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

Introduction: We previously applied generalized additive models for location, scale, and shape to derive amyloid β-negative next-generation norms (NGN) for a comprehensive neuropsychological battery. Here, we evaluated the accuracy of NGN in detecting cognitive impairment compared to traditional norms (TN).

Methods: This multicenter study included N = 2405 participants classified as cognitively normal (CN, n = 987) or with mild cognitive impairment (MCI, n = 1418) using conventional criteria. All participants underwent neuropsychological testing and cerebrospinal fluid Alzheimer's disease (AD) biomarker assessment. We used actuarial neuropsychological criteria to reclassify all participants using TN and NGN. Diagnostic groups were compared on cognitive performance, AD biomarker positivity, and longitudinal cognitive trajectories.

Results: Nineteen percent of TN-classified CN participants were diagnosed with MCI by NGN, whereas 3% of TN-classified MCI were identified as CN by NGN. NGN demonstrated stronger associations with neuropsychological performance, AD biomarkers, and progression than TN.

Discussion: NGN enhance the detection of objective cognitive impairment, with direct implications for clinical practice and research.

Highlights: Next-generation norms (NGN) reclassify one of every five cases from cognitively normal (CN) to mild cognitive impairment (MCI).This group shows poor cognitive performance and a high prevalence of amyloid β positivity.NGN-based diagnosis of MCI predicts cognitive progression on follow-up.Results indicate that NGN improve the detection of objective cognitive impairment.NGN can inform biomarker use, therapy indication, and clinical trial design.

Introduction: We assessed associations of cancer diagnoses with neuropathology of Alzheimer's disease (AD) and related dementias.

Methods: We retrieved 2288 cases from the National Alzheimer Coordinating Center (NACC) cohort with available information on cancer diagnoses and neuropathological scoring of Braak stages, Thal amyloid phases, neuritic plaques, TDP-43 pathology, and Lewy body pathology. We used Bayesian ordinal regression to assess associations of prevalent or incident cancer diagnoses with global cognition and postmortem neuropathological scores.

Results: We found extreme evidence (Bayes factor [BF] > 2000) that both prevalent and incident cancer diagnoses were associated with better global cognition, strong evidence (BF = 26) for an association of a prevalent cancer diagnosis with lower TDP-43 pathology, and weak evidence (BF = 3.2) for an association with lower Lewy body pathology.

Discussion: Our data suggest that selective survival and biological effects may contribute to the lower risk of dementia in people with a cancer diagnosis.

Highlights: A prevalent diagnosis of cancer was associated with a lower risk of cognitive decline in older individuals.A prevalent diagnosis of cancer was associated with a lower risk of TDP-43 pathology and Lewy body pathology in older individuals.Effects of cancer on TDP-43 pathology were maintained when controlling for degree of cognitive decline.

[This corrects the article DOI: 10.1002/dad2.70217.].

Introduction: Effective dementia prevention requires understanding the distribution of modifiable risk factors and identifying high-risk subgroups. We estimated the prevention potential in Germany and identified risk profiles to inform precision public health.

Methods: We analyzed nationally representative data from the 2023 German Aging Survey (n = 4992). Population attributable fractions and potential impact fractions were computed for established modifiable risk factors. Relative risks were taken from meta-analyses. Latent class analysis identified risk profiles.

Results: An estimated 36% of dementia cases in Germany are attributable to modifiable risk factors. Reducing their prevalence by 15%-30% could prevent 170,000-330,000 cases by 2050. We identified four risk profiles-metabolic, sensory impairment, alcohol, and lower-risk-each associated with demographic and regional characteristics.

Discussion: Our findings highlight considerable national prevention potential and reveal population subgroups with shared risk patterns. These profiles provide a foundation for designing targeted, equitable, and efficient dementia prevention strategies.

Highlights: 36% of dementia cases in Germany are linked to modifiable risk factors.A 15% reduction in risk factor prevalence could prevent 170,000 cases by 2050.Key contributors: depression, hearing loss, low education, and obesity.Data-driven risk profiles identified (e.g., metabolic, sensory, low-risk).Risk profiles strongly associated with sociodemographic characteristics.

Introduction: Blood-based biomarkers, most notably plasma phosphorylated tau (p-tau)217, have transformed the diagnostic landscape of Alzheimer's disease (AD).

