Alzheimer's/Vascular Spectrum Dementia: Classification in Addition to Diagnosis

Recent Research Progress on the Use of Transcranial Magnetic Stimulation in the Treatment of Vascular Cognitive Impairment

Vascular Cognitive Impairment (VCI) is a condition where problems with brain blood vessels lead to a decline in cognitive abilities, commonly affecting the elderly and placing a significant burden on both patients and their families. Compared to medication and surgery, Transcranial Magnetic Stimulation (TMS) is a non-invasive treatment option with fewer risks and side effects, making it particularly suitable for elderly patients. TMS not only assesses the excitability and plasticity of the cerebral cortex, but its effectiveness in treating Vascular Cognitive Impairment (VCI) and its subtypes has also been validated in numerous clinical trials worldwide. However, there is still a lack of review on the physiological mechanisms of TMS treatment for VCI and its specific clinical application parameters. Therefore, this article initially provided a brief overview of the risk factors, pathological mechanisms, and classification of VCI. Next, the article explained the potential physiological mechanisms of TMS in treating VCI, particularly its role in promoting synaptic plasticity, regulating neurotransmitter balance, and improving the function of the default mode network. Additionally, The article also summarizes the application of rTMS in treating VCI and its subtypes, VCI-related sleep disorders, and the use of TMS in follow-up studies of VCI patients, providing empirical evidence for the clinical application of TMS and rTMS technologies.

Automated Scoring of Alzheimer's Disease Atrophy Scale with Subtype Classification Using Deep Learning-Based T1-Weighted Magnetic Resonance Image Segmentation

Background

Application of visual scoring scales for regional atrophy in Alzheimer's disease (AD) in clinical settings is limited by their high time cost and low intra/inter-rater agreement.

Objective

To provide automated atrophy scoring using objective volume driven from deep-learning segmentation methods for AD subtype classification using magnetic resonance imaging (MRI).

Methods

We enrolled 3,959 participants (1,732 cognitively normal [CN], 1594 with mild cognitive impairment [MCI], and 633 with AD). The occupancy indices for each regional volume were calculated by dividing each volume by the size of the lateral and inferior ventricular volumes. MR images from 355 participants (119 CN, 119 MCI, and 117 AD) from three different centers were used for validation. Two neuroradiologists performed visual assessments of the medial temporal, posterior, and global cortical atrophy scores in the frontal lobe using T1-weighted MR images. Images were also analyzed using the deep learning-based segmentation software, Neurophet AQUA. Cutoff values for the three scores were determined using the data distribution according to age. The scoring results were compared for consistency and reliability.

Results

Four volumetric-driven scoring results showed a high correlation with the visual scoring results for AD, MCI, and CN. The overall agreement with human raters was weak-to-moderate for atrophy scoring in CN participants, and good-to-almost perfect in AD and MCI participants. AD subtyping by automated scores also showed usefulness as a research tool.

Conclusions

Determining AD subtypes using automated atrophy scoring for late-MCI and AD could be useful in clinical settings or multicenter studies with large datasets.

Statin Use and All-Cause Mortality in Nursing Home Residents With and Without Dementia: A Retrospective Cohort Study Using Claims Data

BACKGROUND AND OBJECTIVES

Little is known about the benefits of statin therapy in older adults with dementia. We aimed to evaluate the role of statin use for all-cause mortality in nursing home residents with and without dementia.

METHODS

This retrospective cohort study used claims data collected between January 2015 and December 2019 from a German health and long-term care insurance provider. Propensity score-based Cox proportional hazards models were used to evaluate the association of statin use with all-cause mortality and adjusted for potential confounders in nursing home residents. Subgroup analyses were performed based on the presence or absence of atherosclerotic cardiovascular disease (ASCVD), statin intensity (low, moderate, high), dementia type, age, sex, and level of care required.

RESULTS

A total of 282,693 participants were included in the study, of which 96,162 were matched. In total, 68.9% were women, and the mean age was 82.91 years (SD ±7.97). The average observation period was 2.25 years (SD ±1.35), and 54,269 deaths were recorded. Statin use in individuals with dementia resulted in lower all-cause mortality (hazard ratio [HR] 0.80, 95% CI 0.78-0.82, p < 0.001) compared with statin nonusers. Similarly, in individuals without dementia, statin use was associated with lower all-cause mortality (HR 0.73, 95% CI 0.71-0.76, p < 0.001) compared with statin nonusers. Similar findings were observed in subanalyses excluding participants with a history of ASCVD and across subgroups stratified by age, sex, care level required, and dementia type. Statin benefits were consistent among individuals with and without dementia.

DISCUSSION

Statin benefits were consistent among individuals with and without dementia. Statin therapy may be continued in nursing home residents with dementia to mitigate the risk of all-cause mortality.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that nursing home patients receiving statins have a lower mortality rate, whether they have a dementia diagnosis or not.

Contributions of amyloid beta and cerebral small vessel disease in clinical decline

INTRODUCTION

We assessed whether co-morbid small vessel disease (SVD) has clinical predictive value in preclinical or prodromal Alzheimer's disease.

METHODS

In 1090 non-demented participants (65.4 ± 10.7 years) SVD was assessed with magnetic resonance imaging and amyloid beta (Aβ) with lumbar puncture and/or positron emission tomography scan (mean follow-up for cognitive function 3.1 ± 2.4 years).

RESULTS

Thirty-nine percent had neither Aβ nor SVD (A-V-), 21% had SVD only (A-V+), 23% Aβ only (A+V-), and 17% had both (A+V+). Pooled cohort linear mixed model analyses demonstrated that compared to A-V- (reference), A+V- had a faster rate of cognitive decline. Co-morbid SVD (A+V+) did not further increase rate of decline. Cox regression showed that dementia risk was modestly increased in A-V+ (hazard ratio [95% confidence interval: 1.8 [1.0-3.2]) and most strongly in A+ groups. Also, mortality risk was increased in A+ groups.

DISCUSSION

In non-demented persons Aβ was predictive of cognitive decline, dementia, and mortality. SVD modestly predicts dementia in A-, but did not increase deleterious effects in A+.

HIGHLIGHTS

Amyloid beta (Aβ; A) was predictive for cognitive decline, dementia, and mortality. Small vessel disease (SVD) had no additional deleterious effects in A+. SVD modestly predicted dementia in A-. Aβ should be assessed even when magnetic resonance imaging indicates vascular cognitive impairment.

Deep learning applications in vascular dementia using neuroimaging

PURPOSE OF REVIEW

Vascular dementia (VaD) is the second common cause of dementia after Alzheimer's disease, and deep learning has emerged as a critical tool in dementia research. The aim of this article is to highlight the current deep learning applications in VaD-related imaging biomarkers and diagnosis.

RECENT FINDINGS

The main deep learning technology applied in VaD using neuroimaging data is convolutional neural networks (CNN). CNN models have been widely used for lesion detection and segmentation, such as white matter hyperintensities (WMH), cerebral microbleeds (CMBs), perivascular spaces (PVS), lacunes, cortical superficial siderosis, and brain atrophy. Applications in VaD subtypes classification also showed excellent results. CNN-based deep learning models have potential for further diagnosis and prognosis of VaD.

SUMMARY

Deep learning neural networks with neuroimaging data in VaD research represent significant promise for advancing early diagnosis and treatment strategies. Ongoing research and collaboration between clinicians, data scientists, and neuroimaging experts are essential to address challenges and unlock the full potential of deep learning in VaD diagnosis and management.

Alzheimer's Disease in Lebanon: Exploring Genetic and Environmental Risk Factors-A Comprehensive Review

Alzheimer's disease (AD) is a neurodegenerative condition that displays a high prevalence in Lebanon causing a local burden in healthcare and socio-economic sectors. Unfortunately, the lack of prevalence studies and clinical trials in Lebanon minimizes the improvement of AD patient health status. In this review, we include over 155 articles to cover the different aspects of AD ranging from mechanisms to possible treatment and management tools. We highlight some important modifiable and non-modifiable risk factors of the disease including genetics, age, cardiovascular diseases, smoking, etc. Finally, we propose a hypothetical genetic synergy model between APOE4 and TREM2 genes which constitutes a potential early diagnostic tool that helps in reducing the risk of AD based on preventative measures decades before cognitive decline. The studies on AD in Lebanon and the Middle East are scarce. This review points out the importance of genetic mapping in the understanding of disease pathology which is crucial for the emergence of novel diagnostic tools. Hence, we establish a rigid basis for further research to identify the most influential genetic and environmental risk factors for the purpose of using more specific diagnostic tools and possibly adopting a local management protocol.

