Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers

Blood-based biomarkers for Alzheimer's disease: towards clinical implementation

For many years, blood-based biomarkers for Alzheimer's disease seemed unattainable, but recent results have shown that they could become a reality. Convincing data generated with new high-sensitivity assays have emerged with remarkable consistency across different cohorts, but also independent of the precise analytical method used. Concentrations in blood of amyloid and phosphorylated tau proteins associate with the corresponding concentrations in CSF and with amyloid-PET or tau-PET scans. Moreover, other blood-based biomarkers of neurodegeneration, such as neurofilament light chain and glial fibrillary acidic protein, appear to provide information on disease progression and potential for monitoring treatment effects. Now the question emerges of when and how we can bring these biomarkers to clinical practice. This step would pave the way for blood-based biomarkers to support the diagnosis of, and development of treatments for, Alzheimer's disease and other dementias.

Deep learning based pipelines for Alzheimer's disease diagnosis: A comparative study and a novel deep-ensemble method

BACKGROUND

Alzheimer's disease is a chronic neurodegenerative disease that destroys brain cells, causing irreversible degeneration of cognitive functions and dementia. Its causes are not yet fully understood, and there is no curative treatment. However, neuroimaging tools currently offer help in clinical diagnosis, and, recently, deep learning methods have rapidly become a key methodology applied to these tools. The reason is that they require little or no image preprocessing and can automatically infer an optimal representation of the data from raw images without requiring prior feature selection, resulting in a more objective and less biased process. However, training a reliable model is challenging due to the significant differences in brain image types.

METHODS

We aim to contribute to the research and study of Alzheimer's disease through computer-aided diagnosis (CAD) by comparing different deep learning models. In this work, there are three main objectives: i) to present a fully automated deep-ensemble approach for dementia-level classification from brain images, ii) to compare different deep learning architectures to obtain the most suitable one for the task, and (iii) evaluate the robustness of the proposed strategy in a deep learning framework to detect Alzheimer's disease and recognise different levels of dementia. The proposed approach is specifically designed to be potential support for clinical care based on patients' brain images.

RESULTS

Our strategy was developed and tested on three MRI and one fMRI public datasets with heterogeneous characteristics. By performing a comprehensive analysis of binary classification (Alzheimer's disease status or not) and multiclass classification (recognising different levels of dementia), the proposed approach can exceed state of the art in both tasks, reaching an accuracy of 98.51% in the binary case, and 98.67% in the multiclass case averaged over the four different data sets.

CONCLUSION

We strongly believe that integrating the proposed deep-ensemble approach will result in robust and reliable CAD systems, considering the numerous cross-dataset experiments performed. Being tested on MRIs and fMRIs, our strategy can be easily extended to other imaging techniques. In conclusion, we found that our deep-ensemble strategy could be efficiently applied for this task with a considerable potential benefit for patient management.

Iron Homeostasis Disorder and Alzheimer's Disease

Iron is an essential trace metal for almost all organisms, including human; however, oxidative stress can easily be caused when iron is in excess, producing toxicity to the human body due to its capability to be both an electron donor and an electron acceptor. Although there is a strict regulation mechanism for iron homeostasis in the human body and brain, it is usually inevitably disturbed by genetic and environmental factors, or disordered with aging, which leads to iron metabolism diseases, including many neurodegenerative diseases such as Alzheimer's disease (AD). AD is one of the most common degenerative diseases of the central nervous system (CNS) threatening human health. However, the precise pathogenesis of AD is still unclear, which seriously restricts the design of interventions and treatment drugs based on the pathogenesis of AD. Many studies have observed abnormal iron accumulation in different regions of the AD brain, resulting in cognitive, memory, motor and other nerve damages. Understanding the metabolic balance mechanism of iron in the brain is crucial for the treatment of AD, which would provide new cures for the disease. This paper reviews the recent progress in the relationship between iron and AD from the aspects of iron absorption in intestinal cells, storage and regulation of iron in cells and organs, especially for the regulation of iron homeostasis in the human brain and prospects the future directions for AD treatments.

Transfer Learning for Alzheimer's Disease through Neuroimaging Biomarkers: A Systematic Review

Alzheimer's disease (AD) is a remarkable challenge for healthcare in the 21st century. Since 2017, deep learning models with transfer learning approaches have been gaining recognition in AD detection, and progression prediction by using neuroimaging biomarkers. This paper presents a systematic review of the current state of early AD detection by using deep learning models with transfer learning and neuroimaging biomarkers. Five databases were used and the results before screening report 215 studies published between 2010 and 2020. After screening, 13 studies met the inclusion criteria. We noted that the maximum accuracy achieved to date for AD classification is 98.20% by using the combination of 3D convolutional networks and local transfer learning, and that for the prognostic prediction of AD is 87.78% by using pre-trained 3D convolutional network-based architectures. The results show that transfer learning helps researchers in developing a more accurate system for the early diagnosis of AD. However, there is a need to consider some points in future research, such as improving the accuracy of the prognostic prediction of AD, exploring additional biomarkers such as tau-PET and amyloid-PET to understand highly discriminative feature representation to separate similar brain patterns, managing the size of the datasets due to the limited availability.

A passive and objective measure of recognition memory in Alzheimer's disease using Fastball memory assessment

Earlier diagnosis of Alzheimer's disease requires biomarkers sensitive to associated structural and functional changes. While considerable progress has been made in the development of structural biomarkers, functional biomarkers of early cognitive change, unconfounded by effort, practice and level of education, are still needed. We present Fastball, a new EEG method for the passive and objective measurement of recognition memory, that requires no behavioural memory response or comprehension of the task . Younger adults, older adults and Alzheimer's disease patients (n = 20 per group) completed the Fastball task, lasting just under 3 min. Participants passively viewed rapidly presented images and EEG assessed their automatic ability to differentiate between images based on previous exposure, i.e. old/new. Participants were not instructed to attend to previously seen images and provided no behavioural response. Following the Fastball task, participants completed a two-alternative forced choice (2AFC) task to measure their explicit behavioural recognition of previously seen stimuli. Fastball EEG detected significantly impaired recognition memory in Alzheimer's disease compared to healthy older adults (P < 0.001, Cohen's d = 1.52), whereas behavioural recognition was not significantly different between Alzheimer's disease and healthy older adults. Alzheimer's disease patients could be discriminated with high accuracy from healthy older adult controls using the Fastball measure of recognition memory (AUC = 0.86, P < 0.001), whereas discrimination performance was poor using behavioural 2AFC accuracy (AUC = 0.63, P = 0.148). There were no significant effects of healthy ageing, with older and younger adult controls performing equivalently in both the Fastball task and behavioural 2AFC task. Early diagnosis of Alzheimer's disease offers potential for early treatment when quality of life and independence can be retained through disease modification and cognitive enhancement. Fastball provides an alternative way of testing recognition responses that holds promise as a functional marker of disease pathology in stages where behavioural performance deficits are not yet evident. It is passive, non-invasive, quick to administer and uses cheap, scalable EEG technology. Fastball provides a new powerful method for the assessment of cognition in dementia and opens a new door in the development of early diagnosis tools.