Methods: We applied an unsupervised machine learning approach to tau positron emission tomography (PET) imaging in 606 participants (age 73.95 ± 7.72; 309 female) to identify AD subtypes. Within each subtype, we evaluated plasma p-tau217 levels, their association with regional tau PET uptake, differences between cognitively unimpaired (CU) and cognitively impaired (CI) individuals, and relationships to cognitive performance.

Results: Four subtypes were identified: limbic, medial temporal lobe (MTL) sparing, posterior, and lateral temporal (l temporal). Plasma p-tau217 was elevated in CI versus CU in limbic, posterior, and l temporal subtypes and strongly associated with tau deposition and cognitive performance. In the MTL-sparing subtype, p-tau217 showed a significant association with tau but no elevation in CI and no relationship to cognition.

Discussion: These findings indicate that p-tau217's diagnostic utility varies across AD subtypes, reflecting distinct biological mechanisms not captured by current blood biomarkers.

Highlights: Plasma phosphorylated tau (p-tau)217 differentiated cognitively unimpaired from impaired individuals in most subtypes, with the notable limitation of the medial temporal lobe (MTL)-sparing group.P-tau217 level was linked to regional tau accumulation as measured by tau positron emission tomography, across all subtypes.The MTL-sparing subtype appeared to be unique, as p-tau217 was not elevated in cognitively impaired individuals, and there was no clear relationship between p-tau217 levels and cognitive performance.

Introduction: Mild cognitive impairment (MCI) is underdiagnosed by primary care providers (PCPs), with detection rates as low as 6%-15%. Predictive models support the identification of individuals at risk, enabling timely intervention.

Methods: This retrospective study was conducted on 271,054 cognitively unimpaired and 14,501 confirmed MCI cohorts from electronic health records. A machine learning model was developed with a data-driven variable selection approach based on demographics and comorbidities.

Results: From 101 variables, 26 were chosen for the final model, achieving an overall area under the curve (AUC) of 86%. Age-stratified AUCs were 79.1% (40-49), 77.0% (50-64), 76.9% (65-79), and 74.4% (≥80), showing the highest predictive performance in younger age groups.

Discussion: Demographic factors and comorbidities can serve as effective predictors for the risk of MCI. The model demonstrates strong predictive performance and assists as a triage tool for PCPs, facilitating the identification of individuals with MCI for early treatment.

Highlights: Predictive algorithms using electronic health records (EHRs) are useful for identifying individuals at risk for mild cognitive impairment (MCI) to triage for further clinical evaluation.A machine learning model was developed using EHR data to predict those at risk for MCI.The model identified 26 variables that were able to distinguish the MCI from non-MCI cohorts.The model accurately detected MCI across the cohort (area under the curve [AUC] = 86%) and trended best for younger age groups (AUC was 77%, 77%, and 74% in 50-64, 65-79, and ≥80 age groups, respectively).Implementation of a triage tool could be used to detect MCI across aging patient populations sooner, leading to a timelier diagnosis, intervention, and treatment management.

Introduction: Alzheimer's disease (AD) is characterized by progressive white matter (WM) degeneration. Circulating lipid metabolites may serve as early indicators of WM microstructural changes. In this study, we investigated the associations between plasma lipid metabolites and WM integrity across the cognitive continuum.

Methods: We included 173 participants from the Alzheimer's Disease Neuroimaging Initiative (51 cognitively normal [CN], 88 mild cognitive impairment [MCI], 34 AD) database. Plasma metabolites were quantified using targeted lipidomics, and diffusion tensor imaging (DTI) metrics were derived from 52 predefined WM regions.

Results: Regression analyses revealed widespread metabolite-DTI associations in MCI, particularly within the corpus callosum. The callosal body and splenium showed significant inverse associations with phosphatidylcholines (PCs) and multiple lysophosphatidylcholines (lysoPCs) species. In AD group, inverse relationships between PCs and the internal capsule were observed.

Discussion: Circulating lipid metabolites are linked to WM microstructure in both prodromal and clinical AD, supporting their potential as sensitive biomarkers of early vulnerability and disease progression.

Highlights: Circulating lipid metabolites link to white matter integrity in early Alzheimer's disease (AD)Phosphatidylcholines (PCs), lysophosphatidylcholines (LPCs), and propionylcarnitine associate with tract-specific diffusion magnetic resonance imaging (dMRI) metricsNo metabolite-white matter associations detected in established ADPlasma metabolites may serve as biomarkers of early white matter degeneration.

Introduction: To address an urgent need for a scalable, accurate blood test for brain amyloid pathology that provides a conclusive result for the greatest number of patients, we developed a multi-analyte algorithmic test combining phosphorylated tau (p-tau) 217 with four other biomarkers.

