Prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage

Considering challenges for the new Alzheimer's drugs: Clinical, population, and health system perspectives

Recent approvals of amyloid immunotherapy drugs for early Alzheimer's disease (AD) have been highly controversial. In this piece, we consider challenges from the clinical, population health, and health systems perspectives to the role that the new AD drugs might be expected to play, now and in the future, in alleviating the morbidity caused by AD in the population. Clinically, short-term effects are small, adverse events are frequent, treatment regimens are burdensome, and, crucially, long-term effects are unknown. At a population level, there is always likely to be a trade-off between breadth of access and magnitude of benefit for any given individual. At a health system level, roll out of treatment even for only narrowly-defined patient groups will involve considerable resources to identify and treat eligible patients, with profound opportunity costs. Our considered view on current evidence is that there are challenges from each perspective to imagining a foreseeable future in which amyloid immunotherapy significantly alleviates AD morbidity at scale. HIGHLIGHTS: Recent approvals of Alzheimer's drugs have met with excitement but also controversy. Trial effects are small, adverse effects concerning, and long-term effects unknown. Results from trial cohorts may not generalize to broader, more complex patients. Significant resource requirements of eligibility assessment and drug administration. Use in "presymptomatic" populations is not supported by current evidence.

The link between Alzheimer's disease and stroke: A detrimental synergism

Being age-related disorders, both Alzheimer's disease (AD) and stroke share multiple risk factors, such as hypertension, smoking, diabetes, and apolipoprotein E (APOE) Ɛ4 genotype, and coexist in patients. Accumulation of amyloid-β plaques and neurofibrillary tangled impair cognitive potential, leading to AD. Blocked blood flow in the neuronal tissues, causes neurodegeneration and cell death in stroke. AD is commonly characterized by cerebral amyloid angiopathy, which significantly elevates the risk of hemorrhagic stroke. Patients with AD and stroke have been both reported to exhibit greater cognitive impairment, followed by multiple pathophysiological mechanisms shared between the two. The manuscript aims to elucidate the relationship between AD and stroke, as well as the common pathways and risk factors while understanding the preventive therapies that might limit the negative impacts of this correlation, with diagnostic modalities and current AD treatments. The authors provide a comprehensive review of the link and aid the healthcare professionals to identify suitable targets and risk factors, that may retard cognitive decline and neurodegeneration in patients. However, more intricate research is required in this regard and an interdisciplinary approach that would target both the vascular and neurodegenerative factors would improve the quality of life in AD patients.

Outcomes of Patients With Mild Cognitive Impairment With Lewy Bodies or Alzheimer Disease at 3 and 5 Years After Diagnosis

BACKGROUND AND OBJECTIVES

Retrospective studies indicate that dementia with Lewy bodies (DLB) may be preceded by a mild cognitive impairment (MCI) prodrome. Research criteria for the prospective identification of MCI with Lewy bodies (MCI-LB) have been developed. We aimed to assess the prognosis of a prospectively identified MCI-LB cohort at 2 key milestones, 3- and 5 years after diagnosis, to examine classification stability over time and rates of adverse outcomes (dementia or death).

METHODS

This was a retrospective examination of data from 2 longitudinal observational cohort studies where participants with MCI were prospectively recruited from North East England and differentially classified as MCI due to Alzheimer disease (MCI-AD), possible MCI-LB, or probable MCI-LB. Adverse outcomes (DLB/other dementia or death) and stability of disease-specific classifications were examined in each group.

RESULTS

Of 152 participants with baseline MCI (54 MCI-AD, 29 possible MCI-LB, and 69 probable MCI-LB), 126 were followed for up to 3 years (mean age 75.3 years; 40% female). We found that prospective probable MCI-LB classifications were both sensitive (91%) and specific (94%) to classifications either remaining as probable MCI-LB or progressing to DLB (in some cases autopsy confirmed) for 3 or more years after. Classifications were at least as stable as those in MCI-AD. In this cohort with disease-specific MCI classifications, rates of progression to dementia were high: 55% of MCI-LB had developed DLB within 3 years. Dementia occurred in 47% of MCI-AD over the same duration (odds ratio 1.68, 95% CI 0.66-4.26, p = 0.278). Premature death was a common competing risk, occurring in 9% of MCI-AD and 11% of MCI-LB within 3 years.

DISCUSSION

These findings support that prospectively identified probable MCI-LB is a prodromal presentation of DLB and that disease-specific classifications of MCI may reliably identify different prodromal dementias.

The clinical importance of suspected non-Alzheimer disease pathophysiology

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

The use of individual-based FDG-PET volume of interest in predicting conversion from mild cognitive impairment to dementia

BACKGROUND

Based on a longitudinal cohort design, the aim of this study was to investigate whether individual-based 18F fluorodeoxyglucose positron emission tomography (18F-FDG-PET) regional signals can predict dementia conversion in patients with mild cognitive impairment (MCI).

METHODS

We included 44 MCI converters (MCI-C), 38 non-converters (MCI-NC), 42 patients with Alzheimer's disease with dementia, and 40 cognitively normal controls. Data from annual cognitive measurements, 3D T1 magnetic resonance imaging (MRI) scans, and 18F-FDG-PET scans were used for outcome analysis. An individual-based FDG-PET approach was applied using seven volumes of interest (VOIs), Z transformed using a normal FDG-PET template. Hypometabolism was defined as a Z score < -2 of regional standard uptake value ratio. For the longitudinal cognitive test scores, generalized estimating equations were used. A linear mixed-effects model was used to compare the temporal impact of cortical hypometabolism and cortical thickness degeneration.

RESULTS

The clinical follow-up period was 6.6 ± 3.8 years (range 3.1 to 16.0 years). The trend of cognitive decline could differentiate MCI-C from MCI-NC after 3 years of follow-up. In the baseline 18F-FDG-PET scan of the patients with MCI, medial temporal lobe (MTL; 94.7% sensitivity, 80.5% specificity) and posterior cingulate cortex (PCC; 89.5% sensitivity, 73.1% specificity) hypometabolism predicted conversion with high accuracy. 18F-FDG-PET hypometabolism preceded dementia conversion at an interval of 3.70 ± 1.68 years and was earlier than volumetric changes, with the exception of the MTL.

CONCLUSIONS

Our finding supports the use of individual-based 18F-FDG-PET analysis to predict MCI conversion to dementia. Reduced FDG-PET metabolism in the MTL and PCC were strongly associated with future cognitive decline in the MCI-C group. Changes in 18F-FDG-PET occurred 1 to 8 years prior to conversion to dementia. Progressive hypometabolism in the PCC, precuneus and lateral temporal lobe, but not MTL, preceded MRI findings at the MCI stage.

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer's disease

Alzheimer's disease is one of the most important health-care challenges in the world. For decades, numerous efforts have been made to develop therapeutics for Alzheimer's disease, but most clinical trials have failed to show significant treatment effects on slowing or halting cognitive decline. Among several challenges in such trials, one recently noticed but unsolved is biased allocation of fast and slow cognitive decliners to treatment and placebo groups during randomization caused by the large individual variation in the speed of cognitive decline. This allocation bias directly results in either over- or underestimation of the treatment effect from the outcome of the trial. In this study, we propose a stratified randomization method using the degree of cognitive decline predicted by an artificial intelligence model as a stratification index to suppress the allocation bias in randomization and evaluate its effectiveness by simulation using ADNI data set.

Prevalence, cognitive characteristics, and influencing factors of amnestic mild cognitive impairment among older adults residing in an urban community in Chengdu, China

Objective

Dementia is a significant public health concern, and mild cognitive impairment (MCI) serves as a transitional stage between normal aging and dementia. Among the various types of MCI, amnestic MCI (aMCI) has been identified as having a higher likelihood of progressing to Alzheimer's dimension. However, limited research has been conducted on the prevalence of aMCI in China. Therefore, the objective of this study is to investigate the prevalence of aMCI, examine its cognitive characteristics, and identify associated risk factors.

Methods

In this cross-sectional study, we investigated a sample of 368 older adults aged 60 years and above in the urban communities of Chengdu, China. The participants underwent a battery of neuropsychological assessments, including the Mini-Mental State Examination (MMSE), the Clinical Dementia Rating (CDR), Auditory Verbal Learning Test (AVLT), Wechsler's Logical Memory Task (LMT), Boston Naming Test (BNT) and Trail Making Test Part A (TMT-A). Social information was collected by standard questionnaire. Multiple logistic regression analysis was utilized to screen for the risk and protective factors of aMCI.

