A systems-based model of Alzheimer's disease

Novel techniques for early diagnosis and monitoring of Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is the most common neurodegenerative disorder, which is characterized by a progressive loss of cognitive functions. The high prevalence, chronicity, and multimorbidity are very common in AD, which significantly impair the quality of life and functioning of patients. Early detection and accurate diagnosis of Alzheimer's disease (AD) can stop the illness from progressing thereby postponing its symptoms. Therefore, for the early diagnosis and monitoring of AD, more sensitive, noninvasive, straightforward, and affordable screening tools are needed.

AREAS COVERED

This review summarizes the importance of early detection methods and novel techniques for Alzheimer's disease diagnosis that can be used by healthcare professionals.

EXPERT OPINION

Early diagnosis assists the patient and caregivers to understand the problem establishing reasonable goals and making future plans together. Early diagnosis techniques not only help in monitoring disease progression but also provide crucial information for the development of novel therapeutic targets. Researchers can plan to potentially alleviate symptoms or slow down the progression of Alzheimer's disease by identifying early molecular changes and targeting altered pathways.

Association between Visceral Adipose Tissue Metabolism and Cerebral Glucose Metabolism in Patients with Cognitive Impairment

Visceral adipose tissue (VAT) dysfunction has been recently recognized as a potential contributor to the development of Alzheimer's disease (AD). This study aimed to explore the relationship between VAT metabolism and cerebral glucose metabolism in patients with cognitive impairment. This cross-sectional prospective study included 54 patients who underwent 18F-fluorodeoxyglucose (18F-FDG) brain and torso positron emission tomography/computed tomography (PET/CT), and neuropsychological evaluations. VAT metabolism was measured by 18F-FDG torso PET/CT, and cerebral glucose metabolism was measured using 18F-FDG brain PET/CT. A voxel-based analysis revealed that the high-VAT-metabolism group exhibited a significantly lower cerebral glucose metabolism in AD-signature regions such as the parietal and temporal cortices. In the volume-of-interest analysis, multiple linear regression analyses with adjustment for age, sex, and white matter hyperintensity volume revealed that VAT metabolism was negatively associated with cerebral glucose metabolism in AD-signature regions. In addition, higher VAT metabolism was correlated with poorer outcomes on cognitive assessments, including the Korean Boston Naming Test, Rey Complex Figure Test immediate recall, and the Controlled Oral Word Association Test. In conclusion, our study revealed significant relationships among VAT metabolism, cerebral glucose metabolism, and cognitive function. This suggests that VAT dysfunction actively contributes to the neurodegenerative processes characteristic of AD, making VAT dysfunction targeting a novel AD therapy approach.

The need for systems thinking to advance Alzheimer's disease research

Despite extensive research efforts to mechanistically understand late-onset Alzheimer's disease (LOAD) and other complex mental health disorders, curative treatments remain elusive. We emphasize the multiscale multicausality inherent to LOAD, highlighting the interplay between interconnected pathophysiological processes and risk factors. Systems thinking methods, such as causal loop diagrams and systems dynamic models, offer powerful means to capture and study this complexity. Recent studies developed and validated a causal loop diagram and system dynamics model using multiple longitudinal data sets, enabling the simulation of personalized interventions on various modifiable risk factors in LOAD. The results indicate that targeting factors like sleep disturbance and depressive symptoms could be promising and yield synergistic benefits. Furthermore, personalized interventions showed significant potential, with top-ranked intervention strategies differing significantly across individuals. We argue that systems thinking approaches can open new prospects for multifactorial precision medicine. In future research, systems thinking may also guide structured, model-driven data collection on the multiple interactions in LOAD's complex multicausality, facilitating theory development and possibly resulting in effective prevention and treatment options.