Comorbidity Trajectories Associated With Alzheimer's Disease: A Matched Case-Control Study in a United States Claims Database

Background: Trajectories of comorbidities among individuals at risk of Alzheimer's disease (AD) may differ from those aging without AD clinical syndrome. Therefore, characterizing the comorbidity burden and pattern associated with AD risk may facilitate earlier detection, enable timely intervention, and help slow the rate of cognitive and functional decline in AD. This case-control study was performed to compare the prevalence of comorbidities between AD cases and controls during the 5 years prior to diagnosis (or index date for controls); and to identify comorbidities with a differential time-dependent prevalence trajectory during the 5 years prior to AD diagnosis. Methods: Incident AD cases and individually matched controls were identified in a United States claims database between January 1, 2000 and December 31, 2016. AD status and comorbidities were defined based on the presence of diagnosis codes in administrative claims records. Generalized estimating equations were used to assess evidence of changes over time and between AD and controls. A principal component analysis and hierarchical clustering was performed to identify groups of AD-related comorbidities with respect to prevalence changes over time (or trajectory), and differences between AD and controls. Results: Data from 186,064 individuals in the IBM MarketScan Commercial Claims and Medicare Supplementary databases were analyzed (93,032 AD cases and 93,032 non-AD controls). In total, there were 177 comorbidities with a ≥ 5% prevalence. Five main clusters of comorbidities were identified. Clusters differed between AD cases and controls in the overall magnitude of association with AD, in their diverging time trajectories, and in comorbidity prevalence. Three clusters contained comorbidities that notably increased in frequency over time in AD cases but not in controls during the 5-year period before AD diagnosis. Comorbidities in these clusters were related to the early signs and/or symptoms of AD, psychiatric and mood disorders, cerebrovascular disease, history of hazard and injuries, and metabolic, cardiovascular, and respiratory complaints. Conclusion: We demonstrated a greater comorbidity burden among those who later developed AD vs. controls, and identified comorbidity clusters that could distinguish these two groups. Further investigation of comorbidity burden is warranted to facilitate early detection of individuals at risk of developing AD.

Tripterygium glycoside ameliorates neuroinflammation in a mouse model of Aβ25-35-induced Alzheimer's disease by inhibiting the phosphorylation of IκBα and p38

Alzheimer's disease (AD) is acommon neurodegenerative disease in the aged population. Tripterygium glycoside (TG) has been reported to protect the nervous system. However, the effect of TG on AD is still unknown. We aimed to explore the effect of TG on AD. Thirty-two C57BL/6J mice were randomly selected and assigned to the normal control, AD model, AD+donepezil, and AD+TG groups. PC12 cells were assigned to the normal control, AD cell model, and AD+TG groups. The alterations in spatial memory and learning abilities of mice were measured by Morris water maze. Neuronal damage in mice was detected using Nissl staining. The expression levels of Aβ_25-35, p-Tau, and CD11b in brain tissues were detected using immunohistochemistry. The expression levels of IL-1β, TNF-α, NO, p-P38, P38, p-IκBα, Caspase1, COX2, and iNOS were measured using ELISAs, qRT-PCR, and western blotting.TG significantly improved the spatial memory and learning abilities of AD mice. Compared toAD model group, significantly lower expression levels of Aβ_25-35, p-Tau, and CD11b were observed in AD+TG group (p < 0.05). The neuron density significantly increased in AD+TG group (p < 0.05). Significantly lower expression levels of IL-1β, TNF-α, NO, caspase-1, COX2, iNOS, p-IκBα and p-P38 MAPK were detected in AD+TG group (p < 0.05). In summary, TG may exert aneuroprotective effect by suppressing the release of inflammatory factors and microglial activity and inhibiting the phosphorylation of IκBα and p38 MAPK. These findings may improve our understanding of the mechanism of TG intervention in AD.

Diagnostic contribution and therapeutic perspectives of transcranial magnetic stimulation in dementia

Transcranial magnetic stimulation (TMS) is a powerful tool to probe in vivo brain circuits, as it allows to assess several cortical properties such asexcitability, plasticity and connectivity in humans. In the last 20 years, TMS has been applied to patients with dementia, enabling the identification of potential markers of thepathophysiology and predictors of cognitive decline; moreover, applied repetitively, TMS holds promise as a potential therapeutic intervention. The objective of this paper is to present a comprehensive review of studies that have employed TMS in dementia and to discuss potential clinical applications, from the diagnosis to the treatment. To provide a technical and theoretical framework, we first present an overview of the basic physiological mechanisms of the application of TMS to assess cortical excitability, excitation and inhibition balance, mechanisms of plasticity and cortico-cortical connectivity in the human brain. We then review the insights gained by TMS techniques into the pathophysiology and predictors of progression and response to treatment in dementias, including Alzheimer's disease (AD)-related dementias and secondary dementias. We show that while a single TMS measure offers low specificity, the use of a panel of measures and/or neurophysiological index can support the clinical diagnosis and predict progression. In the last part of the article, we discuss the therapeutic uses of TMS. So far, only repetitive TMS (rTMS) over the left dorsolateral prefrontal cortex and multisite rTMS associated with cognitive training have been shown to be, respectively, possibly (Level C of evidence) and probably (Level B of evidence) effective to improve cognition, apathy, memory, and language in AD patients, especially at a mild/early stage of the disease. The clinical use of this type of treatment warrants the combination of brain imaging techniques and/or electrophysiological tools to elucidate neurobiological effects of neurostimulation and to optimally tailor rTMS treatment protocols in individual patients or specific patient subgroups with dementia or mild cognitive impairment.

Plasma phospho-tau181 in presymptomatic and symptomatic familial Alzheimer's disease: a longitudinal cohort study

Blood biomarkers have great potential to advance clinical care and accelerate trials in Alzheimer's disease (AD). Plasma phospho-tau181 (p-tau181) is a promising blood biomarker however, it is unknown if levels increase in presymptomatic AD. Therefore, we investigated the timing of p-tau181 changes using 153 blood samples from 70 individuals in a longitudinal study of familial AD (FAD). Plasma p-tau181 was measured, using an in-house single molecule array assay. We compared p-tau181 between symptomatic carriers, presymptomatic carriers, and non-carriers, adjusting for age and sex. We examined the relationship between p-tau181 and neurofilament light and estimated years to/from symptom onset (EYO), as well as years to/from actual onset in a symptomatic subgroup. In addition, we studied associations between p-tau181 and clinical severity, as well testing for differences between genetic subgroups. Twenty-four were presymptomatic carriers (mean baseline EYO -9.6 years) while 27 were non-carriers. Compared with non-carriers, plasma p-tau181 concentration was higher in both symptomatic (p < 0.001) and presymptomatic mutation carriers (p < 0.001). Plasma p-tau181 showed considerable intra-individual variability but individual values discriminated symptomatic (AUC 0.93 [95% CI 0.85-0.98]) and presymptomatic (EYO ≥ -7 years) (AUC 0.86 [95% CI 0.72-0.94]) carriers from non-carriers of the same age and sex. From a fitted model there was evidence (p = 0.050) that p-tau181 concentrations were higher in mutation carriers than non-carriers from 16 years prior to estimated symptom onset. Our finding that plasma p-tau181 concentration is increased in symptomatic and presymptomatic FAD suggests potential utility as an easily accessible biomarker of AD pathology.

Extracellular miRNA biomarkers in neurologic disease: is cerebrospinal fluid helpful?

Aim: The aim of our work is to aggregate data from publications of cerebrospinal fluid extracellular miRNA to identify candidate diagnostic biomarkers, and those warranting further study. Materials & methods: Data were pooled from nine studies, encompassing 864 patients across 16 diseases. Unsupervised clustering grouped patients by a broad category of diseases. Results & conclusion: Compared with healthy controls, in patients with Alzheimer's disease, hsa-miR-767-5p was overexpressed (p < 0.001) and in patients with Huntington's disease, hsa-miR-361-3p was underexpressed (p < 10^-4). We also define a subset of extracellular miRNA as candidate biomarkers that are robustly detected across patients, studies and diseases; thereby, warranting further study.

Retinal imaging in Alzheimer's disease

Identifying biomarkers of Alzheimer's disease (AD) will accelerate the understanding of its pathophysiology, facilitate screening and risk stratification, and aid in developing new therapies. Developments in non-invasive retinal imaging technologies, including optical coherence tomography (OCT), OCT angiography and digital retinal photography, have provided a means to study neuronal and vascular structures in the retina in people with AD. Both qualitative and quantitative measurements from these retinal imaging technologies (eg, thinning of peripapillary retinal nerve fibre layer, inner retinal layer, and choroidal layer, reduced capillary density, abnormal vasodilatory response) have been shown to be associated with cognitive function impairment and risk of AD. The development of computer algorithms for respective retinal imaging methods has further enhanced the potential of retinal imaging as a viable tool for rapid, early detection and screening of AD. In this review, we present an update of current retinal imaging techniques and their potential applications in AD research. We also discuss the newer retinal imaging techniques and future directions in this expanding field.

