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

Introduction: Impaired cerebrovascular reactivity (CVR) is common in type 2 diabetes (T2D) patients and is a risk factor for dementia. However, most prior functional magnetic resonance imaging (fMRI) studies in T2D disregarded the impact of impaired CVR on brain activation patterns. This study investigated the relationship between CVR and brain activation during an fMRI task in T2D patients.

Methods: Seventy-four T2D patients underwent a working-memory (WM) fMRI task. CVR was measured by the breath-holding index test using transcranial Doppler (TCD). Regression analyses examined associations between CVR and brain activation and between glycated hemoglobin (HbA1c) and activation with/without adjusting for CVR.

Results: An association between CVR and brain activation was found in the left middle and inferior frontal gyri. Adjusting for CVR led to a different pattern of HbA1c-related activation.

Discussion: The findings highlight methodological implications, emphasizing the importance of accounting for impaired CVR when analyzing and interpreting fMRI data in T2D patients.

Highlights: The study found that cerebrovascular reactivity impacts brain activation patterns during a working memory task in type 2 diabetes patients.Accounting for cerebrovascular reactivity altered the brain regions showing activation related to working memory and glycemic control.The findings highlight the importance of considering vascular factors when interpreting fMRI data in populations with vascular dysfunction.

Introduction: Knowledge gaps remain about the prognosis of mild cognitive impairment (MCI). Conversion rates to dementia vary widely, and reversion to normal cognition has gained attention. This review updates evidence on MCI conversion risk and probability of stability and reversion.

Methods: We searched databases for studies on MCI prognosis with ≥3 years of follow-up, established criteria for MCI and dementia, and performed a meta-analysis using a random-effects model to assess conversion risk, reversion, and stability probability. Meta-regressions identified sources of heterogeneity and guided subgroup analysis.

Results: From 89 studies (mean follow-up: 5.2 years), conversion risk was 41.5% (38.3%-44.7%) in clinical and 27.0% (22.0%-32.0%) in population-based studies, with Alzheimer's dementia as the most common outcome. Stability rates were 49.3% (clinical) and 49.8% (population). Reversion was 8.7% (clinical) and 28.2% (population).

Discussion: Our findings highlight higher conversion in clinical settings and 30% reversion in population studies, calling for sustainable care pathway development.

Highlights: Prognosis for mild cognitive impairment (MCI) varies by setting; dementia risk is higher and the probability of reversion is lower in clinical-based studies.In both clinical and population settings, cognitive stability is ≈50%.A reorganization of health services could ensure sustainable care for individuals with MCI.Significant heterogeneity in MCI studies impacts data interpretation; follow-up length is crucial.Long-term prognosis studies on MCI in low- and middle-income countries are urgently needed.

Identification of early-stage Alzheimer's disease (AD) remains a challenge due to limited specialist availability, diagnostic access, disease awareness, and cultural factors. Blood-based biomarkers (BBBM) could play a critical role in the identification and referral of patients suspected of AD to specialty care. A multidisciplinary AD Biomarker Task Force was convened to evaluate current biomarker use cases, define an optimal biomarker-enabled AD diagnostic care pathway, and understand factors impacting adoption. The Task Force identified opportunities to support biomarker-enabled AD diagnostic care pathway adoption, including streamlining risk assessment and screening by leveraging digital tools, activating primary care providers through education, generating data to expand applicability to diverse populations, and advocating for aligned policies and quality measures. Adoption of BBBMs in the primary care setting will be critical to improve early AD detection. However, challenges to pathway adoption persist and will require action from clinicians, payers, policy makers, and patients to address.

Highlights: Blood-based biomarkers can streamline the identification of AD in primary care.Future biomarker-enabled diagnostic care pathways will leverage digital assessments.Education, data generation, and policy advocacy are vital to encourage BBBM use.Implementation of AD care pathways requires the activation of diverse stakeholders.

Introduction: The brain age gap estimation (BrainAGE) method uses a machine learning model to generate an age estimate from structural magnetic resonance imaging (MRI) scans. The goal was to study the association of brain age with Alzheimer's disease (AD) imaging and plasma biomarkers.

Methods: One hundred twenty-three individuals from the Indiana Memory and Aging Study underwent structural MRI, amyloid and tau positron emission tomography (PET), and plasma sampling. The MRI scans were processed using the software program BrainAgeR to receive a "brain age" estimate. Plasma biomarker concentrations were measured, and partial Pearson correlation models were used to evaluate their relationship with brain age gap (BAG) estimation (BrainAGE = chronological age - MRI estimated brain age).

