AChE (p < 0.01) and BuChE (p < 0.01) with IC50 values of 0.0148 µmol/mL and 0.0251 µmol/mL respectively. These results, combined with previously identified antioxidative and anti-inflammatory properties, highlight the potential use of EGCG in the treatment of AD, provided it can be delivered to cholinergic neurons in therapeutic concentrations. Further testing of EGCG in vivo is recommended to fully characterise the pharmacokinetic properties, optimal method of administration and efficacy of this novel plant-based compound.

Reaction of Amyloid-β Peptide Antibody with Different Infectious Agents Involved in Alzheimer's Disease

As early as the 1980s, molecular virologist Ruth Itzhaki began to investigate if there was a causal connection between infections and neurodegenerative disorder. Although the theory has yet to be universally embraced, in 2016 Itzhaki and 33 other scientists from all over the world published a review article in this very journal presenting evidence for the causal role of pathogens in Alzheimer's disease (AD). Exactly how and in what way pathogens affect the induction of AD has yet to be determined, but one possible answer may involve the cross-reactivity of different pathogens with amyloid-β (Aβ). Aβ autoantibodies have been detected in the serum and cerebrospinal fluid of AD patients and in some healthy individuals. In the present study our major goal was to investigate whether antibodies made against Aβ would react both with other brain proteins as well as pathogens associated with AD as a result of molecular mimicry or the binding of bacterial toxins to Aβ42. Our study used a specific monoclonal antibody made against Aβ42, which not only reacted strongly with Aβ42, tau protein, and α-synuclein, but also had from weak to strong reactions with 25 different pathogens or their molecules, some of which have been associated with AD. The homology between peptide stretches of microbial origin and proteins involved in AD could be a mechanism by which antibodies to homologous peptides mount attacks against autoantigens in AD. We concluded that bacterial molecules bind to Aβ protein, forming small oligomers, then encasing pathogens and their molecules to form amyloid plaques, the tell-tale markers of AD. Conversely, these same Aβ peptides induce the production of antibodies to both Aβ42 and bacterial molecules, which may inhibit bacterial pathogenesis, but in the process may promote amyloid plaque formation.

Salivary biological biomarkers for Alzheimer's disease

Alzheimer's disease (AD) is becoming a threat to aging population all over the world. The pathogenic process of AD is likely initiated many years before clinical onset, thus biomarkers for AD diagnosis are critical for the prevention and therapy for the disease at the early stage in order to reduce the global burden brought by the disease. Saliva is treated as a potential alternative and universal diagnostic fluid that can be collected noninvasively by participants with moderate training and without side effects. Several potential salivary biomarkers, which might prove to be significant diagnostic tools in AD, have been researched. We address here the present and the future of these salivary biological biomarkers for AD.

Amyloid-Beta 1-42 Cross-Reactive Antibody Prevalent in Human Sera May Contribute to Intraneuronal Deposition of A-Beta-P-42

Antibodies against many neural antigens are detected in the sera of both patients with Alzheimer's disease (AD) and some healthy individuals. Blood-brain barrier dysfunction could make it possible for brain-reactive autoantibodies to reach the brain, where they can react with amyloid ß peptide (AßP). The origin of these autoreactive antibodies in the blood is unclear. The goals of this study were as follows: (1) to examine the immune reactivity of anti-AßP-42 with 22 neuronal and other associated antigens, some of which are involved in the pathophysiology of AD; (2) to classify antibodies to these 22 different antigens into those that cross-react with AßP-42 and those that do not; (3) to determine whether these antibodies react with BBB proteins, nerve growth factors, and enteric neuronal antigens. Using monoclonal AßP-42 antibody and ELISA methodology, we found that the antibody was highly reactive with Aß protein, tau protein, presenilin, rabaptin-5, β-NGF, BDNF, mTG, and enteric nerve. The same antibody produced equivocal to moderate reactions with glutamate-R, S100B, AQP4, GFAP, MBP, α-synuclein, tTG-2, and tTG-3, and not with the rest. These antibodies were also measured in blood samples from 47 AD patients and 47 controls. IgG antibodies were found to be elevated against AßP-42 and many other antigens in a significant percentage of controls. Overall, the mean OD values were significantly higher against 9/23 tested antigens (p <0.001) in the samples with AD. We were indeed able to classify the detected neuronal antibodies into those that cross-react with AßP-42 and those that do not. Our main finding is that although these antibodies may be harmless in a subgroup of controls, in individuals with compromised BBBs these antibodies that cross-react with AßP-42 can reach the brain, where their cross-reactivity with AßP-42 may contribute to the onset and progression of AD, and perhaps other neurodegenerative disorders.