Ultrasensitive techniques and protein misfolding amplification assays for biomarker-guided reconceptualization of Alzheimer's and other neurodegenerative diseases

INTRODUCTION

The clinical validation and qualification of biomarkers reflecting the complex pathophysiology of neurodegenerative diseases (NDDs) is a fundamental challenge for current drug discovery and development and next-generation clinical practice. Novel ultrasensitive detection techniques and protein misfolding amplification assays hold the potential to optimize and accelerate this process.

AREAS COVERED

Here we perform a PubMed-based state of the art review and perspective report on blood-based ultrasensitive detection techniques and protein misfolding amplification assays for biomarkers discovery and development in NDDs.

EXPERT OPINION

Ultrasensitive assays represent innovative solutions for blood-based assessments during the entire Alzheimer's disease (AD) biological and clinical continuum, for contexts of use (COU) such as prediction, detection, early diagnosis, and prognosis of AD. Moreover, cerebrospinal fluid (CSF)-based misfolding amplification assays show encouraging performance in detecting α-synucleinopathies in prodromal or at-high-risk individuals and may serve as tools for patients' stratification by the presence of α-synuclein pathology. Further clinical research will help overcome current methodological limitations, also through exploring multiple accessible bodily matrices. Eventually, integrative longitudinal studies will support precise definitions for appropriate COU across NDDs.

Sex differences in the behavioral variant of frontotemporal dementia: A new window to executive and behavioral reserve

INTRODUCTION

Biological sex is an increasingly recognized factor driving clinical and structural heterogeneity in Alzheimer's disease, but its role in the behavioral variant of frontotemporal dementia (bvFTD) is unknown.

METHODS

We included 216 patients with bvFTD and 235 controls with magnetic resonance imaging (MRI) from a large multicenter cohort. We compared the clinical characteristics and cortical thickness between men and women with bvFTD and controls. We followed the residuals approach to study behavioral and cognitive reserve.

RESULTS

At diagnosis, women with bvFTD showed greater atrophy burden in the frontotemporal regions compared to men despite similar clinical characteristics. For a similar amount of atrophy, women demonstrated better-than-expected scores on executive function and fewer changes in apathy, sleep, and appetite than men.

DISCUSSION

Our findings suggest that women might have greater behavioral and executive reserve than men, and neurodegeneration must be more severe in women to produce symptoms similar in severity to those in men.

Retinal biomarkers in Alzheimer's disease and mild cognitive impairment: A systematic review and meta-analysis

BACKGROUND

Retinal changes may reflect the pathophysiological processes in the central nervous system and can be assessed by imaging modalities non-invasively. We aim to localize candidate retinal biomarkers in Alzheimer's disease (AD), mild cognitive impairment (MCI), and preclinical AD.

METHODS

We systematically searched PubMed, EMBASE, Scopus, and Web of Science from inception to January 2021 for observational studies that investigated retinal imaging and electrophysiological markers in AD, MCI, and preclinical AD. Between-groups standardized mean differences (SMDs) with 95 % confidence intervals were computed using random-effects models.

RESULTS

Of 19,727 citations identified, 126 articles were eligible for inclusion. Compared with healthy controls, the thickness of peripapillary retinal nerve fiber layer (pRNFL; SMD = -0.723, p < 0.001), total macular (SMD = -0.612, p < 0.001), and subfoveal choroid (SMD = -0.888, p < 0.001) were significantly reduced in patients with AD. Compared with healthy controls, patients with MCI also had lower thickness of pRNFL (SMD = -0.324, p < 0.001), total macular (SMD = -0.302, p < 0.001), and subfoveal choroid (SMD = -0.462, p = 0.020). Other candidate biomarkers included the optic nerve head morphology, retinal amyloid deposition, microvascular morphology and densities, blood flow, and electrophysiological markers.

CONCLUSIONS

Retinal structural, vascular, and electrophysiological biomarkers hold great potential for the diagnosis, prognosis and risk assessment of AD and MCI. These biomarkers warrant further development in the future, especially in diagnostic test accuracy and longitudinal studies.

Biomarkers for posttraumatic epilepsy

A biomarker is a characteristic that can be objectively measured as an indicator of normal biologic processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions. Biomarker modalities include molecular, histologic, radiographic, or physiologic characteristics. To improve the understanding and use of biomarker terminology in biomedical research, clinical practice, and medical product development, the Food and Drug Administration (FDA)-National Institutes of Health (NIH) Joint Leadership Council developed the BEST Resource (Biomarkers, EndpointS, and other Tools). The seven BEST biomarker categories include the following: (a) susceptibility/risk biomarkers, (b) diagnostic biomarkers, (c) monitoring biomarkers, (d) prognostic biomarkers, (e) predictive biomarkers, (f) pharmacodynamic/response biomarkers, and (g) safety biomarkers. We hypothesize some potential overlap between the reported biomarkers of traumatic brain injury (TBI), epilepsy, and posttraumatic epilepsy (PTE). Here, we tested this hypothesis by reviewing studies focusing on biomarker discovery for posttraumatic epileptogenesis and epilepsy. The biomarker modalities reviewed here include plasma/serum and cerebrospinal fluid molecular biomarkers, imaging biomarkers, and electrophysiologic biomarkers. Most of the reported biomarkers have an area under the receiver operating characteristic curve greater than 0.800, suggesting both high sensitivity and high specificity. Our results revealed little overlap in the biomarker candidates between TBI, epilepsy, and PTE. In addition to using single parameters as biomarkers, machine learning approaches have highlighted the potential for utilizing patterns of markers as biomarkers. Although published data suggest the possibility of identifying biomarkers for PTE, we are still in the early phase of the development curve. Many of the seven biomarker categories lack PTE-related biomarkers. Thus, further exploration using proper, statistically powered, and standardized study designs with validation cohorts, and by developing and applying novel analytical methods, is needed for PTE biomarker discovery.

Improving autobiographical memory in Alzheimer's disease by transcranial alternating current stimulation

We review the latest evidence from animal models, studies in humans using electrophysiology, experimental memory paradigms, and non-invasive brain stimulation (NIBS), in the form of transcranial alternating current stimulation (tACS), suggesting that the altered activity in networks that contribute to the autobiographical memory (ABM) deficits may be modifiable. ABM involves a specific brain network of interacting regions that store and retrieve life experiences. Deficits in ABM are early symptoms in patients with Alzheimer's disease (AD), and serve as relevant predictors of disease progression. The possibility to modify the neural substrates of ABM opens exciting avenues for the development of therapeutic approaches. Beyond a summary of the causal role of brain oscillations in ABM, we propose a new approach of modulating brain oscillations using personalized tACS with the possibility of reducing ABM deficits. We suggest that human experimental studies using cognitive tasks, EEG, and tACS can have future translational clinical implications.

Feature Extraction and Identification of Alzheimer's Disease based on Latent Factor of Multi-Channel EEG

Alzheimer's disease is a neurodegenerative disease in old age, early diagnosis will help to delay the progression of the disease. Presently, the features of brain functional diseases can be obtained with EEG analysis, but the relationship between characteristics of EEG and Alzheimer's disease has not been clearly clarified. In this work, we hypothesize that there exist default brain variables (latent factors) across subjects in disease processes, decoding latent factor from brain activity contributes to the study of cognitive impairment. To that end, this work proposes to extract characteristics of Alzheimer's disease by combing latent factors of EEG with variational auto-encoder to realize disease identification. Primarily, power spectrum characteristics is investigated and it is found that the dominant frequency of two groups is different. Further analysis reveals that latent factor distribution of Alzheimer's disease exists obvious differences with normal group in the theta frequency band. Moreover, the latent factors are projected onto the three-dimensional state space and the transient rotation of neural state is found, which shows the dynamic characteristics of latent factors. In addition, Takagi-Sugeno-Kang classifier is adopted and multiple latent factors are fed into Takagi-Sugeno-Kang classifier for decoding. Compared with linear classifier, Takagi-Sugeno-Kang fuzzy classifier has better performance in classification of energy feature from sub-frequency bands of latent factors. The accuracy of identification could up to 98.10% when the combination of energy features of four frequency bands is used as model input. Collectively, this work provides a feasible tool for identification of neurological dysfunction from the view of latent factors, especially contributing to the diagnosis of Alzheimer's disease.

