Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring最新文献

[This corrects the article DOI: 10.1002/dad2.70174.].

Introduction: This study aimed to determine whether simulated driving performance can reliably predict cognitive impairment in stroke survivors.

Methods: Cognitively impaired (n = 35) and normal (n = 54) stroke survivors completed a simulated driving course with reactive, distracted, and route-planning sections. Performance was assessed using lane departures, average speed, brake reaction time, task completion time, and route accuracy.

Results: Logistic regression models correctly distinguished cognitive status in 77.5% of cases for reactive and distracted driving, and 80.9% for route planning. Notably, the route planning task also achieved the highest classification rate of cognitively impaired participants (∼70%). Receiver operating characteristic (ROC) analyses on the strongest predictors from each driving section revealed significant areas under the curve (AUCs), with optimal cutoffs identifying cognitively impaired participants at 70%-80% accuracy.

Discussion: These findings provide a critical foundation for developing simulator-based assessments as practical, functionally relevant screening tools for identifying cognitive impairment and determining driving readiness post-stroke.

Highlights: Stroke survivors were tested on simulated driving tasks.Driving metrics were lane departures, speed, reaction time, and route accuracy.Cognitive status was predicted with greater than 75% accuracy.Simulators may be a clinical tool for assessing post-stroke driving readiness.

Introduction: It is unclear how dementia affects loss in life expectancy (LE). In this registry-based study, we aimed to study sex differences in LE and loss in LE in dementia, mild cognitive impairment (MCI), and subjective cognitive decline (SCD).

Methods: A total of 16,358 patients diagnosed with dementia, MCI, or SCD from the Norwegian Registry of Persons Assessed for Cognitive Symptoms (NorCog) during 2009-2022 were included and followed up for mortality. Sex differences in LE and loss in LE were predicted using flexible parametric survival models and sex-specific mortality in the general population as reference.

Results: Among dementia patients, women with dementia had the largest loss in LE: 17 years loss at 60 years; correspondingly, men lost 13.5 years. Similar patterns were observed for MCI and dementia subtypes.

Discussion: Women with dementia or MCI had a larger loss in LE compared to men with these diagnoses.

Highlights: Women with dementia had the largest loss in life expectancy compared to the general population.The excess female loss in life expectancy was also evident for all the dementia subtypes and for mild cognitive impairment.The loss in life expectancy was more pronounced in younger patients with dementia, with a loss of 17 years in women at 60 years of age. Men, in comparison, lost 13.5 years at the same age.Subjective cognitive decline was associated with a minor loss in life expectancy in both sexes.

Introduction: The discrepancy between biological and modeled brain ages-the brain-age gap (BAG)-could indicate potential neuropsychological changes. This study verified if and how longitudinal BAG changes were associated with neuropsychological functions and Alzheimer's disease-related biomarkers in individuals with mild cognitive impairment (MCI).

Methods: One hundred thirty-eight individuals with MCI and 103 healthy controls (HCs) with three rounds of magnetic resonance imaging scanning were selected from the Alzheimer's Disease Neuroimaging Initiative. We applied support vector regression on functional connectivity for modeling the brain age and further calculated the BAG.

Results: Longitudinal BAG changes were higher in participants with MCI compared to HCs. Larger BAG fluctuations were correlated with poorer cognitive performance and more severe depressive symptoms in patients with MCI. Neurofilament light chain and phosphorylated tau levels were associated with the longitudinal BAG changes.

Discussion: Present findings demonstrated the necessity of incorporating longitudinal BAG in monitoring the neuropsychological status among cognitively vulnerable populations.

Highlights: Brain-age gap (BAG) changes are sensitive indicators of cognitive vulnerability in aging.BAG changes were larger in patients with mild cognitive impairment than in the controls.Longitudinal BAG changes were associated with worse cognitive-affective states.The plasma neurofilament light chain and cerebrospinal fluid phosphorylated tau levels were associated with the BAG changes.

Introduction: Machine learning applied to neuroimaging can help with medical diagnosis and early detection by identifying biomarkers of subtle changes in brain structure and function. The effectiveness of advanced diffusion MRI (dMRI) methods for pre-dementia classification remains largely unexplored, particularly when combined with CSF biomarkers.

