Clinical Dementia Research Articles

Assessing clinical progression measures in Alzheimer's disease trials: A systematic review and meta-analysis.

Assessing treatments for Alzheimer's disease (AD) relies on reliable tools for measuring AD progression. In this analysis, we evaluate the sensitivity of clinical progression measures in AD within randomized controlled trials (RCTs) with confirmed positive amyloid (Aβ+) status prior to trial enrollment. Excluding trials targeting non-cognitive symptoms, we conducted meta-analyses on progression measures from 25 selected RCTs using R version 4.2.0, along with the metafor and emmeans libraries. The Functional Activities Questionnaire (FAQ) demonstrated the greatest sensitivity over 12weeks. Other cognitive measures demonstrated lower sensitivity. The integrated Alzheimer's Disease Rating Scale (iADRS) and Clinical Dementia Rating-Sum of Boxes (CDR-SB) seemed more effective than their individual cognitive components. Neuropsychiatric measures were the least sensitive in measuring progression. Functional measures generally outperformed other measure categories. Purely cognitive domain-based measures were suboptimal for tracking early AD progression. Ideally, future measures should incorporate both cognitive and functional components to enhance sensitivity. Concerns remain regarding the limitations of current outcome measures used in AD clinical trials, particularly their sensitivity in the early and preclinical stages of the disease, which hampers their reliability as indicators of AD progression. The Functional Activities Questionnaire (FAQ) demonstrated the most substantial weighted mean change over 12weeks, followed by the Mini-Mental State Examination (MMSE). Functional measures outperformed other measure categories. Composite scores of integrated Alzheimer's Disease Rating Scale and Clinical Dementia Rating-Sum of Boxes are more sensitive to change than their individual cognitive components, possibly driven by the functional components of the score. Neuropsychiatric measures analyzed in this study appeared to be the least sensitive in measuring progression.

Effects of Family Audio Recordings on Depression, Cognitive Function, and Sleep Quality of Individuals With Alzheimer's Disease: A Randomized Controlled Trial.

To explore the effects of family audio recordings on depression, cognitive function, and sleep quality among individuals with Alzheimer's disease in nursing homes. A randomized controlled study design was used, and 107 participants with Alzheimer's disease were stratified and randomly assigned to groups based on Clinical Dementia Rating Scale scores. The control group received usual care and health education, and the experimental group received usual care, health education, and a family audio recording intervention. The experimental group showed significantly lower depression scores compared to the control group post-intervention. A within-group comparison of sleep quality scores in the experimental group was significantly different. At post-intervention, cognitive function scores in the control group significantly decreased compared to before the intervention. Family audio recording interventions helped alleviate depression symptoms in individuals with Alzheimer's disease, improved their sleep quality, and delayed the progression of cognitive decline to some extent. [Journal of Gerontological Nursing, xx(x), xx-xx.].

Characterizing the progression from mild cognitive impairment to dementia: a network analysis of longitudinal clinical visits

BackgroundWith the recent surge in the utilization of electronic health records for cognitive decline, the research community has turned its attention to conducting fine-grained analyses of dementia onset using advanced techniques. Previous works have mostly focused on machine learning-based prediction of dementia, lacking the analysis of dementia progression and its associations with risk factors over time. The black box nature of machine learning models has also raised concerns regarding their uncertainty and safety in decision making, particularly in sensitive domains like healthcare.ObjectiveWe aimed to characterize the progression of health conditions, such as chronic diseases and neuropsychiatric symptoms, of the participants in Mayo Clinic Study of Aging (MCSA) from initial mild cognitive impairment (MCI) diagnosis to dementia onset through network analysis.MethodsWe used the data from the MCSA, a prospective population-based cohort study of cognitive aging, and examined the changing association among variables (i.e., participants’ health conditions) from the first visit of MCI diagnosis to the visit of dementia onset using network analysis. The number of participants for this study are 97 with the number of visits ranging from 2 visits (30 months) to 7 visits (105 months). We identified the network communities among variables from three-fold collection of instances: (i) the first MCI diagnosis, (ii) progression to dementia, and (iii) dementia diagnosis. We determine the variables that play a significant role in the dementia onset, aiming to identify and prioritize specific variables that prominently contribute towards developing dementia. In addition, we explore the sex-specific impact of variables in relation to dementia, aiming to investigate potential differences in the influence of certain variables on dementia onset between males and females.ResultsWe found correlation among certain variables, such as neuropsychiatric symptoms and chronic conditions, throughout the progression from MCI to dementia. Our findings, based on patterns and changing variables within specific communities, reveal notable insights about the time-lapse before dementia sets in, and the significance of progression of correlated variables contributing towards dementia onset. We also observed more changes due to certain variables, such as cognitive and functional scores, in the network communities for the people who progressed to dementia compared to those who does not. Most changes for sex-specific analysis are observed in clinical dementia rating and functional activities questionnaire during MCI onset are followed by chronic diseases, and then by NPI-Q scores.ConclusionsNetwork analysis has shown promising potential to capture significant longitudinal changes in health conditions, spanning from the MCI diagnosis to dementia progression. It can serve as a valuable analytic approach for monitoring the health status of individuals in cognitive impairment assessment. Furthermore, our findings indicate a notable sex difference in the impact of specific health conditions on the progression of dementia.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease.