Hydrophilic fluorinated molecules for spectral 19F MRI

Fluorine-19 (¹⁹F) Magnetic Resonance Imaging (MRI) is an emerging modality for molecular imaging and cell tracking. The hydrophobicity of current exogenous probes, perfluorocarbons (PFCs) and perfluoropolyethers (PFPEs), limits the formulation options available for in vivo applications. Hydrophilic probes permit more formulation flexibility. Further, the broad Nuclear Magnetic Resonance (NMR) chemical shift range of organofluorine species enables multiple probes with unique ¹⁹F MR signatures for simultaneous interrogation of distinct molecular targets in vivo. We report herein a flexible approach to stable liposomal formulations of hydrophilic fluorinated molecules (each bearing numerous magnetically equivalent ¹⁹F atoms), with ¹⁹F encapsulation of up to 22.7 mg/mL and a per particle load of 3.6 × 10^{6 19}F atoms. Using a combination of such probes, we demonstrate, with no chemical shift artifacts, the simultaneous imaging of multiple targets within a given target volume by spectral ¹⁹F MRI.

Alzheimer's disease and blood-based biomarkers - potential contexts of use

Alzheimer's disease (AD) is an irreversible, incurable, progressive neurodegenerative illness, where dementia symptoms gradually worsen over a number of years. The research of validated biomarkers for AD is essential to improve diagnosis and accelerate the development of new therapies. Biochemical markers including neuroimaging could facilitate diagnosis, predict AD progression from a pre-AD state of mild cognitive impairment, and be used to detect the efficacies of disease-modifying therapies. Established biomarkers of AD from cerebrospinal fluid and neuroimaging are highly accurate, but barriers to clinical implementation exist. The focus on blood-based AD biomarkers has grown exponentially during the past few decades. An ideal diagnostic test for AD should be noninvasive and easily applicable. Clinical cost-effectiveness also needs to be established.

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

INTRODUCTION

The number of Alzheimer's Disease (AD) patients is increasing with increased life expectancy and 115.4 million people are expected to be affected in 2050. Unfortunately, AD is commonly diagnosed too late, when irreversible damages have been caused in the patient.

OBJECTIVE

An automatic, continuous and unobtrusive early AD detection method would be required to improve patients' life quality and avoid big healthcare costs. Thus, the objective of this survey is to review the multimodal signals that could be used in the development of such a system, emphasizing on the accuracy that they have shown up to date for AD detection. Some useful tools and specific issues towards this goal will also have to be reviewed.

METHODS

An extensive literature review was performed following a specific search strategy, inclusion criteria, data extraction and quality assessment in the Inspec, Compendex and PubMed databases.

RESULTS

This work reviews the extensive list of psychological, physiological, behavioural and cognitive measurements that could be used for AD detection. The most promising measurements seem to be magnetic resonance imaging (MRI) for AD vs control (CTL) discrimination with an 98.95% accuracy, while electroencephalogram (EEG) shows the best results for mild cognitive impairment (MCI) vs CTL (97.88%) and MCI vs AD distinction (94.05%). Available physiological and behavioural AD datasets are listed, as well as medical imaging analysis steps and neuroimaging processing toolboxes. Some issues such as "label noise" and multi-site data are discussed.