Methods: Multiplexed digital immunoassays measured p-tau 217, amyloid beta 42/40, glial fibrillary acidic protein, and neurofilament light chain in 730 symptomatic individuals (training set) to establish an algorithm with cutoffs, and 1082 symptomatic individuals (validation set) from three independent cohorts to identify brain amyloid pathology.

Results: The algorithmic in validation gave an area under the curve = 0.92, yielding 90% agreement with amyloid positron emission tomography and cerebrospinal fluid. Positive predictive value was 92% at 55% prevalence. The multi-marker algorithm reduced the intermediate zone ≈ 3-fold from 34.4% to 11.9% versus p-tau 217 alone. Diagnostic performance was similar across subgroups.

Discussion: The LucentAD Complete multi-analyte blood test demonstrated high clinical validity for brain amyloid pathology detection while substantially reducing inconclusive intermediate results.

Highlights: We developed a multi-analyte blood test for assessing brain amyloid status that significantly minimizes the ambiguous "intermediate zone," a key limitation of plasma phosphorylated tau (p-tau) 217 alone.Our test combines plasma levels of p-tau 217, amyloid beta 42/40 ratio, glial fibrillary acidic protein, and neurofilament light chain for a more comprehensive evaluation of amyloid status.We rigorously validated the test's clinical performance in > 1000 samples from symptomatic individuals across three independent cohorts, using cerebrospinal fluid biomarkers and amyloid positron emission tomography as comparators.

Introduction: There are few studies analyzing cerebrospinal fluid (CSF) in patients with cerebral amyloid angiopathy (CAA). Our goal was to compare blood-brain barrier and neurodegeneration markers in CSF in CAA patients with and without hemorrhagic markers.

Methods: In a retrospective study of patients with CAA (Boston criteria version 2.0) identified from the Aachen Memory Database and from in-hospital admission records, we compared CSF neurodegeneration markers and albumin ratio (a blood-brain barrier permeability marker) in patients with and without hemorrhagic markers.

Results: Among 371 patients with CAA, 113 patients had hemorrhagic markers (30.5%). Lower amyloid beta (Aβ) 42, lower Aβ40, and higher albumin ratio were independently associated with the presence of hemorrhagic markers and an increasing number of lobar microbleeds. Cortical superficial siderosis and a higher imaging burden of CAA were associated with total tau protein.

Discussion: Presence of hemorrhagic markers in CAA patients is associated with lower CSF Aβ42 and Aβ40 and higher blood-brain barrier permeability.

Highlights: New diagnostic criteria allow for the diagnosis of CAA without hemorrhagic markers.CAA hemorrhagic markers are associated with lower Aβ42 and Aβ40 in CSF.CAA hemorrhagic markers are associated with higher blood-brain barrier permeability.Higher imaging burden of CAA is associated with higher total tau protein in CSF.

Introduction: Plasma biomarkers are minimally invasive tool for identifying Alzheimer's disease pathology. However, evaluation of their clinical utility remains limited.

Methods: This ongoing, open-label, randomized, two-arm, multicenter, U.S., prospective, observational study enrolled 609 patients presenting for initial evaluation of cognitive impairment. Patients were randomized into tau phosphorylated at position 217 (p-tau217) tested (n = 391) and untested (n = 218) arms.

Results: Change in working diagnosis was observed for 70.5% of patients with a t-tau217 result (positive or negative) inconsistent with baseline working diagnosis compared to 2.3% with a result consistent with baseline working diagnosis and 15.6% of untested patients. When the result was consistent with baseline working diagnosis, a significant 15.7% increase in diagnostic confidence was observed compared to 1.7% in untested patients and 5.0% when the result was inconsistent with baseline working diagnosis.

Discussion: P-tau217 testing changed health care providers' intended management and working diagnosis and increased confidence in the diagnosis.

Highlights: Evaluation of the clinical utility of plasma tau phosphorylated at position 217 (p-tau217) for identifying Alzheimer's disease pathology has been limited.In this study, the impact of p-tau testing on health care providers' diagnostic thinking in patients under evaluation for cognitive impairment was assessed.When the result was inconsistent with the working diagnosis, a change in the working diagnosis was observed in 70.5% of tested patients.When the result was consistent, diagnostic confidence increased by 15.7%.P-tau217 testing demonstrated clinical utility by changing the working diagnosis, increasing diagnostic confidence, and altering intended patient management.