The Framing of "Alzheimer's Disease": Differences Between Scientific and Lay Literature and Their Ethical Implications

BACKGROUND AND OBJECTIVES

The meaning of Alzheimer's disease (AD) is changing in research. It now refers to a pathophysiological process, regardless of whether clinical symptoms are present. In the lay literature, on the other hand, AD is understood as a form of dementia. This raises the question of whether researchers and the lay audience are still talking about the same thing. If not, how will these different understandings of AD shape perspectives on (societal) needs for people with AD?

RESEARCH DESIGN AND METHODS

We use framing analysis to retrieve the understandings of the term AD that are upheld in the research literature and in national Dutch newspaper articles. We make explicit how the framings of AD steer our normative attitudes toward the disease.

RESULTS

In the analyzed research articles, AD is framed as a pathological cascade, reflected by biomarkers, starting in cognitively healthy people and ending, inevitably, in dementia. In the lay literature, AD is used as a synonym for dementia, and an AD diagnosis is understood as an incentive to enjoy "the time that is left."

DISCUSSION AND IMPLICATIONS

The two different uses of the term AD in research and in the lay literature may result in misunderstandings, especially those research framings that falsely imply that people with AD biomarkers will inevitably develop dementia. Adoption of the research understanding of AD in clinical practice will have normative implications for our view on priority setting in health care. For example, it legitimizes biomarker testing in people without dementia as improving "diagnostic" certainty.

Clinical validity of increased cortical uptake of [18F]flortaucipir on PET as a biomarker for Alzheimer's disease in the context of a structured 5-phase biomarker development framework

PURPOSE

In 2017, the Geneva Alzheimer's disease (AD) Biomarker Roadmap initiative adapted the framework of the systematic validation of oncological diagnostic biomarkers to AD biomarkers, with the aim to accelerate their development and implementation in clinical practice. With this work, we assess the maturity of [18F]flortaucipir PET and define its research priorities.

METHODS

The level of maturity of [18F]flortaucipir was assessed based on the AD Biomarker Roadmap. The framework assesses analytical validity (phases 1-2), clinical validity (phases 3-4), and clinical utility (phase 5).

RESULTS

The main aims of phases 1 (rationale for use) and 2 (discriminative ability) have been achieved. [18F]Flortaucipir binds with high affinity to paired helical filaments of tau and has favorable kinetic properties and excellent discriminative accuracy for AD. The majority of secondary aims of phase 2 were fully achieved. Multiple studies showed high correlations between ante-mortem [18F]flortaucipir PET and post-mortem tau (as assessed by histopathology), and also the effects of covariates on tracer binding are well studied. The aims of phase 3 (early detection ability) were only partially or preliminarily achieved, and the aims of phases 4 and 5 were not achieved.

CONCLUSION

Current literature provides partial evidence for clinical utility of [18F]flortaucipir PET. The aims for phases 1 and 2 were mostly achieved. Phase 3 studies are currently ongoing. Future studies including representative MCI populations and a focus on healthcare outcomes are required to establish full maturity of phases 4 and 5.

Diagnostic Value of the CSF α-Synuclein Real-Time Quaking-Induced Conversion Assay at the Prodromal MCI Stage of Dementia With Lewy Bodies

OBJECTIVE

To investigate whether the cerebrospinal fluid (CSF) α-synuclein (α-syn) real-time quaking-induced conversion (RT-QuIC) assay accurately identifies patients with mild cognitive impairment due to probable Lewy body disease (MCI-LB).

METHODS

We applied α-syn RT-QuIC to 289 CSF samples obtained from two independent cohorts, including 81 patients with probable MCI-LB (70.7±6.6 y, 13.6% F, MMSE 26.1±2.4), 120 with probable MCI-AD (68.6±7.4 y, 45.8% F, MMSE 25.5±2.8), and 30 with unspecified MCI (65.4±9.3 y, 30.0% F, MMSE 27.0±3.0). Fifty-eight individuals with no cognitive decline or evidence of neurodegenerative disease and 121 individuals lacking brain α-syn deposits at the neuropathological examination were used as controls.

RESULTS

RT-QuIC identified MCI-LB patients against cognitively unimpaired controls with 95% sensitivity, 97% specificity, and 96% accuracy, and showed 98% specificity in neuropathological controls. The accuracy of the test for MCI-LB was consistent between the two cohorts (97.3% vs. 93.7%). Thirteen percent of MCI-AD patients also had a positive test; of note, 44% of them developed one core or supportive clinical feature of dementia with Lewy bodies (DLB) at follow-up, suggesting an underlying LB co-pathology.

CONCLUSIONS

These findings indicate that CSF α-syn RT-QuIC is a robust biomarker for prodromal DLB. Further studies are needed to fully explore the added value of the assay to the current research criteria for MCI-LB.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that CSF α-syn RT-QuIC accurately identifies patients with MCI due to LB disease.

Clinical validity of second-generation tau PET tracers as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

PURPOSE

In 2017, the Geneva Alzheimer's disease (AD) strategic biomarker roadmap initiative proposed a framework of the systematic validation AD biomarkers to harmonize and accelerate their development and implementation in clinical practice. Here, we use this framework to examine the translatability of the second-generation tau PET tracers into the clinical context.

METHODS

All available literature was systematically searched based on a set of search terms that related independently to analytic validity (phases 1-2), clinical validity (phase 3-4), and clinical utility (phase 5). The progress on each of the phases was determined based on scientific criteria applied for each phase and coded as fully, partially, preliminary achieved or not achieved at all.

RESULTS

The validation of the second-generation tau PET tracers has successfully passed the analytical phase 1 of the strategic biomarker roadmap. Assay definition studies showed evidence on the superiority over first-generation tau PET tracers in terms of off-target binding. Studies have partially achieved the primary aim of the analytical validity stage (phase 2), and preliminary evidence has been provided for the assessment of covariates on PET signal retention. Studies investigating of the clinical validity in phases 3, 4, and 5 are still underway.

CONCLUSION

The current literature provides overall preliminary evidence on the establishment of the second-generation tau PET tracers into the clinical context, thereby successfully addressing some methodological issues from the tau PET tracer of the first generation. Nevertheless, bigger cohort studies, longitudinal follow-up, and examination of diverse disease population are still needed to gauge their clinical validity.

Differential associations of APOE-ε2 and APOE-ε4 alleles with PET-measured amyloid-β and tau deposition in older individuals without dementia

PURPOSE

To examine associations between the APOE-ε2 and APOE-ε4 alleles and core Alzheimer's disease (AD) pathological hallmarks as measured by amyloid-β (Aβ) and tau PET in older individuals without dementia.

METHODS

We analyzed data from 462 ADNI participants without dementia who underwent Aβ ([18F]florbetapir or [18F]florbetaben) and tau ([18F]flortaucipir) PET, structural MRI, and cognitive testing. Employing APOE-ε3 homozygotes as the reference group, associations between APOE-ε2 and APOE-ε4 carriership with global Aβ PET and regional tau PET measures (entorhinal cortex (ERC), inferior temporal cortex, and Braak-V/VI neocortical composite regions) were investigated using linear regression models. In a subset of 156 participants, we also investigated associations between APOE genotype and regional tau accumulation over time using linear mixed models. Finally, we assessed whether Aβ mediated the cross-sectional and longitudinal associations between APOE genotype and tau.

RESULTS

Compared to APOE-ε3 homozygotes, APOE-ε2 carriers had lower global Aβ burden (βstd [95% confidence interval (CI)]: - 0.31 [- 0.45, - 0.16], p = 0.034) but did not differ on regional tau burden or tau accumulation over time. APOE-ε4 participants showed higher Aβ (βstd [95%CI]: 0.64 [0.42, 0.82], p < 0.001) and tau burden (βstd range: 0.27-0.51, all p < 0.006). In mediation analyses, APOE-ε4 only retained an Aβ-independent effect on tau in the ERC. APOE-ε4 showed a trend towards increased tau accumulation over time in Braak-V/VI compared to APOE-ε3 homozygotes (βstd [95%CI]: 0.10 [- 0.02, 0.18], p = 0.11), and this association was fully mediated by baseline Aβ.