A Chronic Increase in Blood-Brain Barrier Permeability Facilitates Intraneuronal Deposition of Exogenous Bloodborne Amyloid-Beta1-42 Peptide in the Brain and Leads to Alzheimer's Disease-Relevant Cognitive Changes in a Mouse Model

Background

Increased blood-brain barrier (BBB) permeability and amyloid-β (Aβ) peptides (especially Aβ1-42) (Aβ42) have been linked to Alzheimer's disease (AD) pathogenesis, but the nature of their involvement in AD-related neuropathological changes leading to cognitive changes remains poorly understood.

Objective

To test the hypothesis that chronic extravasation of bloodborne Aβ42 peptide and brain-reactive autoantibodies and their entry into the brain parenchyma via a permeable BBB contribute to AD-related pathological changes and cognitive changes in a mouse model.

Methods

The BBB was rendered chronically permeable through repeated injections of Pertussis toxin (PT), and soluble monomeric, fluorescein isothiocyanate (FITC)-labeled or unlabeled Aβ42 was injected into the tail-vein of 10-month-old male CD1 mice at designated intervals spanning ∼3 months. Acquisition of learned behaviors and long-term retention were assessed via a battery of cognitive and behavioral tests and linked to neuropathological changes.

Results

Mice injected with both PT and Aβ42 demonstrated a preferential deficit in the capacity for long-term retention and an increased susceptibility to interference in selective attention compared to mice exposed to PT or saline only. Immunohistochemical analyses revealed increased BBB permeability and entry of bloodborne Aβ42 and immunoglobulin G (IgG) into the brain parenchyma, selective neuronal binding of IgG and neuronal accumulation of Aβ42 in animals injected with both PT and Aβ42 compared to controls.

Conclusion

Results highlight the potential synergistic role of BBB compromise and the influx of bloodborne Aβ42 into the brain in both the initiation and progression of neuropathologic and cognitive changes associated with AD.

Assessment of Four Serum Biochemical Markers in Elderly Patients with Vascular Dementia after Cerebral Infarction and Their Response to Donepezil and Idebenone

Objective  Our study aimed to explore four serum levels of biochemical markers, including brain-derived neurotrophic factor (BDNF), homocysteine (Hcy), nitric oxide (NO), and γ-interferon (IFN-γ), in elderly patients with vascular dementia (VD) after the cerebral infarction and to elucidate possible connections between them. Method  The elderly patients with VD after cerebral infarction admitted in our hospital, and the elderly persons for physical examination from November 2020 to December 2021 were included in this study. The serum levels of BDNF, Hcy, NO, and IFN-γ were compared between the study group and the control group. Results  In the study group, the serum levels of Hcy and IFN-γ were significantly higher than that in the control group, whereas significantly lower serum levels of BDNF and NO were found in the study group compared with the control group. After receiving the intervention of donepezil and/or idebenone, the serum levels of Hcy and IFN-γ in group B were significantly lower than that in group A, while the serum levels of BDNF and NO in group B were significantly higher than that in Group A. Conclusion  The results of our study showed abnormally expressed serum levels of Hcy, IFN-γ, BDNF, and NO in elderly patients with VD after cerebral infarction which might strongly reflect the severity of VD. Moreover, after intervention of donepezil alone or combined with idebenone, the changes of serum levels of Hcy, IFN-γ, BDNF, and NO may reflect the curative effect of the disease.

Using digital assessment technology to detect neuropsychological problems in primary care settings

Introduction

Screening for neurocognitive impairment and psychological distress in ambulatory primary and specialty care medical settings is an increasing necessity. The Core Cognitive Evaluation™ (CCE) is administered/scored using an iPad, requires approximately 8 min, assesses 3- word free recall and clock drawing to command and copy, asks questions about lifestyle and health, and queries for psychological distress. This information is linked with patients' self- reported concerns about memory and their cardiovascular risks.

Methods

A total of 199 ambulatory patients were screened with the CCE as part of their routine medical care. The CCE provides several summary indices, and scores on 44 individual digital clock variables across command and copy tests conditions.

Results

Subjective memory concerns were endorsed by 41% of participants. Approximately 31% of participants reported psychological distress involving loneliness, anxiety, or depression. Patients with self-reported memory concerns scored lower on a combined delay 3- word/ clock drawing index (p < 0.016), the total summary clock drawing command/ copy score (p < 0.050), and clock drawing to command Drawing Efficiency (p < 0.036) and Simple and Complex Motor (p < 0.029) indices. Patients treated for diabetes and atherosclerotic cardiovascular disease (ASCVD) scored lower on selected CCE outcome measures (p < 0.035). Factor analyses suggest that approximately 10 underlying variables can explain digital clock drawing performance.

Discussion

The CCE is a powerful neurocognitive assessment tool that is sensitive to patient's subjective concerns about possible decline in memory, mood symptoms, possible cognitive impairment, and cardiovascular risk. iPad administration ensures total reliability for test administration and scoring. The CCE is easily deployable in outpatient ambulatory primary care settings.

A common spectrum underlying brain disorders across lifespan revealed by deep learning on brain networks

Brain disorders in the early and late life of humans potentially share pathological alterations in brain functions. However, the key neuroimaging evidence remains unrevealed for elucidating such commonness and the relationships among these disorders. To explore this puzzle, we build a restricted single-branch deep learning model, using multi-site functional magnetic resonance imaging data (N = 4,410, 6 sites), for classifying 5 different early- and late-life brain disorders from healthy controls (cognitively unimpaired). Our model achieves 62.6 ± 1.9% overall classification accuracy and thus supports us in detecting a set of commonly affected functional subnetworks, including default mode, executive control, visual, and limbic networks. In the deep-layer representation of data, we observe young and aging patients with disorders are continuously distributed, which is in line with the clinical concept of the "spectrum of disorders." The relationships among brain disorders from the revealed spectrum promote the understanding of disorder comorbidities and time associations in the lifespan.

Neuropsychological differential diagnosis of Alzheimer's disease and vascular dementia: a systematic review with meta-regressions

Introduction

Diagnostic classification systems and guidelines posit distinguishing patterns of impairment in Alzheimer's (AD) and vascular dementia (VaD). In our study, we aim to identify which diagnostic instruments distinguish them.

Methods

We searched PubMed and PsychInfo for empirical studies published until December 2020, which investigated differences in cognitive, behavioral, psychiatric, and functional measures in patients older than 64 years and reported information on VaD subtype, age, education, dementia severity, and proportion of women. We systematically reviewed these studies and conducted Bayesian hierarchical meta-regressions to quantify the evidence for differences using the Bayes factor (BF). The risk of bias was assessed using the Newcastle-Ottawa-Scale and funnel plots.

Results

We identified 122 studies with 17,850 AD and 5,247 VaD patients. Methodological limitations of the included studies are low comparability of patient groups and an untransparent patient selection process. In the digit span backward task, AD patients were nine times more probable (BF = 9.38) to outperform VaD patients (β g = 0.33, 95% ETI = 0.12, 0.52). In the phonemic fluency task, AD patients outperformed subcortical VaD (sVaD) patients (β g = 0.51, 95% ETI = 0.22, 0.77, BF = 42.36). VaD patients, in contrast, outperformed AD patients in verbal (β g = -0.61, 95% ETI = -0.97, -0.26, BF = 22.71) and visual (β g = -0.85, 95% ETI = -1.29, -0.32, BF = 13.67) delayed recall. We found the greatest difference in verbal memory, showing that sVaD patients outperform AD patients (β g = -0.64, 95% ETI = -0.88, -0.36, BF = 72.97). Finally, AD patients performed worse than sVaD patients in recognition memory tasks (β g = -0.76, 95% ETI = -1.26, -0.26, BF = 11.50).