Identifying individuals with early-stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau positron emission tomography (PET) in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16), logopenic variant Primary Progressive Aphasia (n = 15), and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent magnetic resonance imaging (MRI), tau PET, and amyloid PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, Cohen's d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = .30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = .10), tau in other functional networks (R2 = .11-.26), and the magnitude of cortical atrophy (R2 = .20) and amyloid burden (R2 = .09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients one year later. This simple measure could aid the development of a personalized prognostic, monitoring, and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

Effects of traditional Chinese medicine on outcomes and costs of dementia care: results from a retrospective real-world study

ObjectivesThis study aims to assess the impact of Traditional Chinese Medicine (TCM) on dementia patients, utilizing real-world data. Specifically, it seeks to evaluate how TCM influences clinical outcomes by examining changes in the Clinical Dementia Rating (CDR) and Mini-Mental State Examination (MMSE) scores, as well as its effect on medical expenses over a two-year period. Data from a multi-center research database spanning from 2004 to 2021 will be used to achieve these objectives, addressing the current gap in empirical data concerning intuitive outcomes and cognitive function assessments.MethodsPropensity score matching was adopted to improve comparability among the intervention and control groups. Due to repeated dependent variable measurements, the generalized estimating equation was used to control for socio-demographic characteristics, regional characteristics, and Western medicine treatments for dementia.ResultsAfter propensity score matching, a total of 441 research subjects were included: 90 in the TCM intervention group and 351 in the non-TCM intervention group. The results of multivariate regression analysis showed that compared with the non-TCM intervention group, the MMSE scores in the TCM intervention group increased by 0.608 points each year. The annual change in CDR scores in the TCM intervention group was 0.702 times that of the non-TCM utilization group. After TCM intervention, annual outpatient expenses increased by US$492.2, hospitalization expenses increased by US$324.3, and total medical expenses increased by US$815.9, compared with the non-intervention group.ConclusionsTCM interventions significantly decelerate cognitive decline in dementia patients, evidenced by slower reductions in MMSE scores and mitigated increases in CDR scores. However, these benefits are accompanied by increased medical expenses, particularly for outpatient care. Future healthcare strategies should balance the cognitive benefits of TCM with its economic impact, advocating for its inclusion in dementia care protocols.

Apathy, gait slowness, and executive dysfunction (AGED) triad: opportunities to predict and delay dementia onset.

This study investigates whether older adults diagnosed with the apathy, gait impairment, and executive dysfunction (AGED) triad, frequently associated with cerebrovascular disease and confounded with depression, have earlier dementia onset. We followed 322 community-dwelling older individuals (mean age 72.0 ± 6.4years; 58.3% women) free of dementia at baseline for up to 9years. The AGED triad was identified when gait slowness (< 1m/s), apathy (assessed by Geriatric Depression Scale-3A with ≥ 2 items), and executive dysfunction (assessed by the 75th percentile of Trail Making Test-part B by age range) were simultaneously present. Incident dementia was diagnosed using the clinical dementia rating scale. Over the 9-year follow-up (mean 45.1 ± 28.6months), 44 participants (13.6%) converted to dementia. Sixteen participants (5.0%) were diagnosed with AGED triad + and showed a significantly higher risk of earlier conversion to dementia compared with AGED triad- (hazard ratio = 5.08, 95%CI 2.16-11.97; p = 0.0001), as well as to those with only one AGED factor or fewer AGED factors. Hypertension and diabetes were 2 and 3 times more prevalent, respectively, in individuals with AGED triad + . These findings suggest that the AGED triad serves as a simplified and effective behavioral marker for accelerated progression to dementia.

Identifying Gaps and Barriers in Alzheimer's Disease and Related Dementia Research and Management in Low- and Middle-Income Countries: A Survey of Health Professionals and Researchers.