High-frequency repetitive transcranial magnetic stimulation (HF-rTMS) on global cognitive function of elderly in mild to moderate Alzheimer's disease: a systematic review and meta-analysis

OBJECTIVE

High-frequency repetitive transcranial magnetic stimulation (HF-rTMS) is a non-invasive brain stimulation technique used to improve cognitive deficits in patients with Alzheimer's disease (AD). This systematic review and meta-analysis aimed to evaluate the efficacy of HF-rTMS in improving global cognitive function rehabilitation in elderly patients with mild to moderate AD.

METHODS

A detailed literature search of publications using ten databases (Chinese: Wanfang, VIP Periodical, SinoMed, the Chinese National Knowledge Infrastructure; English: PubMed, Embase, OVID, Web of Science, Cochrane Library, and EBSCOhost) was performed to identify English and Chinese language articles published up to December 2022. We only included randomized controlled trials (RCTs) that evaluate the effect of HF-rTMS on elderly patients with mild to moderate AD. The retrieved studies were carefully reviewed, extracted data, and assessed quality.

RESULTS

Seventeen studies, including 1161 elderly patients with mild to moderate AD, were included in this meta-analysis. Compared to the control group, HF-rTMS could increase MMSE (mean difference [MD] = 3.64; 95%CI 1.86-5.42; P < 0.0001), MoCA (MD = 3.69; 95%CI 1.84-5.54; P < 0.0001), P300 amplitude (MD = 1.09; 95%CI 0.45-1.72; P = 0.0008), and total effective rate scores (MD = 3.64; 95% CI 2.14-6.18; P < 0.00001) while decreasing ADAS-Cog (MD =  - 3.53; 95%CI - 4.91- - 2.15; P < 0.00001) and P300 latency scores (MD =  - 38.32; 95%CI - 72.40- - 4.24; P = 0.03). Our study showed that HF-rTMS could improve the global cognitive function of elderly patients with mild to moderate AD.

CONCLUSION

HF-rTMS can improve global cognitive function in elderly patients with mild to moderate AD, which is an effective and safe rehabilitation treatment tool for AD patients.

Research Progress on Effects of Ginsenoside Rg2 and Rh1 on Nervous System and Related Mechanisms

Neurological-related disorders are diseases that affect the body's neurons or peripheral nerve tissue, such as Parkinson's disease (PD) and Alzheimer's disease (AD). The development of neurological disorders can cause serious harm to the quality of life and functioning of the patient. The use of traditional therapeutic agents such as dopamine-promoting drugs, anticholinergic drugs, cholinesterase inhibitors, and NMDA receptor antagonists is often accompanied by a series of side effects such as drug resistance, cardiac arrhythmia, liver function abnormalities, and blurred vision. Therefore, there is an urgent need to find a therapeutic drug with a high safety profile and few side effects. Herbal medicines are rich in active ingredients that are natural macromolecules. Ginsenoside is the main active ingredient of ginseng, which has a variety of pharmacological effects and is considered to have potential value in the treatment of human diseases. Modern pharmacological studies have shown that ginsenosides Rg2 and Rh1 have strong pharmacological activities in the nervous system, with protective effects on nerve cells, improved resistance to neuronal injury, modulation of neural activity, resistance to cerebral ischemia/reperfusion injury, improvement of brain damage after eclampsia hemorrhage, improvement of memory and cognitive deficits, treatment of AD and vascular dementia, alleviation of anxiety, pain, and inhibition of ionic-like behavior. In this article, we searched the pharmacological research literature of Rg2 and Rh1 in the field of neurological diseases, summarized the latest research progress of the two ginsenosides, and reviewed the pharmacological effects and mechanisms of Rg2 and Rh1, which provided a new way of thinking for the research of the active ingredients in ginseng anti-neurological diseases and the development of new drugs.

