Biomarkers in dementia: clinical utility and new directions

Biomarkers of sleep-wake disturbance as predictors of cognitive decline and accelerated disease progression

INTRODUCTION

In older adults, where sleep disturbances and cognitive impairment are common, mounting evidence suggests a potential connection between sleep and cognitive function, highlighting the significance of utilizing sleep as a biomarker for early detection of cognitive impairment to improve clinical outcomes in a noninvasive, cost-effective manner.

AREAS COVERED

This review describes the relationship between sleep and cognitive function in older adults, encompassing both subjective and objective measures of sleep quality, duration, architecture, and sleep-disordered breathing. The authors consider the directionality of the associations observed in prospective and cross-sectional studies, exploring whether sleep disturbances precede cognitive decline or vice versa. Furthermore, they discuss the potential bidirectional relationships between sleep and Alzheimer's disease (AD) risks in older adults while also examining the neurodegenerative pathways of this relationship.

EXPERT OPINION

Routine sleep monitoring in primary care settings has the potential to bolster early detection and treatment of sleep disturbance, and by extension, reduce the risk of dementia. Improving sleep assessment tools, such as wearables, provide scalable alternatives to traditional methods like polysomnography, potentially enabling widespread monitoring of sleep characteristics. Standardized measurement and inclusive participant recruitment are needed to enhance generalizability, while longitudinal studies are essential to understand the interaction between sleep and AD pathology.

Technology-based group exercise interventions for people living with dementia or mild cognitive impairment: A scoping review

Older people living with dementia or mild cognitive impairment (MCI) are more vulnerable to experiencing social isolation and loneliness due to their cognitive and physical impairments. Increasingly integrating technology into group exercises contributed to the improved resilience and well-being of older adults living with dementia and MCI. The purpose of this scoping review was to identify the various types, feasibility, outcome measures, and impacts of technology-based group exercise interventions for people with dementia or MCI. We utilized the Joanna Briggs Institute approach, a three-step process. A comprehensive literature search on five databases-CINAHL, MEDLINE, Embase, Web of Science, and PsycInfo-until January 2024 yielded 1,585 publications; the final review included 14 publications that recruited a total of 379 participants, with mean age of 69 (SD = 4.21) years to 87.07 (SD = 3.92) years. Analysis of data showed three types of technology-based group exercise interventions for people with dementia or MCI: (a) exergames, (b) virtual cycling or kayak paddling, and (c) video-conferencing platforms. In addition, we identified three key impacts: (a) feasibility and accessibility; (b) physical, psychosocial, and cognitive benefits; and (c) adaptations necessary for persons with dementia or MCI. Our study suggests that technology-based group exercise interventions are feasible and acceptable to persons with dementia or MCI. Future studies should involve individuals with dementia and their caregivers in the design and implementation of technology-based group exercise programs.

Scottish Intercollegiate Guidelines Network Guidance on Dementia: The Investigation of Suspected Dementia (SIGN 168) with Focus on Biomarkers-Executive Summary

This is an executive summary of the recent guidance produced by the Scottish Intercollegiate Guidelines Network (SIGN) dementia guideline group with regards to the investigation of suspected dementia. This is a sub-section of the broader SIGN 168 guideline released in November 2023. The guideline group included clinicians with expertise in Old Age Psychiatry, Neurology, Radiology, and Nuclear Medicine supported by colleagues from the SIGN and Healthcare Improvement Scotland teams. There was representation from carers and support organizations with experience of dementia, to ensure the recommendations were appropriate from the perspective of the people being assessed for possible dementia and their carers. As the 2018 National Institute for Health and Clinical Excellence (NICE) dementia review included a review of the evidenced investigation of dementia, the SIGN guideline development group decided to focus on a review on the up-to-date evidence regarding the role of imaging and fluid biomarkers in the diagnosis of dementia. To give context to the consideration of more advanced diagnostic biomarker investigations, the guideline and this summary include the NICE guidance on the use of standard investigations as well as more specialist investigations. The evidence review supports consideration of the use of structural imaging, nuclear medicine imaging, and established Alzheimer's cerebrospinal fluid biomarkers (amyloid and tau) in the diagnosis of dementia. Although routine use of amyloid positron emission tomography imaging was not recommended, its potential use, under specialist direction, in patients with atypical or young-onset presentations of suspected Alzheimer's dementia was included as a clinical good practice point.

Cognitive trajectories preluding the onset of different dementia entities: a descriptive longitudinal study using the NACC database

OBJECTIVE

To describe the 10-year preclinical cognitive trajectories of older, non-demented individuals towards the onset of the four most prevalent types of dementia, i.e., Alzheimer's disease(AD), Lewy body(LBD), vascular(VD) and frontotemporal dementia(FTD).

METHODS

Our analysis focused on data from older (≥ 60years) NACC (National Alzheimer's Coordinating Center) participants. Four distinct presymptomatic dementia groups (AD-LBD-VD-FTD) and a comparison group of cognitively unimpaired(CU) participants were formed. Comprehensive cognitive assessments involving verbal episodic memory, semantic verbal fluency, confrontation naming, mental processing speed - attention and executive function - cognitive flexibility were conducted at baseline and on an approximately yearly basis. Descriptive analyses (adjusted general linear models) were performed to determine and compare the yearly cognitive scores of each group throughout the follow-up. Exploratory analyses were conducted to estimate the rates of cognitive decline.

RESULTS

There were 3343 participants who developed AD, 247 LBD, 108 FTD, 155 VD and 3398 composed the CU group. Participants with AD performed worse on episodic memory than those with VD and LBD for about 3 to 4 years prior to dementia onset (the FTD group documented an intermediate course). Presymptomatic verbal fluency and confrontation naming trajectories differentiated quite well between the FTD group and the remaining dementia entities. Participants with incident LBD and VD performed worse than those with AD on executive functions and mental processing speed-attention since about 5 years prior to the onset of dementia, and worse than those with FTD more proximally to the diagnosis of the disorder.

CONCLUSIONS

Heterogeneous cognitive trajectories characterize the presymptomatic courses of the most prevalent dementia entities.

Advancements in Cerebrospinal Fluid Biosensors: Bridging the Gap from Early Diagnosis to the Detection of Rare Diseases

Cerebrospinal fluid (CSF) is a body fluid that can be used for the diagnosis of various diseases. However, CSF collection requires an invasive and painful procedure called a lumbar puncture (LP). This procedure is applied to any patient with a known risk of central nervous system (CNS) damage or neurodegenerative disease, regardless of their age range. Hence, this can be a very painful procedure, especially in infants and elderly patients. On the other hand, the detection of disease biomarkers in CSF makes diagnoses as accurate as possible. This review aims to explore novel electrochemical biosensing platforms that have impacted biomedical science. Biosensors have emerged as techniques to accelerate the detection of known biomarkers in body fluids such as CSF. Biosensors can be designed and modified in various ways and shapes according to their ultimate applications to detect and quantify biomarkers of interest. This process can also significantly influence the detection and diagnosis of CSF. Hence, it is important to understand the role of this technology in the rapidly progressing field of biomedical science.

Performance of SOBA-AD blood test in discriminating Alzheimer's disease patients from cognitively unimpaired controls in two independent cohorts

Amyloid-beta (Aβ) toxic oligomers are critical early players in the molecular pathology of Alzheimer's disease (AD). We have developed a Soluble Oligomer Binding Assay (SOBA-AD) for detection of these Aβ oligomers that contain α-sheet secondary structure that discriminates plasma samples from patients on the AD continuum from non-AD controls. We tested 265 plasma samples from two independent cohorts to investigate the performance of SOBA-AD. Testing was performed at two different sites, with different personnel, reagents, and instrumentation. Across two cohorts, SOBA-AD discriminated AD patients from cognitively unimpaired (CU) subjects with 100% sensitivity, > 95% specificity, and > 98% area under the curve (AUC) (95% CI 0.95-1.00). A SOBA-AD positive readout, reflecting α-sheet toxic oligomer burden, was found in AD patients, and not in controls, providing separation of the two populations, aside from 5 SOBA-AD positive controls. Based on an earlier SOBA-AD study, the Aβ oligomers detected in these CU subjects may represent preclinical cases of AD. The results presented here support the value of SOBA-AD as a promising blood-based tool for the detection and confirmation of AD.

Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease

Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aβ40lumi and Aβ42/Aβ40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aβ40lumi and t-tau/Aβ40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aβ40lumi, p-tau181/Aβ40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.

Metabolomics and Risk of Dementia: A Systematic Review of Prospective Studies

BACKGROUND

The projected increase in the prevalence of dementia has sparked interest in understanding the pathophysiology and underlying causal factors in its development and progression. Identifying novel biomarkers in the preclinical or prodromal phase of dementia may be important for predicting early disease risk. Applying metabolomic techniques to prediagnostic samples in prospective studies provides the opportunity to identify potential disease biomarkers.

OBJECTIVE

The objective of this systematic review was to summarize the evidence on the associations between metabolite markers and risk of dementia and related dementia subtypes in human studies with a prospective design.

DESIGN

We searched PubMed, PsycINFO, and Web of Science databases from inception through December 8, 2023. Thirteen studies (mean/median follow-up years: 2.1-21.0 y) were included in the review.

RESULTS

Several metabolites detected in biological samples, including amino acids, fatty acids, acylcarnitines, lipid and lipoprotein variations, hormones, and other related metabolites, were associated with risk of developing dementia. Our systematic review summarized the adjusted associations between metabolites and dementia risk; however, our findings should be interpreted with caution because of the heterogeneity across the included studies and potential sources of bias. Further studies are warranted with well-designed prospective cohort studies that have defined study populations, longer follow-up durations, the inclusion of additional diverse biological samples, standardization of techniques in metabolomics and ascertainment methods for diagnosing dementia, and inclusion of other related dementia subtypes.

CONCLUSIONS

This study contributes to the limited systematic reviews on metabolomics and dementia by summarizing the prospective associations between metabolites in prediagnostic biological samples with dementia risk. Our review discovered additional metabolite markers associated with the onset of developing dementia and may help aid in the understanding of dementia etiology. The protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (https://www.crd.york.ac.uk/prospero/; registration ID: CRD42022357521).

Biomarkers and Cognition Study, Singapore (BIOCIS): Protocol, Study Design, and Preliminary Findings

BACKGROUND

The focus of medicine is shifting from treatment to preventive care. The expression of biomarkers of dementia and Alzheimer's disease (AD) appear decades before the onset of observable symptoms, and evidence has emerged supporting pharmacological and non-pharmacological interventions to treat modifiable risk factors of dementia. However, there is limited research on the epidemiology, clinical phenotypes, and underlying pathobiology of cognitive diseases in Asian populations.

OBJECTIVES

The objectives of the Biomarkers and Cognition Study, Singapore(BIOCIS) are to characterize the underlying pathobiology of Cognitive Impairment through a longitudinal study incorporating fluid biomarker profiles, neuroimaging, neuropsychological and clinical outcomes in a multi-ethnic Southeast Asian population.

DESIGN, SETTING, PARTICIPANTS

BIOCIS is a 5-year longitudinal study where participants are assessed annually. 2500 participants aged 30 to 95 will be recruited from the community in Singapore. To investigate how pathology presents with or without minimal clinical symptoms and vice versa, CI and unimpaired individuals will be recruited. Participants will undergo assessments to characterise biomarkers of dementia through neuroimaging, fluid biomarkers, cognitive assessments, behavioural and lifestyle profiles, retinal scans and microbiome indicators.

RESULTS

Since commencement of recruitment in February 2022, 1148 participants have been enrolled, comprising 1012 Chinese, 62 Indian, and 35 Malay individuals. Mean age and education is 61.32 years and 14.34 years respectively with 39.8% males. 47.9 % of the cohort are employed and 32.06% have a family history of dementia. The prevalence of cerebral small vessel disease is 90.2% with a mean modified Fazekas white matter hyperintensity score of 4.1.

CONCLUSION

The BIOCIS cohort will help identify novel biomarkers, pathological trajectories, epidemiology of dementia, and reversible risk factors in a Southeast Asian population. Completion of BIOCIS longitudinal data could provide insights into risk-stratification of Asians populations, and potentially inform public healthcare and precision medicine for better patient outcomes in the prevention of Alzheimer's disease and dementia.

Higher fresh fruit intake relates to larger grey matter volumes in areas involved in dementia and depression: A UK Biobank study

The benefits of consuming fruits and vegetables are widely accepted. While previous studies suggest a protective role of fruits and vegetables against a variety of diseases such as dementia and depression, the biological mechanisms/effects remain unclear. Here we investigated the effect of fruit and vegetable consumption on brain structure. Particularly on grey matter (GM) and white matter (WM) volumes, regional GM volumes and subcortical volumes. Cross-sectional imaging data from UK Biobank cohort was used. A total of 9925 participants (Mean age 62.4 ± 7.5 years, 51.1 % men) were included in the present analysis. Measures included fruit and vegetable intake, other dietary patterns and a number of selected lifestyle factors and clinical data. Brain volumes were derived from structural brain magnetic resonance imaging. General linear model was used to study the associations between brain volumes and fruit/vegetable intakes. After adjusting for selected confounding factors, salad/raw vegetable intake showed a positive association with total white matter volume, fresh fruit intake showed a negative association with total grey matter (GM) volume. Regional GM analyses showed that higher fresh fruit intake was associated with larger GM volume in the left hippocampus, right temporal occipital fusiform cortex, left postcentral gyrus, right precentral gyrus, and right juxtapositional lobule cortex. We conclude that fruit and vegetable consumption seems to specifically modulate brain volumes. In particular, fresh fruit intake may have a protective role in specific cortical areas such as the hippocampus, areas robustly involved in the pathophysiology of dementia and depression.

Investigating the associations between upper limb motor function and cognitive impairment: a scoping review

Upper limb motor function is a potential new biomarker of cognitive impairment and may aid discrimination from healthy ageing. However, it remains unclear which assessments to use. This study aimed to explore what methods have been used and to describe associations between upper limb function and cognitive impairment. A scoping review was conducted using PubMed, CINAHL and Web of Science. A systematic search was undertaken, including synonyms for key concepts 'upper limb', 'motor function' and 'cognitive impairment'. Selection criteria included tests of upper limb motor function and impaired cognition in adults. Analysis was by narrative synthesis. Sixty papers published between 1998 and 2022, comprising 41,800 participants, were included. The most common assessment tasks were finger tapping, Purdue Pegboard Test and functional tasks such as writing. Protocols were diverse in terms of equipment used and recording duration. Most participants were recruited from clinical settings. Alzheimer's Disease was the most common cause of cognitive impairment. Results were mixed but, generally, slower speed, more errors, and greater variability in upper limb movement variables was associated with cognitive impairment. This review maps the upper limb motor function assessments used and summarises the available evidence on how these associate with cognitive impairment. It identifies research gaps and may help guide protocols for future research. There is potential for upper limb motor function to be used in assessments of cognitive impairment.

Prevention, Intervention and Care of Neurodegenerative Diseases

Chronic neurodegenerative diseases encompass a wide spectrum of disorders and affect millions of people worldwide [...].

Efficacy and Safety of Woohwangchungsimwon Combined with Donepezil in Behavioral and Psychological Symptoms of Dementia in Patients with Probable Alzheimer's Disease: Study Protocol for a Randomized Controlled Trial

Behavioral and psychological symptoms of dementia are a major factor in the burden of care and medical expenses. Conventional pharmacological treatments do not exert a distinct effect on the benefits versus the risks. The herbal medicine woohwangchungsimwon is frequently prescribed for neuropsychiatric disorders. An effect of woohwangchungsimwon on behavioral and psychological symptoms of dementia has been previously reported; however, no clinical studies have been conducted. We aim to evaluate the efficacy and safety of woohwangchungsimwon combined with donepezil for alleviating these symptoms in probable Alzheimer's disease. In this randomized, assessor-blinded, parallel-group clinical trial, 74 participants with probable Alzheimer's disease will be divided via block randomization into a woohwangchungsimwon + donepezil combination group (n = 37) or a donepezil single group (n = 37). Participants will include patients under donepezil treatment for at least a month. We will perform the study for 24 weeks. The Neuro-Psychiatric Inventory subscale scores will be the primary outcome. Secondary outcomes will include cognitive function, dementia severity, physical function, quality of life, depression, anxiety, and insomnia. For safety evaluation, we will assess adverse reactions, measure vital signs, and conduct laboratory tests. This is the first trial aiming to confirm the efficacy and safety of woohwangchungsimwon combined with donepezil for alleviating behavioral and psychological symptoms of dementia. Its findings could provide a basis for their co-administration to control these symptoms in probable Alzheimer's disease.