Conclusion

Our findings show inferior performance of AD in episodic memory and superior performance in working memory. We found little support for other differences proposed by diagnostic systems and diagnostic guidelines. The utility of cognitive, behavioral, psychiatric, and functional measures in differential diagnosis is limited and should be complemented by other information. Finally, we identify research areas and avenues, which could significantly improve the diagnostic value of cognitive measures.

Genetic Evidence for Causal Association Between Atrial Fibrillation and Dementia: A Mendelian Randomization Study

Background The knowledge gap regarding whether the correlation between atrial fibrillation (AF) and dementia in observational studies is causation or driven by other shared risk factors remains substantially unfilled. Methods and Results We performed a comprehensive 2-sample Mendelian randomization study to evaluate the causal effect of AF on overall dementia and its subtypes, including vascular dementia, Alzheimer dementia, Lewy body dementia, and frontotemporal dementia. The primary results in inverse variance-weighted analyses were further validated by various Mendelian randomization sensitivity analyses. Additionally, we conducted multivariable Mendelian randomization to examine 10 candidate mediators of the causal association of AF and dementia. Genetic predisposition to AF was modestly associated with an increased risk of overall dementia (odds ratio, 1.140 [95% CI, 1.023-1.271]; P=0.018) and strongly associated with vascular dementia (odds ratio, 1.350 [95% CI, 1.076-1.695]; P=0.010). Genetically predicted AF indicated neutral effects on Alzheimer dementia, Lewy body dementia, and frontotemporal dementia. In multivariable Mendelian randomization analysis, the total effect of AF on overall dementia was remarkably attenuated by adjusting for genetic effect for ischemic stroke (odds ratio, 1.068 [95% CI, 0.953-1.197]; P=0.259) and low cardiac output (odds ratio, 1.046 [95% CI, 0.926-1.181]; P=0.475), indicating that the causal association of genetically predicted AF with dementia was potentially mediated by ischemic stroke and low cardiac output. The causal effect of genetically predicted AF on dementia was independent of cerebral small-vessel disease and brain volume phenotypes. Conclusions Our findings provided novel evidence supporting the causal effect of genetically predicted AF on dementia mediated by ischemic stroke and low cardiac output. Future clinical trials are warranted to evaluate the potential role of appropriate AF management in dementia prevention.

Turning the Spotlight to Cholinergic Pharmacotherapy of the Human Language System

Even though language is essential in human communication, research on pharmacological therapies for language deficits in highly prevalent neurodegenerative and vascular brain diseases has received little attention. Emerging scientific evidence suggests that disruption of the cholinergic system may play an essential role in language deficits associated with Alzheimer's disease and vascular cognitive impairment, including post-stroke aphasia. Therefore, current models of cognitive processing are beginning to appraise the implications of the brain modulator acetylcholine in human language functions. Future work should be directed further to analyze the interplay between the cholinergic system and language, focusing on identifying brain regions receiving cholinergic innervation susceptible to modulation with pharmacotherapy to improve affected language domains. The evaluation of language deficits in pharmacological cholinergic trials for Alzheimer's disease and vascular cognitive impairment has thus far been limited to coarse-grained methods. More precise, fine-grained language testing is needed to refine patient selection for pharmacotherapy to detect subtle deficits in the initial phases of cognitive decline. Additionally, noninvasive biomarkers can help identify cholinergic depletion. However, despite the investigation of cholinergic treatment for language deficits in Alzheimer's disease and vascular cognitive impairment, data on its effectiveness are insufficient and controversial. In the case of post-stroke aphasia, cholinergic agents are showing promise, particularly when combined with speech-language therapy to promote trained-dependent neural plasticity. Future research should explore the potential benefits of cholinergic pharmacotherapy in language deficits and investigate optimal strategies for combining these agents with other therapeutic approaches.

Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands

The clock drawing test is a simple and inexpensive method to screen for cognitive frailties, including dementia. In this study, we used the relevance factor variational autoencoder (RF-VAE), a deep generative neural network, to represent digitized clock drawings from multiple institutions using an optimal number of disentangled latent factors. The model identified unique constructional features of clock drawings in a completely unsupervised manner. These factors were examined by domain experts to be novel and not extensively examined in prior research. The features were informative, as they distinguished dementia from non-dementia patients with an area under receiver operating characteristic (AUC) of 0.86 singly, and 0.96 when combined with participants' demographics. The correlation network of the features depicted the "typical dementia clock" as having a small size, a non-circular or "avocado-like" shape, and incorrectly placed hands. In summary, we report a RF-VAE network whose latent space encoded novel constructional features of clocks that classify dementia from non-dementia patients with high performance.

Endothelial Dysfunction in Neurodegenerative Diseases

The cerebral vascular system stringently regulates cerebral blood flow (CBF). The components of the blood-brain barrier (BBB) protect the brain from pathogenic infections and harmful substances, efflux waste, and exchange substances; however, diseases develop in cases of blood vessel injuries and BBB dysregulation. Vascular pathology is concurrent with the mechanisms underlying aging, Alzheimer's disease (AD), and vascular dementia (VaD), which suggests its involvement in these mechanisms. Therefore, in the present study, we reviewed the role of vascular dysfunction in aging and neurodegenerative diseases, particularly AD and VaD. During the development of the aforementioned diseases, changes occur in the cerebral blood vessel morphology and local cells, which, in turn, alter CBF, fluid dynamics, and vascular integrity. Chronic vascular inflammation and blood vessel dysregulation further exacerbate vascular dysfunction. Multitudinous pathogenic processes affect the cerebrovascular system, whose dysfunction causes cognitive impairment. Knowledge regarding the pathophysiology of vascular dysfunction in neurodegenerative diseases and the underlying molecular mechanisms may lead to the discovery of clinically relevant vascular biomarkers, which may facilitate vascular imaging for disease prevention and treatment.

Neurocognitive Operations Underlying Working Memory Abilities: An Analysis of Latency and Time-Based Parameters

BACKGROUND

The theory of executive attention (Fuster, 2015) suggests considerable plasticity regarding when specific neurocognitive operations are recruited to bring executive tasks to fruition.

OBJECTIVE

We tested the hypothesis that differing neurocognitive operations are recruited upon the initiation of a response, but that other distinct neurocognitive operations are recruited towards the middle or end of a response.

METHODS

The Backward Digit Span Test (BDST) was administered to 58 memory clinic patients (MCI, n = 22; no-MCI, n = 36). Latency to generate all correct 5-span responses was obtained. Statistical analyses found that optimal group classification was achieved using the first and third digit backward. First and third response latencies were analyzed in relation to verbal working memory (WM), visual WM, processing speed, visuospatial operations, naming/lexical access, and verbal episodic memory tests.

RESULTS

For the first response, slower latencies were associated with better performance in relation to verbal WM and visuospatial test performance. For the third response, faster latencies were associated with better processing speed and visuospatial test performance.

CONCLUSION

Consistent with the theory of executive attention, these data show that the neurocognitive operations underlying successful executive test performance are not monolithic but can be quite nuanced with differing neurocognitive operations associated with specific time epochs. Results support the efficacy of obtaining time-based latency parameters to help disambiguate successful executive neurocognitive operations in memory clinic patients.

Midlife Neuropsychological Profiles and Associated Vascular Risk: The Bogalusa Heart Study

BACKGROUND

Individuals with Alzheimer's disease (AD) often present with coexisting vascular pathology that is expressed to different degrees and can lead to clinical heterogeneity.

OBJECTIVE

To examine the utility of unsupervised statistical clustering approaches in identifying neuropsychological (NP) test performance subtypes that closely correlate with carotid intima-media thickness (cIMT) in midlife.

METHODS

A hierarchical agglomerative and k-means clustering analysis based on NP scores (standardized for age, sex, and race) was conducted among 1,203 participants (age 48±5.3 years) from the Bogalusa Heart Study. Regression models assessed the association between cIMT ≥50th percentile and NP profiles, and global cognitive score (GCS) tertiles for sensitivity analysis.

RESULTS

Three NP profiles were identified: Mixed-low performance [16%, n = 192], scores ≥1 SD below the mean on immediate, delayed free recall, recognition verbal memory, and information processing; Average [59%, n = 704]; and Optimal [26%, n = 307] NP performance. Participants with greater cIMT were more likely to have a Mixed-low profile [OR = 3.10, 95% CI (2.13, 4.53), p < 0.001] compared to Optimal. After adjusting for education and cardiovascular (CV) risks, results remained. The association with GCS tertiles was more attenuated [lowest (34%, n = 407) versus highest (33%, n = 403) tertile: adjusted OR = 1.66, 95% CI (1.07, 2.60), p = 0.024].