The citrus flavonoid "Nobiletin" impedes STZ-induced Alzheimer's disease in a mouse model through regulating autophagy mastered by SIRT1/FoxO3a mechanism

The prominence of autophagy in the modulation of neurodegenerative disorders has sparked interest to investigate its stimulation in Alzheimer's disease (AD). Nobiletin possesses several bioactivities such as anti-inflammation, antioxidation, and neuroprotection. Consequently, the study's aim was to inspect the possible neurotherapeutic impact of Nobiletin in damping AD through autophagy regulation. Mice were randomly assigned into: Group I which received DMSO, Groups II, III, and IV obtained STZ (3 mg/kg) intracerebroventricularly once with Nobiletin (50 mg/kg/day; i.p.) in Group III and Nobiletin with EX-527 (2 mg/kg, i.p.) in Group IV. Interestingly, Nobiletin ameliorated STZ-induced AD through enhancing the motor performance and repressing memory defects. Moreover, Nobiletin de-escalated hippocampal acetylcholinesterase (AChE) activity and enhanced acetylcholine level while halting BACE1 and amyloid-β levels. Meanwhile, Nobiletin stimulated the autophagy process through activating the SIRT1/FoxO3a, LC3B-II, and ATG7 pathway. Additionally, Nobiletin inhibited Akt pathway and controlled the level of NF-κB and TNF-α. Nobiletin amended the oxidative stress through enhancing GSH and cutting down MDA levels. However, EX527, SIRT1 inhibitor, counteracted the neurotherapeutic effects of Nobiletin. Therefore, the present study provides a strong verification for the therapeutic influence of Nobiletin in AD. This outcome may be assigned to autophagy stimulation through SIRT1/FoxO3a, inhibiting AChE activity, reducing neuroinflammation and oxidative stress.

An Insight into Cellular and Molecular Mechanisms Underlying the Pathogenesis of Neurodegeneration in Alzheimer's Disease

Alzheimer's disease (AD) is the most prominent neurodegenerative disorder in the aging population. It is characterized by cognitive decline, gradual neurodegeneration, and the development of amyloid-β (Aβ)-plaques and neurofibrillary tangles, which constitute hyperphosphorylated tau. The early stages of neurodegeneration in AD include the loss of neurons, followed by synaptic impairment. Since the discovery of AD, substantial factual research has surfaced that outlines the disease's causes, molecular mechanisms, and prospective therapeutics, but a successful cure for the disease has not yet been discovered. This may be attributed to the complicated pathogenesis of AD, the absence of a well-defined molecular mechanism, and the constrained diagnostic resources and treatment options. To address the aforementioned challenges, extensive disease modeling is essential to fully comprehend the underlying mechanisms of AD, making it easier to design and develop effective treatment strategies. Emerging evidence over the past few decades supports the critical role of Aβ and tau in AD pathogenesis and the participation of glial cells in different molecular and cellular pathways. This review extensively discusses the current understanding concerning Aβ- and tau-associated molecular mechanisms and glial dysfunction in AD. Moreover, the critical risk factors associated with AD including genetics, aging, environmental variables, lifestyle habits, medical conditions, viral/bacterial infections, and psychiatric factors have been summarized. The present study will entice researchers to more thoroughly comprehend and explore the current status of the molecular mechanism of AD, which may assist in AD drug development in the forthcoming era.

Advanced Overview of Biomarkers and Techniques for Early Diagnosis of Alzheimer's Disease

The development of early non-invasive diagnosis methods and identification of novel biomarkers are necessary for managing Alzheimer's disease (AD) and facilitating effective prognosis and treatment. AD has multi-factorial nature and involves complex molecular mechanism, which causes neuronal degeneration. The primary challenges in early AD detection include patient heterogeneity and lack of precise diagnosis at the preclinical stage. Several cerebrospinal fluid (CSF) and blood biomarkers have been proposed to show excellent diagnosis ability by identifying tau pathology and cerebral amyloid beta (Aβ) for AD. Intense research endeavors are being made to develop ultrasensitive detection techniques and find potent biomarkers for early AD diagnosis. To mitigate AD worldwide, understanding various CSF biomarkers, blood biomarkers, and techniques that can be used for early diagnosis is imperative. This review attempts to provide information regarding AD pathophysiology, genetic and non-genetic factors associated with AD, several potential blood and CSF biomarkers, like neurofilament light, neurogranin, Aβ, and tau, along with biomarkers under development for AD detection. Besides, numerous techniques, such as neuroimaging, spectroscopic techniques, biosensors, and neuroproteomics, which are being explored to aid early AD detection, have been discussed. The insights thus gained would help in finding potential biomarkers and suitable techniques for the accurate diagnosis of early AD before cognitive dysfunction.