Results

The data analysis included 309 subjects with normal cognitive function and 59 with aMCI, resulting in a prevalence of 16.0% for aMCI. The average age of participants was 69.06 ± 7.30 years, with 56.0% being females. After controlling for age, gender and education, the Spearman partial correlation coefficient between various cognitive assessments and aMCI ranged from -0.52 for the long-term delayed recall scores in AVLT to 0.19 for the time-usage scores in TMT-A. The results indicated that all cognitive domains, except for naming scores (after semantic cue of BNT) and error quantity (in TMT-A), showed statistically significant associations with aMCI. Furthermore, the multiple logistic regression analysis revealed that older age (OR = 1.044, 95%CI: 1.002~1.087), lower educational level, and diabetes (OR = 2.450, 95%CI: 1.246~4.818) were risk factors of aMCI.

Conclusion

This study found a high prevalence of aMCI among older adults in Chengdu, China. Individuals with aMCI exhibited lower cognitive function in memory, language, and executive domains, with long-term delayed recall showing the strongest association. Clinicians should prioritize individuals with verbal learning and memory difficulties, especially long-term delayed recall, in clinical practice.

Estimating Dementia Onset: AT(N) Profiles and Predictive Modeling in Mild Cognitive Impairment Patients

BACKGROUND

Mild Cognitive Impairment (MCI) usually precedes the symptomatic phase of dementia and constitutes a window of opportunities for preventive therapies.

OBJECTIVES

The objective of this study was to predict the time an MCI patient has left to reach dementia and obtain the most likely natural history in the progression of MCI towards dementia.

METHODS

This study was conducted on 633 MCI patients and 145 subjects with dementia through 4726 visits over 15 years from Alzheimer Disease Neuroimaging Initiative (ADNI) cohort. A combination of data from AT(N) profiles at baseline and longitudinal predictive modeling was applied. A data-driven approach was proposed for categorical diagnosis prediction and timeline estimation of cognitive decline progression, which combined supervised and unsupervised learning techniques.

RESULTS

A reduced vector of only neuropsychological measures was selected for training the models. At baseline, this approach had high performance in detecting subjects at high risk of converting from MCI to dementia in the coming years. Furthermore, a Disease Progression Model (DPM) was built and also verified using three metrics. As a result of the DPM focused on the studied population, it was inferred that amyloid pathology (A+) appears about 7 years before dementia, and tau pathology (T+) and neurodegeneration (N+) occur almost simultaneously, between 3 and 4 years before dementia. In addition, MCI-A+ subjects were shown to progress more rapidly to dementia compared to MCI-A- subjects.

CONCLUSION

Based on proposed natural histories and cross-sectional and longitudinal analysis of AD markers, the results indicated that only a single cerebrospinal fluid sample is necessary during the prodromal phase of AD. Prediction from MCI into dementia and its timeline can be achieved exclusively through neuropsychological measures.

Economic Impact of Progression from Mild Cognitive Impairment to Alzheimer Disease in the United States

BACKGROUND

Limited evidence exists on the economic burden of individuals who progress from mild cognitive impairment (MCI) to Alzheimer disease and related dementia disorders (ADRD).

OBJECTIVES

To assess the all-cause health care resource utilization and costs for individuals who develop ADRD following an MCI diagnosis compared to those with stable MCI.

DESIGN

This was a retrospective cohort study from January 01, 2014, to December 31, 2019.

SETTING

The Merative MarketScan Commercial and Medicare Databases were used.

PARTICIPANTS

Individuals were included if they: (1) were aged 50 years or older; (2) had ≥1 claim with an MCI diagnosis based on the International Classification of Diseases, Ninth Revision (ICD-9) code of 331.83 or the Tenth Revision (ICD-10) code of G31.84; and had continuous enrollment. Individuals were excluded if they had a diagnosis of Parkinson's disease or ADRD or prescription of ADRD medication.

MEASUREMENTS

Outcomes included all-cause utilization and costs per patient per year in the first 12 months following MCI diagnosis, in total and by care setting: inpatient admissions, emergency department (ED) visits, outpatient visits, and pharmacy claims.

RESULTS

Out of the total of 5185 included individuals, 1962 (37.8%) progressed to ADRD (MCI-to-ADRD subgroup) and 3223 (62.2%) did not (Stable MCI subgroup). Adjusted all-cause utilization was higher for all care settings in the MCI-to-ADRD subgroup compared with the Stable MCI subgroup. Adjusted all-cause mean total costs ($34 599 vs $24 541; mean ratio [MR], 1.41 [95% CI, 1.31-1.51]; P<.001), inpatient costs ($47 463 vs $38 004; MR, 1.25 [95% CI, 1.08-1.44]; P=.002), ED costs ($4875 vs $3863; MR, 1.26 [95% CI, 1.11-1.43]; P<.001), and outpatient costs ($16 652 vs $13 015; MR, 1.28 [95% CI, 1.20-1.37]; P<.001) were all significantly higher for the MCI-to-ADRD subgroup compared with the Stable MCI subgroup.

CONCLUSIONS

Individuals who progressed from MCI to ADRD had significantly higher health care costs than individuals with stable MCI. Early identification of MCI and delaying its progression is important to improve patient and economic outcomes.

Disease2Vec: Encoding Alzheimer's progression via disease embedding tree

For decades, a variety of predictive approaches have been proposed and evaluated in terms of their prediction capability for Alzheimer's Disease (AD) and its precursor - mild cognitive impairment (MCI). Most of them focused on prediction or identification of statistical differences among different clinical groups or phases, especially in the context of binary or multi-class classification. The continuous nature of AD development and transition states between successive AD related stages have been typically overlooked. Though a few progression models of AD have been studied recently, they were mainly designed to determine and compare the order of specific biomarkers. How to effectively predict the individual patient's status within a wide spectrum of continuous AD progression has been largely understudied. In this work, we developed a novel learning-based embedding framework to encode the intrinsic relations among AD related clinical stages by a set of meaningful embedding vectors in the latent space (Disease2Vec). We named this process as disease embedding. By Disease2Vec, our framework generates a disease embedding tree (DETree) which effectively represents different clinical stages as a tree trajectory reflecting AD progression and thus can be used to predict clinical status by projecting individuals onto this continuous trajectory. Through this model, DETree can not only perform efficient and accurate prediction for patients at any stages of AD development (across five fine-grained clinical groups instead of typical two groups), but also provide richer status information by examining the projecting locations within a wide and continuous AD progression process. (Code will be available: https://github.com/qidianzl/Disease2Vec.).

A Chiral Nanocomplex for Multitarget Therapy to Alleviate Neuropathology and Rescue Alzheimer's Cognitive Deficits

Alzheimer's disease (AD) is a severe neurodegenerative condition characterized by inflammation, beta-amyloid (Aβ) plaques, and neurodegeneration, which currently lack effective treatments. Chiral nanomaterials have emerged as a promising option for treating neurodegenerative disorders due to their high biocompatibility, strong sustained release ability, and specific enantiomer selectivity. The development of a stimulus-responsive chiral nanomaterial, UiO-66-NH2 @l-MoS2 QDs@PA-Ni (MSP-U), for the treatment of AD is reported. MSP-U is found to stimulate neural stem cell (NSCs) differentiation, promote in situ hydrogen (H2 ) production, and clear Aβ plaques. l-MoS2 QDs modified with l-Cysteine (l-Cys) effectively enhance the differentiation of NSCs into neurons through circularly polarized near-infrared radiation. Doped-phytic acid nickel (PA-Ni) improves the activity of l-MoS2 QDs in scavenging reactive oxygen species at the lesion site via photocatalytic H2 production. Loading l-MoS2 QDs with UiO-66 type metal oxide suppresses electron-hole recombination effect, thereby achieving rapid charge separation and improving transport of photogenerated electrons, leading to significantly improved H2 production efficiency. The photothermal effect of MSP-U also clears the generated Aβ plaques. In vivo evaluations show that MSP-U improves spatial cognition and memory, suggesting a promising potential candidate for the treatment of AD using chiral nanomaterials.

Neuroprotective factors affect the progression of Alzheimer's disease

Alzheimer's disease(AD) is a neurodegenerative disease that occurs mostly in the elderly and is characterized by chronic progressive cognitive dysfunction, which seriously threatens the health and life-quality of patients. Alterations at the molecular level, which causes pathological changes of AD brain, have impacted the progression of AD. In this review, we illustrate the recent evidence of the alteration of neuroprotective proteins in AD, such as changes in their contents and variants. Furthermore, we elucidate the single nucleotide polymorphism (SNP) and gene changes. Finally, we highlight the epigenetic changes in AD, which helps to display the characteristics of the disease and provides guidance regarding research hot spots in the field against AD.