CONCLUSIONS

The development of an unobtrusive and transparent AD detection system should be based on a multimodal system in order to take full advantage of all kinds of symptoms, detect even the smallest changes and combine them, so as to detect AD as early as possible. Such a multimodal system might probably be based on physiological monitoring of MRI or EEG, as well as behavioural measurements like the ones proposed along the article. The mentioned AD datasets and image processing toolboxes are available for their use towards this goal. Issues like "label noise" and multi-site neuroimaging incompatibilities may also have to be overcome, but methods for this purpose are already available.

Redox Proteomic Profiling of Specifically Carbonylated Proteins in the Serum of Triple Transgenic Alzheimer's Disease Mice

Oxidative stress is a key event in the onset and progression of neurodegenerative diseases, including Alzheimer’s disease (AD). To investigate the role of oxidative stress in AD and to search for potential biomarkers in peripheral blood, serums were collected in this study from the 3-, 6-, and 12-month-old triple transgenic AD mice (3×Tg-AD mice) and the age- and sex-matched non-transgenic (non-Tg) littermates. The serum oxidized proteins were quantified by slot-blot analysis and enzyme-linked immunosorbent assay (ELISA) to investigate the total levels of serum protein carbonyl groups. Western blotting, in conjunction with two-dimensional gel electrophoresis (2D-Oxyblot), was employed to identify and quantify the specifically-carbonylated proteins in the serum of 3×Tg-AD mice. The results showed that the levels of serum protein carbonyls were increased in the three month old 3×Tg-AD mice compared with the non-Tg control mice, whereas no significant differences were observed in the six and 12 months old AD mice, suggesting that oxidative stress is an early event in AD progression. With the application of 2D-Oxyblot analysis, (immunoglobin) Ig gamma-2B chain C region (IGH-3), Ig lambda-2 chain C region (IGLC2), Ig kappa chain C region (IGKC), and Ig kappa chain V-V region HP R16.7 were identified as significantly oxidized proteins compared with the control. Among them IGH-3 and IGKC were validated via immunoprecipitation and Western blot analysis. Identification of oxidized proteins in the serums of 3×Tg-AD mice can not only reveal potential roles of those proteins in the pathogenesis of AD but also provide potential biomarkers of AD at the early stage.

DNA methylation dynamics in plants and mammals: overview of regulation and dysregulation

DNA methylation is a major epigenetic marking mechanism regulating various biological functions in mammals and plant. The crucial role of DNA methylation has been observed in cellular differentiation, embryogenesis, genomic imprinting and X-chromosome inactivation. Furthermore, DNA methylation takes part in disease susceptibility, responses to environmental stimuli and the biodiversity of natural populations. In plant, different types of environmental stress have demonstrated the ability to alter the archetype of DNA methylation through the genome, change gene expression and confer a mechanism of adaptation. DNA methylation dynamics are regulated by three processes de novo DNA methylation, methylation maintenance and DNA demethylation. These processes have their similarities and differences between mammals and plants. Furthermore, the dysregulation of DNA methylation dynamics represents one of the primary molecular mechanisms of developing diseases in mammals. This review discusses the regulation and dysregulation of DNA methylation in plants and mammals. Copyright © 2016 John Wiley & Sons, Ltd.

Actin dynamics and cofilin-actin rods in alzheimer disease

Cytoskeletal abnormalities and synaptic loss, typical of both familial and sporadic Alzheimer disease (AD), are induced by diverse stresses such as neuroinflammation, oxidative stress, and energetic stress, each of which may be initiated or enhanced by proinflammatory cytokines or amyloid-β (Aβ) peptides. Extracellular Aβ-containing plaques and intracellular phospho-tau-containing neurofibrillary tangles are postmortem pathologies required to confirm AD and have been the focus of most studies. However, AD brain, but not normal brain, also have increased levels of cytoplasmic rod-shaped bundles of filaments composed of ADF/cofilin-actin in a 1:1 complex (rods). Cofilin, the major ADF/cofilin isoform in mammalian neurons, severs actin filaments at low cofilin/actin ratios and stabilizes filaments at high cofilin/actin ratios. It binds cooperatively to ADP-actin subunits in F-actin. Cofilin is activated by dephosphorylation and may be oxidized in stressed neurons to form disulfide-linked dimers, required for bundling cofilin-actin filaments into stable rods. Rods form within neurites causing synaptic dysfunction by sequestering cofilin, disrupting normal actin dynamics, blocking transport, and exacerbating mitochondrial membrane potential loss. Aβ and proinflammatory cytokines induce rods through a cellular prion protein-dependent activation of NADPH oxidase and production of reactive oxygen species. Here we review recent advances in our understanding of cofilin biochemistry, rod formation, and the development of cognitive deficits. We will then discuss rod formation as a molecular pathway for synapse loss that may be common between all three prominent current AD hypotheses, thus making rods an attractive therapeutic target. © 2016 Wiley Periodicals, Inc.