Does adding MRI and CSF-based biomarkers improve cognitive status classification based on cognitive performance questionnaires?

BACKGROUND

Cognitive status classification (e.g. dementia, cognitive impairment without dementia, and normal) based on cognitive performance questionnaires has been widely used in population-based studies, providing insight into the population dynamics of dementia. However, researchers have raised concerns about the accuracy of cognitive assessments. MRI and CSF biomarkers may provide improved classification, but the potential improvement in classification in population-based studies is relatively unknown.

METHODS

Data come from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We examined whether the addition of MRI and CSF biomarkers improved cognitive status classification based on cognitive status questionnaires (MMSE). We estimated several multinomial logistic regression models with different combinations of MMSE and CSF/MRI biomarkers. Based on these models, we also predicted prevalence of each cognitive status category using a model with MMSE only and a model with MMSE + MRI + CSF measures and compared them to diagnosed prevalence.

RESULTS

Our analysis showed a slight improvement in variance explained (pseudo-R2) between the model with MMSE only and the model including MMSE and MRI/CSF biomarkers; the pseudo-R2 increased from .401 to .445. Additionally, in evaluating differences in predicted prevalence for each cognitive status, we found a small improvement in the predicted prevalence of cognitively normal individuals between the MMSE only model and the model with MMSE and CSF/MRI biomarkers (3.1% improvement). We found no improvement in the correct prediction of dementia prevalence.

CONCLUSION

MRI and CSF biomarkers, while important for understanding dementia pathology in clinical research, were not found to substantially improve cognitive status classification based on cognitive status performance, which may limit adoption in population-based surveys due to costs, training, and invasiveness associated with their collection.

Vascular Risk Predicts Plasma Amyloid β 42/40 Through Cerebral Amyloid Burden in Apolipoprotein E ε4 Carriers

BACKGROUND

Understanding the neurobiological underpinnings between established multimodal dementia risk factors and noninvasive blood-based biomarkers may lead to greater precision and earlier identification of older adults at risk of accelerated decline and dementia. We examined whether key vascular and genetic risk impact the association between cerebral amyloid burden and plasma aβ (amyloid β) 42/40 in nondemented older adults.

METHODS

We used nondemented older adults from the UCD-ADRC (University of California, Davis-Alzheimer's Disease Research Center) study (n=96) and Alzheimer's Disease Neuroimaging Initiative (n=104). Alzheimer's Disease Neuroimaging Initiative was examined as confirmatory study cohort. We followed a cross-sectional design and examined linear regression followed by mediation analyses. Vascular risk score was obtained as the sum of hypertension, diabetes, hyperlipidemia, coronary artery disease, and cerebrovascular disease. Apolipoprotein E (APOE) ε4+ risk was genotyped, and plasma aβ42 and aβ40 were assayed. Cerebral amyloid burden was quantified using Florbetapir-PET scans. Baseline age was included as a covariate in all models.

RESULTS

Vascular risk significantly predicted cerebral amyloid burden in Alzheimer's Disease Neuroimaging Initiative but not in the UCD-ADRC cohort. Cerebral amyloid burden was associated with plasma aβ 42/40 in both cohorts. Higher vascular risk increased cerebral amyloid burden was indirectly associated with reduced plasma aβ 42/40 in Alzheimer's Disease Neuroimaging Initiative but not in UCD-ADRC cohort. However, when stratified by APOE ε4+ risk, we consistently observed this indirect relationship only in APOE ε4+ carriers across both cohorts.

CONCLUSIONS

Vascular risk is indirectly associated with the level of plasma aβ 42/40 via cerebral amyloid burden only in APOE ε4+ carriers. Nondemented older adults with genetic vulnerability to dementia and accelerated decline may benefit from careful monitoring of vascular risk factors directly associated with cerebral amyloid burden and indirectly with plasma aβ 42/40.

Sex, Age, and Regional Differences in CHRM1 and CHRM3 Genes Expression Levels in the Human Brain Biopsies: Potential Targets for Alzheimer's Disease-related Sleep Disturbances

BACKGROUND

Cholinergic hypofunction and sleep disturbance are hallmarks of Alzheimer's disease (AD), a progressive disorder leading to neuronal deterioration. Muscarinic acetylcholine receptors (M1-5 or mAChRs), expressed in hippocampus and cerebral cortex, play a pivotal role in the aberrant alterations of cognitive processing, memory, and learning, observed in AD. Recent evidence shows that two mAChRs, M1 and M3, encoded by CHRM1 and CHRM3 genes, respectively, are involved in sleep functions and, peculiarly, in rapid eye movement (REM) sleep.

METHODS

We used twenty microarray datasets extrapolated from post-mortem brain tissue of nondemented healthy controls (NDHC) and AD patients to examine the expression profile of CHRM1 and CHRM3 genes. Samples were from eight brain regions and stratified according to age and sex.

RESULTS

CHRM1 and CHRM3 expression levels were significantly reduced in AD compared with ageand sex-matched NDHC brains. A negative correlation with age emerged for both CHRM1 and CHRM3 in NDHC but not in AD brains. Notably, a marked positive correlation was also revealed between the neurogranin (NRGN) and both CHRM1 and CHRM3 genes. These associations were modulated by sex. Accordingly, in the temporal and occipital regions of NDHC subjects, males expressed higher levels of CHRM1 and CHRM3, respectively, than females. In AD patients, males expressed higher levels of CHRM1 and CHRM3 in the temporal and frontal regions, respectively, than females.

CONCLUSION

Thus, substantial differences, all strictly linked to the brain region analyzed, age, and sex, exist in CHRM1 and CHRM3 brain levels both in NDHC subjects and in AD patients.

Cognition and brain health among older adults in Iceland: the AGES-Reykjavik study

The paper aimed to compare how factors previously identified as predictive factors for cognitive decline and dementia related to cognitive performance on the one hand and brain health on the other. To that aim, multiple linear regression was applied to the AGES-Reykjavik study epidemiological data. Additionally, a regression analysis was performed for change in cognition over 5 years, using the same exposure factors. The study ran from 2002 to 2011, and the sample analyzed included 1707 participants between the ages of 66 and 90. The data contains MR imaging, cognitive testing, background data, and physiological measurements. Overall, we conclude that risk factors linked to dementia relate differently to cognition and brain health. Mobility, physical strength, alcohol consumption, coronary artery disease, and hypertension were associated with cognition and brain volume. Smoking, depression, diabetes, and body fat percentage were only associated with brain volume, not cognitive performance. Modifiable factors previously linked to cognitive reserve, such as educational attainment, participation in leisure activities, multilingualism and good self-reported health, were associated with cognitive function but did not relate to brain volume. These findings show that, within the same participant pool, cognitive reserve proxy variables have a relationship with cognitive performance but have no association with relative brain volume measured simultaneously.

Blood Biomarkers for the Diagnosis of Neurodegenerative Dementia: A Systematic Review

IMPORTANCE

Accurately diagnosing neurodegenerative dementia is often challenging due to overlapping clinical features. Disease specific biomarkers could enhance diagnostic accuracy. However, CSF analysis procedures and advanced imaging modalities are either invasive or high-priced, and routinely unavailable. Easily accessible disease biomarkers would be of utmost value for accurate differential diagnosis of dementia subtypes.

OBJECTIVE

To assess the diagnostic accuracy of blood-based biomarkers for the differential diagnosis of AD from Frontotemporal Lobar Degeneration (FTLD), or AD from Dementia with Lewy Bodies (DLB).

METHODS

Systematic review. Three databases (PubMed, Scopus, and Web of Science) were searched. Studies assessing blood-based biomarkers levels in AD versus FTLD, or AD versus DLB, and its diagnostic accuracy, were selected. When the same biomarker was assessed in three or more studies, a meta-analysis was performed. QUADAS-2 criteria were used for quality assessment.

RESULTS

Twenty studies were included in this analysis. Collectively, 905 AD patients were compared to 1262 FTLD patients, and 209 AD patients were compared to 246 DLB patients. Regarding biomarkers for AD versus FTLD, excellent discriminative accuracy (AUC >0.9) was found for p-tau181, p-tau217, synaptophysin, synaptopodin, GAP43 and calmodulin. Other biomarkers also demonstrated good accuracy (AUC = 0.8-0.9). For AD versus DLB distinction, only miR-21-5p and miR-451a achieved excellent accuracy (AUC >0.9).