Results: Significant associations between BAG and amyloid and tau levels on PET and in plasma were observed depending on diagnostic categories.

Discussion: These findings suggest that BAG is potentially a biomarker of pathology in AD which can be applied to routine brain imaging.

Highlights: Novel research that uses an artificial intelligence learning tool to estimate brain age.Findings suggest that brain age gap is associated with plasma and positron emission tomography Alzheimer's disease (AD) biomarkers.Differential relationships are seen in different stages of disease (preclinical vs. clinical).Results could play a role in early AD diagnosis and treatment.

Introduction: Whether temporal proximity to parental onset of dementia (PPO) can be used to estimate timing of the preclinical stage of sporadic Alzheimer's disease (AD) remains uncertain.

Methods: We investigated cross-sectionally adults aged > 50 without dementia included in the European Prevention of Alzheimer's Dementia (EPAD) study. PPO was tested as a predictor of quantitative levels of cerebrospinal fluid (CSF) β-amyloid (1-42) (Aβ1-42) in those with a parental history of dementia (n = 688) and of phosphorylated tau (p-tau) and EPAD neuropsychological examination (ENE) subscores in an amyloid positive subgroup (n = 226). Possible interactions were explored.

Results: Shorter PPO predicted lower CSF Aβ1-42 level (β = 9.357; T = 4.161; p < 0.001), interacting with apolipoprotein E (APOE) -𝜀4 carriage in a dose-dependent manner. Concomitant APOE-𝜀2 carriage appeared to provide protection. PPO did not predict p-tau levels or cognitive performance.

Discussion: PPO may provide a valid method of stratifying risk of early AD pathologic change in APOE-𝜀4 carriers, with empirical and clinical applications.

Highlights: Proximity to age of parental dementia onset can predict amyloid accrualThe effect is APOE-𝜀4 dose-dependent and APOE-𝜀2 appears to provide protectionPPO does not appear to predict further advancement along the AD continuumIn the era of anti-amyloid treatments, this may inform timing of amyloid screeningUsed as an empirical metric, PPO could help elucidate the natural history of LOAD.

Introduction: This study examines the link between daytime and nighttime excessive sleep and cognition, cognitive decline, and dementia in individuals with existing mild cognitive impairment (MCI).

Methods: Using data from the Swedish longitudinal study Good Aging in Skåne, participants aged 60-102 years were retrospectively classified as MCI based on cognitive testing. The average follow-up time was 6.59 years. Mixed linear models assessed cross-sectional and longitudinal associations between excessive sleep patterns (napping ≥2 h or nighttime sleep ≥9 h) and multiple cognitive domains. Cox regressions estimated dementia risk for excessive sleep.

Results: Of 4930 participants, 2052 (41%) had MCI. Excessive daytime napping and nighttime sleep were associated with worse cognition and cognitive decline. Excessive napping and nighttime sleep were also linked to higher dementia risk (hazard ratios: 1.75 and 1.86, respectively).

Discussion: These findings suggest that excessive sleep in MCI is associated with further cognitive decline and dementia.

Highlights: Excessive daytime napping and nighttime sleep are linked cognitive decline for those with MCI.Excessive sleep during the day or at night heighten dementia risk.Worse test scores across multiple cognitive domains were observed for excessive daytime nappers.Excessive sleep in MCI may be a warning sign for further cognitive decline.

Introduction: This study aimed to explore the association between plasma amyloid-β oligomerization tendency (OAβ) and cognitive performance in Alzheimer's disease (AD) and determine its predictive value for outcomes of mild cognitive impairment (MCI).

Methods: Plasma from 727 subjects (286 AD, 260 MCI, and 181 controls) in a case registry was analyzed using the multimer detection system (MDS) to measure plasma OAβ.

Results: Elevated plasma OAβ was strongly correlated with multidomain cognitive performance in patients with MCI and AD. Patients with MCI with high baseline plasma OAβ demonstrated a higher risk of progressing to dementia (hazard ratio = 1.083, 95% confidence interval [CI] 1.032-1.137). Baseline plasma OAβ effectively predicted MCI-dementia conversion (area under the curve [AUC] = 0.824, 95% CI 0.752-0.897).

Discussion: The real-world findings underscore the clinical relevance of plasma OAβ as a potential predictor for the conversion from mild cognitive impairment (MCI) to dementia.