Cerebrospinal Fluid Biomarkers in Familial Forms of Alzheimer's Disease and Frontotemporal Dementia

As dementia is a fast-growing health care problem, it is becoming an increasingly urgent need to provide an early diagnosis in order to offer patients the best medical treatment and care. Validated biomarkers which reflect the pathology and disease progression are essential for diagnosis and are important when developing new therapies. Today, the core protein biomarkers amyloid-β42, total tau and phosphorylated tau in the cerebrospinal fluid (CSF) are used to diagnose Alzheimer's disease (AD), because these biomarkers have shown to reflect the underlying amyloid and tau pathology. However, the biomarkers have proved insufficient predictors of dementias with a different pathology, e.g. frontotemporal dementia (FTD); furthermore, the biomarkers are not useful for early AD diagnosis. Familial dementias with a known disease-causing mutation can be extremely valuable to study; yet the biomarker profiles in patients with familial dementias are not clear. This review summarizes CSF biomarker findings from studies on symptomatic and presymptomatic individuals carrying a mutation in one of the genes known to cause early-onset familial AD or FTD. In conclusion, the biomarker profile of inherited AD is quite similar between carriers of different mutations as well as similar to the profile found in sporadic AD, whereas familial FTD does not seem to have a clear biomarker profile. Hence, new biomarkers are needed for FTD.

The elusive nature and diagnostics of misfolded Aβ oligomers

Amyloid-beta (Aβ) peptide oligomers are believed to be the causative agents of Alzheimer's disease (AD). Though post-mortem examination shows that insoluble fibrils are deposited in the brains of AD patients in the form of intracellular (tangles) and extracellular (plaques) deposits, it has been observed that cognitive impairment is linked to synaptic dysfunction in the stages of the illness well before the appearance of these mature deposits. Increasing evidence suggests that the most toxic forms of Aβ are soluble low-oligomer ligands whose amounts better correlate with the extent of cognitive loss in patients than the amounts of fibrillar insoluble forms. Therefore, these ligands hold the key to a better understanding of AD prompting the search for clearer correlations between their structure and toxicity. The importance of such correlations and their diagnostic value for the early diagnosis of AD is discussed here with a particular emphasis on the transient nature and structural plasticity of misfolded Aβ oligomers.

Circulating microRNAs in Alzheimer's disease: the search for novel biomarkers

Alzheimer’s disease (AD) is the most common neurodegenerative disease in the elderly. While advancements have been made in understanding the genetic and molecular basis of AD, the clinical diagnosis of AD remains difficult, and post-mortem confirmation is often required. Furthermore, the onset of neurodegeneration precedes clinical symptoms by approximately a decade. Consequently, there is a crucial need for an early and accurate diagnosis of AD, which can potentially lead to strategies that can slow down or stop the progression of neurodegeneration and dementia. Recent advances in the non-coding RNA field have shown that microRNAs (miRNAs) can function as powerful biomarkers in human diseases. Studies are emerging suggesting that circulating miRNAs in the cerebrospinal fluid and blood serum have characteristic changes in AD patients. Whether miRNAs can be used in AD diagnosis, alone or in combination with other AD biomarkers (e.g., amyloid and tau), warrants further investigation.