Simulating the multicausality of Alzheimer's disease with system dynamics

INTRODUCTION

In Alzheimer's disease (AD), cognitive decline is driven by various interlinking causal factors. Systems thinking could help elucidate this multicausality and identify opportune intervention targets.

METHODS

We developed a system dynamics model (SDM) of sporadic AD with 33 factors and 148 causal links calibrated with empirical data from two studies. We tested the SDM's validity by ranking intervention outcomes on 15 modifiable risk factors to two sets of 44 and 9 validation statements based on meta-analyses of observational data and randomized controlled trials, respectively.

RESULTS

The SDM answered 77% and 78% of the validation statements correctly. Sleep quality and depressive symptoms yielded the largest effects on cognitive decline with which they were connected through strong reinforcing feedback loops, including via phosphorylated tau burden.

DISCUSSION

SDMs can be constructed and validated to simulate interventions and gain insight into the relative contribution of mechanistic pathways.

Toward Reagent-Free Discrimination of Alzheimer's Disease Using Blood Plasma Spectral Digital Biomarkers and Machine Learning

BACKGROUND

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease. The detection of early-stage AD is particularly desirable because it would allow early intervention. However, a minimally invasive, low-cost, and accurate discrimination or diagnostic method for AD is especially difficult in the earliest stage of AD.

OBJECTIVE

The aim of this research is to discover blood plasma spectral digital biomarkers of AD, develop a novel intelligent method for the discrimination of AD and accelerate the translation of Fourier transform infrared (FTIR) spectral-based disease discrimination methods from the laboratory to clinical practice.

METHODS

Since vibration spectroscopy can provide the structure and chemical composition information of biological samples at the molecular level, we investigated the potential of FTIR spectral biomarkers of blood plasma to differentiate between AD patients and healthy controls. Combined with machine learning technology, we designed a hierarchical discrimination system that provides reagent-free and accurate AD discrimination based on blood plasma spectral digital biomarkers of AD.

RESULTS

Accurate segregation between AD patients and healthy controls was achieved with 89.3% sensitivity and 85.7% specificity for early-stage AD patients, 92.8% sensitivity and 87.5% specificity for middle-stage AD patients, and 100% sensitivity and 100% specificity for late-stage AD patients.

CONCLUSIONS

Our results show that blood plasma spectral digital biomarkers hold great promise as discrimination markers of AD, indicating the potential for the development of an inexpensive, reagent-free, and less laborious clinical test. As a result, our research outcome will accelerate the clinical application of spectral digital biomarkers and machine learning.

Dynamic changes of CSF clusterin levels across the Alzheimer's disease continuum

BACKGROUND

Clusterin is a multifunctional protein, which is associated with the pathogenesis and the development of Alzheimer's disease (AD). Compared with normal controls, inconsistent results have yielded in previous studies for concentration of cerebrospinal fluid (CSF) clusterin in AD patients. We explored CSF clusterin levels in different pathological processes of AD.