Highlights: We recruit study participants of Alzheimer's dementia (AD), mild cognitive impairment (MCI), and cognitively normal controls in a case registry.We use the multimer detection system (MDS) to measure plasma amyloid-β oligomerization tendency (OAβ).We observe that elevated plasma OAβ strongly correlates with multidomain cognitive performance in patients with MCI and AD.MCI individuals with high baseline plasma OAβ demonstrate a higher risk of progressing to dementia.The real-world findings underscore the clinical relevance of plasma Oaβ as a potential predictor for the conversion from MCI to dementia.

Introduction: Retinal vasculometry (RV) provides a neurovascular biomarker which may relate to cognitive status. However, the presence and form of association remains unclear and unexamined at scale.

Methods: Artificial intelligence-enabled RV measures from 66,350 UK Biobank study participants were related to combined cognition scores. Differences in RV were examined per standard deviation (SD) increase in cognitive score, using multilevel linear regression, adjusted for age, sex, measurement center, ethnicity, and within-person RV clustering.

Results: One hundred ten thousand two hundred eighty-two retinal images from 63,165 (95%) participants (mean age 56.6 years, 55.5% female) were analyzed. A one SD increase in cognition score was strongly associated with increased arteriolar width, arteriolar tortuosity, increased venular width particularly among those < 50 years and venular area among those > 50 years; also, inversely associated with venular tortuosity, and arteriolar and venular width variance.

Discussion: These easily accessible, affordable, and non-invasive RV measures should be evaluated further as an early predictor of future neurodegenerative disease.

Highlights: How cognitive status relates to retinal vasculometry (RV) measures remains uncertain and unexamined at scale.Using data from a large population-based study (UK Biobank) we show strong graded associations between cognitive status and RV, which contrast with some RV associations observed with aging. Specifically, increased arteriolar tortuosity, arteriolar and venular width (at younger ages), and area are positively associated, and venular tortuosity and arteriolar and venular width variability are inversely associated with higher cognitive status, all showing strong, graded, precise relationships. These associations appeared to be strongest for fluid intelligence and prospective memory tests.These easily accessible, non-invasive RV measures provide a neurovascular marker indicative of cognitive status, which should be evaluated as early predictors of neurodegenerative disease.

Introduction: In neuropsychological diagnostics, the assignment of cognitive tests to domains is usually not empirically based. Hence, we aimed to assess the dimensionality structure of cognition in individuals with Parkinson's disease (PD) and conceptually replicate the findings in cognitively healthy individuals (CHIs).

Methods: We performed Exploratory Graph Analysis (EGA) for dimensionality analysis of cognitive test scores in N = 698 individuals with PD from the DEMPARK/LANDSCAPE study. Redundancy was reduced based on Unique Variable Analysis (UVA) before re-performing EGA. CHI data (N = 60,398) served as a conceptual replication base.

Results: EGA identified five dimensions. After removing redundancy identified by UVA, EGA identified a unidimensional structure of cognitive test scores. The findings were conceptually replicated in CHIs.

Discussion: The findings imply the need to re-evaluate the composition of cognitive test batteries to reduce redundancy and improve the validity of cognitive diagnostics. Cognition may be better described as a network of interrelated cognitive functions rather than a factorial structure of latent cognitive domains.

Highlights: Cognitive test scores of the same paradigm were strongly associated with each other.This finding indicates redundancy in the cognitive test battery.After removing redundancy, scores were best represented by unidimensional structures.The findings in Parkinson's disease were conceptually replicated in healthy controls.The results suggest that cognition should be viewed as a complex "network" of interrelated functions.

Introduction: This study examined the association of longitudinal atrophy with baseline cerebrospinal fluid (CSF) amyloid beta (Aβ, A) and phosphorylated tau (p-tau, T) biomarkers (Aβ42/40, p-tau181) in 406 cognitively unimpaired (CU) individuals (6.670 years of follow-up on average, up to 13 imaging visits) to assess whether A+ is associated with Alzheimer's disease-like atrophy and whether this depends on p-tau181 levels.

Methods: An A-T- CU group free from abnormal neurodegeneration (N) was identified using a robust normative approach and used to model normal age-related atrophy via z-scoring. Linear mixed-effects models tested differences in longitudinal atrophy between A+ and A-T-N- individuals and between A/T subgroups.

Results: A+ was associated with worse atrophy within and beyond the medial temporal lobe, even at low levels of p-tau181.

Discussion: Neurodegeneration likely begins soon after the onset of abnormal Aβ pathology. Clinical intervention at the earliest signs of Aβ pathology may be needed to mitigate further neurodegeneration.

Highlights: An A-T-N- control group was identified using a robust normative approachA+ was associated with accelerated atrophy in cognitively unimpaired individualsAtrophy was observed even at low p-tau181 levels.