Methods: We implemented XGBoost machine learning models to evaluate the classification potential of dMRI parameters (derived using NODDI, C-NODDI, MAP, or SMI), CSF biomarkers of Alzheimer's pathology (Tau, pTau, Aβ42, Aβ40), and pairwise dMRI + CSF combinations in distinguishing cognitive normality from mild cognitive impairment.

Results: MAP-RTAP (AUC = 0.78) and pTau/Aβ42 (AUC = 0.76) were the best performing individual biomarkers. Combining C-NDI derived using C-NODDI and Aβ42/Aβ40 achieved the highest performance (AUC = 0.84) and accuracy (0.84), while other combinations optimized either sensitivity (0.93) or specificity (0.88).

Discussion: dMRI biomarkers demonstrate comparable performance to CSF biomarkers, with notable improvements achieved when combined. This study highlights dMRI's effectiveness for enhancing early AD detection.

Highlights: Advanced multishell diffusion MRI provides equivalent performance as CSF biomarkers in classifying MCICombining diffusion MRI and CSF biomarkers improves classification performanceStatistical diffusion MRI models perform best when used individually to classify MCIThe pTau/Aβ42 ratio outperforms other individual CSF biomarkers in MCI diagnosisBiophysical diffusion MRI models achieve the best performance when combined with CSF data.

Introduction: Blood-based biomarkers for Alzheimer's disease (AD) have the potential to improve diagnostic accessibility, but their clinical interpretation requires understanding of variability and biological influences.

Methods: We repeatedly sampled blood from 57 adults referred for lumbar puncture as part of a cognitive evaluation at a memory clinic. We measured serum phosphorylated- tau-181 (s-p-tau181) and plasma amyloid beta (Aβ)42/40 ratio (p-Aβ42/Aβ40) and evaluated the impact of renal and blood-brain barrier (BBB) function.

Results: Test-retest analysis revealed large variability of s-p-tau181 and small for p-Aβ42/Aβ40. Markers of renal function and BBB integrity significantly influenced s-p-tau181 levels, whereas p-Aβ42/Aβ40 was not affected.

Discussion: This study emphasizes the need for caution when interpreting longitudinal changes in s-p-tau181. Inter-individual variability is to a large degree due to susceptibility to biological influences where a novel association with integrity of BBB function were identified. These results have implications for the clinical application of blood-based biomarkers in AD diagnostics and monitoring.

Highlights: Blood phosphorylated- tau-181 (p-tau181) shows high test-retest variability in memory clinic patients.Blood amyloid beta (Aβ)42/Aβ40 ratio is stable but has poor diagnostic accuracy.Renal function and blood-brain barrier (BBB) integrity affect blood p-tau181 levels.Caution is needed when interpreting longitudinal changes in blood p-tau181.Renal and BBB disorders should be considered when assessing blood p-tau181.

Introduction: Simple screening tools are critical for assessing Alzheimer's disease (AD)-related pre-dementia changes. This study investigated longitudinal scores from the Quick Dementia Rating System (QDRS), a brief study partner-reported measure, in relation to baseline levels of the AD biomarker plasma pTau217 in individuals unimpaired at baseline.

Methods: Data from the Wisconsin Registry for Alzheimer's Prevention (N = 639) were used to examine whether baseline plasma pTau217 (ALZpath assay on Quanterix platform) modified QDRS or Preclinical Alzheimer's Cognitive Composite (PACC3) trajectories (mixed-effects models; time = age). pTau217*age interaction effects (e.g., high vs low pTau217 simple age slopes) were compared across outcomes.

Results: Higher baseline pTau217 levels were associated with faster functional (QDRS) and cognitive (PACC3) decline. Effect sizes were similar between PACC3 and QDRS. Exploratory analyses showed increased risk of transitioning to impaired QDRS classifications in those with high-baseline pTau217.

Discussion: This study demonstrates the utility of QDRS for tracking pre-dementia AD-related decline.