CONCLUSION

As early as midlife, individuals with higher subclinical atherosclerosis were more likely to be in the Mixed-low profile, underscoring the potential malignancy of CV risk as related to NP test performance, suggesting that classification approaches may aid in identifying those at risk for AD/vascular dementia spectrum illness.

The Ties That Bind: Glial Transplantation in White Matter Ischemia and Vascular Dementia

White matter injury is a progressive vascular disease that leads to neurological deficits and vascular dementia. It comprises up to 30% of all diagnosed strokes, though up to ten times as many events go undiagnosed in early stages. There are several pathologies that can lead to white matter injury. While some studies suggest that white matter injury starts as small infarcts in deep penetrating blood vessels in the brain, others point to the breakdown of endothelial function or the blood-brain barrier as the primary cause of the disease. Whether due to local endothelial or BBB dysfunction, or to local small infarcts (or a combination), white matter injury progresses, accumulates, and expands from preexisting lesions into adjacent white matter to produce motor and cognitive deficits that present as vascular dementia in the elderly. Vascular dementia is the second leading cause of dementia, and white matter injury-attributed vascular dementia represents 40% of all diagnosed dementias and aggravates Alzheimer's pathology. Despite the advances in the last 15 years, there are few animal models of progressive subcortical white matter injury or vascular dementia. This review will discuss recent progress in animal modeling of white matter injury and the emerging principles to enhance glial function as a means of promoting repair and recovery.

Frequency and Underlying Pathology of Pure Vascular Cognitive Impairment

Importance

It is not clear how common pure vascular cognitive impairment (VCI) is in the absence of Alzheimer disease (AD) and/or other neurodegenerative pathologies.

Objective

To identify participants without AD and other neurodegenerative pathologies and determine the extent to which cerebrovascular disease pathologies were associated with cognitive impairment.

Design, Setting, and Participants

This clinical pathological study included participants from 2 ongoing community-based cohorts that began enrollment in 1994 and 1997. Prior to death, participants were observed for a mean (SD) of 8.4 (5.3) years with annual assessments. From 2096 participants who died, 1799 (85.8%) underwent autopsy and 1767 had complete postmortem pathological examination data at the time of data analyses. To identify participants without neurodegenerative pathologies, we categorized them in 3 subgroups. A vascular subgroup was composed of participants without significant levels of neurodegenerative brain pathologies. A neurodegenerative subgroup was composed of participants without significant levels of cerebrovascular disease pathologies. A mixed subgroup was composed of the rest of the participants. Data were analyzed from May 2021 to July 2022.

Exposures

Brain pathology indices obtained by postmortem pathological assessments.

Main Outcomes and Measures

The primary outcome was cognitive impairment defined by presence of mild cognitive impairment or dementia. The secondary outcome was cognition assessed by 19 neuropsychological tests.

Results

Of 1767 included participants, 1189 (67.3%) were women, and the mean (SD) age at death was 89.4 (6.6) years. In the vascular subgroup (n = 369), cognitive impairment was present in 156 participants (42.3%) and was associated with cerebrovascular disease pathologies (macroinfarcts: odds ratio [OR], 2.05; 95% CI, 1.49-2.82; P < .001; arteriolosclerosis in basal ganglia: OR, 1.35; 95% CI, 1.04-1.76; P = .03) but not AD or other neurodegenerative pathologies, an indication of pure VCI. In mixed-effects models including all the pathologies, only macroinfarcts were associated with a faster cognitive decline rate (estimate, -0.019; SE, 0.005; P < .001) in the vascular subgroup. Further analyses identified macroinfarcts in the frontal white matter to be associated with faster cognitive decline rate when macroinfarcts of cortical and subcortical brain regions were examined in a single model.

Conclusions and Relevance

In this study, pure VCI was not rare. Macroinfarcts, specifically in frontal white matter, were the main cerebrovascular disease pathologies associated with cognitive decline in pure VCI.

Neurodegenerative Diseases: Implications of Environmental and Climatic Influences on Neurotransmitters and Neuronal Hormones Activities

Neurodegenerative and neuronal-related diseases are major public health concerns. Human vulnerability to neurodegenerative diseases (NDDs) increases with age. Neuronal hormones and neurotransmitters are major determinant factors regulating brain structure and functions. The implications of environmental and climatic changes emerged recently as influence factors on numerous diseases. However, the complex interaction of neurotransmitters and neuronal hormones and their depletion under environmental and climatic influences on NDDs are not well established in the literature. In this review, we aim to explore the connection between the environmental and climatic factors to NDDs and to highlight the available and potential therapeutic interventions that could use to improve the quality of life and reduce susceptibility to NDDs.

APOE in the bullseye of neurodegenerative diseases: impact of the APOE genotype in Alzheimer’s disease pathology and brain diseases

ApoE is the major lipid and cholesterol carrier in the CNS. There are three major human polymorphisms, apoE2, apoE3, and apoE4, and the genetic expression of APOE4 is one of the most influential risk factors for the development of late-onset Alzheimer's disease (AD). Neuroinflammation has become the third hallmark of AD, together with Amyloid-β plaques and neurofibrillary tangles of hyperphosphorylated aggregated tau protein. This review aims to broadly and extensively describe the differential aspects concerning apoE. Starting from the evolution of apoE to how APOE's single-nucleotide polymorphisms affect its structure, function, and involvement during health and disease. This review reflects on how APOE's polymorphisms impact critical aspects of AD pathology, such as the neuroinflammatory response, particularly the effect of APOE on astrocytic and microglial function and microglial dynamics, synaptic function, amyloid-β load, tau pathology, autophagy, and cell–cell communication. We discuss influential factors affecting AD pathology combined with the APOE genotype, such as sex, age, diet, physical exercise, current therapies and clinical trials in the AD field. The impact of the APOE genotype in other neurodegenerative diseases characterized by overt inflammation, e.g., alpha- synucleinopathies and Parkinson's disease, traumatic brain injury, stroke, amyotrophic lateral sclerosis, and multiple sclerosis, is also addressed. Therefore, this review gathers the most relevant findings related to the APOE genotype up to date and its implications on AD and CNS pathologies to provide a deeper understanding of the knowledge in the APOE field.

Shared Risk Factors between Dementia and Atherosclerotic Cardiovascular Disease

Alzheimer’s disease is the most common form of dementia, and the prodromal phases of Alzheimer’s disease can last for decades. Vascular dementia is the second most common form of dementia and is distinguished from Alzheimer’s disease by evidence of previous stroke or hemorrhage and current cerebrovascular disease. A compiled group of vascular-related dementias (vascular dementia and unspecified dementia) is often referred to as non-Alzheimer dementia. Recent evidence indicates that preventing dementia by lifestyle interventions early in life with a focus on reducing cardiovascular risk factors is a promising strategy for reducing future risk. Approximately 40% of dementia cases is estimated to be preventable by targeting modifiable, primarily cardiovascular risk factors. The aim of this review is to describe the association between risk factors for atherosclerotic cardiovascular disease and the risk of Alzheimer’s disease and non-Alzheimer dementia by providing an overview of the current evidence and to shed light on possible shared pathogenic pathways between dementia and cardiovascular disease. The included risk factors are body mass index (BMI); plasma triglyceride-, high-density lipoprotein (HDL) cholesterol-, low-density lipoprotein (LDL) cholesterol-, and total cholesterol concentrations; hypertension; diabetes; non-alcoholic fatty liver disease (NAFLD); physical inactivity; smoking; diet; the gut microbiome; and genetics. Furthermore, we aim to disentangle the difference between associations of risk factors in midlife as compared with in late life.