Novel fluid biomarkers for mild cognitive impairment: A systematic review and meta-analysis

Mild cognitive impairment (MCI) is a well-established prodromal stage of dementia (e.g., Alzheimer's disease) that is often accompanied by early signs of neurodegeneration. To facilitate a better characterization of the underlying pathophysiology, we assessed the available literature to evaluate potential fluid biomarkers in MCI. Peer-reviewed articles that measured cerebrospinal fluid (CSF) and/or peripheral biomarkers of neuronal injury (total-tau [T-tau], neurofilament light chain [NfL], heart-type fatty acid binding protein [HFABP], neuron-specific enolase, ubiquitin C-terminal hydrolase L1) and/or astroglial pathology (glial fibrillary acidic protein [GFAP], S100 calcium-binding protein B) in MCI and healthy controls were assessed. Group differences were summarized by standardized mean differences (SMDs) and 95% confidence intervals calculated using a random-effects model. Heterogeneity was quantified using I2. A total of 107 studies were included in the meta-analysis and 10 studies were qualitatively reviewed. In CSF, concentrations of NfL (SMD = 0.69 [0.56, 0.83]), GFAP (SMD = 0.41 [0.07, 0.75]), and HFABP (SMD = 0.57 [0.26, 0.89]) were elevated in MCI. In blood, increased concentrations of T-tau (SMD = 0.19 [0.09, 0.29]), NfL (SMD = 0.41 [0.32, 0.49]), and GFAP (SMD = 0.39 [0.23, 0.55]) were found in MCI. Heterogeneity that was identified in all comparisons was explored using meta-regression and subgroup analysis. Elevated NfL and GFAP can be detected in both CSF and peripheral blood. Monitoring these biomarkers in clinical settings may provide important insight into underlying neurodegenerative processes in MCI.

Differences in Life Space Activity Patterns Between Older Adults With Mild Cognitive Impairment Living Alone or as a Couple: Cohort Study Using Passive Activity Sensing

BACKGROUND

Measuring function with passive in-home sensors has the advantages of real-world, objective, continuous, and unobtrusive measurement. However, previous studies have focused on 1-person homes only, which limits their generalizability.

OBJECTIVE

This study aimed to compare the life space activity patterns of participants living alone with those of participants living as a couple and to compare people with mild cognitive impairment (MCI) with cognitively normal participants in both 1- and 2-person homes.

METHODS

Passive infrared motion sensors and door contact sensors were installed in 1- and 2-person homes with cognitively normal residents or residents with MCI. A home was classified as an MCI home if at least 1 person in the home had MCI. Time out of home (TOOH), independent life space activity (ILSA), and use of the living room, kitchen, bathroom, and bedroom were calculated. Data were analyzed using the following methods: (1) daily averages over 4 weeks, (2) hourly averages (time of day) over 4 weeks, or (3) longitudinal day-to-day changes.

RESULTS

In total, 129 homes with people living alone (n=27, 20.9%, MCI and n=102, 79.1%, no-MCI homes) and 52 homes with people living as a couple (n=24, 46.2%, MCI and n=28, 53.8%, no-MCI homes) were included with a mean follow-up of 719 (SD 308) days. Using all 3 analysis methods, we found that 2-person homes showed a shorter TOOH, a longer ILSA, and shorter living room and kitchen use. In MCI homes, ILSA was higher in 2-person homes but lower in 1-person homes. The effects of MCI status on other outcomes were only found when using the hourly averages or longitudinal day-to-day changes over time, and they depended on the household type (alone vs residing as a couple).

CONCLUSIONS

This study shows that in-home behavior is different when a participant is living alone compared to when they are living as a couple, meaning that the household type should be considered when studying in-home behavior. The effects of MCI status can be detected with in-home sensors, even in 2-person homes, but data should be analyzed on an hour-to-hour basis or longitudinally.

Decision making in clinical trials: Interim analyses, innovative design, and biomarkers

The efficient and accurate execution of clinical trials testing novel treatments for Alzheimer's disease (AD) is a critical component of the field's collective efforts to develop effective disease-modifying treatments for AD. The lengthy and heterogeneous nature of clinical progression in AD contributes to the challenges inherent in demonstrating a clinically meaningful benefit of any potential new AD therapy. The failure of many large and expensive clinical trials to date has prompted a focus on optimizing all aspects of decision making, to not only expedite the development of new treatments, but also maximize the value of the information that each clinical trial yields, so that all future clinical trials (including those that are negative) will contribute toward advancing the field. To address this important topic the Alzheimer's Association Research Roundtable convened December 1-2, 2020. The goals focused around identifying new directions and actionable steps to enhance clinical trial decision making in planned future studies.

Pathogenesis of Alzheimer's Disease and Diversity of 1,2,3-Triazole Scaffold in Drug Development: Design Strategies, Structural Insights, and Therapeutic Potential

Alzheimer's disease is a most prevalent form of dementia all around the globe and currently poses a significant challenge to the healthcare system. Currently available drugs only slow the progression of this disease rather than provide proper containment. Identification of multiple targets responsible for this disease in the last three decades established it as a multifactorial neurodegenerative disorder that needs novel multifunctional agents for its management and the possible reason for the failure of currently available single target clinical drugs. 1,2,3-Triazole is a miraculous nucleus in medicinal chemistry and the first choice for development of multifunctional hybrid molecules. Apart from that, it is an integral component of various drugs in clinical trials as well as in clinical practice. This review is focused on the pathogenesis of Alzheimer's disease and 1,2,3-triazole containing derivatives developed in recent decades as potential anti-Alzheimer's agents. The review will provide (A) precise insight of various established targets of Alzheimer's disease including cholinergic, amyloid, tau, monoamine oxidases, glutamate, calcium, and reactive oxygen species hypothesis and (B) design hypothesis, structure-activity relationships, and pharmacological outcomes of 1,2,3-triazole containing multifunctional anti-Alzheimer's agents. This review will provide a baseline for various research groups working on Alzheimer's drug development in designing potent, safer, and effective multifunctional anti-Alzheimer's candidates of the future.

Disease severity and mortality in Alzheimer's disease: an analysis using the U.S. National Alzheimer's Coordinating Center Uniform Data Set

BACKGROUND

Evidence on the relative risk of death across all stages of Alzheimer's disease (AD) is lacking but greatly needed for the evaluation of new interventions. We used data from the Uniform Data Set (UDS) of the National Alzheimer's Coordinating Center (NACC) to assess the expected survival of a person progressing to a particular stage of AD and the relative risk of death for a person in a particular stage of AD compared with cognitively normal (CN) people.

METHODS

This was a retrospective observational cohort study of mortality and its determinants in participants with incident mild cognitive impairment (MCI) due to AD or AD dementia compared with CN participants. Overall survival and hazard ratios of all-cause mortality in participants ≥ 50 years of age with clinically assessed or diagnosed MCI due to AD, or mild, moderate, or severe AD dementia, confirmed by Clinical Dementia Rating scores, versus CN participants were estimated, using NACC UDS data. Participants were followed until death, censoring, or until information to determine disease stage was missing.

RESULTS

Aged between 50 and 104 years, 12,414 participants met the eligibility criteria for the study. Participants progressing to MCI due to AD or AD dementia survived a median of 3-12 years, with higher mortality observed in more severe stages. Risk of death increased with the severity of AD dementia, with the increase significantly higher at younger ages. Participants with MCI due to AD and CN participants had a similar risk of death after controlling for confounding factors.

CONCLUSIONS

Relative all-cause mortality risk increases with AD severity, more so at younger ages. Mortality does not seem to be higher for those remaining in MCI due to AD. Findings might imply potential benefit of lower mortality if preventing or delaying the progression of AD is successful, and importantly, this potential benefit might be greater in relatively younger people. Future research should replicate our study in other samples more representative of the general US population as well as other populations around the world.

The value of maintaining cognition in patients with mild cognitive impairment: The innovation headroom and potential cost-effectiveness of roflumilast

INTRODUCTION

Early health-technology assessment can support discussing scarce resource allocation among stakeholders. We explored the value of maintaining cognition in patients with mild cognitive impairment (MCI) by estimating: (1) the innovation headroom and (2) the potential cost effectiveness of roflumilast treatment in this population.

METHODS

The innovation headroom was operationalized by a fictive 100% efficacious treatment effect, and the roflumilast effect on memory word learning test was assumed to be associated with 7% relative risk reduction of dementia onset. Both were compared to Dutch setting usual care using the adapted International Pharmaco-Economic Collaboration on Alzheimer's Disease (IPECAD) open-source model.

RESULTS

The total innovation headroom expressed as net health benefit was 4.2 (95% bootstrap interval: 2.9-5.7) quality-adjusted life years (QALYs). The potential cost effectiveness of roflumilast was k€34 per QALY.