METHODS

Following the National Institute on Aging-Alzheimer's Association (NIA-AA) criteria, we employed on the levels of CSF Aβ₄₂(A), phosphorylated-Tau (T), and total-tau (N). Based on previously published cutoffs and the close correlation between CSF p-tau and t-tau, 276 participants from the publicly available ADNI database with CSF biomarkers were divided into four groups: A-(TN)- (normal Aβ₄₂ and normal p-tau and t-tau; n = 50), A+(TN)- (abnormal Aβ₄₂ and normal p-tau and t-tau; n = 39), A+(TN) + (abnormal Aβ₄₂ and abnormal p-tau or t-tau; n = 147), A-(TN) + (normal Aβ₄₂ and abnormal p-tau or t-tau; n = 40). To assess CSF clusterin levels in AD continuum, intergroup differences in four groups were compared. Pairwise comparisons were conducted as appropriate followed by Bonferroni post hoc analyses. To further study the relationships between CSF clusterin levels and AD core pathological biomarkers, we employed multiple linear regression method in subgroups.

RESULTS

Compared with the A-(TN)- group, CSF clusterin levels were decreased in A+ (TN)- group (P = 0.002 after Bonferroni correction), but increased in the A+(TN) + group and the A-(TN) + group (both P <  0.001 after Bonferroni correction). Moreover, we found CSF clusterin levels are positively associated with CSF Aβ₄₂ (β = 0.040, P <  0. 001), CSF p-tau (β = 0.325, P <  0.001) and CSF t-tau (β = 0.346, P <  0.001).

CONCLUSIONS

Our results indicated that there are differences levels of CSF clusterin in different stages of AD pathology. The CSF clusterin level decreased at the early stage are related to abnormal Aβ pathology; and the increased levels are associated with tau pathology and neurodegeneration.

Phytochemical Compounds and Nanoparticles as Phytochemical Delivery Systems for Alzheimer's Disease Management

Alzheimer's disease remains one of the most widespread neurodegenerative reasons for dementia worldwide and is associated with considerable mortality and morbidity. Therefore, it has been considered a priority for research. Indeed, several risk factors are involved in the complexity of the therapeutic ways of this pathology, including age, traumatic brain injury, genetics, exposure to aluminum, infections, diabetes, vascular diseases, hypertension, dyslipidemia, and obesity. The pathophysiology of Alzheimer's disease is mostly associated with hyperphosphorylated protein in the neuronal cytoplasm and extracellular plaques of the insoluble β-amyloid peptide. Therefore, the management of this pathology needs the screening of drugs targeting different pathological levels, such as acetylcholinesterase (AchE), amyloid β formation, and lipoxygenase inhibitors. Among the pharmacological strategies used for the management of Alzheimer's disease, natural drugs are considered a promising therapeutic strategy. Indeed, bioactive compounds isolated from different natural sources exhibit important anti-Alzheimer effects by their effectiveness in promoting neuroplasticity and protecting against neurodegeneration as well as neuroinflammation and oxidative stress in the brain. These effects involve different sub-cellular, cellular, and/or molecular mechanisms, such as the inhibition of acetylcholinesterase (AchE), the modulation of signaling pathways, and the inhibition of oxidative stress. Moreover, some nanoparticles were recently used as phytochemical delivery systems to improve the effects of phytochemical compounds against Alzheimer's disease. Therefore, the present work aims to provide a comprehensive overview of the key advances concerning nano-drug delivery applications of phytochemicals for Alzheimer's disease management.

Delineation of Neuroprotective Effects and Possible Benefits of AntioxidantsTherapy for the Treatment of Alzheimer's Diseases by Targeting Mitochondrial-Derived Reactive Oxygen Species: Bench to Bedside