CONCLUSION

Our data suggest that the established protective effect of the APOE-ε2 allele against developing clinical AD is primarily linked to resistance against Aβ deposition rather than tau pathology.

European Academy of Neurology/European Alzheimer's Disease Consortium position statement on diagnostic disclosure, biomarker counseling, and management of patients with mild cognitive impairment

BACKGROUND AND PURPOSE

Careful counseling through the diagnostic process and adequate postdiagnostic support in patients with mild cognitive impairment (MCI) is important. Previous studies have indicated heterogeneity in practice and the need for guidance for clinicians.

METHODS

A joint European Academy of Neurology/European Alzheimer's Disease Consortium panel of dementia specialists was appointed. Through online meetings and emails, positions were developed regarding disclosing a syndrome diagnosis of MCI, pre- and postbiomarker sampling counseling, and postdiagnostic support.

RESULTS

Prior to diagnostic evaluation, motives and wishes of the patient should be sought. Diagnostic disclosure should be carried out by a dementia specialist taking the ethical principles of "the right to know" versus "the wish not to know" into account. Disclosure should be accompanied by written information and a follow-up plan. It should be made clear that MCI is not dementia. Prebiomarker counseling should always be carried out if biomarker sampling is considered and postbiomarker counseling if sampling is carried out. A dementia specialist knowledgeable about biomarkers should inform about pros and cons, including alternatives, to enable an autonomous and informed decision. Postbiomarker counseling will depend in part on the results of biomarkers. Follow-up should be considered for all patients with MCI and include brain-healthy advice and possibly treatment for specific underlying causes. Advice on advance directives may be relevant.

CONCLUSIONS

Guidance to clinicians on various aspects of the diagnostic process in patients with MCI is presented here as position statements. Further studies are needed to enable more evidence-based and standardized recommendations in the future.

Higher CSF sTNFR1-related proteins associate with better prognosis in very early Alzheimer's disease

Neuroinflammation is associated with Alzheimer's disease, but the application of cerebrospinal fluid measures of inflammatory proteins may be limited by overlapping pathways and relationships between them. In this work, we measure 15 cerebrospinal proteins related to microglial and T-cell functions, and show them to reproducibly form functionally-related groups within and across diagnostic categories in 382 participants from the Alzheimer's Disease Neuro-imaging Initiative as well participants from two independent cohorts. We further show higher levels of proteins related to soluble tumor necrosis factor receptor 1 are associated with reduced risk of conversion to dementia in the multi-centered (p = 0.027) and independent (p = 0.038) cohorts of people with mild cognitive impairment due to predicted Alzheimer's disease, while higher soluble TREM2 levels associated with slower decline in the dementia stage of Alzheimer's disease. These inflammatory proteins thus provide prognostic information independent of established Alzheimer's markers.

Early disease biomarkers can be found using animal models urine proteomics

INTRODUCTION

Early disease detection is a prerequisite for early intervention. Urine is not subjected to homeostatic control, and therefore, it accumulates very early changes associated with disease processes, some of which may be used as biomarkers. Animal models must be used to identify urinary changes associated with very early stages of diseases to avoid potential interfering factors and obtain urine samples at a sufficiently early time point before pathological or clinical manifestations occur.

AREAS COVERED

We reviewed recent (from 2009-2020) urine proteome studies using animal models of many diseases. We focused on early changes in urine proteome of animal models, particularly changes occurring prior to alterations in blood tests, light microscopy observations and clinical manifestations. Additional studies relevant to the topic were also extracted from the references of the cited papers. Changes in the urine proteome at different disease stages and the ability of the urine proteome to differentiate among different animal models are also discussed in this review.

EXPERT COMMENTARY

Urine proteomes of animal models may reflect early changes that occur even before changes in blood parameters, light microscopy observations and clinical manifestations, suggesting the potential use of urinary biomarkers for the very early detection of human diseases.

Gait Disturbances are Associated with Increased Cognitive Impairment and Cerebrospinal Fluid Tau Levels in a Memory Clinic Cohort

Background:

Gait analysis with accelerometers is a relatively inexpensive and easy to use method to potentially support clinical diagnoses of Alzheimer’s disease and other dementias. It is not clear, however, which gait features are most informative and how these measures relate to Alzheimer’s disease pathology.

Objective:

In this study, we tested if calculated features of gait 1) differ between cognitively normal subjects (CN), mild cognitive impairment (MCI) patients, and dementia patients, 2) are correlated with cerebrospinal fluid (CSF) biomarkers related to Alzheimer’s disease, and 3) predict cognitive decline.

Methods:

Gait was measured using tri-axial accelerometers attached to the fifth lumbar vertebra (L5) in 58 CN, 58 MCI, and 26 dementia participants, while performing a walk and dual task. Ten gait features were calculated from the vertical L5 accelerations, following principal component analysis clustered in four domains, namely pace, rhythm, time variability, and length variability. Cognitive decline over time was measured using MMSE, and CSF biomarkers were available in a sub-group.

Results:

Linear mixed models showed that dementia patients had lower pace scores than MCI patients and CN subjects (p < 0.05). In addition, we found associations between the rhythm domain and CSF-tau, especially in the dual task. Gait was not associated with CSF Aβ₄₂ levels and cognitive decline over time as measured with the MMSE.

Conclusion:

These findings suggest that gait — particularly measures related to pace and rhythm — are altered in dementia and have a direct link with measures of neurodegeneration.

Potential Neuroregenerative and Neuroprotective Effects of Uridine/Choline-Enriched Multinutrient Dietary Intervention for Mild Cognitive Impairment: A Narrative Review

In mild cognitive impairment (MCI) due to Alzheimer disease (AD), also known as prodromal AD, there is evidence for a pathologic shortage of uridine, choline, and docosahexaenoic acid [DHA]), which are key nutrients needed by the brain. Preclinical and clinical evidence shows the importance of nutrient bioavailability to support the development and maintenance of brain structure and function in MCI and AD. Availability of key nutrients is limited in MCI, creating a distinct nutritional need for uridine, choline, and DHA. Evidence suggests that metabolic derangements associated with ageing and disease-related pathology can affect the body's ability to generate and utilize nutrients. This is reflected in lower levels of nutrients measured in the plasma and brains of individuals with MCI and AD dementia, and progressive loss of cognitive performance. The uridine shortage cannot be corrected by normal diet, making uridine a conditionally essential nutrient in affected individuals. It is also challenging to correct the choline shortfall through diet alone, because brain uptake from the plasma significantly decreases with ageing. There is no strong evidence to support the use of single-agent supplements in the management of MCI due to AD. As uridine and choline work synergistically with DHA to increase phosphatidylcholine formation, there is a compelling rationale to combine these nutrients. A multinutrient enriched with uridine, choline, and DHA developed to support brain function has been evaluated in randomized controlled trials covering a spectrum of dementia from MCI to moderate AD. A randomized controlled trial in subjects with prodromal AD showed that multinutrient intervention slowed brain atrophy and improved some measures of cognition. Based on the available clinical evidence, nutritional intervention should be considered as a part of the approach to the management of individuals with MCI due to AD, including adherence to a healthy, balanced diet, and consideration of evidence-based multinutrient supplements.

Relationship between F-18 florbetapir uptake in occipital lobe and neurocognitive performance in Alzheimer's disease

PURPOSE

To determine the association between occipital amyloid-PET uptake and neurocognitive performance in Alzheimer's disease (AD).

MATERIALS AND METHODS

Fifty-eight participants with normal aged, mild cognitive impairment (MCI) due to AD and AD subjects who underwent F-18 florbetapir brain PET/CT scans were divided into four groups (A, normal; B, MCI; C, mild AD; and D, moderate/severe AD). Semiquantitative analyses of SUVR images were performed. The differences between groups and the correlations between florbetapir uptake and Thai Mental State Examination (TMSE) scores were determined. Significant differences were defined using a P < 0.001, uncorrected, or a P < 0.05, FWE for the voxel-based analyses with Statistical Parametric Mapping (SPM).