DISCUSSION

The innovation headroom in MCI is substantial. Although the potential cost effectiveness of roflumilast treatment is uncertain, further research on its effect on dementia onset is likely valuable.

Oxazole-4-carboxamide/butylated hydroxytoluene hybrids with GSK-3β inhibitory and neuroprotective activities against Alzheimer's disease

Neuronal cells overexpressing phosphorylated Tau proteins can increase the susceptibility to oxidative stress. Regulation of glycogen synthase-3β (GSK-3β) and reduction of Tau protein hyperphosphorylation, along with alleviation of oxidative stress, may be an effective way to prevent or treat Alzheimer's disease (AD). For this purpose, a series of Oxazole-4-carboxamide/butylated hydroxytoluene hybrids were designed and synthesized to achieve multifunctional effects on AD. The biological evaluation showed that the optimized compound KWLZ-9e displayed potential GSK-3β (IC₅₀ = 0.25 μM) inhibitory activity and neuroprotective capacity. Tau protein inhibition assays showed that KWLZ-9e reduced the expression of GSK-3β and downstream p-Tau in HEK GSK-3β 293T cells. Meanwhile, KWLZ-9e could alleviate H₂O₂-induced ROS damage, mitochondrial membrane potential imbalance, Ca²⁺ influx and apoptosis. Mechanistic studies suggest that KWLZ-9e activates the Keap1-Nrf2-ARE signaling pathway and enhances the expression of downstream oxidative stress proteins including TrxR1, HO-1, NQO1, GCLM to exert cytoprotective effects. We also confirmed that KWLZ-9e could ameliorate learning and memory impairments in vivo model of AD. The multifunctional properties of KWLZ-9e suggest that it is a promising lead for the treatment of AD.

Saccadic Eye Movements in Patients with Mild Cognitive Impairment: A Longitudinal Study

Saccadic eye movements are one of the sensitive and noninvasive methods to help monitor the cognitive course of mild cognitive impairment (MCI). The study aimed to evaluate both pro and anti-saccade longitudinally and the relationship between cognitive functions and eye movements in MCI subgroups and healthy controls (HCs) at a two-year follow-up. This study revealed that the anti-saccade anticipatory responses decreased in amnestic MCI (aMCI). Correct vertical pro-saccades increased in non-amnestic MCI (naMCI), while the express saccades decreased. Our study demonstrated that longer than two years of follow-up is necessary to monitor the course of MCI. Findings of the relationships between longitudinal changes of saccades and cognitive measurements demonstrated the usability of eye movements in evaluating the process of MCI.

Prognostic value of cerebrospinal fluid biomarkers in mild cognitive impairment due to Alzheimer disease

We performed a retrospective analysis of the patients assessed at our memory unit for whom Alzheimer disease (AD) cerebrospinal fluid biomarker results were available. We selected patients diagnosed with mild cognitive impairment due to AD (National Institute on Aging-Alzheimer's Association clinical criteria), confirmed neuropsychological deficit, a Global Deterioration Scale score of 3, and an abnormal profile of cerebrospinal fluid biomarkers. Of the 588 cases reviewed, 110 met the inclusion criteria. During follow-up, 50 cases (45.45%) progressed to dementia due to AD. Baseline levels of total and phosphorylated tau were higher in the group of patients that progressed to dementia than in those remaining with mild cognitive impairment. After adjusting for age, sex, history of hypertension, diabetes, and educational level, a 10% increase in total tau protein values was associated with a 7.60% increase in the risk of progression to dementia (hazard ratio: 2.22; 95% confidence interval, 1.28-3.84]; P =  .004). Among patients with mild cognitive impairment due to AD and abnormal cerebrospinal fluid biomarker profiles, progressively higher concentrations of total or phosphorylated tau were associated with increased risk of progression to dementia.

Acupuncture on mild cognitive impairment: A systematic review of neuroimaging studies

Mild cognitive impairment (MCI) is a multifactorial and complex central neurodegenerative disease. Acupuncture appears to be an effective method for cognitive function improvement in MCI patients. Neural plasticity remaining in the MCI brain implies that acupuncture-associated benefits may not be limited to the cognitive function. Instead, neurological alternations in the brain play a vital role in corresponding to the cognitive improvement. However, previous studies have mainly focused on the effects of cognitive function, leaving neurological findings relatively unclear. This systematic review summarized existing studies that used various brain imaging techniques to explore the neurological effect regarding acupuncture use for MCI treatment. Potential neuroimaging trials were searched, collected, and identified independently by two researchers. Four Chinese databases, four English databases, and additional sources were searched to identify studies reporting the use of acupuncture for MCI from the inception of databases until 1 June 2022. Methodological quality was appraised using the Cochrane risk-of-bias tool. In addition, general, methodological, and brain neuroimaging information was extracted and summarized to investigate the potential neural mechanisms by which acupuncture affects patients with MCI. In total, 22 studies involving 647 participants were included. The methodological quality of the included studies was moderate to high. The methods used included functional magnetic resonance imaging, diffusion tensor imaging, functional near-infrared spectroscopy, and magnetic resonance spectroscopy. Acupuncture-induced brain alterations observed in those patients with MCI tended to be observable in the cingulate cortex, prefrontal cortex, and hippocampus. The effect of acupuncture on MCI may play a role in regulating the default mode network, central executive network, and salience network. Based on these studies, researchers could extend the recent research focus from the cognitive domain to the neurological level. Future researches should develop additional relevant, well-designed, high-quality, and multimodal neuroimaging researches to detect the effects of acupuncture on the brains of MCI patients.

A Case of Minimally Progressive Prodromal Alzheimer's Disease

Prodromal Alzheimer's disease (AD) is a neurodegenerative condition typically progressing to dementia within 3 years. We describe a case of a mild cognitive impairment (MCI) patient with biomarker evidence for amyloidosis, tau, and neurodegeneration who had minimal changes in clinical phenotype during an 11-year period. AD biomarkers were obtained with cerebrospinal fluid analysis and amyloid PET imaging, both of which supported a biological diagnosis of AD. However, the patient's neuropsychological profile remained stable over 11 years except for mild memory-retrieval changes. This case provides evidence that MCI with supportive AD biomarkers may have an atypically minimal progression.

Why a clinical trial is as good as its outcome measure: A framework for the selection and use of cognitive outcome measures for clinical trials of Alzheimer's disease

A crucial aspect of any clinical trial is using the right outcome measure to assess treatment efficacy. Compared to the rapidly evolved understanding and measurement of pathophysiology in preclinical and early symptomatic stages of Alzheimer's disease (AD), relatively less progress has been made in the evolution of clinical outcome assessments (COAs) for those stages. The current paper aims to provide a benchmark for the design and evaluation of COAs for use in early AD trials. We discuss lessons learned on capturing cognitive changes in predementia stages of AD, including challenges when validating novel COAs for those early stages and necessary evidence for their implementation in clinical trials. Moving forward, we propose a multi-step framework to advance the use of more effective COAs to assess clinically meaningful changes in early AD, which will hopefully contribute to the much-needed consensus around more appropriate outcome measures to assess clinical efficacy of putative treatments. HIGHLIGHTS: We discuss lessons learned on capturing cognitive changes in predementia stages of AD. We propose a framework for the design and evaluation of performance based cognitive tests for use in early AD trials. We provide recommendations to facilitate the implementation of more effective cognitive outcome measures in AD trials.

Global estimates on the number of persons across the Alzheimer's disease continuum

INTRODUCTION

Global estimates on numbers of persons in early stages of Alzheimer's disease (AD), including prodromal and preclinical, are lacking, yet are needed to inform policy decisions on preventive measures and planning for future therapies targeting AD pathology.

METHODS

We synthesized the literature on prevalence across the AD continuum and derived a model estimating the number of persons, stratified by 5-year age groups, sex, and disease stage (AD dementia, prodromal AD, and preclinical AD).

RESULTS

The global number of persons with AD dementia, prodromal AD, and preclinical AD were estimated at 32, 69, and 315 million, respectively. Together they constituted 416 million across the AD continuum, or 22% of all persons aged 50 and above.

DISCUSSION

Considering predementia stages, the number of persons with AD is much larger than conveyed in available literature. Our estimates are uncertain, especially for predementia stages in low- and middle-income regions where biomarker studies are missing.

Clinical and Economic Assessment in Early-Stage Dementia by Severity and Amyloid-β Status: A 5-Year Retrospective Claims Study of GERAS-US Patients

BACKGROUND

The high burden of dementia and Alzheimer's disease (AD) increases substantially as disease progresses. Characterizing early patterns of health care utilization among patients who develop cognitive impairment may deepen our understanding of early disease trajectory and potentially facilitate timely diagnosis and management.