CONCLUSION

Encouraging results were found for several biomarkers, alone or in combination. Prospective longitudinal designs and consensual protocols, comprising larger cohorts and homogeneous testing modalities across centres, are essential to validate the clinical value of blood biomarkers for the precise etiological diagnosis of dementia.

MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe's aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.

Small and long RNA transcriptome of whole human cerebrospinal fluid and serum as compared to their extracellular vesicle fractions reveal profound differences in expression patterns and impacts on biological processes

BACKGROUND

Next generation sequencing (NGS) of human specimen is expected to improve prognosis and diagnosis of human diseases, but its sensitivity urges for well-defined sampling and standardized protocols in order to avoid error-prone conclusions.

METHODS

In this study, large volumes of pooled human cerebrospinal fluid (CSF) were used to prepare RNA from human CSF-derived extracellular vesicles (EV) and from whole CSF, as well as from whole human serum and serum-derived EV. In all four fractions small and long coding and non-coding RNA expression was analyzed with NGS and transcriptome analyses.

RESULTS

We show, that the source of sampling has a large impact on the acquired NGS pattern, and differences between small RNA fractions are more distinct than differences between long RNA fractions. The highest percentual discrepancy between small RNA fractions and the second highest difference between long RNA fractions is seen in the comparison of CSF-derived EV and whole CSF. Differences between miR (microRNA) and mRNA fractions of EV and the respective whole body fluid have the potential to affect different cellular and biological processes. I.e. a comparison of miR in both CSF fractions reveals that miR from EV target four transcripts sets involved in neurobiological processes, whereas eight others, also involved in neurobiological processes are targeted by miR found in whole CSF only. Likewise, three mRNAs sets derived from CSF-derived EV are associated with neurobiological and six sets with mitochondrial metabolism, whereas no such mRNA transcript sets are found in the whole CSF fraction. We show that trace amounts of blood-derived contaminations of CSF can bias RNA-based CSF diagnostics.

CONCLUSIONS

This study shows that the composition of small and long RNA differ significantly between whole body fluid and its respective EV fraction and thus can affect different cellular and molecular functions. Trace amounts of blood-derived contaminations of CSF can bias CSF analysis. This has to be considered for a meaningful RNA-based diagnostics. Our data imply a transport of EV from serum to CSF across the blood-brain barrier.

Mapping cortical disease-burden at individual-level in frontotemporal dementia: implications for clinical care and pharmacological trials

Imaging studies of FTD typically present group-level statistics between large cohorts of genetically, molecularly or clinically stratified patients. Group-level statistics are indispensable to appraise unifying radiological traits and describe genotype-associated signatures in academic studies. However, in a clinical setting, the primary objective is the meaningful interpretation of imaging data from individual patients to assist diagnostic classification, inform prognosis, and enable the assessment of progressive changes compared to baseline scans. In an attempt to address the pragmatic demands of clinical imaging, a prospective computational neuroimaging study was undertaken in a cohort of patients across the spectrum of FTD phenotypes. Cortical changes were evaluated in a dual pipeline, using standard cortical thickness analyses and an individualised, z-score based approach to characterise subject-level disease burden. Phenotype-specific patterns of cortical atrophy were readily detected with both methodological approaches. Consistent with their clinical profiles, patients with bvFTD exhibited orbitofrontal, cingulate and dorsolateral prefrontal atrophy. Patients with ALS-FTD displayed precentral gyrus involvement, nfvPPA patients showed widespread cortical degeneration including insular and opercular regions and patients with svPPA exhibited relatively focal anterior temporal lobe atrophy. Cortical atrophy patterns were reliably detected in single individuals, and these maps were consistent with the clinical categorisation. Our preliminary data indicate that standard T1-weighted structural data from single patients may be utilised to generate maps of cortical atrophy. While the computational interpretation of single scans is challenging, it offers unrivalled insights compared to visual inspection. The quantitative evaluation of individual MRI data may aid diagnostic classification, clinical decision making, and assessing longitudinal changes.

Sulfiredoxin-1 blood mRNA expression levels negatively correlate with hippocampal atrophy and cognitive decline

Introduction: Cognitive decline, correlating with hippocampal atrophy, characterizes several neurodegenerative disorders having a background of low-level chronic inflammation and oxidative stress.

Methods: In this cross-sectional study, we examined how cognitive decline and hippocampal subfields volume are associated with the expression of redox and inflammatory genes in peripheral blood. We analyzed 34 individuals with different cognitive scores according to Mini-Mental State Examination, corrected by age and education (adjMMSE). We identified a group presenting cognitive decline (CD) with adjMMSE<27 (n=14) and a normal cognition (NC) group with adjMMSE≥27 (n=20). A multiparametric approach, comprising structural magnetic resonance imaging measurement of different hippocampal segments and blood mRNA expression of redox and inflammatory genes was applied.

Results: Our findings indicate that hippocampal segment volumes correlate positively with adjMMSE and negatively with the blood transcript levels of 19 genes, mostly redox genes correlating especially with the left subiculum and presubiculum. A strong negative correlation between hippocampal subfields atrophy and Sulfiredoxin-1 ( SRXN1) redox gene was emphasized.

Conclusions: Concluding, these results suggest that SRXN1 might be a valuable candidate blood biomarker for non-invasively monitoring the evolution of hippocampal atrophy in CD patients.

Assessment of finger motor function that reflects the severity of cognitive function

OBJECTIVES

We conducted a finger tapping movement test using a finger tapping device with magnetic sensors (UB-2) and performed multiple regression analyses using a number of finger movements parameters to estimate the severity of cognitive impairment.

METHODS

The subjects of this study were 64 patients, including 44 diagnosed with Alzheimer's disease (AD) (mean age: 73.8±7.0 years) and 20 diagnosed with mild cognitive impairment (MCI) (mean age: 76.7±4.2 years). For the finger-tapping movement tasks, we tested single-hand (left and right) tapping, simultaneous tapping of both hands, and alternate tapping between hands. After measurement, multiple regression analysis adjusted for age and sex was performed to predict the Mini-Mental State Examination (MMSE) score from the calculated hand parameters.

RESULTS

Relatively high standardized partial regression coefficients were observed for the following two parameters: standard deviation (SD) of distance rate of velocity peak in extending movement and the SD of contact duration. The coefficients of determination (R²) ranged between 0.1 to 0.28.

CONCLUSIONS

Our results suggest the possibility that these parameters may be used to assess cognitive function. We shall obtain large-scale data from older people to examine the possibility of these parameters to be used as an early diagnostic tool for dementia patients.

Dissecting Digital Card Games to Yield Digital Biomarkers for the Assessment of Mild Cognitive Impairment: Methodological Approach and Exploratory Study

Background

Mild cognitive impairment (MCI), the intermediate cognitive status between normal cognitive decline and pathological decline, is an important clinical construct for signaling possible prodromes of dementia. However, this condition is underdiagnosed. To assist monitoring and screening, digital biomarkers derived from commercial off-the-shelf video games may be of interest. These games maintain player engagement over a longer period of time and support longitudinal measurements of cognitive performance.

Objective

This paper aims to explore how the player actions of Klondike Solitaire relate to cognitive functions and to what extent the digital biomarkers derived from these player actions are indicative of MCI.

Methods

First, 11 experts in the domain of cognitive impairments were asked to correlate 21 player actions to 11 cognitive functions. Expert agreement was verified through intraclass correlation, based on a 2-way, fully crossed design with type consistency. On the basis of these player actions, 23 potential digital biomarkers of performance for Klondike Solitaire were defined. Next, 23 healthy participants and 23 participants living with MCI were asked to play 3 rounds of Klondike Solitaire, which took 17 minutes on average to complete. A generalized linear mixed model analysis was conducted to explore the differences in digital biomarkers between the healthy participants and those living with MCI, while controlling for age, tablet experience, and Klondike Solitaire experience.

Results

All intraclass correlations for player actions and cognitive functions scored higher than 0.75, indicating good to excellent reliability. Furthermore, all player actions had, according to the experts, at least one cognitive function that was on average moderately to strongly correlated to a cognitive function. Of the 23 potential digital biomarkers, 12 (52%) were revealed by the generalized linear mixed model analysis to have sizeable effects and significance levels. The analysis indicates sensitivity of the derived digital biomarkers to MCI.