The significant increase in Alzheimer's disease and related dementia prevalence is a global health crisis, acutely impacting low- and lower-middle and upper-middle-income countries (LLMICs/UMICs). The objective of this study is to identify key barriers and gaps in dementia care and research in LLMICs and UMICs. We conducted an international, cross-sectional survey among clinicians and healthcare professionals (n = 249 in 34 countries) across LLMICs and UMICs, exploring patient demographics, use of clinical diagnosis, dementia evaluation, screening/evaluation tools, and care and treatment. Significant disparities were found in diagnostic practices, access to assessments, and access to care. On average, clinicians in LLMICs saw more patients, had less time for evaluations, lower use of formal screening and tools, and less access to biomarkers. They were also under-resourced compared to UMICs. The findings provide insights for policymakers, healthcare organizations, and researchers to address the complex challenges associated with dementia care in diverse settings. Addressing these challenges requires a multipronged approach involving local, national, and international stakeholders.

Referral Sources Across Racial and Ethnic Groups at Alzheimer's Disease Research Centers.

Despite the need to increase engagement of underrepresented groups (URG) in Alzheimer's disease and related dementias (ADRD) studies, enrollment remains low. Compare referral sources across racial and ethnic groups among participants enrolled in ADRC studies. Data for this cross-sectional secondary analysis were extracted from the National Alzheimer's Coordinating Center Uniform Data Set. We performed mixed effects logistic regression models using generalized estimating equations for professional referral versus non-professional referral by racial and ethnic group, adjusted for age, gender, education, visit year, and Clinical Dementia Rating scale (CDR) with a random effect for study site. Included in the analysis were 48,330 participants across 46 ADRCs (mean [SD] age, 71.3 [10.5] years; 20,767 female [57%]; 4,138 Hispanic [8.6%]; 1,392 non-Hispanic Asian [2.9%]; 6,766 non-Hispanic Black [14%] individuals; and 676 individuals [1.4%] of other races. Non-Hispanic Black and Asian participants had lower odds of being referred by a professional contact compared to non-Hispanic White participants (Black: adjusted OR = 0.61, 95% CI = 0.44-0.86, p = 0.005; Asian: adjusted OR = 0.65, 95% CI, p = 0.004). In participants who had completed an MRI, there was no significant difference in referral source across ethnic and racial groups. Further studies are needed to better understand the systemic and structural factors that contribute to differences in referral sources and disparities in recruitment of URG into ADRD studies.

Association of Vascular Risk Factors and Cerebrovascular Pathology With Alzheimer Disease Pathologic Changes in Individuals Without Dementia.

Vascular risk factors (VRFs) and cerebral small vessel disease (cSVD) are common in patients with Alzheimer disease (AD). It remains unclear whether this coexistence reflects shared risk factors or a mechanistic relationship and whether vascular and amyloid pathologies have independent or synergistic influence on subsequent AD pathophysiology in preclinical stages. We investigated links between VRFs, cSVD, and amyloid levels (Aβ1-42) and their combined effect on downstream AD biomarkers, that is, CSF hyperphosphorylated tau (P-tau181), atrophy, and cognition. This retrospective study included nondemented participants (Clinical Dementia Rating < 1) from the European Prevention of Alzheimer's Dementia (EPAD) cohort and assessed VRFs with the Framingham risk score (FRS) and cSVD features on MRI using visual scales and white matter hyperintensity volumes. After preliminary linear analysis, we used structural equation modeling (SEM) to create a "cSVD severity" latent variable and assess the direct and indirect effects of FRS and cSVD severity on Aβ1-42, P-tau181, gray matter volume (baseline and longitudinal), and cognitive performance (baseline and longitudinal). A total cohort of 1,592 participants were evaluated (mean age = 65.5 ± 7.4 years; 56.16% F). We observed positive associations between FRS and all cSVD features (all p < 0.05) and a negative association between FRS and Aβ1-42 (β = -0.04 ± 0.01). All cSVD features were negatively associated with CSF Aβ1-42 (all p < 0.05). Using SEM, the cSVD severity fully mediated the association between FRS and CSF Aβ1-42 (indirect effect: β = -0.03 ± 0.01), also when omitting vascular amyloid-related markers. We observed a significant indirect effect of cSVD severity on P-tau181 (indirect effect: β = 0.12 ± 0.03), baseline and longitudinal gray matter volume (indirect effect: β = -0.10 ± 0.03; β = -0.12 ± 0.05), and baseline cognitive performance (indirect effect: β = -0.16 ± 0.03) through CSF Aβ1-42. In a large nondemented population, our findings suggest that cSVD is a mediator of the relationship between VRFs and CSF Aβ1-42 and affects downstream neurodegeneration and cognitive impairment. We provide evidence of VRFs indirectly affecting the pathogenesis of AD, highlighting the importance of considering cSVD burden in memory clinics for AD risk evaluation and as an early window for intervention. These results stress the role of VRFs and cerebrovascular pathology as key biomarkers for accurate design of anti-amyloid clinical trials and offer new perspectives for patient stratification.