OBJECTIVE

Describe clinical characteristics, healthcare utilization, and costs in early-stage dementia by disease severity and amyloid-β status before enrollment in an observational study (GERAS-US).

METHODS

Consented patients' GERAS-US data were linked to available five-years of Medicare claims history before GERAS-US enrollment. Clinical characteristics, comorbidity, and pre-/post-diagnosis healthcare use and costs were assessed. Continuous and categorical variables were compared between severity and amyloid-status cohorts using t-test and Chi-square statistics; linear regression models were used to compare cost and utilization measures after adjusting for differences in patients' observation time. Relative likelihood of observed diagnoses, comorbidity, and prescription drug use among cohorts were presented as OR and 90% confidence interval (CI).

RESULTS

Of 174 patients clinically diagnosed with early dementia (mild cognitive impairment (MCI): 101; mild dementia (MILD): 73), 55% were amyloid-positive. Memory loss was more likely in MILD versus MCI (OR:1.85, 90% CI 1.10-3.09) and in amyloid-positive versus amyloid-negative cohorts (OR:1.98, 90% CI 1.19-3.29). Mean annual healthcare costs after cognitive impairment/dementia diagnosis were significantly higher for MILD versus MCI ($1191 versus $712, p = 0.067) and amyloid-negative versus amyloid-positive ($1281 versus $701, p = 0.034). Diabetes was more prevalent in MILD and amyloid-negative cohorts.

CONCLUSION

Comorbidity and economic burden increased in earliest stages of MCI and MILD and were higher in patients who were amyloid-negative.

Assessing the mechanisms of brain plasticity by transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a non-invasive technique for focal brain stimulation based on electromagnetic induction where a fluctuating magnetic field induces a small intracranial electric current in the brain. For more than 35 years, TMS has shown promise in the diagnosis and treatment of neurological and psychiatric disorders in adults. In this review, we provide a brief introduction to the TMS technique with a focus on repetitive TMS (rTMS) protocols, particularly theta-burst stimulation (TBS), and relevant rTMS-derived metrics of brain plasticity. We then discuss the TMS-EEG technique, the use of neuronavigation in TMS, the neural substrate of TBS measures of plasticity, the inter- and intraindividual variability of those measures, effects of age and genetic factors on TBS aftereffects, and then summarize alterations of TMS-TBS measures of plasticity in major neurological and psychiatric disorders including autism spectrum disorder, schizophrenia, depression, traumatic brain injury, Alzheimer's disease, and diabetes. Finally, we discuss the translational studies of TMS-TBS measures of plasticity and their therapeutic implications.

Early Detection of Dementia using Risk Classification in MCI: Outcomes of Shanghai Mild Cognitive Impairment Cohort Study

INTRODUCTION

The purpose of this study is to identify the risk factors and risk classification associated with the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia to facilitate early intervention and the design of clinical trials for AD.

METHODS

The study comprised a prospective cohort study of 400 subjects with MCI who had annual follow-ups for 3 years.

RESULTS

During an average follow-up period of 3.5 years, 109 subjects were diagnosed with all cause of dementia, of whom 104 subjects converted to Alzheimer's dementia and 5 subjects converted to other types of dementia. The cumulative conversion rate was 5.5% (95% CI: 3.4, 8.6), 16.3% (95% CI: 12.9, 21.1), and 31.0% (95% CI: 25.4, 36.5) in each of the first 3 follow-up years, respectively. The factors associated with a greater risk of conversion from MCI to AD included smoking status, ApoE4 carrier status, right hippocampal volume (rt. HV), left temporal lobe volume, and scores on the Revised Chinese version of the Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 (ADAS-Cog-C). The risk classification of the ADAS-Cog-C or Preclinical Alzheimer Cognitive Composite (PACC) score combined with the rt. HV showed a conversion difference among the groups at every annual follow-up.

CONCLUSION

A simple risk classification using the rt. HV and neuropsychological test scores, including those from the ADAS-Cog-C and PACC, could be a practicable and efficient approach to indentify individuals at risk of all-cause dementia.

Retinal Examinations Provides Early Warning of Alzheimer's Disease

Patients with Alzheimer's disease have difficulty maintaining independent living abilities as the disease progresses, causing an increased burden of care on family caregivers and the healthcare system and related financial strain. This patient group is expected to continue to expand as life expectancy climbs. Current diagnostics for Alzheimer's disease are complex, unaffordable, and invasive without regard to diagnosis quality at early stages, which urgently calls for more technical improvements for diagnosis specificity. Optical coherence tomography or tomographic angiography has been shown to identify retinal thickness loss and lower vascular density present earlier than symptom onset in these patients. The retina is an extension of the central nervous system and shares anatomic and functional similarities with the brain. Ophthalmological examinations can be an efficient tool to offer a window into cerebral pathology with the merit of easy operation. In this review, we summarized the latest observations on retinal pathology in Alzheimer's disease and discussed the feasibility of retinal imaging in diagnostic prediction, as well as limitations in current retinal examinations for Alzheimer's disease diagnosis.

Long-term exposure to outdoor light at night and mild cognitive impairment: A nationwide study in Chinese veterans

BACKGROUND

Evidence is limited for the association between outdoor light at night (LAN) and mild cognitive impairment (MCI), a transitional stage between normal aging and dementia and Alzheimer's disease in the elderly. In this study, the association between outdoor LAN and MCI was examined based on a multi-city study among veterans in China.

METHODS

A total of 5496 participants from 18 cities across China were investigated during 2009-2011, selected using a multi-stage random sampling method. Participants' cognitive function was firstly assessed using the Mini Mental State Examination and the Montreal Cognitive Assessment in the Chinese version, and then was further confirmed by clinical examination. Participants' exposure to outdoor LAN was estimated using the Global Radiance Calibrated Nighttime Lights Product at a spatial resolution of around 1 km. The mixed-effects logistic regression model was used to examine the association between outdoor LAN and MCI.

RESULTS

After controlling for covariates, odds ratio (OR) and 95 % confidence intervals (95%CI) of MCI was 1.44 (95%CI: 1.36, 1.52) associated with per interquartile range (IQR = 21.17 nW/cm²/sr) increase in exposure to outdoor LAN during the 3 years before the investigation, and for categorical variable of LAN, the highest OR was observed for the highest against the lowest quartile of LAN with a monotonically increasing trend (p values for trend <0.001). Furthermore, higher ORs were observed for females, veterans who had less educational attainment, and had no regular social activities.

CONCLUSIONS

Our study revealed that exposure to excessive outdoor LAN was associated with higher risk of MCI. Effective measures should be taken to reduce LAN exposure, which may help to prevent MCI.

Cost‐effectiveness models for Alzheimer's disease and related dementias: IPECAD modeling workshop cross‐comparison challenge

INTRODUCTION

The credibility of model-based economic evaluations of Alzheimer's disease (AD) interventions is central to appropriate decision-making in a policy context. We report on the International PharmacoEconomic Collaboration on Alzheimer's Disease (IPECAD) Modeling Workshop Challenge.

METHODS

Two common benchmark scenarios, for the hypothetical treatment of AD mild cognitive impairment (MCI) and mild dementia, were developed jointly by 29 participants. Model outcomes were summarized, and cross-comparisons were discussed during a structured workshop.

RESULTS

A broad concordance was established among participants. Mean 10-year restricted survival and time in MCI in the control group ranged across 10 MCI models from 6.7 to 9.5 years and 3.4 to 5.6 years, respectively; and across 4 mild dementia models from 5.4 to 7.9 years (survival) and 1.5 to 4.2 years (mild dementia).

DISCUSSION

The model comparison increased our understanding of methods, data used, and disease progression. We established a collaboration framework to assess cost-effectiveness outcomes, an important step toward transparent and credible AD models.

Amyloid-Tau-Neurodegeneration Profiles and Longitudinal Cognition in Sporadic Young-Onset Dementia

We examined amyloid-tau-neurodegeneration biomarker effects on cognition in a Southeast-Asian cohort of 84 sporadic young-onset dementia (YOD; age-at-onset <65 years) patients. They were stratified into A+N+, A– N+, and A– N– profiles via cerebrospinal fluid amyloid-β1–42 (A), phosphorylated-tau (T), MRI medial temporal atrophy (neurodegeneration– N), and confluent white matter hyperintensities cerebrovascular disease (CVD). A, T, and CVD effects on longitudinal Mini-Mental State Examination (MMSE) were evaluated. A+N+ patients demonstrated steeper MMSE decline than A– N+ (β = 1.53; p = 0.036; CI 0.15:2.92) and A– N– (β = 4.68; p = 0.001; CI 1.98:7.38) over a mean follow-up of 1.24 years. Within A– N+, T– CVD+ patients showed greater MMSE decline compared to T+CVD– patients (β = – 2.37; p = 0.030; CI – 4.41:– 0.39). A+ results in significant cognitive decline, while CVD influences longitudinal cognition in the A– sub-group.