Conclusions

Commercial off-the-shelf games such as digital card games show potential as a complementary tool for screening and monitoring cognition.

Trial Registration

ClinicalTrials.gov NCT02971124; https://clinicaltrials.gov/ct2/show/NCT02971124

Diagnostic accuracy of blood biomarkers for Alzheimer's disease and amnestic mild cognitive impairment: A meta-analysis

OBJECTIVE

To examine the diagnostic accuracy of blood-based biomarkers for detecting Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI).

METHODS

Seven electronic databases were comprehensively searched for studies evaluating the diagnostic accuracy of blood-based biomarkers for detecting AD or aMCI up to July 31, 2020. The pooled sensitivity, specificity, and the diagnostic odds ratio (DOR) were calculated using a hierarchical summary receiver operating characteristic model.

RESULTS

A total of 17 studies (n = 2,083) were included. In differentiating patients with AD from the controls, the DOR was 32.2 for the plasma Aβ42 (sensitivity = 88 %, specificity = 81 %), 29.1 for the plasma Aβ oligomer (sensitivity = 80 %, specificity = 88 %), and 52.1 for the plasma tau (sensitivity = 90 %, specificity = 87 %). For differentiating aMCI from the controls, the DOR was 60.4 for the plasma Aβ42 (sensitivity = 86 %, specificity = 90 %) and 49.1 for the plasma tau (sensitivity = 79 %, specificity = 94 %). The use of ultra-high sensitive technology explained the heterogeneity in the diagnostic performance of blood-based biomarkers (P =  .01).

CONCLUSIONS

We suggest that blood-based biomarkers are minimally invasive and cost-effective tools for detecting AD; however, the evidence for detecting aMCI was still limited.

Discovery of a Metabolic Signature Predisposing High Risk Patients with Mild Cognitive Impairment to Converting to Alzheimer's Disease

Assessing dementia conversion in patients with mild cognitive impairment (MCI) remains challenging owing to pathological heterogeneity. While many MCI patients ultimately proceed to Alzheimer’s disease (AD), a subset of patients remain stable for various times. Our aim was to characterize the plasma metabolites of nineteen MCI patients proceeding to AD (P-MCI) and twenty-nine stable MCI (S-MCI) patients by untargeted metabolomics profiling. Alterations in the plasma metabolites between the P-MCI and S-MCI groups, as well as between the P-MCI and AD groups, were compared over the observation period. With the help of machine learning-based stratification, a 20-metabolite signature panel was identified that was associated with the presence and progression of AD. Furthermore, when the metabolic signature panel was used for classification of the three patient groups, this gave an accuracy of 73.5% using the panel. Moreover, when specifically classifying the P-MCI and S-MCI subjects, a fivefold cross-validation accuracy of 80.3% was obtained using the random forest model. Importantly, indole-3-propionic acid, a bacteria-generated metabolite from tryptophan, was identified as a predictor of AD progression, suggesting a role for gut microbiota in AD pathophysiology. Our study establishes a metabolite panel to assist in the stratification of MCI patients and to predict conversion to AD.

Electroencephalography as a Non-Invasive Biomarker of Alzheimer's Disease: A Forgotten Candidate to Substitute CSF Molecules?

Biomarkers for disease diagnosis and prognosis are crucial in clinical practice. They should be objective and quantifiable and respond to specific therapeutic interventions. Optimal biomarkers should reflect the underlying process (pathological or not), be reproducible, widely available, and allow measurements repeatedly over time. Ideally, biomarkers should also be non-invasive and cost-effective. This review aims to focus on the usefulness and limitations of electroencephalography (EEG) in the search for Alzheimer's disease (AD) biomarkers. The main aim of this article is to review the evolution of the most used biomarkers in AD and the need for new peripheral and, ideally, non-invasive biomarkers. The characteristics of the EEG as a possible source for biomarkers will be revised, highlighting its advantages compared to the molecular markers available so far.

Platelet miRNA Biosignature Discriminates between Dementia with Lewy Bodies and Alzheimer's Disease

Dementia with Lewy bodies (DLB) is one of the most common causes of degenerative dementia, after Alzheimer's disease (AD), and presents pathological and clinical overlap with both AD and Parkinson's disease (PD). Consequently, only one in three DLB cases is diagnosed correctly. Platelets, previously related to neurodegeneration, contain microRNAs (miRNAs) whose analysis may provide disease biomarkers. Here, we profiled the whole platelet miRNA transcriptome from DLB patients and healthy controls. Differentially expressed miRNAs were further validated in three consecutive studies from 2017 to 2019 enrolling 162 individuals, including DLB, AD, and PD patients, and healthy controls. Results comprised a seven-miRNA biosignature, showing the highest diagnostic potential for the differentiation between DLB and AD. Additionally, compared to controls, two miRNAs were down-regulated in DLB, four miRNAs were up-regulated in AD, and two miRNAs were down-regulated in PD. Predictive target analysis identified three disease-specific clusters of pathways as a result of platelet-miRNA deregulation. Our cross-sectional study assesses the identification of a novel, highly specific and sensitive platelet-associated miRNA-based biosignature, which distinguishes DLB from AD.

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.

Practical recommendations for timely, accurate diagnosis of symptomatic Alzheimer's disease (MCI and dementia) in primary care: a review and synthesis

The critical role of primary care clinicians (PCCs) in Alzheimer's disease (AD) prevention, diagnosis and management must evolve as new treatment paradigms and disease-modifying therapies (DMTs) emerge. Our understanding of AD has grown substantially: no longer conceptualized as a late-in-life syndrome of cognitive and functional impairments, we now recognize that AD pathology builds silently for decades before cognitive impairment is detectable. Clinically, AD first manifests subtly as mild cognitive impairment (MCI) due to AD before progressing to dementia. Emerging optimism for improved outcomes in AD stems from a focus on preventive interventions in midlife and timely, biomarker-confirmed diagnosis at early signs of cognitive deficits (i.e. MCI due to AD and mild AD dementia). A timely AD diagnosis is particularly important for optimizing patient care and enabling the appropriate use of anticipated DMTs. An accelerating challenge for PCCs and AD specialists will be to respond to innovations in diagnostics and therapy for AD in a system that is not currently well positioned to do so. To overcome these challenges, PCCs and AD specialists must collaborate closely to navigate and optimize dynamically evolving AD care in the face of new opportunities. In the spirit of this collaboration, we summarize here some prominent and influential models that inform our current understanding of AD. We also advocate for timely and accurate (i.e. biomarker-defined) diagnosis of early AD. In doing so, we consider evolving issues related to prevention, detecting emerging cognitive impairment and the role of biomarkers in the clinic.

Neuroscience Education: Making It Relevant to Psychiatric Training

Psychiatric education has struggled to move past dualistic notions separating mind from brain, and embrace the field's identity as a clinical neuroscience discipline. To modernize our educational systems, we must integrate neuroscience perspectives into every facet of our clinical work. To do this effectively, neuroscience education should be clinically relevant, informed by adult learning theory, and tailored to the individualized needs of learners. Classic neuropsychiatry skills can help us better understand our patients' brain function at the bedside. Integrating neuroscience perspectives alongside the other rich perspectives in psychiatry will help trainees appreciate the relevance of neuroscience to modern medical practice.

Augmenting Clinical Interventions in Psychiatric Disorders: Systematic Review and Update on Nutrition

There is a strong relationship between a healthy diet and mental well-being. Several foods and food compounds are known to modulate biomarkers and molecular mechanisms involved in the aetiogenesis of several mental disorders, and this can be useful in containing the disease progression, including its prophylaxis. This is an updated systematic review of the literature to justify the inclusion and recognition of nutrition in the management of psychiatric illnesses. Such foods and their compounds include dietary flavanols from fruits and vegetables, notable antioxidant and anti-inflammatory agents, probiotics (fermented foods) known to protect good gut bacteria, foods rich in polyunsaturated fatty acids (e.g., Omega-3), and avoiding diets high in saturated fats and refined sugars among others. While the exact mechanism(s) of mitigation of many nutritional interventions are yet to be fully understood, the evidence-based approach warrants the inclusion and co-recognition of nutrition in the management of psychiatric illnesses. For the greater public health benefit, there is a need for policy advocacy aimed at bridging the knowledge gap and encouraging the integration of nutritional intervention with contemporary therapies in clinical settings, as deficiencies of certain nutrients make therapy difficult even with appropriate medication.