RESULTS

There was a slightly higher florbetapir uptake in the precuneus, parietal, and occipital association cortices in Group B > A. The occipital florbetapir uptake in Groups C and D was significantly higher than in Group A, in addition to the precuneus, anterior cingulate, posterior cingulate, temporoparietal, and frontal cortices. There was a strong negative correlation between TMSE scores and florbetapir uptake in the occipital lobe.

CONCLUSIONS

Occipital amyloid uptake is associated with clinically advanced AD, and is inversely correlated with neurocognitive performance and may be useful for evaluating AD severity.

lncRNA-Associated Competitive Endogenous RNA Regulatory Network in an Aβ25-35-Induced AD Mouse Model Treated with Tripterygium Glycoside

BACKGROUND

Tripterygium glycoside (TG) has been suggested to have protective effects on the diseases of the central nervous system including Alzheimer's disease (AD). The mechanisms involving lncRNA-associated competing endogenous RNAs (ceRNAs) were shown to play important roles in the development of AD. However, the ceRNA mechanism of TG in treating AD is still unknown. Thus, we aimed to explore the ceRNA mechanism in the treatment of AD with TG.

METHODS

A total of 32 C57BL/6J mice were administered 3 µL of Aβ25-35 (dual side, 1 mg/mL) by a single stereotactic injection in the brain to conduct AD mouse model. AD mouse models were randomly selected and divided into the AD+normal saline (NS) group (n=16) and the AD+TG group (n=16). The expression data of lncRNAs, mRNAs, and miRNAs in the hippocampus of mice from AD+NS group (n=3) and the AD+TG group (n=3) were obtained by microarray analysis. The MuTaME method was used to predict the ceRNA regulatory network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the DAVID database. A protein-protein interaction (PPI) network was constructed by using STRING software.

RESULTS

TG can significantly improve spatial memory and inhibit the production of p-tau in an Aβ25-35-induced AD mouse model. A total of 661 differentially expressed lncRNAs, 503 mRNAs, and 13 miRNAs were identified. A ceRNA network involving the top 200 mRNA-miRNA-lncRNA pairs with 16 lncRNAs, 11 miRNAs, and 52 mRNAs was visualized. And a PPI network complex filtered 26 gene nodes in DEGs was predicted.

CONCLUSION

We have identified 503 DEGs, 661 DElncRNAs, and 13 DEmiRNAs during treatment with TG in Aβ25-35-induced AD mouse model. A ceRNA network based on the DElncRNAs, DEmRNAs, and DEmiRNAs was conducted, which provided new insight into the lncRNA-mediated ceRNA regulatory mechanisms underlying the effects of TG in the treatment of AD.

PET Neuroimaging of Alzheimer's Disease: Radiotracers and Their Utility in Clinical Research

Alzheimer's Disease (AD), the leading cause of senile dementia, is a progressive neurodegenerative disorder affecting millions of people worldwide and exerting tremendous socioeconomic burden on all societies. Although definitive diagnosis of AD is often made in the presence of clinical manifestations in late stages, it is now universally believed that AD is a continuum of disease commencing from the preclinical stage with typical neuropathological alterations appearing decades prior to its first symptom, to the prodromal stage with slight symptoms of amnesia (amnestic mild cognitive impairment, aMCI), and then to the terminal stage with extensive loss of basic cognitive functions, i.e., AD-dementia. Positron emission tomography (PET) radiotracers have been developed in a search to meet the increasing clinical need of early detection and treatment monitoring for AD, with reference to the pathophysiological targets in Alzheimer's brain. These include the pathological aggregations of misfolded proteins such as β-amyloid (Aβ) plagues and neurofibrillary tangles (NFTs), impaired neurotransmitter system, neuroinflammation, as well as deficient synaptic vesicles and glucose utilization. In this article we survey the various PET radiotracers available for AD imaging and discuss their clinical applications especially in terms of early detection and cognitive relevance.

Discerning rural Appalachian stakeholder attitudes toward memory screening

OBJECTIVE

The aim of this descriptive study was to examine Appalachian stakeholder attitudes toward routine memory screening, and to compare and contrast results from a similar study conducted in an ethnically diverse rural Florida cohort. Determining perceptions about memory screening is essential prior to developing culturally relevant programs for increasing early dementia detection and management among rural underserved older adults at risk of cognitive impairment. Benefits of early detection include ruling out other causes of illness and treating accordingly, delaying onset of dementia symptoms through behavior management and medications, and improving long-term care planning (Dubois, Padovani, Scheltens, Rossi, & Dell'Agnello, 2016). These interventions can potentially help to maintain independence, decrease dementia care costs, and reduce family burdens (Frisoni, et al., 2017).

METHOD

Researchers applied a parallel mixed method design (Tashakkori & Newman, 2010) of semi-structured interviews, measurements of health literacy (REALM-SF) (Arozullah, et al., 2007), sociodemographics, and cognitive screening perceptions (PRISM-PC) (Boustani, et al., 2008), to examine beliefs and attitudes about memory screening among 22 FL and 21 WV rural stakeholders (residents, health providers, and administrators).

RESULTS

Findings included that > 90% participants across both cohorts were highly supportive of earlier dementia detection through routine screening regardless of sample characteristics. However, half of those interviewed were doubtful that provider care or assistance would be adequate for this terminal illness. Despite previous concerns of stigma associated with an Alzheimer's disease diagnosis, rural providers are encouraged to educate patients and community members regarding Alzheimer's disease and offer routine cognitive screening and follow-through.

Predicting the Prognosis of MCI Patients Using Longitudinal MRI Data

The aim of this study is to develop a computer-aided diagnosis system with a deep-learning approach for distinguishing "Mild Cognitive Impairment (MCI) due to Alzheimer's Disease (AD)" patients among a list of MCI patients. In this system we are using the power of longitudinal data extracted from magnetic resonance (MR). For this work, a total of 294 MCI patients were selected from the ADNI database. Among them, 125 patients developed AD during their follow-up and the rest remained stable. The proposed computer-aided diagnosis system (CAD) attempts to identify brain regions that are significant for the prediction of developing AD. The longitudinal data were constructed using a 3D Jacobian-based method aiming to track the brain differences between two consecutive follow-ups. The proposed CAD system distinguishes MCI patients who developed AD from those who remained stable with an accuracy of 87.2 percent. Moreover, it does not depend on data acquired by invasive methods or cognitive tests. This work demonstrates that the use of data in different time periods contains information that is beneficial for prognosis prediction purposes that outperform similar methods and are slightly inferior only to those systems that use invasive methods or neuropsychological tests.

Alzheimer's disease

In this Seminar, we highlight the main developments in the field of Alzheimer's disease. The most recent data indicate that, by 2050, the prevalence of dementia will double in Europe and triple worldwide, and that estimate is 3 times higher when based on a biological (rather than clinical) definition of Alzheimer's disease. The earliest phase of Alzheimer's disease (cellular phase) happens in parallel with accumulating amyloid β, inducing the spread of tau pathology. The risk of Alzheimer's disease is 60-80% dependent on heritable factors, with more than 40 Alzheimer's disease-associated genetic risk loci already identified, of which the APOE alleles have the strongest association with the disease. Novel biomarkers include PET scans and plasma assays for amyloid β and phosphorylated tau, which show great promise for clinical and research use. Multidomain lifestyle-based prevention trials suggest cognitive benefits in participants with increased risk of dementia. Lifestyle factors do not directly affect Alzheimer's disease pathology, but can still contribute to a positive outcome in individuals with Alzheimer's disease. Promising pharmacological treatments are poised at advanced stages of clinical trials and include anti-amyloid β, anti-tau, and anti-inflammatory strategies.

Use of Alzheimer's Disease Cerebrospinal Fluid Biomarkers in A Tertiary Care Memory Clinic

INTRODUCTION

Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers are promising tools to help identify the underlying pathology of neurocognitive disorders. In this manuscript, we report our experience with AD CSF biomarkers in 262 consecutive patients in a tertiary care memory clinic.

METHODS

We retrospectively reviewed 262 consecutive patients who underwent lumbar puncture (LP) and CSF measurement of AD biomarkers (Aβ1-42, total tau or t-tau, and p-tau181). We studied the safety of the procedure and its impact on patient's diagnosis and management.