Association of Resilience-Related Life Experiences on Variability on Age of Onset in Dominantly Inherited Alzheimer Disease.

It remains unknown whether the associations between protective lifestyles and sporadic dementia risk reported in observational studies also affect age at symptom onset (AAO) in autosomal dominant Alzheimer disease (ADAD) with predominant genetic influences. We investigated the associations between resilience-related life experiences and interindividual AAO variability in ADAD. We performed a longitudinal and confirmatory analysis of the Dominantly Inherited Alzheimer Network prospective observational cohort (January 2009-June 2018, follow-up duration 2.13 ± 2.22 years), involving clinical, CSF, and lifestyle/behavioral assessments. We performed a 2-pronged comprehensive resilience assessment in each cohort. Cohort 1, incorporating the general resilience definition (cognitive maintenance [Clinical Dementia Rating = 0] despite high pathology), included carriers during the periods of significant CSFp-tau181 variability and grouped into resilience/resistance outcome bins according to the dichotomous pathologic and cognitive statuses, subcategorized by the estimated years from expected symptom onset (EYO). Cohort 2, focused on ADAD-specific genetically determined time frame characterizing the onset predictability, included asymptomatic participants with available preclinical lifestyle data and AAO outcomes and grouped into delayed or earlier AAO relative to the parental AAO. Associations of cognitive, CSFp-tau181, and lifestyle/behavioral predictors with binary outcomes were investigated using logistic regression. Of 320 carriers (age 38.19 ± 10.94 years, female 56.25%), cohort 1 included 218 participants (39.00 ± 9.37 years, 57.34%) and cohort 2 included 28 participants (43.34 ± 7.40 years, 71.43%). In cohort 1, 218 carriers after -20 EYO, when the interindividual variability (SD) of CSFp-tau181 first became more than twice greater in carriers than in noncarriers, were grouped into low-risk control (asymptomatic, low pathology, n = 103), high-resilience (asymptomatic despite high pathology, n = 60), low-resilience (symptomatic despite low pathology, n = 15), and susceptible control (symptomatic, high pathology, n = 40) groups. Multivariable predictors of high resilience, controlling for age and depression, included higher conscientiousness (odds ratio 1.051 [95% CI 1.016-1.086], p = 0.004), openness to experience (1.068 [1.005-1.135], p = 0.03) (vs. susceptible controls), and agreeableness (1.082 [1.015-1.153], p = 0.02) (vs. low resilience). From 1 to 3 years before parental AAO (cohort 2), the multivariable predictor of delayed AAO, controlling for CSFp-tau181, was higher conscientiousness (0.916 [0.845-0.994], p = 0.036). Among the cognitively and socially integrated life experiences associated with resilience, measures of conscientiousness were useful indicators for evaluating resilience and predicting future dementia onset in late preclinical ADAD.

Adenosine Metabolism Pathway Alterations in Frontal Cortical Neurons in Schizophrenia.

Schizophrenia is a neuropsychiatric illness characterized by altered neurotransmission, in which adenosine, a modulator of glutamate and dopamine, plays a critical role that is relatively unexplored in the human brain. In the present study, postmortem human brain tissue from the anterior cingulate cortex (ACC) of individuals with schizophrenia (n = 20) and sex- and age-matched control subjects without psychiatric illness (n = 20) was obtained from the Bronx-Mount Sinai NIH Brain and Tissue Repository. Enriched populations of ACC pyramidal neurons were isolated using laser microdissection (LMD). The mRNA expression levels of six key adenosine pathway components-adenosine kinase (ADK), equilibrative nucleoside transporters 1 and 2 (ENT1 and ENT2), ectonucleoside triphosphate diphosphohydrolases 1 and 3 (ENTPD1 and ENTPD3), and ecto-5'-nucleotidase (NT5E)-were quantified using real-time PCR (qPCR) in neurons from these individuals. No significant mRNA expression differences were observed between the schizophrenia and control groups (p > 0.05). However, a significant sex difference was found in ADK mRNA expression, with higher levels in male compared with female subjects (Mann-Whitney U = 86; p < 0.05), a finding significantly driven by disease (t(17) = 3.289; p < 0.05). Correlation analyses also demonstrated significant associations (n = 12) between the expression of several adenosine pathway components (p < 0.05). In our dementia severity analysis, ENTPD1 mRNA expression was significantly higher in males in the "mild" clinical dementia rating (CDR) bin compared with males in the "none" CDR bin (F(2, 13) = 5.212; p < 0.05). Lastly, antipsychotic analysis revealed no significant impact on the expression of adenosine pathway components between medicated and non-medicated schizophrenia subjects (p > 0.05). The observed sex-specific variations and inter-component correlations highlight the value of investigating sex differences in disease and contribute to the molecular basis of schizophrenia's pathology.