Statins and cognition: Modifying factors and possible underlying mechanisms

Statins are a class of widely prescribed drugs used to reduce low-density lipoprotein cholesterol (LDL-C) and important to prevent cardiovascular diseases (CVD). Most statin users are older adults with CVD, who are also at high risk of cognitive decline. It has been suggested that statins can alter cognitive performance, although their positive or negative effects are still debated. With more than 200 million people on statin therapy worldwide, it is crucial to understand the reasons behind discrepancies in the results of these studies. Here, we review the effects of statins on cognitive function and their association with different etiologies of dementia, and particularly, Alzheimer’s disease (AD). First, we summarized the main individual and statin-related factors that could modify the cognitive effects of statins. Second, we proposed the underlying mechanisms for the protective and adverse effects of statins on cognitive performance. Finally, we discussed potential causes of discrepancies between studies and suggested approaches to improve future studies assessing the impact of statins on dementia risk and cognitive function.

Development and validation of the age-associated dementia policy (AgeD-Pol) computer simulation model in the USA and Europe

OBJECTIVE

To develop and validate a novel, microsimulation model that accounts for the prevalence and incidence of age-associated dementias (AAD), disease progression and associated mortality.

DESIGN, DATA SOURCES AND OUTCOME MEASURES

We developed the AAD policy (AgeD-Pol) model, a microsimulation model to simulate the natural history, morbidity and mortality associated with AAD. We populated the model with age-stratified and sex-stratified data on AAD prevalence, AAD incidence and mortality among people with AAD. We first performed internal validation using data from the Adult Changes in Thought (ACT) cohort study. We then performed external validation of the model using data from the Framingham Heart Study, the Rotterdam Study and Kaiser Permanente Northern California (KPNC). We compared model-projected AAD cumulative incidence and mortality with published cohort data using mean absolute percentage error (MAPE) and root-mean-square error (RMSE).

RESULTS

In internal validation, the AgeD-Pol model provided a good fit to the ACT cohort for cumulative AAD incidence, 10.4% (MAPE, 0.2%) and survival, 66.5% (MAPE, 8.8%), after 16 years of follow-up among those initially aged 65-69 years. In the external validations, the model-projected lifetime cumulative incidence of AAD was 30.5%-32.4% (females) and 16.7%-23.0% (males), using data from the Framingham and Rotterdam cohorts, and AAD cumulative incidence was 21.5% over 14 years using KPNC data. Model projections demonstrated a good fit to all three cohorts (MAPE, 0.9%-9.0%). Similarly, model-projected survival provided good fit to the Rotterdam (RMSE, 1.9-3.6 among those with and without AAD) and KPNC cohorts (RMSE, 7.6-18.0 among those with AAD).

CONCLUSIONS

The AgeD-Pol model performed well when validated to published data for AAD cumulative incidence and mortality and provides a useful tool to project the AAD disease burden for health systems planning in the USA.

Hypertension and cognitive function: a review of life-course factors and disparities

PURPOSE OF REVIEW

Dementia is a life-course condition with modifiable risk factors many from cardiovascular (CV) origin, and disproportionally affects some race/ethnic groups and underserved communities in the USA. Hypertension (HTN) is the most common preventable and treatable condition that increases the risk for dementia and exacerbates dementia pathology. Epidemiological studies beginning in midlife provide strong evidence for this association. This study provides an overview of the differences in the associations across the lifespan, and the role of social determinants of health (SDoH).

RECENT FINDINGS

Clinical trials support HTN management in midlife as an avenue to lower the risk for late-life cognitive decline. However, the association between HTN and cognition differs over the life course. SDoH including higher education modify the association between HTN and cognition which may differ by race and ethnicity. The role of blood pressure (BP) variability, interactions among CV risk factors, and cognitive assessment modalities may provide information to better understand the relationship between HTN and cognition.

SUMMARY

Adopting a life-course approach that considers SDoH, may help develop tailored interventions to manage HTN and prevent dementia syndromes. Where clinical trials to assess BP management from childhood to late-life are not feasible, observational studies remain the best available evidence.

The Influence of Cerebrovascular Pathology on Cluster Analysis of Neuropsychological Scores in Patients With Mild Cognitive Impairment

OBJECTIVES

The diagnostic entity of mild cognitive impairment (MCI) is heterogeneous, highlighting the need for data-driven classification approaches to identify patient subgroups. However, these approaches can be strongly determined by sample characteristics and selected measures. Here, we applied a cluster analysis to an MCI patient database from a neuropsychology clinic to determine whether the inclusion of patients with MCI with vascular pathology would result in a different classification of subgroups.

METHODS

Participants diagnosed with MCI (n = 166), vascular cognitive impairment-no dementia (n = 26), and a group of older adults with subjective cognitive concerns but no objective impairment (n = 144) were assessed using a full neuropsychological battery and other clinical measures. Cognitive measures were analyzed using a hierarchical cluster analysis and then a k-means approach, with resulting clusters compared on a range of demographic and clinical variables.

RESULTS

We found a 4-factor solution: a cognitively intact cluster, a globally impaired cluster, an amnestic/visuospatial impairment cluster, and a mild, mixed-domain cluster. Interestingly, group differences in self-reported multilingualism emerged in the derived clusters that were not observed when comparing diagnostic groups.

CONCLUSIONS

Our results were generally consistent with previous studies using cluster analysis in MCI. Including patients with primarily cerebrovascular disease resulted in subtle differences in the derived clusters and revealed new insights into shared cognitive profiles of patients beyond diagnostic categories. These profiles should be further explored to develop individualized assessment and treatment approaches.

Characterization of Retinal Drusen in Subjects at High Genetic Risk of Developing Sporadic Alzheimer’s Disease: An Exploratory Analysis

Having a family history (FH+) of Alzheimer’s disease (AD) and being a carrier of at least one ɛ4 allele of the ApoE gene are two of the main risk factors for the development of AD. AD and age-related macular degeneration (AMD) share one of the main risk factors, such as age, and characteristics including the presence of deposits (Aβ plaques in AD and drusen in AMD); however, the role of apolipoprotein E isoforms in both pathologies is controversial. We analyzed and characterized retinal drusen by optical coherence tomography (OCT) in subjects, classifying them by their AD FH (FH- or FH+) and their allelic characterization of ApoE ɛ4 (ApoE ɛ4- or ApoE ɛ4+) and considering cardiovascular risk factors (hypercholesterolemia, hypertension, and diabetes mellitus). In addition, we analyzed the choroidal thickness by OCT and the area of the foveal avascular zone with OCTA. We did not find a relationship between a family history of AD or any of the ApoE isoforms and the presence or absence of drusen. Subjects with drusen show choroidal thinning compared to patients without drusen, and thinning could trigger changes in choroidal perfusion that may give rise to the deposits that generate drusen.

Variational autoencoder provides proof of concept that compressing CDT to extremely low-dimensional space retains its ability of distinguishing dementia

The clock drawing test (CDT) is an inexpensive tool to screen for dementia. In this study, we examined if a variational autoencoder (VAE) with only two latent variables can capture and encode clock drawing anomalies from a large dataset of unannotated CDTs (n = 13,580) using self-supervised pre-training and use them to classify dementia CDTs (n = 18) from non-dementia CDTs (n = 20). The model was independently validated using a larger cohort consisting of 41 dementia and 50 non-dementia clocks. The classification model built with the parsimonious VAE latent space adequately classified dementia from non-dementia (0.78 area under receiver operating characteristics (AUROC) in the original test dataset and 0.77 AUROC in the secondary validation dataset). The VAE-identified atypical clock features were then reviewed by domain experts and compared with existing literature on clock drawing errors. This study shows that a very small number of latent variables are sufficient to encode important clock drawing anomalies that are predictive of dementia.

Addressing Blood–Brain Barrier Impairment in Alzheimer’s Disease

The blood–brain barrier (BBB) plays a vital role in maintaining the specialized microenvironment of the brain tissue. It facilitates communication while separating the peripheral circulation system from the brain parenchyma. However, normal aging and neurodegenerative diseases can alter and damage the physiological properties of the BBB. In this review, we first briefly present the essential pathways maintaining and regulating BBB integrity, and further review the mechanisms of BBB breakdown associated with normal aging and peripheral inflammation-causing neurodegeneration and cognitive impairments. We also discuss how BBB disruption can cause or contribute to Alzheimer’s disease (AD), the most common form of dementia and a devastating neurological disorder. Next, we document overlaps between AD and vascular dementia (VaD) and briefly sum up the techniques for identifying biomarkers linked to BBB deterioration. Finally, we conclude that BBB breakdown could be used as a biomarker to help diagnose cognitive impairment associated with normal aging and neurodegenerative diseases such as AD.