Alzheimer's disease (AD) is considered the sixth leading cause of death in elderly patients and is characterized by progressive neuronal degeneration and impairment in memory, language, etc. AD is characterized by the deposition of senile plaque, accumulation of fibrils, and neurofibrillary tangles (NFTs) which are responsible for neuronal degeneration. Amyloid-β (Aβ) plays a key role in the process of neuronal degeneration in the case of AD. It has been reported that Aβ is responsible for the production of reactive oxygen species (ROS), depletion of endogenous antioxidants, increase in intracellular Ca²⁺ which further increases mitochondria dysfunctions, oxidative stress, release of pro-apoptotic factors, neuronal apoptosis, etc. Thus, oxidative stress plays a key role in the pathogenesis of AD. Antioxidants are compounds that have the ability to counteract the oxidative damage conferred by ROS. Therefore, the antioxidant therapy may provide benefits and halt the progress of AD to advance stages by counteracting neuronal degeneration. However, despite the beneficial effects imposed by the antioxidants, the findings from the clinical studies suggested inconsistent results which might be due to poor study design, selection of the wrong antioxidant, inability of the molecule to cross the blood-brain barrier (BBB), treatment in the advanced state of disease, etc. The present review insights into the neuroprotective effects and limitations of the antioxidant therapy for the treatment of AD by targeting mitochondrial-derived ROS. This particular article will certainly help the researchers to search new avenues for the treatment of AD by utilizing mitochondrial-derived ROS-targeted antioxidant therapies.

Lipidomic Network of Mild Cognitive Impairment from the Mayo Clinic Study of Aging

BACKGROUND

Lipid alterations contribute to Alzheimer's disease (AD) pathogenesis. Lipidomics studies could help systematically characterize such alterations and identify potential biomarkers.

OBJECTIVE

To identify lipids associated with mild cognitive impairment and amyloid-β deposition, and to examine lipid correlation patterns within phenotype groupsMethods:Eighty plasma lipids were measured using mass spectrometry for 1,255 non-demented participants enrolled in the Mayo Clinic Study of Aging. Individual lipids associated with mild cognitive impairment (MCI) were first identified. Correlation network analysis was then performed to identify lipid species with stable correlations across conditions. Finally, differential correlation network analysis was used to determine lipids with altered correlations between phenotype groups, specifically cognitively unimpaired versus MCI, and with elevated brain amyloid versus without.

RESULTS

Seven lipids were associated with MCI after adjustment for age, sex, and APOE4. Lipid correlation network analysis revealed that lipids from a few species correlated well with each other, demonstrated by subnetworks of these lipids. 177 lipid pairs differently correlated between cognitively unimpaired and MCI patients, whereas 337 pairs of lipids exhibited altered correlation between patients with and without elevated brain amyloid. In particular, 51 lipid pairs showed correlation alterations by both cognitive status and brain amyloid. Interestingly, the lipids central to the network of these 51 lipid pairs were not significantly associated with either MCI or amyloid, suggesting network-based approaches could provide biological insights complementary to traditional association analyses.

CONCLUSION

Our attempt to characterize the alterations of lipids at network-level provides additional insights beyond individual lipids, as shown by differential correlations in our study.

Serum Levels of Clusterin, PKR, and RAGE Correlate with Amyloid Burden in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is the most common form of dementia and biomarkers are essential to help in the diagnosis of this disease. Image techniques and cerebrospinal fluid (CSF) biomarkers are limited in their use because they are expensive or invasive. Thus, the search for blood-borne biomarkers is becoming central to the medical community.

OBJECTIVE

The main objective of this study is the evaluation of three serum proteins as potential biomarkers in AD patients.

METHODS

We recruited 27 healthy controls, 19 mild cognitive impairment patients, and 17 AD patients. Using the recent A/T/N classification we split our population into two groups (AD and control). We used ELISA kits to determine Aβ42, tau, and p-tau in CSF and clusterin, PKR, and RAGE in serum.

RESULTS

The levels of serum clusterin, PKR, and RAGE were statistically different in the AD group compared to controls. These proteins showed a statistically significant correlation with CSF Aβ42. So, they were selected to generate an AD detection model showing an AUC-ROC of 0.971 (CI 95%, 0.931-0.998).

CONCLUSION

The developed model based on serum biomarkers and other co-variates could reflect the AD core pathology. So far, not one single blood-biomarker has been described, with effectiveness offering high sensitivity and specificity. We propose that the complexity of AD pathology could be reflected in a set of biomarkers also including clinical features of the patients.