There are a relatively small number of investigations into brain aging in those with intellectual and developmental disability (I/DD). This project seeks to (1) characterize the internationally available multi-omics Alzheimer's disease (AD) biomarker studies including those with I/DD, and (2) discuss future research directions. PubMed, Web of Science, and Scopus were searched under the following criteria: cross-sectional or longitudinal AD-omics studies on adults (18 +) with I/DD. 532 studies were identified, 186 studies were evaluated for full-text, 79 studies were excluded, and 117 studies were extracted. Most biological specimens were analyzed in blood, plasma, or serum. Metabolomics, hormonomics, and transcriptomics were most understudied. Sex differences were investigated in nine studies. Two studies included participants with non-Down syndrome neurodevelopmental disorders. European-based city populations were primarily represented across studies. Future studies including a broader range of I/DD presentations, and considering sex differences, comorbidities, and novel biomarkers beta synuclein are interesting future directions.

Highlights: Small sample sizes, cross-sectional designs, and few prospective and retrospective studies highlight the need for more rigorous research design.A focus on European-based city populations and Down syndrome (DS) clinical groups prompts the need for inclusive, community-based recruitment methods across broader clinical and ethnic groups.The vesicle-associated membrane protein 2 (VAMP2) shows promise for early detection of synaptic degeneration, potentially across I/DD groups, showing correlations with CSF biomarkers of Alzheimer's disease, axonal injury, and cognitive performance in DS.

Introduction: Subjective cognitive complaints often precede declines in objective measures of cognitive performance. Associations of incipient Alzheimer's disease (AD) neuropathology with subjective cognitive complaints may be detectable earlier than associations with neuropsychological testing among cognitively normal individuals.

Methods: We examined the independent associations of positron emission tomography measures of amyloid beta and tau pathologies with longitudinal subjective complaints and memory among 91 cognitively normal Baltimore Longitudinal Study of Aging participants using linear mixed effects models. Subjective complaints and memory performance were assessed with the Cognitive Failures Questionnaire and the California Verbal Learning Test, respectively.

Results: Greater parahippocampal tau, independent of amyloid, was associated with higher subjective complaints (estimate = 0.25, standard error [SE] = 0.1, P = $0.015$ ), while greater entorhinal tau corresponded to an attenuated increase in complaints over time (estimate = -0.06, SE = 0.03, P = $0.047$ ). Hippocampal tau was associated with steeper memory decline (estimate = -0.03, SE = 0.01, P = $0.040$ ).

Conclusion: Subjective cognitive complaints may be a reflection of early cerebral tau pathology in cognitively normal individuals.

Highlights: Greater parahippocampal tau was linked with higher subjective cognitive complaints.Entorhinal tau was associated with slower increases in cognitive complaints over time.Subjective complaints may reflect early amyloid and tau in cognitively normal adults.

Introduction: This study investigated gender differences in cognitive reserve (CR) in subjective cognitive decline (SCD) and examined the impact of gender-CR interaction on the risk of progression to mild cognitive impairment (MCI).

Methods: We enrolled 440 SCD patients and estimated CR using premorbid intelligence (Test di Intelligenza Breve [TIB]). To account for socio-cultural differences, patients were stratified by birth cohort (pre-/post-1950). A Markov random-field (MRF) model explored relationships between gender, CR, education, and age. Logistic regression assessed MCI progression risk.

Results: Women showed lower TIB scores than men (p < 0.001). The MRF model revealed an inverse connection between TIB and female gender, while no link was observed between TIB and generation. Progression to MCI was predicted by age at onset (p < 0.001), apolipoprotein E (APOE) status (p = 0.002), and TIB (p = 0.018), but not gender.

Discussion: Gender has an impact on CR, but not through socio-economic variables. In turn, CR influenced the risk of MCI progression, whereas gender did not.

Highlights: Subjective cognitive decline (SCD) women presented lower cognitive reserve (CR) levels than men, despite similar education levels.Social-cultural factors did not explain these gender differences in CR in SCD.The gender-CR interaction was not mediated by social-cultural factors.The risk of progression to mild cognitive impairment (MCI) was influenced by CR but not by gender.