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.

Biomarkers of Neurodegeneration and Precision Therapy in Retinal Disease

Vision-threatening retinal diseases affect millions of people worldwide, representing an important public health issue (high social cost) for both technologically advanced and new-industrialized countries. Overall RD group comprises the retinitis pigmentosa, the age-related macular degeneration (AMD), the diabetic retinopathy (DR), and idiopathic epiretinal membrane formation. Endocrine, metabolic, and even lifestyles risk factors have been reported for these age-linked conditions that represent a "public priority" also in this COVID-19 emergency. Chronic inflammation and neurodegeneration characterize the disease evolution, with a consistent vitreoretinal interface impairment. As the vitreous chamber is significantly involved, the latest diagnostic technologies of imaging (retina) and biomarker detection (vitreous) have provided a huge input at both medical and surgical levels. Complement activation and immune cell recruitment/infiltration as well as detrimental intra/extracellular deposits occur in association with a reactive gliosis. The cell/tissue aging route shows a specific signal path and biomolecular profile characterized by the increased expression of several glial-derived mediators, including angiogenic/angiostatic, neurogenic, and stress-related factors (oxidative stress metabolites, inflammation, and even amyloid formation). The possibility to access vitreous chamber by collecting vitreous reflux during intravitreal injection or obtaining vitreous biopsy during a vitrectomy represents a step forward for an individualized therapy. As drug response and protein signature appear unique in each single patient, therapies should be individualized. This review addresses the current knowledge about biomarkers and pharmacological targets in these vitreoretinal diseases. As vitreous fluids might reflect the early stages of retinal sufferance and/or late stages of neurodegeneration, the possibility to modulate intravitreal levels of growth factors, in combination to anti-VEGF therapy, would open to a personalized therapy of retinal diseases.

Frailty, MRI, and FDG-PET Measures in an Australian Memory Clinic Cohort

Given that the global population is aging, the number of age-related syndromes, such as frailty, is expected to rise in conjunction. Frailty is characterized by the loss of homeostatic reserve, rendering the individual vulnerable to poor health outcomes. Many biological mechanisms have been proposed to contribute to frailty. However, few studies have assessed the associations between frailty and brain diseases or neuroimaging biomarkers. Aims: The aims of this study were to measure the prevalence of frailty in a memory clinic and to examine associations between frailty and brain changes found on magnetic resonance imaging (MRI) and 18-F deoxyglucose (FDG) positron emission tomography (PET) in memory clinic attendees. Methods: A 54-items Frailty Index was retrospectively assessed for all clinic attendees from 2014. Frailty was defined as FI > 0.25. MR images were analyzed for stroke, cerebral small vessel disease [CSVD, including cerebral microbleeds (CMBs), cortical superficial siderosis (CSS), and white matter hyperintensity (WMH)], and neurodegenerative changes [MRI: mesial temporal atrophy (MTA), FDG-PET: regional hypometabolism], blind to clinical findings. Results: There were 209 clinic attendees in 2014, of whom 121 had MRI performed. The prevalence of frailty (using FI) in the memory clinic in 2014 was 38.3% overall (patients without MRI: 43.2%, patients with MRI 34.7%, p = 0.25). Frailty was associated with presence of deep WMH, increased severity of periventricular WMH, and presence of CSS, but not neurodegeneration markers (MTA atrophy/FDG-PET hypometabolism). Conclusion: The findings support the idea that previously reported associations between frailty and imaging evidence of CSVD in other cohorts are also relevant to the Australian clinic setting. Given that a large proportion of memory clinic attendees are frail, there may be opportunities for interventions to reduce preventable adverse health outcomes, such as falls and fractures, and reduce the prevalence and impact of frailty in this cohort.

Fluid Biomarkers of Frontotemporal Lobar Degeneration

A timely diagnosis of frontotemporal degeneration (FTD) is frequently challenging due to the heterogeneous symptomatology and poor phenotype-pathological correlation. Fluid biomarkers that reflect FTD pathophysiology could be instrumental in both clinical practice and pharmaceutical trials. In recent years, significant progress has been made in developing biomarkers of neurodegenerative diseases: amyloid-β and tau in cerebrospinal fluid (CSF) can be used to exclude Alzheimer's disease, while neurofilament light chain (NfL) is emerging as a promising, albeit nonspecific, marker of neurodegeneration in both CSF and blood. Gene-specific biomarkers such as PGRN in GRN mutation carriers and dipeptide repeat proteins in C9orf72 mutation carriers are potential target engagement markers in genetic FTD trials. Novel techniques capable of measuring very low concentrations of brain-derived proteins in peripheral fluids are facilitating studies of blood biomarkers as a minimally invasive alternative to CSF. A major remaining challenge is the identification of a biomarker that can be used to predict the neuropathological substrate in sporadic FTD patients.

Comparing fluid biomarkers of Alzheimer's disease between African American or Black African and white groups: A systematic review and meta-analysis

RATIONALE

Biomarker research for Alzheimer's disease (AD) has grown rapidly in recent years, ensuing the integration of the AD fluid biomarker profile: Aβ1-42, t-tau, and p-tau₁₈₁, into clinical and research criteria. However, current insights of AD arise almost exclusively from studies on white individuals. Some studies have revealed that epidemiology, clinical features, and genetics of AD show variations between individuals from black and white backgrounds, conveying the importance of ethnoracial differences, and the possibility of such differences also influencing AD biomarker levels. This systematic review explored whether AD fluid biomarker levels differ between African American (AA) or Black African and white groups.

AIM

To compare AD fluid biomarkers (Aβ1-42, p-tau₁₈₁, and t-tau) levels between AA or Black Africans and white individuals.

METHOD

PubMed, Scopus, and other sources were explored for studies that quantified AD biomarkers in biological fluid from whites and AA or Black African groups. Meta-analyses were performed to find the standardized mean difference for biomarkers that were quantified in ≥3 studies.

RESULTS

Five studies were included; studies on Black Africans were not found. The meta-analyses found CSF t-tau and p-tau₁₈₁ were consistently lower in AA than white individuals, in samples with normal cognition or with mild cognitive impairment/dementia.

CONCLUSIONS

The meta-analyses found significant differences for CSF tau between AA and white individuals with normal cognition and within the dementia spectrum, expressing the importance of taking into account ethnoracial factors when interpreting CSF AD biomarkers levels. However, the generalisability of these differences is restricted by small samples' size, lack of unified methodologies and recruitment's biases within studies; further large multicentre studies with harmonized protocols and sufficient power are imperative to investigate the extent of ethnoracial differences across the spectrum of cognitive decline, with vaster efforts necessary to diversify recruitment.

Added value of cerebrospinal fluid multimarker analysis in diagnosis and progression of dementia

BACKGROUND AND PURPOSE

Recently, some emerging cerebrospinal fluid (CSF) markers have been proposed as diagnostic tools for Alzheimer disease (AD) that can have an effect on disease progression. We analyze the accuracy of these CSF markers for diagnosis of AD in reference to brain amyloid positron emission tomography (PET). We also investigated whether they help in differentiating AD from other dementias and examined their influence in tracing the progression to dementia.

METHODS

Amyloid-β (Aβ) 1-42, total tau (t-tau), phosphorylated tau, Aβ₄₀ , Aβ₃₈ , beta-site amyloid precursor protein cleaving enzyme 1 (BACE-1), neurogranin (ng), phosphorylated neurofilament heavy-chain, and α-synuclein (α-syn) CSF levels were analyzed in 319 subjects, among whom 57 also underwent an amyloid PET scan. We also analyzed longitudinal clinical data from 239 subjects.

RESULTS

Emerging CSF markers, especially ng/BACE-1 ratio (area under the curve = 0.77) and their combinations with core AD CSF markers (all AUCs >0.85), showed high accuracy to discriminate amyloid PET positivity. Subjects with AD had higher CSF BACE-1, ng, and α-syn levels than those with non-AD dementia. CSF t-tau/α-syn ratio was higher in subjects with dementia with Lewy bodies than in those with frontotemporal dementia. Most emerging/core AD ratios predicted a faster conversion from mild cognitive impairment (MCI) stage to AD and appeared to be helpful when core AD CSF markers were discordant. In addition, the rate of cognitive decline was associated with all CSF core AD markers, several emerging/core AD two-marker ratios, and CSF ng levels.