Mapping the multicausality of Alzheimer's disease through group model building

Alzheimer’s disease (AD) is a complex, multicausal disorder involving several spatiotemporal scales and scientific domains. While many studies focus on specific parts of this system, the complexity of AD is rarely studied as a whole. In this work, we apply systems thinking to map out known causal mechanisms and risk factors ranging from intracellular to psychosocial scales in sporadic AD. We report on the first systemic causal loop diagram (CLD) for AD, which is the result of an interdisciplinary group model building (GMB) process. The GMB was based on the input of experts from multiple domains and all proposed mechanisms were supported by scientific literature. The CLD elucidates interaction and feedback mechanisms that contribute to cognitive decline from midlife onward as described by the experts. As an immediate outcome, we observed several non-trivial reinforcing feedback loops involving factors at multiple spatial scales, which are rarely considered within the same theoretical framework. We also observed high centrality for modifiable risk factors such as social relationships and physical activity, which suggests they may be promising leverage points for interventions. This illustrates how a CLD from an interdisciplinary GMB process may lead to novel insights into complex disorders. Furthermore, the CLD is the first step in the development of a computational model for simulating the effects of risk factors on AD.

Overview of Transgenic Mouse Models for Alzheimer's Disease

This review describes several transgenic mouse models of Alzheimer's disease (AD), a devastating neurodegenerative disorder that causes progressive cognitive decline and is diagnosed postmortem by the presence of extracellular amyloid-β (Aβ) plaques and intraneuronal tau neurofibrillary tangles in the cerebral cortex. Currently there is no intervention that cures, prevents, or even slows disease progression. Its complex etiology and pathology pose significant challenges for animal model development, and there is no single model that faithfully recapitulates both the pathological aspects and behavioral phenotypes of AD. Nearly 200 transgenic rodent models of AD have been generated primarily based on mutations linked to Aβ protein misprocessing in the familial form of the disease. More recent models incorporate mutations in tau protein, as well as mutations associated with the sporadic form of the disease. The salient features, strengths, limitations, and key differentiators for the most commonly used and best characterized of these models are considered here. While the translational utility of many of these models to assess the potential of novel therapeutics is in dispute, knowledge of the different models available and a detailed understanding of their features can aid in the selection of the optimal model to explore disease mechanisms or evaluate candidate medications. We comment on the predictive utility of these models considering recent clinical trial failures and discuss trends and future directions in the development of models for AD based on the plethora of clinical data that have been generated over the last decade. © 2019 by John Wiley & Sons, Inc.

Robotic assistance for people with dementia: a viable option for the future?

INTRODUCTION

Demographic changes in society and fewer personnel working in healthcare services have resulted in an increase in the speed of development of safe, reliable robotic assistance technologies for patients with neurological diseases. This paper aims to advocate for the frailty of patients in light of the economic need for robotic assistance, discuss potential hazards, and outline related factors that influence positive outcomes.

AREAS COVERED

This article reviews the state of the art and perspectives regarding the use of robotics in older adults with dementia. We focus on current trends in the development of robotic technologies for these patients and discuss the potential hazards associated with the implementation of such cutting-edge technology in daily practice.

EXPERT OPINION

We envisage a gradual increase in the usage of robot-based devices for the management and support of patients with cognitive deficits. In particular, the introduction of artificial intelligence will enhance the functionality of these technologies, but also increase potential hazards resulting from human-robot interactions. The development of such technology must consider whether neurological syndromes are static or progressive. Progressive syndromes pose the biggest challenge since the functionality of robotic devices must adapt to patients changing cognitive and motor performance profiles.