Increases in amyloid-β42 slow cognitive and clinical decline in Alzheimer's disease trials.

Positive effects of new anti-amyloid-β (Aβ) monoclonal antibodies in Alzheimer's disease (AD) have been attributed to brain amyloid reduction. However, most anti-Aβ antibodies also increase the CSF levels of the 42-amino acid isoform (Aβ42). We evaluated the associations of changes in CSF Aβ42 and brain Aβ-PET with cognitive and clinical end points in randomized trials of anti-Aβ drugs that lowered (β- and γ-secretase inhibitors) or increased CSF Aβ42 levels (anti-Aβ monoclonal antibodies) to test the hypothesis that post-treatment increases in CSF Aβ42 levels are independently associated with cognitive and clinical outcomes. From long-term (≥12 months) randomized placebo-controlled clinical trials of anti-Aβ drugs published until November 2023, we calculated the post-treatment versus baseline difference in ADAS-Cog (cognitive subscale of the Alzheimer's Disease Assessment Scale) and CDR-SB (Clinical Dementia Rate-Sum of Boxes) and z-standardized changes in CSF Aβ42 and Aβ-PET Centiloids (CL). We estimated the effect size [regression coefficients (RCs) and confidence intervals (CIs)] and the heterogeneity (I2) of the associations between AD biomarkers and cognitive and clinical end points using random-effects meta-regression models. We included 25 966 subjects with AD from 24 trials. In random-effects analysis, increases in CSF Aβ42 were associated with slower decline in ADAS-Cog (RC: -0.55; 95% CI: -0.89, -0.21, P = 0.003, I2 = 61.4%) and CDR-SB (RC: -0.16; 95% CI: -0.26, -0.06, P = 0.002, I2 = 34.5%). Similarly, decreases in Aβ-PET were associated with slower decline in ADAS-Cog (RC: 0.69; 95% CI: 0.48, 0.89, P < 0.001, I2 = 0%) and CDR-SB (RC: 0.26; 95% CI: 0.18, 0.33, P < 0.001, I2 = 0%). Sensitivity analyses yielded similar results. Higher CSF Aβ42 levels after exposure to anti-Aβ drugs are independently associated with slowing cognitive impairment and clinical decline. Increases in Aβ42 may represent a mechanism of potential benefit of anti-Aβ monoclonal antibodies in AD.

Enhancing guidelines for managing cognitively impaired drivers: Insights from Western evidence for Asian adaptation.

The global incidence of dementia is increasing, and cognitively impaired drivers are at a higher risk of crashes compared to healthy drivers. Doctors face challenges in assessing these at-risk drivers, with questionable adherence to existing guidelines. This study aimed to review and compare guidelines for managing cognitively impaired drivers from various countries. A scoping review was conducted to identify relevant guidelines, which were then descriptively compared with Singapore's guideline. Eleven guidelines from 8 countries: US (n=2), Canada (n=2), UK (n=2), Ireland, Belgium, Australia, New Zealand and Singapore were reviewed. All guidelines support driving assessments and conditional licensing in ordinary (i.e. non-professional) drivers with dementia. Canada stands out for not allowing co-piloting and geographical restrictions in conditional licensing practice. Few guidelines provide indemnity for doctors reporting to licensing authorities, and communication about the impact of dementia on car insurance is rarely addressed. Most Western guidelines include evidence-based approaches, provisions for drivers with mild cognitive impairment and early discussions on transitioning from driving. A clinic-based functional screening toolbox and 2 clinical algorithms (1 with and 1 without the Clinical Dementia Rating scale) were identified as having universal applicability. Singapore's guideline, by comparison, is outdated and lacks both developmental rigour and guidance on managing mild cognitive impairment and transitioning drivers out of driving. Comprehensive, evidence-based guidelines from Western countries provide valuable resources that can help Singapore design or update its guideline.