CONCLUSIONS

These results suggest that emerging biomarkers in conjunction with core AD markers improve diagnosis of AD, are associated with the conversion from MCI into AD, and predict a faster progression of dementia.

Altered prefrontal cortex responses in older adults with subjective memory complaints and dementia during dual-task gait: An fNIRS study

People with cognitive impairments show deficits during physical performances such as gait, in particular during cognitively challenging conditions (i.e. dual-task gait [DTG]). However, it is unclear if people at risk of dementia, such as those with subjective memory complaints (SMC), also display gait and central deficits associated with DTG. In this study, we investigated the effects of single- and dual-task gait (STG and DTG), on left prefrontal cortex (PFC) activation in elderly people with subjective memory complaints (SMC) and Dementia. A total of 58 older adults (aged 65-94 years; 26 Healthy; 23 SMC; 9 Dementia) were recruited. Gait spatiotemporal characteristics (i.e. stride velocity and length) were assessed using an instrumented walkway during STG and DTG. Single-channel functional near-infrared spectroscopy over the left PFC was used to measure changes in oxyhaemoglobin (O₂ Hb) during gait. Stride velocity and length during STG (all p < .05) and DTG (all p < .000) were significantly impaired in people with Dementia compared to Healthy and SMC individuals. No differences were observed between Healthy and SMC. For STG, a greater increase in O₂ Hb (p < .05) was observed in those with Dementia compared to the Healthy and SMC, while no differences were observed between Healthy and SMC. A significant increase and decline in O₂ Hb was observed during DTG in the SMC and Dementia groups, respectively, compared to Healthy. Our findings indicate an altered pattern of cerebral haemodynamic response of the left PFC in DTG in people with SMC and Dementia, which may suggest that central changes precede functional impairments in people with SMC.

The importance of multidisciplinary team in the treatment of severe traumatic brain injury

Noticeable advances have occurred in the field of traumatic brain injury in the past ten years. Brain imagery provides a more precise representation of what occurs in the brain, diffuse axonal injury being an important cause of morbidity and mortality in patients with traumatic brain injury. We present 2 cases that were admitted and discharged from our department. Actually we want to emphasize differences and similarities between the two cases and to highlight different sequelae that traumatic brain injury can do in young patients. Both patients were admitted in a critical state – GCS 4 points and were discharged with an improved neurological status after approximately 30 days. We decided to present these cases to issue a warning about the rehabilitation for these patients which most of the times have a prolonged hospitalization. We wanted to highlight that the rehabilitation does not consist only in the motor part, but in the psychiatric and behaviour part too.

Lifestyle, multi-omics features, and preclinical dementia among Chinese: The Taizhou Imaging Study

China has the largest number of patients with dementia in the world. However, dementia in the Chinese population is still poorly understood and under-researched. Given the differences in genetic, demographic, sociocultural, lifestyle, and health profiles among Chinese and other ethnic/racial groups, it is crucial to build appropriate infrastructure for long-term longitudinal studies to advance Chinese cognitive aging and dementia research. We initiated a community-based prospective cohort-the Taizhou Imaging Study (TIS)-to accelerate the understanding of dementia and cerebrovascular diseases in Chinese. This article presents the rationale, aims, study design, and organization of TIS. In addition, we described some examples of the types of studies such a resource might support. The TIS provides a new framework for facilitating Chinese dementia research, encompassing invaluable resources including detailed epidemiological, sociocultural, neuroimaging, and omics data.

Approach to the Older Adult With New Cognitive Symptoms

Dementia affects nearly 50 million people worldwide, translating into one new case every 3 seconds. Dementia syndrome is one of the leading causes of disability among older adults, yet it remains vastly underdiagnosed. A timely diagnosis of dementia is essential to ensuring optimal care and support of individuals and their loved ones. Although there is no single test for dementia, health care providers can use a structured approach to the workup and management of new cognitive symptoms. Comprehensive MEDLINE and PubMed searches were performed to develop an unbiased, practical diagnostic approach to these symptoms. This review guides primary care providers in the workup, diagnosis, delivery, and initial management of patients presenting with new cognitive symptoms.

Novel fluid biomarkers to differentiate frontotemporal dementia and dementia with Lewy bodies from Alzheimer's disease: A systematic review

RATIONALE

Frontotemporal dementia (FTD) and dementia with Lewy bodies (DLB) are two common forms of neurodegenerative dementia, subsequent to Alzheimer's disease (AD). AD is the only dementia that includes clinically validated cerebrospinal fluid (CSF) biomarkers in the diagnostic criteria. FTD and DLB often overlap with AD in their clinical and pathological features, making it challenging to differentiate between these conditions.

AIM

This systematic review aimed to identify if novel fluid biomarkers are useful in differentiating FTD and DLB from AD. Increasing the certainty of the differentiation between dementia subtypes would be advantageous clinically and in research.

METHODS

PubMed and Scopus were searched for studies that quantified and assessed diagnostic accuracy of novel fluid biomarkers in clinically diagnosed patients with FTD or DLB, in comparison to patients with AD. Meta-analyses were performed on biomarkers that were quantified in 3 studies or more.

RESULTS

The search strategy yielded 614 results, from which, 27 studies were included. When comparing bio-fluid levels in AD and FTD patients, neurofilament light chain (NfL) level was often higher in FTD, whilst brain soluble amyloid precursor protein β (sAPPβ) was higher in patients with AD. When comparing bio-fluid levels in AD and DLB patients, α-synuclein ensued heterogeneous findings, while the noradrenaline metabolite (MHPG) was found to be lower in DLB. Ratios of Aβ42/Aβ38 and Aβ42/Aβ40 were lower in AD than FTD and DLB and offered better diagnostic accuracy than raw amyloid-β (Aβ) concentrations.

CONCLUSIONS

Several promising novel biomarkers were highlighted in this review. Combinations of fluid biomarkers were more often useful than individual biomarkers in distinguishing subtypes of dementia. Considering the heterogeneity in methods and results between the studies, further validation, ideally with longitudinal prospective designs with large sample sizes and unified protocols, are fundamental before conclusions can be finalised.

Metabolomics and incident dementia in older Chinese adults: The Shanghai Aging Study

INTRODUCTION

Metabolomics provide a promising tool to understand the pathogenesis and to identify novel biomarkers of dementia. This study aimed to determine circulating metabolites associated with incident dementia in a Chinese cohort, and whether a selected metabolite panel could predict dementia.

METHODS

Thirty-eight metabolites in baseline serum were profiled by nuclear magnetic resonance in 1440 dementia-free participants followed 5 years in the Shanghai Aging Study.

RESULTS

Higher serum levels of glutamine and O-acetyl-glycoproteins were associated with increased risk of dementia, whereas glutamate, tyrosine, acetate, glycine, and phenylalanine were negatively related to incident dementia. A panel of five metabolites selected by least absolute shrinkage and selection operator within cross-validation regression analysis could predict incident dementia with an area under the receiver-operating characteristic curve of 0.72.

DISCUSSION

We identified seven candidate serum metabolic biomarkers for dementia. These findings and the underlying biological mechanisms need to be further replicated and elucidated in future studies.

Fluselenamyl: Evaluation of radiation dosimetry in mice and pharmacokinetics in brains of non-human primate

INTRODUCTION

To allow quantitative assessment of therapeutic efficacy for therapeutic interventions (either approved or undergoing FDA approvals) for either inhibiting or reducing development of Aβ pathophysiology in vivo, ¹⁸F-labelled tracers, such as Florbetapir, Florbetaben, and Flutemetamol have been approved. Previously, we have reported on development and preclinical validation of ¹⁸F-Fluselenamyl, comprising traits of translatable Aβ imaging agents. Herein, we report the dosimetry data for ¹⁸F-Fluselenamyl to provide radiation dose deposited within organs and determine effective dose (ED) for human studies, while also evaluating its pharmacokinetics in the nonhuman primate brains.

METHODS

To evaluate safety profiles of ¹⁸F-Fluselenamyl for enabling its deployment as a PET imaging agent for monitoring Aβ pathophysiology in vivo, we estimated the human radiation dosimetry extrapolated from rodent biodistribution data obtained by standard method of organ dissection. Animal biodistribution studies were performed in FVB/NCR mice (20 males, 20 females), following tail-vein injection of the tracer. Following euthanasia of mice, organs were harvested, counted, radiation dose to each organ and whole body was determined using the standard MIRD methodology. For evaluation of pharmacokinetics in non-human primates, following intravenous injection of the tracer, dynamic PET scan of rhesus monkey brains were performed, and co-registered with MR for anatomical reference. Parametric images of tracer transport rate constant and distribution volume relative to cerebellum were generated using a simplified reference tissue model and a spatially-constraint linear regression algorithm.