RESULTS

The LP allowed to identify underlying AD pathology in 72 of the 121 patients (59%) with early onset amnestic mild cognitive impairment (aMCI) with a high probability of progression to AD; to distinguish the behavioral/dysexecutive variant of AD from the behavioral variant of frontotemporal dementia (bvFTD) in 25 of the 45 patients (55%) with an atypical neurobehavioral profile; to identify AD as the underlying pathology in 15 of the 27 patients (55%) with atypical or unclassifiable primary progressive aphasia (PPA); and to distinguish AD from other disorders in 9 of the 29 patients (31%) with psychiatric differential diagnoses and 19 of the 40 patients (47%) with lesional differential diagnoses (normal pressure hydrocephalus, encephalitis, prion disease, etc.). No major complications occurred following the LP.

INTERPRETATION

Our results suggest that CSF analysis is a safe and effective diagnostic tool in select patients with neurocognitive disorders. We advocate for a wider use of this biomarker in tertiary care memory clinics in Canada.

Stimuli-responsive polymer-based systems for diagnostic applications

Stimuli-responsive polymers exhibit properties that make them ideal candidates for biosensing and molecular diagnostics. Through rational design of polymer composition combined with new polymer functionalization and synthetic strategies, polymers with myriad responsivities, e.g., responses to temperature, pH, biomolecules, CO2, light, and electricity can be achieved. When these polymers are specifically designed to respond to biomarkers, stimuli-responsive devices/probes, capable of recognizing and transducing analyte signals, can be used to diagnose and treat disease. In this review, we highlight recent state-of-the-art examples of stimuli-responsive polymer-based systems for biosensing and bioimaging.

Identification of clinically relevant biomarkers of epileptogenesis - a strategic roadmap

Onset of many forms of epilepsy occurs after an initial epileptogenic insult or as a result of an identified genetic defect. Given that the precipitating insult is known, these epilepsies are, in principle, amenable to secondary prevention. However, development of preventive treatments is difficult because only a subset of individuals will develop epilepsy and we cannot currently predict which individuals are at the highest risk. Biomarkers that enable identification of these individuals would facilitate clinical trials of potential anti-epileptogenic treatments, but no such prognostic biomarkers currently exist. Several putative molecular, imaging, electroencephalographic and behavioural biomarkers of epileptogenesis have been identified, but clinical translation has been hampered by fragmented and poorly coordinated efforts, issues with inter-model reproducibility, study design and statistical approaches, and difficulties with validation in patients. These challenges demand a strategic roadmap to facilitate the identification, characterization and clinical validation of biomarkers for epileptogenesis. In this Review, we summarize the state of the art with respect to biomarker research in epileptogenesis and propose a five-phase roadmap, adapted from those developed for cancer and Alzheimer disease, that provides a conceptual structure for biomarker research.

Quantitative Methods for the Detection of Tau Seeding Activity in Human Biofluids

The ability of tau aggregates to recruit and misfold monomeric tau and propagate across brain regions has been studied extensively and is now recognized as a critical pathological step in Alzheimer’s disease (AD) and other tauopathies. Recent evidence suggests that the detection of tau seeds in human samples may be relevant and correlate with clinical data. Here, we review the available methods for the measurement of such tau seeds, their limitations and their potential implementation for the development of the next-generation biomarkers.

Clinical validity of increased cortical binding of tau ligands of the THK family and PBB3 on PET as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

PURPOSE

The research community has focused on defining reliable biomarkers for the early detection of the pathological hallmarks of Alzheimer's disease (AD). In 2017, the Geneva AD Biomarker Roadmap initiative adapted the framework for the systematic validation of oncological biomarkers to AD, with the aim to accelerate their development and implementation in clinical practice. The aim of this work was to assess the validation status of tau PET ligands of the THK family and PBB3 as imaging biomarkers for AD, based on the Biomarker Roadmap methodology.

METHODS

A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of clinical validity of tau PET ligands of the THK family and PBB3 was assessed based on the 5-phase development framework before the meeting and discussed during the workshop.

RESULTS

PET radioligands of the THK family discriminate well between healthy controls and patients with AD dementia (phase 2; partly achieved) and recent evidence suggests an accurate diagnostic accuracy at the mild cognitive impairment (MCI) stage of the disease (phase 3; partly achieved). The phases 2 and 3 were considered not achieved for PBB3 since no evidence exists about the ligand's diagnostic accuracy. Preliminary evidence exists about the secondary aims of each phase for all ligands.

CONCLUSION

Much work remains for completing the aims of phases 2 and 3 and replicating the available evidence. However, it is unlikely that the validation process for these tracers will be completed, given the presence of off-target binding and the development of second-generation tracers with improved binding and pharmacokinetic properties.

Plasma hydrogen sulfide: A biomarker of Alzheimer's disease and related dementias

While heart disease remains a common cause of mortality, cerebrovascular disease also increases with age, and has been implicated in Alzheimer's disease and related dementias (ADRD). We have described hydrogen sulfide (H₂S), a signaling molecule important in vascular homeostasis, as a biomarker of cardiovascular disease. We hypothesize that plasma H₂S and its metabolites also relate to vascular and cognitive dysfunction in ADRD. We used analytical biochemical methods to measure plasma H₂S metabolites and MRI to evaluate indicators of microvascular disease in ADRD. Levels of total H₂S and specific metabolites were increased in ADRD versus controls. Cognition and microvascular disease indices were correlated with H₂S levels. Total plasma sulfide was the strongest indicator of ADRD, and partially drove the relationship between cognitive dysfunction and white matter lesion volume, an indicator of microvascular disease. Our findings show that H₂S is dysregulated in dementia, providing a potential biomarker for diagnosis and intervention.

What Happens to the Worried Well? Follow-Up of Subjective Cognitive Impairment

BACKGROUND

Increasing concern around perceived neurocognitive decline is increasing the number of referrals to specialists and anxiety for patients. We aimed to explore the likelihood of the "worried well" experiencing neurocognitive decline and developing a neurological diagnosis.

METHODS

A total of 166 "worried well" patients who attended the Rural and Remote Memory Clinic (RRMC) between 2004 and 2019 were included in this study. Demographic, health, social, and behavioral factors were measured at the initial visit. Mini-Mental State Examination (MMSE), Center for Epidemiologic Studies Depression Scale (CESD), and Functional Activities Questionnaire (FAQ) scores were measured and compared at initial assessment and at 1-year follow-up. MMSE scores over time were assessed with a mean follow-up of 2.95 years (SD 2.87).

RESULTS

No statistically significant difference was seen in MMSE, CESD, or FAQ scores when comparing clinic day to 1-year follow-up, and no consistent pattern of MMSE score over time was seen. Of the 166 patients with subjective cognitive impairment (SCI) on initial assessment, 5 were diagnosed with Alzheimer's disease (AD) at 8.5, 3.5, 5, 3, and 1.75 years; 2 were diagnosed with MCI at 1 and 2 years; 1 was diagnosed with vascular cognitive impairment at 5 years; and 1 was diagnosed with frontotemporal dementia (FTD) at 0.5 years.

CONCLUSION

The likelihood of a patient with SCI developing a neurological diagnosis is reassuringly low (9/166), but not irrelevant. This, along with the benefits of early diagnosis and treatment for dementia, leads us to believe that patients with SCI should still be seen in follow-up at least at the 1-year mark.

The strategic biomarker roadmap for the validation of Alzheimer's diagnostic biomarkers: methodological update

Background

The 2017 Alzheimer’s disease (AD) Strategic Biomarker Roadmap (SBR) structured the validation of AD diagnostic biomarkers into 5 phases, systematically assessing analytical validity (Phases 1–2), clinical validity (Phases 3–4), and clinical utility (Phase 5) through primary and secondary Aims. This framework allows to map knowledge gaps and research priorities, accelerating the route towards clinical implementation. Within an initiative aimed to assess the development of biomarkers of tau pathology, we revised this methodology consistently with progress in AD research.