Future avenues for Alzheimer's disease detection and therapy: liquid biopsy, intracellular signaling modulation, systems pharmacology drug discovery

When Alzheimer's disease (AD) disease-modifying therapies will be available, global healthcare systems will be challenged by a large-scale demand for clinical and biological screening. Validation and qualification of globally accessible, minimally-invasive, and time-, cost-saving blood-based biomarkers need to be advanced. Novel pathophysiological mechanisms (and related candidate biomarkers) - including neuroinflammation pathways (TREM2 and YKL-40), axonal degeneration (neurofilament light chain protein), synaptic dysfunction (neurogranin, synaptotagmin, α-synuclein, and SNAP-25) - may be integrated into an expanding pathophysiological and biomarker matrix and, ultimately, integrated into a comprehensive blood-based liquid biopsy, aligned with the evolving ATN + classification system and the precision medicine paradigm. Liquid biopsy-based diagnostic and therapeutic algorithms are increasingly employed in Oncology disease-modifying therapies and medical practice, showing an enormous potential for AD and other brain diseases as well. For AD and other neurodegenerative diseases, newly identified aberrant molecular pathways have been identified as suitable therapeutic targets and are currently investigated by academia/industry-led R&D programs, including the nerve-growth factor pathway in basal forebrain cholinergic neurons, the sigma1 receptor, and the GTPases of the Rho family. Evidence for a clinical long-term effect on cognitive function and brain health span of cholinergic compounds, drug candidates for repositioning programs, and non-pharmacological multidomain interventions (nutrition, cognitive training, and physical activity) is developing as well. Ultimately, novel pharmacological paradigms, such as quantitative systems pharmacology-based integrative/explorative approaches, are gaining momentum to optimize drug discovery and accomplish effective pathway-based strategies for precision medicine. This article is part of the special issue on 'The Quest for Disease-Modifying Therapies for Neurodegenerative Disorders'.

TRanscranial AlterNating current Stimulation FOR patients with Mild Alzheimer's Disease (TRANSFORM-AD study): Protocol for a randomized controlled clinical trial

Introduction

Recently, transcranial alternating current stimulation (tACS), which can interact with ongoing neuronal activity, has emerged as a potentially effective and promising treatment for Alzheimer's disease (AD), and the 40 Hz gamma frequency was suggested as a suitable stimulation frequency for AD.

Methods

The TRANSFORM‐AD study is a double‐blind, randomized‐controlled trial that will include 40 individuals with mild AD. Eligible patients need to have amyloid β (Aβ) loads examined by Pittsburgh compound B (PiB) positron emission tomography (PET) or decreased Aβ level in cerebrospinal fluid. Participants will be randomized into either a 40 Hz tACS group or a sham stimulation group. Both groups will undergo 30 one‐hour sessions across 3 weeks (21 days). The outcome measures will be assessed at baseline, at the end of the intervention, and 3 months after the first session. The primary outcome is global cognitive function, assessed by the 11‐item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS‐Cog), and the secondary outcomes include changes in other neuropsychological assessments and in PiB‐PET, structural magnetic resonance imaging (MRI), resting electroencephalography (EEG), and simultaneous EEG–functional MRI (EEG‐fMRI) results.

Results

The trial is currently ongoing, and it is anticipated that recruitment will be completed in June 2021.

Discussion

This trial will evaluate the efficacy and safety of 40 Hz tACS in patients with AD, and further explore the potential mechanisms by analyzing amyloid deposits using PiB‐PET, brain volume and white matter integrity by structural MRI, and neural activity by EEG and EEG‐fMRI.

The de-Alzheimerization of age-related dementias: implications for drug targets and approaches to effective therapeutics

Alzheimer's disease (AD) was differentiated from senile dementia (SD) in 1910 due to its early onset and pathological severity. In 1976, this distinction was upended when SD was redesignated as AD to focus efforts and funding in dementia-related research. AD then became conflated with amyloid plaques and, to a lesser degree, neurofibrillary tangles complicating efforts in understanding dementia causality and its treatment. The resultant four-decade search for therapies-based almost exclusively on amyloid was an exercise in futility. While dementia is a complex, multifactorial syndrome, AD is viewed as a homogeneous, linear disease. An amyloid-agnostic approach is necessary to discover therapeutics for age-related dementias.