Overview of therapeutic targets in management of dementia

Dementia is defined as a gradual cognitive impairment that interferes with everyday tasks, and is a leading cause of dependency, disability, and mortality. According to the current scenario, millions of individuals worldwide have dementia. This review provides with an overview of dementia before moving on to its subtypes (neurodegenerative and non-neurodegenerative) and pathophysiology. It also discusses the incidence and severity of dementia, focusing on Alzheimer's disease with its different hypotheses such as Aβ cascade hypothesis, Tau hypothesis, inflammatory hypothesis, cholinergic and oxidative stress hypothesis. Alzheimer's disease is the most common type and a progressive neurodegenerative illness distinct by neuronal loss and resulting cognitive impairment, leading to dementia. Alzheimer's disease (AD) is considered the most familiar neurodegenerative dementias that affect mostly older population. There are still no disease-modifying therapies available for any dementias at this time, but there are various methods for lowering the risk to dementia patients by using suitable diagnostic and evaluation methods. Thereafter, the management and treatment of primary risk elements of dementia are reviewed. Finally, the future perspectives of dementia (AD) focusing on the impact of the new treatment are discussed.

Predictive value of phospho-tau/total-tau ratio in amyloid-negative Mild Cognitive Impairment

BACKGROUND

In patients with Mild Cognitive Impairment and normal biomarkers of amyloid-β deposition, prognostication remains challenging.

METHODS

We aimed at identifying clinical features, patterns of brain atrophy, and risk of subsequent conversion to dementia in a clinical cohort of consecutive patients with Mild Cognitive Impairment and normal CSF amyloid-β_1-42 presenting to our Cognitive Neurology Clinic who were followed prospectively over an average of 25 months. We stratified them as Converters/Non-Converters to dementia based on clinical follow-up and compared baseline clinical features, CSF biomarkers, and pattern of atrophy on MRI data between groups.

RESULTS

Among 111 eligible patients (mean age 65,61 years; 56,8% were male), 41 patients developed a clinical diagnosis of dementia. Subjects with low baseline p/t-tau had twofold risk of future conversion compared to high p/t-tau ratio subjects (HR = 2.0, p = 0.026). When stratifying converters according to CSF p/t-tau ratio cut off value (0,17), those with values lower than the cut-off had significantly more MRI atrophy at baseline relative to Non-Converters in limbic structures.

CONCLUSION

In Mild Cognitive Impairment patients with negative CSF amyloid biomarker, CSF p/t-tau ratio may be useful to identify those at greater risk of subsequent conversion, possibly because of TDP43-related underlying pathology.

Effects of combined cognitive and physical intervention on enhancing cognition in older adults with and without mild cognitive impairment: A systematic review and meta-analysis

Background

Combined cognitive and physical intervention is commonly used as a non-pharmacological therapy to improve cognitive function in older adults, but it is uncertain whether combined intervention can produce stronger cognitive gains than either single cognitive or sham intervention. To address this uncertainty, we performed a systematic review and meta-analysis to evaluate the effects of combined intervention on cognition in older adults with and without mild cognitive impairment (MCI).

Methods

We systematically searched eight databases for relevant articles published from inception to November 1, 2021. Randomized controlled trials (RCTs) and non-randomized controlled trials (NRCTs) were used to compare the effects of the combined intervention with a single cognitive or sham intervention on cognition in older adults with and without MCI aged ≥ 50 years. We also searched Google Scholar, references of the included articles, and relevant reviews. Two independent reviewers performed the article screening, data extraction, and bias assessment. GRADEpro was used to rate the strength of evidence, and RevMan software was used to perform the meta-analysis.

Results

Seventeen studies were included in the analysis, comprising eight studies of cognitively healthy older adults and nine studies of older adults with MCI. The meta-analysis showed that the combined intervention significantly improved most cognitive functions and depression (SMD = 0.99, 95% CI 0.54–1.43, p < 0.0001) in older adults compared to the control groups, but the intervention effects varied by cognition domains. However, there was no statistically significant difference in the maintenance between the combined and sham interventions (SMD = 1.34, 95% CI −0.58–3.27, p = 0.17). The subgroup analysis also showed that there was no statistical difference in the combined intervention to improve global cognition, memory, attention, and executive function between cognitive healthy older adults and older adults with MCI.

Conclusions

Combined intervention improves cognitive functions in older adults with and without MCI, especially in global cognition, memory, and executive function. However, there was no statistical difference in the efficacy of the combined intervention to improve cognition between cognitive healthy older adults and older adults with MCI. Moreover, the maintenance of the combined intervention remains unclear due to the limited follow-up data and high heterogeneity. In the future, more stringent study designs with more follow-ups are needed further to explore the effects of combined intervention in older adults.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier: CRD42021292490.

Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non-Alzheimer's disease pathophysiology

BACKGROUND

Suspected non-Alzheimer's disease pathophysiology (SNAP) is a biomarker concept that encompasses individuals with neuronal injury but without amyloidosis. We aim to investigate the pathophysiology of SNAP, defined as abnormal tau without amyloidosis, in individuals with mild cognitive impairment (MCI) by cerebrospinal fluid (CSF) proteomics.

METHODS

Individuals were classified based on CSF amyloid beta (Aβ)1-42 (A) and phosphorylated tau (T), as cognitively normal A-T- (CN), MCI A-T+ (MCI-SNAP), and MCI A+T+ (MCI-AD). Proteomics analyses, Gene Ontology (GO), brain cell expression, and gene expression analyses in brain regions of interest were performed.

RESULTS

A total of 96 proteins were decreased in MCI-SNAP compared to CN and MCI-AD. These proteins were enriched for extracellular matrix (ECM), hemostasis, immune system, protein processing/degradation, lipids, and synapse. Fifty-one percent were enriched for expression in the choroid plexus.

CONCLUSION

The pathophysiology of MCI-SNAP (A-T+) is distinct from that of MCI-AD. Our findings highlight the need for a different treatment in MCI-SNAP compared to MCI-AD.

Retinal Vascular Study Using OCTA in Subjects at High Genetic Risk of Developing Alzheimer’s Disease and Cardiovascular Risk Factors

In 103 subjects with a high genetic risk of developing Alzheimer’s disease (AD), family history (FH) of AD and ApoE ɛ4 characterization (ApoE ɛ4)) were analyzed for changes in the retinal vascular network by OCTA (optical coherence tomography angiography), and AngioTool and Erlangen-Angio-Tool (EA-Tool) as imaging analysis software. Retinal vascularization was analyzed by measuring hypercholesterolemia (HCL) and high blood pressure (HBP). Angio-Tool showed a statistically significant higher percentage of area occupied by vessels in the FH+ ApoE ɛ4- group vs. in the FH+ ApoE ɛ4+ group, and EA-Tool showed statistically significant higher vascular densities in the C3 ring in the FH+ ApoE ɛ4+ group when compared with: i)FH- ApoE ɛ4- in sectors H3, H4, H10 and H11; and ii) FH+ ApoE ɛ4- in sectors H4 and H12. In participants with HCL and HBP, statistically significant changes were found, in particular using EA-Tool, both in the macular area, mainly in the deep plexus, and in the peripapillary area. In conclusion, OCTA in subjects with genetic risk factors for the development of AD showed an apparent increase in vascular density in some sectors of the retina, which was one of the first vascular changes detectable. These changes constitute a promising biomarker for monitoring the progression of pathological neuronal degeneration.

Increase in Mitochondrial D-Loop Region Methylation Levels in Mild Cognitive Impairment Individuals

Methylation levels of the mitochondrial displacement loop (D-loop) region have been reported to be altered in the brain and blood of Alzheimer’s disease (AD) patients. Moreover, a dynamic D-loop methylation pattern was observed in the brain of transgenic AD mice along with disease progression. However, investigations on the blood cells of AD patients in the prodromal phases of the disease have not been performed so far. The aim of this study was to analyze D-loop methylation levels by means of the MS-HRM technique in the peripheral blood cells of 14 mild cognitive impairment (MCI) patients, 18 early stage AD patients, 70 advanced stage AD patients, and 105 healthy control subjects. We found higher D-loop methylation levels in MCI patients than in control subjects and AD patients. Moreover, higher D-loop methylation levels were observed in control subjects than in AD patients in advanced stages of the disease, but not in those at early stages. The present pilot study shows that peripheral D-loop methylation levels differ in patients at different stages of AD pathology, suggesting that further studies deserve to be performed in order to validate the usefulness of D-loop methylation analysis as a peripheral biomarker for the early detection of AD.