Methods

We critically appraised the adequacy of the 2017 Biomarker Roadmap within current diagnostic frameworks, discussed updates at a workshop convening the Alzheimer’s Association and 8 leading AD biomarker research groups, and detailed the methods to allow consistent assessment of aims achievement for tau and other AD diagnostic biomarkers.

Results

The 2020 update applies to all AD diagnostic biomarkers. In Phases 2–3, we admitted a greater variety of study designs (e.g., cross-sectional in addition to longitudinal) and reference standards (e.g., biomarker confirmation in addition to clinical progression) based on construct (in addition to criterion) validity. We structured a systematic data extraction to enable transparent and formal evidence assessment procedures. Finally, we have clarified issues that need to be addressed to generate data eligible to evidence-to-decision procedures.

Discussion

This revision allows for more versatile and precise assessment of existing evidence, keeps up with theoretical developments, and helps clinical researchers in producing evidence suitable for evidence-to-decision procedures. Compliance with this methodology is essential to implement AD biomarkers efficiently in clinical research and diagnostics.

ABCA1-Labeled Exosomes in Serum Contain Higher MicroRNA-193b Levels in Alzheimer's Disease

Objective

We aimed to establish a method to determine whether microRNA-193b (miR-193b) levels in ABCA1-labeled serum exosomes might serve as a marker for the diagnosis of Alzheimer's disease.

Methods

We used immunocapture methods to determine the levels of ABCA1-labeled exosomal miR-193b in cultures of white blood cells (WBCs), red blood cells (RBCs), mouse hippocampal neuron HT-22 cells, and primary mouse neuronal cells. ABCA1-labeled exosomal miR-193b levels were also evaluated in the cerebrospinal fluid (CSF) and serum of APP/PS1 double-transgenic mice, as well as control subjects (n = 60) and study participants with subjective cognitive decline (SCD, n = 89), stage and mild cognitive impairment (MCI, n = 92), and dementia of the Alzheimer type (DAT, n = 92).

Results

ABCA1 levels of exosomes harvested from the medium of HT-22 cells and neurons were significantly higher than those of RBCs and WBCs (P < 0.05). Exosomal ABCA1 from the CSF of APP/PS1 mice were transmitted to the serum of wild-type mice after injection, and high miR-193b levels were observed in both the serum and CSF after injection. The ABCA1-labeled exosomal miR-193b levels were higher in the CSF of MCI and DAT patients compared with the CSF of the control group (P < 0.05). The ABCA1-labeled exosomal miR-193b were also slightly higher (P > 0.05) in the serum of SCD patients and significantly higher in the serum of MCI and DAT patients compared with the serum of the control group (P < 0.05).

Conclusion

This study provides a method to capture specific exosomes. Detection of serum exosomes labeled with ABCA1 may facilitate the early diagnosis of AD.

Abnormalities of Cortical Sources of Resting State Alpha Electroencephalographic Rhythms are Related to Education Attainment in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment

In normal old (Nold) and Alzheimer's disease (AD) persons, a high cognitive reserve (CR) makes them more resistant and resilient to brain neuropathology and neurodegeneration. Here, we tested whether these effects may affect neurophysiological oscillatory mechanisms generating dominant resting state electroencephalographic (rsEEG) alpha rhythms in Nold and patients with mild cognitive impairment (MCI) due to AD (ADMCI). Data in 60 Nold and 70 ADMCI participants, stratified in higher (Edu+) and lower (Edu-) educational attainment subgroups, were available in an Italian-Turkish archive. The subgroups were matched for age, gender, and education. RsEEG cortical sources were estimated by eLORETA freeware. As compared to the Nold-Edu- subgroup, the Nold-Edu+ subgroup showed greater alpha source activations topographically widespread. On the contrary, in relation to the ADMCI-Edu- subgroup, the ADMCI-Edu+ subgroup displayed lower alpha source activations topographically widespread. Furthermore, the 2 ADMCI subgroups had matched cerebrospinal AD diagnostic biomarkers, brain gray-white matter measures, and neuropsychological scores. The current findings suggest that a high CR may be related to changes in rsEEG alpha rhythms in Nold and ADMCI persons. These changes may underlie neuroprotective effects in Nold seniors and subtend functional compensatory mechanisms unrelated to brain structure alterations in ADMCI patients.

Ethical Implications of Alzheimer's Disease Prediction in Asymptomatic Individuals through Artificial Intelligence

Biomarker-based predictive tests for subjectively asymptomatic Alzheimer’s disease (AD) are utilized in research today. Novel applications of artificial intelligence (AI) promise to predict the onset of AD several years in advance without determining biomarker thresholds. Until now, little attention has been paid to the new ethical challenges that AI brings to the early diagnosis in asymptomatic individuals, beyond contributing to research purposes, when we still lack adequate treatment. The aim of this paper is to explore the ethical arguments put forward for AI aided AD prediction in subjectively asymptomatic individuals and their ethical implications. The ethical assessment is based on a systematic literature search. Thematic analysis was conducted inductively of 18 included publications. The ethical framework includes the principles of autonomy, beneficence, non-maleficence, and justice. Reasons for offering predictive tests to asymptomatic individuals are the right to know, a positive balance of the risk-benefit assessment, and the opportunity for future planning. Reasons against are the lack of disease modifying treatment, the accuracy and explicability of AI aided prediction, the right not to know, and threats to social rights. We conclude that there are serious ethical concerns in offering early diagnosis to asymptomatic individuals and the issues raised by the application of AI add to the already known issues. Nevertheless, pre-symptomatic testing should only be offered on request to avoid inflicted harm. We recommend developing training for physicians in communicating AI aided prediction.

The Neuroprotective Effect of Byu d Mar 25 in LPS-Induced Alzheimer's Disease Mice Model

Inflammatory factors play an important role in the pathogenesis of Alzheimer's disease (AD). Byu d Mar 25 (BM25) has been suggested to have protective effects in the central nervous system. However, the effect of BM25 on AD has not been determined. This study aims to investigate the neuroprotective effect of BM25 in AD. A total of 40 AD model mice were randomly assigned to the following five groups (n = 8 per group): the AD + NS group, the AD + donepezil group, and three AD + BM25 groups treated with either 58.39 mg/kg (AD + BM25-L), 116.77 mg/kg (AD + BM25-M), or 233.54 mg/kg BM25 (AD + BM25-H). The Morris water maze test was performed to assess alterations in spatial learning and memory deficits. Nissl staining was performed to detect Nissl bodies and neuronal damage. The expression of IL-1β and TNF-α was evaluated by ELISA. The protein expression of P-P38, P38, P-IκBα, caspase 1, COX2, and iNOS was determined by western blotting. The expression of Aβ, p-Tau, and CD11b was measured by immunohistochemistry. The mRNA expression levels of IL-1β, TNF-α, COX2, and iNOS were measured by qRT-PCR. Spatial memory significantly improved in the AD + BM25-M and AD + BM25-H groups compared with the AD + NS group (p < 0.05). The expression of Aβ and p-Tau significantly decreased in the AD + BM25-M and AD + BM25-H groups (p < 0.05). The neuron density and hierarchy and number of pyramidal neurons significantly increased in the AD + BM25-M and AD + BM25-H groups (p < 0.05). In addition, the expression levels of CD11b, IL-1β, TNF-α, COX2, iNOS, caspase 1, p-IκBα, and p-P38 significantly decreased in the AD + BM25-M and AD + BM25-H groups (p < 0.05). In conclusion, our findings suggest that BM25 may exert anti-inflammatory and neuroprotective effects in AD model mice by suppressing the activity of microglia and inhibiting the phosphorylation of IκBα and p38 MAPK.

Visual assessment of [18F]flutemetamol PET images can detect early amyloid pathology and grade its extent

Purpose

To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR.

Methods

[¹⁸F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the [¹⁸F]flutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density.

Results

VR showed excellent agreement against CL = 12 (κ = .89, 95.2%) and CL = 30 (κ = .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERAD_SOT-based classification (i.e., any region mCERAD_SOT > 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density.

Conclusion

VR is an appropriate method for assessing early amyloid pathology and that grading the extent of visual amyloid positivity could present clinical value.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-020-05174-2.