Longitudinal association of depressive symptoms with cognition and neuroimaging biomarkers in cognitively unimpaired older adults, mild cognitive impairment, and Alzheimer's disease.

We aimed to longitudinally examine the relationship between depression and cognitive function and investigate the mediating effects of imaging indicators in this relationship. 2,251 subjects with longitudinal assessment of geriatric depression scale, Mini-Mental State Examination, Montreal Cognitive Assessment, Clinical Dementia Rating-Sum of Boxes (CDRSB), Alzheimer's Disease Assessment Scale11, Alzheimer's Disease Assessment Scale13 and imaging of 3DT1, diffusion tensor imaging, fluid-attenuated inversion recovery, arterial spin labeling, fluorodeoxyglucose positron emission tomography, 18F-AV45-PET, and 18F-AV1451-PET were included from the Alzheimer's Disease Neuroimaging Initiative database. The multivariate mixed-effects models were employed to analyze the correlation between geriatric depression scale scores, cognitive function, and imaging indicators. The sgmediation software package was utilized to analyze the mediating effects of imaging indicators. The geriatric depression scale was negatively correlated with Mini-Mental State Examination and Montreal Cognitive Assessment, and positively correlated with CDRSB, Alzheimer's Disease Assessment Scale11, and Alzheimer's Disease Assessment Scale13 when the subjects were not grouped. The geriatric depression scale was negatively correlated with Montreal Cognitive Assessment and positively correlated with Alzheimer's Disease Assessment Scal13 in groups with baseline diagnosis of early mild cognitive impairment and late mild cognitive impairment. Furthermore, depression was associated with regional imaging indicators, while cognitive function was linked to broad imaging indicators. Some of these indicators were related to both depression and cognitive function, playing a mediating role in their relationship. Depression was related to cognitive function, especially in subjects with mild cognitive impairment. Some imaging indicators may represent the underlying basis for the association between depression and cognitive function.

Global genomic profile of hippocampal endothelial cells by single-nuclei RNA sequencing in female diabetic mice is associated with cognitive dysfunction.

Type II diabetes mellitus (T2D) is a chronic metabolic disease and a risk factor for cardiovascular disease and cerebrovascular dysfunction including vascular dementia. Sex differences in the prevalence of T2D, dementia, and global genomic changes in the brain have been observed; however, most studies have been performed in males. Therefore, our aim was to evaluate the consequence of T2D on cognitive function and decipher the underlying molecular transcriptomic mechanisms of endothelial cells in an important brain memory center, the hippocampus, using a female murine diabetes model. We assessed cognitive function, metabolic parameters, and then performed hippocampal single-nuclei RNA sequencing (snRNA seq) in adult female db/db and control wild-type (WT) mice. db/db mice exhibited characteristic T2D metabolism with hyperglycemia, hyperinsulinemia, and hyperlipidemia when compared with WT mice. Female db/db mice presented cognitive decline compared with wild-type mice, as determined by open field and Morris water maze tests. snRNAseq showed that T2D induced significant changes in the global transcriptomic profile of hippocampal endothelial cells by modulating the expression of not only protein-coding genes but also long noncoding RNAs. These genes regulate cell-cell junctions, cell chemotaxis, actin cytoskeleton organization, and cell adhesion, suggesting that diabetes increases endothelial cell permeability. Observed genomic changes also correlated with the genetics of persons with clinical Alzheimer's disease and vascular dementia. In conclusion, T2D, by transcriptional and posttranscriptional regulation, regulates endothelial cell dysfunction predictive of increased vascular permeability, and negatively impacts cognitive function. Our work has implications for sex-specific molecular therapeutic targets for dementia in females.NEW & NOTEWORTHY Female db/db mice presented cognitive decline as determined by open field and Morris water maze tests. snRNAseq showed that T2D induced changes in the global transcriptomic profile of hippocampal endothelial cells by modulating the expression of not only protein-coding genes but also long noncoding RNAs. These genes regulate cell-cell junctions, cell chemotaxis, or cell adhesion, suggesting increased endothelial permeability. Genomic changes correlated with the genetics of persons with clinical Alzheimer's disease and vascular dementia.