Impact of financial barriers on health status, healthcare utilisation and economic burden among individuals with cognitive impairment: a national cross-sectional survey

OBJECTIVE

To study the impact of financial barriers to healthcare on health status, healthcare utilisation and costs among patients with cognitive impairment.

DESIGN

Cross-sectional.

SETTING

National Health Interview Survey (NHIS), 2011-2017.

PARTICIPANTS

Patients with cognitive impairment aged 18 years or older.

INTERVENTIONS

Financial barriers to healthcare were identified using a series of NHIS prompts asking about the affordability of healthcare services.

PRIMARY OUTCOME MEASURES

Health status was based on a survey prompt about respondents' general health. Healthcare utilisation included office visits, home healthcare visits, hospital stays and emergency department (ED) visits. Economic burden was based on the family spending on medical care. Logistic regression models were used to examine the impact of financial barriers to healthcare access on health status, home healthcare visits, office visits, hospital stays and ED visits, respectively.

RESULTS

Compared with cognitively impaired respondents without financial barriers to healthcare access, those with financial barriers were more likely to be unhealthy (OR 0.64, 95% CI 0.57 to 0.72). Cognitively impaired respondents with financial barriers were less likely to have home healthcare (OR 0.69, 95% CI 0.48 to 0.99) and more likely to have hospital stays (OR 1.33, 95% CI 1.19 to 1.48) and ED visits (OR 1.50, 95% CI 1.35 to 1.67). In addition, compared with cognitively impaired respondents without financial barriers to healthcare access, those with the barriers were more likely to have an increased economic burden (OR=1.85, 95% CI 1.65 to 2.07).

CONCLUSION

Financial barriers to healthcare worsened health status and increased use of ED, hospitalisation and economic burden. Policy decision-makers, providers and individuals with cognitive impairment should be aware of the impact of financial barriers and take corresponding actions to reduce the impact.

A deep learning MRI approach outperforms other biomarkers of prodromal Alzheimer's disease

BACKGROUND

The three core pathologies of Alzheimer's disease (AD) are amyloid pathology, tau pathology, and neurodegeneration. Biomarkers exist for each. Neurodegeneration is often detected by neuroimaging, and we hypothesized that a voxel-based deep learning approach using structural MRI might outperform other neuroimaging methods.

METHODS

First, we implement an MRI-based deep learning model, trained with a data augmentation strategy, which classifies Alzheimer's dementia and generates class activation maps. Next, we tested the model in prodromal AD and compared its performance to other biomarkers of amyloid pathology, tau pathology, and neuroimaging biomarkers of neurodegeneration.

RESULTS

The model distinguished between controls and AD with high accuracy (AUROC = 0.973) with class activation maps that localized to the hippocampal formation. As hypothesized, the model also outperformed other neuroimaging biomarkers of neurodegeneration in prodromal AD (AUROC = 0.788) but also outperformed biomarkers of amyloid (CSF Aβ = 0.702) or tau pathology (CSF tau = 0.682), and the findings are interpreted in the context of AD's known anatomical biology.

CONCLUSIONS

The advantages of using deep learning to extract biomarker information from conventional MRIs extend practically, potentially reducing patient burden, risk, and cost.

Biomarkers and Tools for Predicting Alzheimer's Disease in the Preclinical Stage

Alzheimer's disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Over the past decade, a string of disappointing clinical trial results has forced us to shift our focus to the preclinical stage of AD, which represents the most promising therapeutic window. However, the accurate diagnosis of preclinical AD requires the presence of brain β- amyloid deposition determined by cerebrospinal fluid or amyloid-positron emission tomography, significantly limiting routine screening and diagnosis in non-tertiary hospital settings. Thus, an easily accessible marker or tool with high sensitivity and specificity is highly needed. Recently, it has been discovered that individuals in the late stage of preclinical AD may not be truly "asymptomatic" in that they may have already developed subtle or subjective cognitive decline. In addition, advances in bloodderived biomarker studies have also allowed the detection of pathologic changes in preclinical AD. Exosomes, as cell-to-cell communication messengers, can reflect the functional changes of their source cell. Methodological advances have made it possible to extract brain-derived exosomes from peripheral blood, making exosomes an emerging biomarker carrier and liquid biopsy tool for preclinical AD. The eye and its associated structures have rich sensory-motor innervation. In this regard, studies have indicated that they may also provide reliable markers. Here, our report covers the current state of knowledge of neuropsychological and eye tests as screening tools for preclinical AD and assesses the value of blood and brain-derived exosomes as carriers of biomarkers in conjunction with the current diagnostic paradigm.

Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer's disease

Background

Increased total tau (t-tau) in cerebrospinal fluid (CSF) is a key characteristic of Alzheimer’s disease (AD) and is considered to result from neurodegeneration. T-tau levels, however, can be increased in very early disease stages, when neurodegeneration is limited, and can be normal in advanced disease stages. This suggests that t-tau levels may be driven by other mechanisms as well. Because tau pathophysiology is emerging as treatment target for AD, we aimed to clarify molecular processes associated with CSF t-tau levels.

Methods

We performed a proteomic, genomic, and imaging study in 1380 individuals with AD, in the preclinical, prodromal, and mild dementia stage, and 380 controls from the Alzheimer’s Disease Neuroimaging Initiative and EMIF-AD Multimodality Biomarker Discovery study.

Results

We found that, relative to controls, AD individuals with increased t-tau had increased CSF concentrations of over 400 proteins enriched for neuronal plasticity processes. In contrast, AD individuals with normal t-tau had decreased levels of these plasticity proteins and showed increased concentrations of proteins indicative of blood–brain barrier and blood-CSF barrier dysfunction, relative to controls. The distinct proteomic profiles were already present in the preclinical AD stage and persisted in prodromal and dementia stages implying that they reflect disease traits rather than disease states. Dysregulated plasticity proteins were associated with SUZ12 and REST signaling, suggesting aberrant gene repression. GWAS analyses contrasting AD individuals with and without increased t-tau highlighted several genes involved in the regulation of gene expression. Targeted analyses of SNP rs9877502 in GMNC, associated with t-tau levels previously, correlated in individuals with AD with CSF concentrations of 591 plasticity associated proteins. The number of APOE-e4 alleles, however, was not associated with the concentration of plasticity related proteins.

Conclusions

CSF t-tau levels in AD are associated with altered levels of proteins involved in neuronal plasticity and blood–brain and blood-CSF barrier dysfunction. Future trials may need to stratify on CSF t-tau status, as AD individuals with increased t-tau and normal t-tau are likely to respond differently to treatment, given their opposite CSF proteomic profiles.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13024-022-00521-3.

Cerebrovascular disease in Suspected Non-Alzheimer's Pathophysiology and cognitive decline over time

BACKGROUND

The underlying cause of cognitive decline in individuals who are positive for biomarkers of neurodegeneration (N) but negative for biomarkers of amyloid-beta (A), designated as Suspected Non-Alzheimer's Pathophysiology (SNAP), remains unclear. We evaluate whether cerebrovascular disease (CeVD) is more prevalent in those with SNAP compared to A-N- and A+N+ individuals and whether CeVD is associated with cognitive decline over time in SNAP patients.

METHODS

A total of 216 individuals from a prospective memory clinic cohort [mean (SD) age, 72.7(7.3) years, 100 women (56.5%)] were included and were diagnosed as no cognitive impairment (NCI), cognitive impairment no dementia (CIND), Alzheimer's dementia (AD) or Vascular dementia (VaD). All individuals underwent clinical evaluation and neuropsychological assessment annually for up to 5 years. [¹¹ C]-PiB or [¹⁸ F]-Flutafuranol-PET imaging was performed to ascertain amyloid-beta status. MRI was performed to assess neurodegeneration as measured by medial temporal atrophy≥2, as well as significant CeVD (sCeVD) burden, defined by cortical infarct count≥1, Fazekas-score≥2, lacune count≥2 or cerebral microbleed count≥2.

RESULTS

Of the 216 individuals, 50(23.1%) A-N+ were (SNAP), 93(43.1%) A-N-, 36(16.7%) A+N- and 37(17.1%) A+N+. A+N+ individuals were significantly older, while A+N+ and SNAP individuals were more likely to have dementia. The SNAP group had a higher prevalence of sCeVD (90.0%) compared to A-N-. Moreover, SNAP individuals with sCeVD had significantly steeper decline in global cognition compared to A-N- over 5 years (P=0.042).