RESULTS

The critical organ in humans has been determined to be the gall bladder with a gender average radiation absorbed dose of 0.079 mGy/MBq with an effective dose of 0.017 mSv/MBq and 0.020 mSv/MBq, in males and females, respectively. Therefore, these data provide preliminary projections on human dosimetry derived from rodent estimates, thereby defining safe imaging conditions for further validations in human subjects. Additionally, the tracer penetrated the non-human primate brain and excreted to background levels at later-time points thus pointing to the potential for high signal/noise ratios during noninvasive imaging. Tissue time activity curves (TACs) also show fast initial uptake with maximum projection of activity at 2-6 min post administration followed by clearance of activity at later time-points from cortex, cerebellum, and white matter of nonhuman primate brain. Parametric images confirmed that the ¹⁸F-Fluselenamyl has relative high transport rate constant at striatum, thalamus, and cortex.

CONCLUSIONS

The data obtained from radiation dosimetry studies in mice indicate that ¹⁸F-Fluselenamyl can be safely used for further evaluation in humans. Additionally, ¹⁸F-Fluselenamyl demonstrated ability to traverse the blood brain barrier (BBB) and indicated high initial influx, followed by clearance to background levels in non-human primate brains. Combined information indicates that ¹⁸F-Fluselenamyl would be a potential candidate for detecting amyloid plaques in the living human brain.

Cerebrospinal fluid and plasma neurofilament light relate to abnormal cognition

Introduction

Neuroaxonal damage may contribute to cognitive changes preceding clinical dementia. Accessible biomarkers are critical for detecting such damage.

Methods

Plasma and cerebrospinal fluid (CSF) neurofilament light (NFL) were related to neuropsychological performance among Vanderbilt Memory & Aging Project participants (plasma n = 333, 73 ± 7 years; CSF n = 149, 72 ± 6 years) ranging from normal cognition (NC) to mild cognitive impairment (MCI). Models adjusted for age, sex, race/ethnicity, education, apolipoprotein E ε4 carriership, and Framingham Stroke Risk Profile.

Results

Plasma NFL was related to all domains (P values ≤ .008) except processing speed (P values ≥ .09). CSF NFL was related to memory and language (P values ≤ .04). Interactions with cognitive diagnosis revealed widespread plasma associations, particularly in MCI participants, which were further supported in head-to-head comparison models.

Discussion

Plasma and CSF NFL (reflecting neuroaxonal injury) relate to cognition among non-demented older adults albeit with small to medium effects. Plasma NFL shows particular promise as an accessible biomarker with relevance to cognition in MCI.

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Plasma and cerebrospinal fluid neurofilament light (NFL) were moderately correlated.

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Cerebrospinal fluid NFL was related to language and memory functions.

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Plasma NFL exhibited widespread cognitive associations.

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Plasma NFL associations were particularly robust in mild cognitive impairment.

Prediction and Classification of Alzheimer's Disease Based on Combined Features From Apolipoprotein-E Genotype, Cerebrospinal Fluid, MR, and FDG-PET Imaging Biomarkers

Alzheimer's disease (AD), including its mild cognitive impairment (MCI) phase that may or may not progress into the AD, is the most ordinary form of dementia. It is extremely important to correctly identify patients during the MCI stage because this is the phase where AD may or may not develop. Thus, it is crucial to predict outcomes during this phase. Thus far, many researchers have worked on only using a single modality of a biomarker for the diagnosis of AD or MCI. Although recent studies show that a combination of one or more different biomarkers may provide complementary information for the diagnosis, it also increases the classification accuracy distinguishing between different groups. In this paper, we propose a novel machine learning-based framework to discriminate subjects with AD or MCI utilizing a combination of four different biomarkers: fluorodeoxyglucose positron emission tomography (FDG-PET), structural magnetic resonance imaging (sMRI), cerebrospinal fluid (CSF) protein levels, and Apolipoprotein-E (APOE) genotype. The Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset was used in this study. In total, there were 158 subjects for whom all four modalities of biomarker were available. Of the 158 subjects, 38 subjects were in the AD group, 82 subjects were in MCI groups (including 46 in MCIc [MCI converted; conversion to AD within 24 months of time period], and 36 in MCIs [MCI stable; no conversion to AD within 24 months of time period]), and the remaining 38 subjects were in the healthy control (HC) group. For each image, we extracted 246 regions of interest (as features) using the Brainnetome template image and NiftyReg toolbox, and later we combined these features with three CSF and two APOE genotype features obtained from the ADNI website for each subject using early fusion technique. Here, a different kernel-based multiclass support vector machine (SVM) classifier with a grid-search method was applied. Before passing the obtained features to the classifier, we have used truncated singular value decomposition (Truncated SVD) dimensionality reduction technique to reduce high dimensional features into a lower-dimensional feature. As a result, our combined method achieved an area under the receiver operating characteristic (AU-ROC) curve of 98.33, 93.59, 96.83, 94.64, 96.43, and 95.24% for AD vs. HC, MCIs vs. MCIc, AD vs. MCIs, AD vs. MCIc, HC vs. MCIc, and HC vs. MCIs subjects which are high relative to single modality results and other state-of-the-art approaches. Moreover, combined multimodal methods have improved the classification performance over the unimodal classification.

Exploratory study on microRNA profiles from plasma-derived extracellular vesicles in Alzheimer's disease and dementia with Lewy bodies

Background

Because of the increasing life expectancy in our society, aging-related neurodegenerative disorders are one of the main issues in global health. Most of these diseases are characterized by the deposition of misfolded proteins and a progressive cognitive decline. Among these diseases, Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) are the most common types of degenerative dementia. Although both show specific features, an important neuropathological and clinical overlap between them hampers their correct diagnosis. In this work, we identified molecular biomarkers aiming to improve the misdiagnosis between both diseases.

Methods

Plasma extracellular vesicles (EVs) -from DLB, AD and healthy controls- were isolated using size-exclusion chromatography (SEC) and characterized by flow cytometry, Nanoparticle Tracking Analysis (NTA) and cryo-electron microscopy. Next Generation Sequencing (NGS) and related bibliographic search was performed and a selected group of EV-associated microRNAs (miRNAs) was analysed by qPCR.

Results

Results uncovered two miRNAs (hsa-miR-451a and hsa-miR-21-5p) significantly down-regulated in AD samples respect to DLB patients, and a set of four miRNAs (hsa-miR-23a-3p, hsa-miR-126-3p, hsa-let-7i-5p, and hsa-miR-151a-3p) significantly decreased in AD respect to controls. The two miRNAs showing decreased expression in AD in comparison to DLB provided area under the curve (AUC) values of 0.9 in ROC curve analysis, thus suggesting their possible use as biomarkers to discriminate between both diseases. Target gene analysis of these miRNAs using prediction online tools showed accumulation of phosphorylation enzymes, presence of proteasome-related proteins and genes involved in cell death among others.

Conclusion

Our data suggest that plasma-EV associated miRNAs may reflect a differential profile for a given dementia-related disorder which, once validated in larger cohorts of patients, could help to improve the differential diagnosis of DLB versus AD.

Electronic supplementary material

The online version of this article (10.1186/s40035-019-0169-5) contains supplementary material, which is available to authorized users.

Impairments of attention in Alzheimer's disease

Alzheimer's Disease (AD) is characteristically perceived as primarily being a disorder of episodic memory, with prominent attentional impairments more typically being associated with other neurodegenerative conditions, such as Dementia with Lewy Bodies. However, attention is also affected early on in Alzheimer's, particularly in individuals with young onset and atypical syndromes. In addition, some initial symptoms that are apparently due to episodic memory loss may be secondary to failures of attentional processes. This review delineates the various attentional impairments that can be observed in patients with AD, and addresses them through the conceptual framework of attention proposed by Posner and Petersen. It also describes how current knowledge of the development of AD has influenced our understanding of how these deficits arise. Finally, there is a brief summary of the effects of current AD treatments on attentional processes, and how future pharmacological approaches might better target these deficits.