Carotid Intima-media Thickness and Midlife Cognitive Function: Impact of Race and Social Disparities in the Bogalusa Heart Study

BACKGROUND AND OBJECTIVE

Carotid intima-media thickness (c-IMT) is a measurement of atherosclerosis, a progressive disease that develops as early as childhood and has been linked with cognitive impairment and dementia in the elderly. However, the relationship between c-IMT and midlife cognitive function as well as race and social disparities on this relationship remains unclear. We examined the association between c-IMT and cognitive function in midlife among Black and White participants from a semi-rural community-based cohort in Bogalusa, Louisiana.

METHODS

In this cross-sectional analysis of participants from the Bogalusa Heart Study, linear regression models were used to determine the association between c-IMT dichotomized above the 50^th percentile (> 0.87mm), an a demographically standardized global cognitive (GCS) and individual cognitive domain-based z-scores. Stratified analyses were performed to evaluate the impact of race and the individual's education status.

RESULTS

A total of 1,217 participants (age 48 ± 5.28 years) were included, 66% (804) self-identified as White and 34% (413) as Black. Of those, 58% (708) were women, and 42% (509) were men Having a c-IMT > 50^th percentile was inversely associated with GCS ([B ± SE]: -0.39 ± 0.18, P=0.03), independent of cardiovascular risk factors (CVRFs) and achieved education. The effect remained significant in Black and White participants after adjustment for CVRFs (Blacks: [B ± SE]: -1.25 ± 0.45, P=0.005; Whites: [B ± SE]: -0.92 ± 0.35, P=0.008), but not for education. The interaction between c-IMT >50^th percentile and education was significant (P=0.03), and stratified analysis showed an association with GCS among those with lower achieved education ([B ± SE]: -0.81 ± 0.33, P=0.013) independent of major CVRFs.

DISCUSSION

Subclinical atherosclerosis, measured as c-IMT, was associated with worse midlife cognitive function, independent of major CVRFs. The association was buffered by education and may be stronger among Black than White participants, likely due to corresponding structural and social determinants. These findings underscore the importance of establishing preventive measures in midlife and suggest subclinical atherosclerosis as a potential target to prevent cognitive decline.

Pathological Gait Signatures of Post-stroke Dementia With Toe-Off and Heel-to-Ground Angles Discriminate From Alzheimer's Disease

Given the limited power of neuropsychological tests, there is a need for a simple, reliable means, such as gait, to identify mild dementia and its subtypes. However, gait characteristics of patients with post-stroke dementia (PSD) and Alzheimer’s disease (AD) are unclear. We sought to describe their gait signatures and to explore gait parameters distinguishing PSD from post-stroke non-dementia (PSND) and patients with AD. We divided 3-month post-stroke patients into PSND and PSD groups based on the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and the activity of daily living (ADL). Thirty-one patients with AD and thirty-two healthy controls (HCs) were also recruited. Ten gait parameters in one single and two dual-task gait tests (counting-backward or naming-animals while walking) were compared among the groups, with adjustment for baseline demographic covariates and the MMSE score. The area under the receiver operating characteristic curve (AUC) was used to identify parameters discriminating PSD from individuals with PSND and AD. Patients with PSD and patients with AD showed impaired stride length, velocity, stride time, and cadence while patients with PSD had altered stance and swing phase proportions (all p ≤ 0.01, post hoc). Patients with AD had smaller toe-off (ToA) and heel-to-ground angles (HtA) (p ≤ 0.01) than HCs in dual-task gait tests. Individuals with PSD had a shorter stride length, slower velocity, and altered stance and swing phase percentages in all tests (p ≤ 0.01), but a higher coefficient of variation of stride length (CoV_SL) and time (CoV_ST) only in the naming animals-task gait test (p ≤ 0.001) than individuals with PSND. ToA and HtA in the naming animals-task gait test were smaller in individuals with AD than those with PSD (p ≤ 0.01). Statistical significance persisted after adjusting for demographic covariates, but not for MMSE. The pace and the percentage of stance or swing phase in all tests, CoV_ST in the dual-task paradigm, and CoV_SL only in the naming animals-task gait test (moderate accuracy, AUC > 0.700, p ≤ 0.01) could distinguish PSD from PSND. Furthermore, the ToA and HtA in the naming animals-task gait paradigm discriminated AD from PSD (moderate accuracy, AUC > 0.700, p ≤ 0.01). Thus, specific gait characteristics could allow early identification of PSD and may allow non-invasive discrimination between PSD and AD, or even other subtypes of dementia.

The "Counseling+" Roles of the Speech-Language Pathologist Serving Older Adults With Mild Cognitive Impairment and Dementia From Alzheimer's Disease

Purpose

Persons with dementia and mild cognitive impairment (MCI) are major consumers of services provided by speech-language pathologists (SLPs). These services include not only direct assessment and treatment of communication and swallowing but also counseling, collaboration, prevention, and wellness. These "counseling+" activities can be especially challenging for SLPs to deliver because of the lack of evidence, as well as the complex nature of Alzheimer's disease (AD) and other conditions that cause MCI and dementia.

Method

This tutorial is written by a speech-language pathologist, a neuropsychologist, and a geriatric psychiatrist to provide education, resources, and recommendations for SLPs delivering counseling+ activities to patients with MCI and dementia from AD and related disorders.

Results and Conclusions

We describe counseling+ activities across the continuum of care ranging from educating and conducting cognitive screenings with adults experiencing age-related cognitive decline to supporting end-of-life wishes. Because of their expertise in communication, SLPs can provide an array of important leading and supporting services to patients, their family, and other health care professionals on the care team, such as providing patients with appropriate feedback following a cognitive screening and helping caregivers identify the communicative intent of a responsive behavior. The demand for SLP services for patients with MCI and dementia will grow significantly over the next few decades, necessitating more systematic research and clinical evidence in this area.

Blood-Brain Barrier Breakdown: An Emerging Biomarker of Cognitive Impairment in Normal Aging and Dementia

The blood–brain barrier (BBB) plays a vital role in maintaining the specialized microenvironment of the neural tissue. It separates the peripheral circulatory system from the brain parenchyma while facilitating communication. Alterations in the distinct physiological properties of the BBB lead to BBB breakdown associated with normal aging and various neurodegenerative diseases. In this review, we first briefly discuss the aging process, then review the phenotypes and mechanisms of BBB breakdown associated with normal aging that further cause neurodegeneration and cognitive impairments. We also summarize dementia such as Alzheimer's disease (AD) and vascular dementia (VaD) and subsequently discuss the phenotypes and mechanisms of BBB disruption in dementia correlated with cognition decline. Overlaps between AD and VaD are also discussed. Techniques that could identify biomarkers associated with BBB breakdown are briefly summarized. Finally, we concluded that BBB breakdown could be used as an emerging biomarker to assist to diagnose cognitive impairment associated with normal aging and dementia.

Associations of increased interstitial fluid with vascular and neurodegenerative abnormalities in a memory clinic sample

The vascular and neurodegenerative processes related to clinical dementia cause cell loss which induces, amongst others, an increase in interstitial fluid (ISF). We assessed microvascular, parenchymal integrity, and a proxy of ISF volume alterations with intravoxel incoherent motion imaging in 21 healthy controls and 53 memory clinic patients - mainly affected by neurodegeneration (mild cognitive impairment, Alzheimer's disease dementia), vascular pathology (vascular cognitive impairment), and presumed to be without significant pathology (subjective cognitive decline). The microstructural components were quantified with spectral analysis using a non-negative least squares method. Linear regression was employed to investigate associations of these components with hippocampal and white matter hyperintensity (WMH) volumes. In the normal appearing white matter, a large f_int (a proxy of ISF volume) was associated with a large WMH volume and low hippocampal volume. Likewise, a large f_int value was associated with a lower hippocampal volume in the hippocampi. Large ISF volume (f_int) was shown to be a prominent factor associated with both WMHs and neurodegenerative abnormalities in memory clinic patients and is argued to play a potential role in impaired glymphatic functioning.