CONCLUSIONS

These findings suggest that CeVD is a contributing factor to cognitive decline in SNAP. Therefore, SNAP-individuals should be carefully assessed and treated for CeVD.

Alzheimer’s Disease: Epidemiology and Clinical Progression

Alzheimer’s disease (AD) is prevalent throughout the world and is the leading cause of dementia in older individuals (aged ≥ 65 years). To gain a deeper understanding of the recent literature on the epidemiology of AD and its progression, we conducted a review of the PubMed-indexed literature (2014–2021) in North America, Europe, and Asia. The worldwide toll of AD is evidenced by rising prevalence, incidence, and mortality due to AD—estimates which are low because of underdiagnosis of AD. Mild cognitive impairment (MCI) due to AD can ultimately progress to AD dementia; estimates of AD dementia etiology among patients with MCI range from 40% to 75% depending on the populations studied and whether the MCI diagnosis was made clinically or in combination with biomarkers. The risk of AD dementia increases with progression from normal cognition with no amyloid-beta (Aβ) accumulation to early neurodegeneration and subsequently to MCI. For patients with Aβ accumulation and neurodegeneration, lifetime risk of AD dementia has been estimated to be 41.9% among women and 33.6% among men. Data on progression from preclinical AD to MCI are sparse, but an analysis of progression across the three preclinical National Institute on Aging and Alzheimer’s Association (NIA-AA) stages suggests that NIA-AA stage 3 (subtle cognitive decline with AD biomarker positivity) could be useful in combination with other tools for treatment decision-making. Factors shown to increase risk include lower Mini-Mental State Examination (MMSE) score, higher Alzheimer’s Disease Assessment Scale (ADAS-cog) score, positive APOE4 status, white matter hyperintensities volume, entorhinal cortex atrophy, cerebrospinal fluid (CSF) total tau, CSF neurogranin levels, dependency in instrumental activities of daily living (IADL), and being female. Results suggest that use of biomarkers alongside neurocognitive tests will become an important part of clinical practice as new disease-modifying therapies are introduced.

Grey matter network markers identify individuals with prodromal Alzheimer’s disease who will show rapid clinical decline

Individuals with prodromal Alzheimer’s disease show considerable variability in rates of cognitive decline, which hampers the ability to detect potential treatment effects in clinical trials. Prognostic markers to select those individuals who will decline rapidly within a trial time frame are needed. Brain network measures based on grey matter covariance patterns have been associated with future cognitive decline in Alzheimer’s disease. In this longitudinal cohort study, we investigated whether cut-offs for grey matter networks could be derived to detect fast disease progression at an individual level. We further tested whether detection was improved by adding other biomarkers known to be associated with future cognitive decline [i.e. CSF tau phosphorylated at threonine 181 (p-tau181) levels and hippocampal volume]. We selected individuals with mild cognitive impairment and abnormal CSF amyloid β_1–42 levels from the Amsterdam Dementia Cohort and the Alzheimer’s Disease Neuroimaging Initiative, when they had available baseline structural MRI and clinical follow-up. The outcome was progression to dementia within 2 years. We determined prognostic cut-offs for grey matter network properties (gamma, lambda and small-world coefficient) using time-dependent receiver operating characteristic analysis in the Amsterdam Dementia Cohort. We tested the generalization of cut-offs in the Alzheimer’s Disease Neuroimaging Initiative, using logistic regression analysis and classification statistics. We further tested whether combining these with CSF p-tau181 and hippocampal volume improved the detection of fast decliners. We observed that within 2 years, 24.6% (Amsterdam Dementia Cohort, n = 244) and 34.0% (Alzheimer’s Disease Neuroimaging Initiative, n = 247) of prodromal Alzheimer’s disease patients progressed to dementia. Using the grey matter network cut-offs for progression, we could detect fast progressors with 65% accuracy in the Alzheimer’s Disease Neuroimaging Initiative. Combining grey matter network measures with CSF p-tau and hippocampal volume resulted in the best model fit for classification of rapid decliners, increasing detecting accuracy to 72%. These data suggest that single-subject grey matter connectivity networks indicative of a more random network organization can contribute to identifying prodromal Alzheimer’s disease individuals who will show rapid disease progression. Moreover, we found that combined with p-tau and hippocampal volume this resulted in the highest accuracy. This could facilitate clinical trials by increasing chances to detect effects on clinical outcome measures.

Psychotherapeutic interventions in individuals at risk for Alzheimer's dementia: a systematic review

BACKGROUND

Expanding technologies of early detection of Alzheimer's disease allow to identify individuals at risk of dementia in early and asymptomatic disease stages. Neuropsychiatric symptoms, such as anxiety and depression, are common in the course of AD and may be clinically observed many years before the onset of significant cognitive symptoms. To date, therapeutic interventions for AD focus on pharmacological and life style modification-based strategies. However, despite good evidence for psychotherapy in late-life depression, evidence for such therapeutic approaches to improve cognitive and emotional well-being and thereby reduce psychological risk factors in the course of AD are sparse.

METHODS

A systematic review was conducted in PUBMED, PsycINFO, Web of Science, and Clinical Trials to summarize the state of evidence on psychotherapeutic and psychoeducational interventions for individuals at risk for Alzheimer's dementia. Eligible articles needed to apply a manualized and standardized psychotherapeutic or psychoeducational content administered by trained professionals for individuals with subjective cognitive decline or mild cognitive impairment and measure mental health, quality of life or well-being.

RESULTS

The literature search yielded 32 studies that were included in this narrative summary. The data illustrates heterogeneous therapeutic approaches with mostly small sample sizes and short follow-up monitoring. Strength of evidence from randomized-controlled studies for interventions that may improve mood and well-being is scarce. Qualitative data suggests positive impact on cognitive restructuring, and disease acceptance, including positive effects on quality of life. Specific therapeutic determinants of efficacy have not been identified to date.

CONCLUSIONS

This review underlines the need of specific psychotherapeutic and psychoeducational approaches for individuals at risk of Alzheimer's dementia, particularly in terms of an early intervention aiming at improving mental health and well-being. One challenge is the modification of psychotherapeutic techniques according to the different stages of cognitive decline in the course of AD, which is needed to be sensitive to the individual needs.

The Road to Personalized Medicine in Alzheimer’s Disease: The Use of Artificial Intelligence

Dementia remains an extremely prevalent syndrome among older people and represents a major cause of disability and dependency. Alzheimer’s disease (AD) accounts for the majority of dementia cases and stands as the most common neurodegenerative disease. Since age is the major risk factor for AD, the increase in lifespan not only represents a rise in the prevalence but also adds complexity to the diagnosis. Moreover, the lack of disease-modifying therapies highlights another constraint. A shift from a curative to a preventive approach is imminent and we are moving towards the application of personalized medicine where we can shape the best clinical intervention for an individual patient at a given point. This new step in medicine requires the most recent tools and analysis of enormous amounts of data where the application of artificial intelligence (AI) plays a critical role on the depiction of disease–patient dynamics, crucial in reaching early/optimal diagnosis, monitoring and intervention. Predictive models and algorithms are the key elements in this innovative field. In this review, we present an overview of relevant topics regarding the application of AI in AD, detailing the algorithms and their applications in the fields of drug discovery, and biomarkers.

The Outcome of Patients with Amyloid-Negative Amnestic Mild Cognitive Impairment

Background: Patients with amnestic mild cognitive impairment (aMCI) are usually at an initial stage of Alzheimer’s disease (AD). However, some patients with aMCI do not present biomarkers of amyloid pathology characteristic of AD. The significance of amyloid-negative aMCI is not presently clear. Objective: To know the etiology and prognosis of amyloid-negative aMCI. Methods: Patients who fulfilled criteria for aMCI and were amyloid negative were selected from a large cohort of non-demented patients with cognitive complaints and were followed with clinical and neuropsychological assessments. Results: Few amyloid-negative aMCI had evidence of neurodegeneration at the baseline, as reflected in cerebrospinal fluid elevated tau protein levels. About half of the patients remained essentially stable for long periods of time. Others manifested a psychiatric disorder that was not apparent at baseline, namely major depression or bipolar disorder. Remarkably, about a quarter of patients developed neurodegenerative disorders other than AD, mostly frontotemporal dementia or Lewy body disease. Conclusion: Amyloid-negative aMCI is a heterogeneous condition. Many patients remain clinically stable, but others may later manifest psychiatric conditions or evolve to neurodegenerative disorders. Prudence is needed when communicating to the patient and family the results of biomarkers, and clinical follow-up should be advised.