IPECAD Modeling Workshop 2023 Cross-Comparison Challenge on Cost-Effectiveness Models in Alzheimer’s Disease

ObjectivesDecision-analytic models assessing the value of emerging Alzheimer’s disease (AD) treatments are challenged by limited evidence on short-term trial outcomes and uncertainty in extrapolating long-term patient-relevant outcomes. To improve understanding and foster transparency and credibility in modeling methods, we cross-compared AD decision models in a hypothetical context of disease-modifying treatment for mild cognitive impairment (MCI) due to AD. MethodsA benchmark scenario (US setting) was used with target population MCI due to AD and a set of synthetically generated hypothetical trial efficacy estimates. Treatment costs were excluded. Model predictions (10-year horizon) were assessed and discussed during a 2-day workshop. ResultsNine modeling groups provided model predictions. Implementation of treatment effectiveness varied across models based on trial efficacy outcome selection (clinical dementia rating – sum of boxes, clinical dementia rating – global, mini-mental state examination, functional activities questionnaire) and analysis method (observed severity transitions, change from baseline, progression hazard ratio, or calibration to these). Predicted mean time in MCI ranged from 2.6 to 5.2 years for control strategy and from 0.1 to 1.0 years for difference between intervention and control strategies. Predicted quality-adjusted life-year gains ranged from 0.0 to 0.6 and incremental costs (excluding treatment costs) from −US$66 897 to US$11 896. ConclusionsTrial data can be implemented in different ways across health-economic models leading to large variation in model predictions. We recommend (1) addressing the choice of outcome measure and treatment effectiveness assumptions in sensitivity analysis, (2) a standardized reporting table for model predictions, and (3) exploring the use of registries for future AD treatments measuring long-term disease progression to reduce uncertainty of extrapolating short-term trial results by health-economic models.

18F]FDG PET integrated with structural MRI for accurate brain age prediction.

Brain aging is a complex and heterogeneous process characterized by both structural and functional decline. This study aimed to establish a novel deep learning (DL) method for predicting brain age by utilizing structural and metabolic imaging data. The dataset comprised participants from both the Universal Medical Imaging Diagnostic Center (UMIDC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The former recruited 395 normal control (NC) subjects, while the latter included 438 NC subjects, 51 mild cognitive impairment (MCI) subjects, and 56 Alzheimer's disease (AD) subjects. We developed a novel dual-pathway, 3D simple fully convolutional network (Dual-SFCNeXt) to estimate brain age using [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET) and structural magnetic resonance imaging (sMRI) images of NC subjects as input. Several prevailing DL models were trained and tested using either MRI or PET data for comparison. Model accuracies were evaluated using mean absolute error (MAE) and Pearson's correlation coefficient (r). Brain age gap (BAG), deviations of brain age from chronologic age, was correlated with cognitive assessments in MCI and AD subjects. Both PET- and MRI-based models achieved high prediction accuracy. The leading model was the SFCNeXt (the single-pathway version) for PET (MAE = 2.92, r = 0.96) and MRI (MAE = 3.23, r = 0.95) on all samples. By integrating both PET and MRI images, the Dual-SFCNeXt demonstrated significantly improved accuracy (MAE = 2.37, r = 0.97) compared to all single-modality models. Significantly higher BAG was observed in both the AD (P < 0.0001) and MCI (P < 0.0001) groups compared to the NC group. BAG correlated significantly with Mini-Mental State Examination (MMSE) scores (r=-0.390 for AD, r=-0.436 for MCI) and the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) scores (r = 0.333 for AD, r = 0.372 for MCI). The integration of [18F]FDG PET with structural MRI enhances the accuracy of brain age prediction, potentially introducing a new avenue for related multimodal brain age prediction studies.

Clinical Study on Mesenchymal Stem Cell Factors Therapy for Alzheimer’s Disease

Background: Alzheimer’s disease (AD), characterized by cognitive decline, lacked effective cures. Mesenchymal stem cell (MSC) factors (MSCFs) offered a new approach by promoting brain tissue repair and modulating immune responses, presenting a promising alternative to AD treatment with minimal risks. Aim: This study aimed to investigate the effects of MSCF on AD and to compare the effects with traditional MSC treatments. Methods: Sixty patients were divided into control and observation groups, with 30 cases in each group. The control group were injected intravenously with 10 mL of MSCs (5.0 × 109 L-1) plus 100 mL normal saline (once every 5 days for six consecutive treatments). The observation group received intramuscular injections of 0.5 mL (1 mL for the first dose) of MSCF (every other day for 15 consecutive treatments). Amyloid-β 42 (Aβ42) and Tau protein concentrations in cerebrospinal fluid were determined by ELISA pretreatment and at 1, 3, and 6 months’ post-treatment. The Clinical Dementia Rating of AD patients was recorded at these intervals to evaluate treatment efficacy. Results: Aβ42 levels increased, and Tau protein levels decreased in both groups. The CDR score dropped post treatment. The total effective rate and clinical cure rate were 86.67% and 6.70% in the control group and 100% and 40% in the observation group, respectively. MSCF and MSCs uniquely impact AD. Conclusion: MSCs contributed to damaged nerve cell repair, new nerve cell differentiation, and the participation of some dormant nerve cells in physiological activity. MSCF offered a small-dose, rapid, and safe treatment with simple operation.