Classifying Non-Dementia and Alzheimer's Disease/Vascular Dementia Patients Using Kinematic, Time-Based, and Visuospatial Parameters: The Digital Clock Drawing Test

BACKGROUND

Advantages of digital clock drawing metrics for dementia subtype classification needs examination.

OBJECTIVE

To assess how well kinematic, time-based, and visuospatial features extracted from the digital Clock Drawing Test (dCDT) can classify a combined group of Alzheimer's disease/Vascular Dementia patients versus healthy controls (HC), and classify dementia patients with Alzheimer's disease (AD) versus vascular dementia (VaD).

METHODS

Healthy, community-dwelling control participants (n = 175), patients diagnosed clinically with Alzheimer's disease (n = 29), and vascular dementia (n = 27) completed the dCDT to command and copy clock drawing conditions. Thirty-seven dCDT command and 37 copy dCDT features were extracted and used with Random Forest classification models.

RESULTS

When HC participants were compared to participants with dementia, optimal area under the curve was achieved using models that combined both command and copy dCDT features (AUC = 91.52%). Similarly, when AD versus VaD participants were compared, optimal area under the curve was, achieved with models that combined both command and copy features (AUC = 76.94%). Subsequent follow-up analyses of a corpus of 10 variables of interest determined using a Gini Index found that groups could be dissociated based on kinematic, time-based, and visuospatial features.

CONCLUSION

The dCDT is able to operationally define graphomotor output that cannot be measured using traditional paper and pencil test administration in older health controls and participants with dementia. These data suggest that kinematic, time-based, and visuospatial behavior obtained using the dCDT may provide additional neurocognitive biomarkers that may be able to identify and tract dementia syndromes.

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.

Imaging of vascular cognitive impairment

Vascular cognitive impairment (VCI) is a major health challenge and represents the second most common cause of dementia. We review the updated imaging classification and imaging findings of different subtypes of VCI. We will focus on the magnetic resonance imaging (MRI) markers of each subtype and highlight the role of advanced MR imaging sequences in the evaluation of these patients. Small vessel dementia appears as white matter hyperintensity, lacunae, microinfarcts, and microbleeds. Large vessel dementia includes strategic infarction and multi-infarction dementias. Hypoperfusion dementia can be seen as watershed infarcts and cortical laminar necrosis. Hemorrhagic dementia results from cerebral amyloid angiopathy and cortical superficial siderosis. Hereditary forms of VCI, caused by gene mutations such as CADASIL, should be suspected when dementia presents in young patients. Mixed dementia is seen in patients with Alzheimer's disease and the coexistence of cerebrovascular disease.

Normative References for Graphomotor and Latency Digital Clock Drawing Metrics for Adults Age 55 and Older: Operationalizing the Production of a Normal Appearing Clock

BACKGROUND

Relative to the abundance of publications on dementia and clock drawing, there is limited literature operationalizing 'normal' clock production.

OBJECTIVE

To operationalize subtle behavioral patterns seen in normal digital clock drawing to command and copy conditions.

METHODS

From two research cohorts of cognitively-well participants age 55 plus who completed digital clock drawing to command and copy conditions (n = 430), we examined variables operationalizing clock face construction, digit placement, clock hand construction, and a variety of time-based, latency measures. Data are stratified by age, education, handedness, and number anchoring.

RESULTS

Normative data are provided in supplementary tables. Typical errors reported in clock research with dementia were largely absent. Adults age 55 plus produce symmetric clock faces with one stroke, with minimal overshoot and digit misplacement, and hands with expected hour hand to minute hand ratio. Data suggest digitally acquired graphomotor and latency differences based on handedness, age, education, and anchoring.

CONCLUSION

Data provide useful benchmarks from which to assess digital clock drawing performance in Alzheimer's disease and related dementias.

Evaluation and Treatment of Vascular Cognitive Impairment by Transcranial Magnetic Stimulation

The exact relationship between cognitive functioning, cortical excitability, and synaptic plasticity in dementia is not completely understood. Vascular cognitive impairment (VCI) is deemed to be the most common cognitive disorder in the elderly since it encompasses any degree of vascular-based cognitive decline. In different cognitive disorders, including VCI, transcranial magnetic stimulation (TMS) can be exploited as a noninvasive tool able to evaluate in vivo the cortical excitability, the propension to undergo neural plastic phenomena, and the underlying transmission pathways. Overall, TMS in VCI revealed enhanced cortical excitability and synaptic plasticity that seem to correlate with the disease process and progression. In some patients, such plasticity may be considered as an adaptive response to disease progression, thus allowing the preservation of motor programming and execution. Recent findings also point out the possibility to employ TMS to predict cognitive deterioration in the so-called "brains at risk" for dementia, which may be those patients who benefit more of disease-modifying drugs and rehabilitative or neuromodulatory approaches, such as those based on repetitive TMS (rTMS). Finally, TMS can be exploited to select the responders to specific drugs in the attempt to maximize the response and to restore maladaptive plasticity. While no single TMS index owns enough specificity, a panel of TMS-derived measures can support VCI diagnosis and identify early markers of progression into dementia. This work reviews all TMS and rTMS studies on VCI. The aim is to evaluate how cortical excitability, plasticity, and connectivity interact in the pathophysiology of the impairment and to provide a translational perspective towards novel treatments of these patients. Current pitfalls and limitations of both studies and techniques are also discussed, together with possible solutions and future research agenda.

APOE4 is associated with cognitive and pathological heterogeneity in patients with Alzheimer's disease: a systematic review

Possession of the ε4 allele of apolipoprotein E (APOE) is the primary genetic risk factor for the sporadic form of Alzheimer’s disease (AD). While researchers have extensively characterized the impact that APOE ε4 (APOE4) has on the susceptibility of AD, far fewer studies have investigated the phenotypic differences of patients with AD who are APOE4 carriers vs. those who are non-carriers. In order to understand these differences, we performed a qualitative systematic literature review of the reported cognitive and pathological differences between APOE4-positive (APOE4+) vs. APOE4-negative (APOE4−) AD patients. The studies performed on this topic to date suggest that APOE4 is not only an important mediator of AD susceptibility, but that it likely confers specific phenotypic heterogeneity in AD presentation, as well. Specifically, APOE4+ AD patients appear to possess more tau accumulation and brain atrophy in the medial temporal lobe, resulting in greater memory impairment, compared to APOE4− AD patients. On the other hand, APOE4− AD patients appear to possess more tau accumulation and brain atrophy in the frontal and parietal lobes, resulting in greater impairment in executive function, visuospatial abilities, and language, compared to APOE4+ AD patients. Although more work is necessary to validate and interrogate these findings, these initial observations of pathological and cognitive heterogeneity between APOE4+ vs. APOE4− AD patients suggest that there is a fundamental divergence in AD manifestation related to APOE genotype, which may have important implications in regard to the therapeutic treatment of these two patient populations.

microRNA-Based Biomarkers in Alzheimer's Disease (AD)

Alzheimer's disease (AD) is a multifactorial, age-related neurological disease characterized by complex pathophysiological dynamics taking place at multiple biological levels, including molecular, genetic, epigenetic, cellular and large-scale brain networks. These alterations account for multiple pathophysiological mechanisms such as brain protein accumulation, neuroinflammatory/neuro-immune processes, synaptic dysfunction, and neurodegeneration that eventually lead to cognitive and behavioral decline. Alterations in microRNA (miRNA) signaling have been implicated in the epigenetics and molecular genetics of all neurobiological processes associated with AD pathophysiology. These changes encompass altered miRNA abundance, speciation and complexity in anatomical regions of the CNS targeted by the disease, including modified miRNA expression patterns in brain tissues, the systemic circulation, the extracellular fluid (ECF) and the cerebrospinal fluid (CSF). miRNAs have been investigated as candidate biomarkers for AD diagnosis, disease prediction, prognosis and therapeutic purposes because of their involvement in multiple brain signaling pathways in both health and disease. In this review we will: (i) highlight the significantly heterogeneous nature of miRNA expression and complexity in AD tissues and biofluids; (ii) address how information may be extracted from these data to be used as a diagnostic, prognostic and/or screening tools across the entire continuum of AD, from the preclinical stage, through the prodromal, i.e., mild cognitive impairment (MCI) phase all the way to clinically overt dementia; and (iii) consider how specific miRNA expression patterns could be categorized using miRNA reporters that span AD pathophysiological initiation and disease progression.