The HOPE4MCI study: AGB101 treatment slows progression of entorhinal cortex atrophy in APOE ε4 non‐carriers with mild cognitive impairment due to Alzheimer's disease

AbstractIntroductionHippocampal hyperactivity is a hallmark of prodromal Alzheimer's disease (AD) that predicts progression in patients with amnestic mild cognitive impairment (aMCI). AGB101 is an extended‐release formulation of levetiracetam in the dose range previously demonstrated to normalize hippocampal activity and improve cognitive performance in aMCI. The HOPE4MCI study was a 78‐week trial to assess the progression of MCI due to AD. As reported in Mohs et al., the decline in the Clinical Dementia Rating Sum of Boxes score (CDR‐SB) was reduced by 40% in apolipoprotein E (APOE) ε4 non‐carriers over the 78‐week duration of the study with a negligible effect in carriers. Here we report an exploratory analysis of the effects of AGB101 on neuroimaging and biomarker measures in the 44 APOE ε4 non‐carriers who completed the 78‐week protocol.MethodsStructural magnetic resonance imaging scans obtained at baseline and after 78 weeks were analyzed using the Automated Segmentation of Hippocampal Subfields software providing volume measures of key structures of the medial temporal lobe relevant to AD progression. Blood samples collected at 78 weeks in the study were analyzed for plasma biomarkers.ResultsTreatment with AGB101 significantly reduced atrophy of the left entorhinal cortex (ERC) compared to placebo. This reduction in atrophy was correlated with less decline in the CDR‐SB score over 78 weeks and with lower neurofilament light chain (NfL), a marker of neurodegeneration.DiscussionThe HOPE4MCI study showed that APOE ε4 non‐carriers treated with AGB101 demonstrated a substantially more favorable treatment effect compared to carriers. Here we report that treatment with AGB101 in non‐carriers of APOE ε4 significantly reduced atrophy of the left ERC over 78 weeks. That reduction in atrophy was closely coupled with the change in CDR‐SB and with plasma NfL indicative of neurodegeneration in the brain. These exploratory analyses are consistent with a reduction in neurodegeneration in APOE ε4 non‐carriers treated with AGB101 before a clinical diagnosis of dementia.Highlights AGB101 slows entorhinal cortex (ERC) atrophy in apolipoprotein E (APOE) ε4 non‐carriers with mild cognitive impairment (MCI) due to Alzheimer's disease (AD). Slowing ERC atrophy by AGB101 is associated with less Clinical Dementia Rating Sum of Boxes decline. Slowing ERC atrophy by AGB101 is associated with lower neurofilament light chain. AGB101 treatment reduces neurodegeneration in APOE ε4 non‐carriers with MCI due to AD.

Predicting CDR status over 36 months with a recall-based digital cognitive biomarker.

Word-list recall tests are routinely used for cognitive assessment, and process scoring may improve their accuracy. We examined whether Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) derived, process-based digital cognitive biomarkers (DCBs) at baseline predicted Clinical Dementia Rating (CDR) longitudinally and compared them to standard metrics. Analyses were performed with Alzheimer's Disease Neuroimaging Initiative (ADNI) data from 330 participants (mean age=71.4±7.2). We conducted regression analyses predicting CDR at 36 months, controlling for demographics and genetic risk, with ADAS-Cog traditional scores and DCBs as predictors. The best predictor of CDR at 36 months was M, a DCB reflecting recall ability (area under the curve =0.84), outperforming traditional scores. Diagnostic results suggest that M may be particularly useful to identify individuals who are unlikely to decline. These results suggest that M outperforms ADAS-Cog traditional metrics and supports process scoring for word-list recall tests. More research is needed to determine further applicability with other tests and populations. Process scoring and latent modeling were more effective than traditional scoring. Latent recall ability (M) was the best predictor of Clinical Dementia Rating decline at 36 months. The top digital cognitive biomarker model had odds ≈ 90 times greater than the top Alzheimer's Disease Assessment Scale-Cognitive subscale model. Particularly high negative predictive value supports literature on cognitive testing as a useful screen. Consideration of both cognitive and pathological outcomes is needed.