Evidence for the Utility of Actuarial Neuropsychological Criteria Across the Continuum of Normal Aging, Mild Cognitive Impairment, and Dementia

Background:

Research suggests that actuarial neuropsychological criteria improve the accuracy of mild cognitive impairment (MCI) diagnoses relative to conventional diagnostic methods.

Objective:

We sought to examine the utility of actuarial criteria relative to consensus diagnostic methods used in the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS), and more broadly across the continuum of normal aging, MCI, and dementia.

Methods:

We compared rates of cognitively normal (CN), MCI, and dementia diagnoses at baseline using actuarial versus consensus diagnostic methods in 1524 individuals from the NACC UDS.

Results:

Approximately one-third (33.59%) of individuals diagnosed as CN and more than one-fifth (22.03%) diagnosed with dementia based on consensus methods, met actuarial criteria for MCI. Many participants diagnosed with MCI via consensus methods also appeared to represent possible diagnostic errors. Notably, the CN_a/CN_c group (i.e., participants diagnosed as CN based on both actuarial [_a] and consensus [_c] criteria) had a lower proportion of apolipoprotein E ɛ4 carriers than the MCI_a/MCI_c group, which in turn had a lower proportion of ɛ4 carriers than the dementia (Dem)_a/Dem_c group. Proportions of ɛ4 carriers were comparable between the CN_a/CN_c and CN_a/MCI_c, MCI_a/MCI_c and MCI_a/CN_c, MCI_a/MCI_c and MCI_a/Dem_c, and Dem_a/Dem_c and Dem_a/MCI_c groups. These results were largely consistent with diagnostic agreement/discrepancy group comparisons on neuropsychological performance.

Conclusion:

The present results extend previous findings and suggest that actuarial neuropsychological criteria may enhance diagnostic accuracy relative to consensus methods, and across the wider continuum of normal aging, MCI, and dementia. Findings have implications for both clinical practice and research.

Biomarkers for Alzheimer's Disease (AD) and the Application of Precision Medicine

An accurate diagnosis of Alzheimer's disease (AD) currently stands as one of the most difficult and challenging in all of clinical neurology. AD is typically diagnosed using an integrated knowledge and assessment of multiple biomarkers and interrelated factors. These include the patient's age, gender and lifestyle, medical and genetic history (both clinical- and family-derived), cognitive, physical, behavioral and geriatric assessment, laboratory examination of multiple AD patient biofluids, especially within the systemic circulation (blood serum) and cerebrospinal fluid (CSF), multiple neuroimaging-modalities of the brain's limbic system and/or retina, followed up in many cases by post-mortem neuropathological examination to finally corroborate the diagnosis. More often than not, prospective AD cases are accompanied by other progressive, age-related dementing neuropathologies including, predominantly, a neurovascular and/or cardiovascular component, multiple-infarct dementia (MID), frontotemporal dementia (FTD) and/or strokes or 'mini-strokes' often integrated with other age-related neurological and non-neurological disorders including cardiovascular disease and cancer. Especially over the last 40 years, enormous research efforts have been undertaken to discover, characterize, and quantify more effectual and reliable biological markers for AD, especially during the pre-clinical or prodromal stages of AD so that pre-emptive therapeutic treatment strategies may be initiated. While a wealth of genetic, neurobiological, neurochemical, neuropathological, neuroimaging and other diagnostic information obtainable for a single AD patient can be immense: (i) it is currently challenging to integrate and formulate a definitive diagnosis for AD from this multifaceted and multidimensional information; and (ii) these data are unfortunately not directly comparable with the etiopathological patterns of other AD patients even when carefully matched for age, gender, familial genetics, and drug history. Four decades of AD research have repeatedly indicated that diagnostic profiles for AD are reflective of an extremely heterogeneous neurological disorder. This commentary will illuminate the heterogeneity of biomarkers for AD, comment on emerging investigative approaches and discuss why 'precision medicine' is emerging as our best paradigm yet for the most accurate and definitive prediction, diagnosis, and prognosis of this insidious and lethal brain disorder.

Common Protective Strategies in Neurodegenerative Disease: Focusing on Risk Factors to Target the Cellular Redox System

Neurodegenerative disease is an umbrella term for different conditions which primarily affect the neurons in the human brain. In the last century, significant research has been focused on mechanisms and risk factors relevant to the multifaceted etiopathogenesis of neurodegenerative diseases. Currently, neurodegenerative diseases are incurable, and the treatments available only control the symptoms or delay the progression of the disease. This review is aimed at characterizing the complex network of molecular mechanisms underpinning acute and chronic neurodegeneration, focusing on the disturbance in redox homeostasis, as a common mechanism behind five pivotal risk factors: aging, oxidative stress, inflammation, glycation, and vascular injury. Considering the complex multifactorial nature of neurodegenerative diseases, a preventive strategy able to simultaneously target multiple risk factors and disease mechanisms at an early stage is most likely to be effective to slow/halt the progression of neurodegenerative diseases.

Brain injury-induced dysfunction of the blood brain barrier as a risk for dementia

The blood-brain barrier (BBB) is a complex and dynamic physiological interface between brain parenchyma and cerebral vasculature. It is composed of closely interacting cells and signaling molecules that regulate movement of solutes, ions, nutrients, macromolecules, and immune cells into the brain and removal of products of normal and abnormal brain cell metabolism. Dysfunction of multiple components of the BBB occurs in aging, inflammatory diseases, traumatic brain injury (TBI, severe or mild repetitive), and in chronic degenerative dementing disorders for which aging, inflammation, and TBI are considered risk factors. BBB permeability changes after TBI result in leakage of serum proteins, influx of immune cells, perivascular inflammation, as well as impairment of efflux transporter systems and accumulation of aggregation-prone molecules involved in hallmark pathologies of neurodegenerative diseases with dementia. In addition, cerebral vascular dysfunction with persistent alterations in cerebral blood flow and neurovascular coupling contribute to brain ischemia, neuronal degeneration, and synaptic dysfunction. While the idea of TBI as a risk factor for dementia is supported by many shared pathological features, it remains a hypothesis that needs further testing in experimental models and in human studies. The current review focusses on pathological mechanisms shared between TBI and neurodegenerative disorders characterized by accumulation of pathological protein aggregates, such as Alzheimer's disease and chronic traumatic encephalopathy. We discuss critical knowledge gaps in the field that need to be explored to clarify the relationship between TBI and risk for dementia and emphasize the need for longitudinal in vivo studies using imaging and biomarkers of BBB dysfunction in people with single or multiple TBI.

Evaluation and Treatment of Vascular Cognitive Impairment by Transcranial Magnetic Stimulation

The exact relationship between cognitive functioning, cortical excitability, and synaptic plasticity in dementia is not completely understood. Vascular cognitive impairment (VCI) is deemed to be the most common cognitive disorder in the elderly since it encompasses any degree of vascular-based cognitive decline. In different cognitive disorders, including VCI, transcranial magnetic stimulation (TMS) can be exploited as a noninvasive tool able to evaluate in vivo the cortical excitability, the propension to undergo neural plastic phenomena, and the underlying transmission pathways. Overall, TMS in VCI revealed enhanced cortical excitability and synaptic plasticity that seem to correlate with the disease process and progression. In some patients, such plasticity may be considered as an adaptive response to disease progression, thus allowing the preservation of motor programming and execution. Recent findings also point out the possibility to employ TMS to predict cognitive deterioration in the so-called "brains at risk" for dementia, which may be those patients who benefit more of disease-modifying drugs and rehabilitative or neuromodulatory approaches, such as those based on repetitive TMS (rTMS). Finally, TMS can be exploited to select the responders to specific drugs in the attempt to maximize the response and to restore maladaptive plasticity. While no single TMS index owns enough specificity, a panel of TMS-derived measures can support VCI diagnosis and identify early markers of progression into dementia. This work reviews all TMS and rTMS studies on VCI. The aim is to evaluate how cortical excitability, plasticity, and connectivity interact in the pathophysiology of the impairment and to provide a translational perspective towards novel treatments of these patients. Current pitfalls and limitations of both studies and techniques are also discussed, together with possible solutions and future research agenda.