Journal of Alzheimer's Disease最新文献

BackgroundRetinal imaging is proposed as a biomarker for Alzheimer's disease, but evidence linking retinal changes to cerebral amyloid remains inconsistent, particularly in preclinical populations.ObjectiveThis article evaluates whether retinal structural and microvascular changes measured by optical coherence tomography (OCT) and OCT-angiography (OCT-A) are associated with cerebral amyloid-β (Aβ) burden assessed by positron emission tomography (PET).MethodsPubMed, Embase, Scopus, and Web of Science were searched on November 10, 2025. Two reviewers independently did screening, extraction, and quality assessment. Extracted outcomes included macular and peripapillary retinal nerve fiber layer and ganglion cell-inner plexiform layer thickness, vessel density, foveal avascular zone size, and PET tracers.ResultsTwenty-two studies including 1616 participants met inclusion criteria. Fifteen assessed OCT, five OCT-A, and two both. Among cognitively normal individuals, seven studies compared retinal nerve fiber layer thickness by Aβ status, with only one reporting a significant difference. Overall, OCT metrics showed no consistent differences by Aβ status. OCT-A results were similarly inconsistent, with one study linking larger foveal avascular zone to Aβ positivity. Substantial heterogeneity in imaging devices, segmentation methods, and PET quantification was observed, and few studies adjusted for these factors.ConclusionsCurrent evidence does not demonstrate a consistent relationship between retinal OCT or OCT-A metrics and cerebral Aβ burden measured by PET. Methodological heterogeneity, small sample sizes, and limited statistical rigor contribute to inconclusive results. Standardized imaging protocols and longitudinal studies are required to determine whether retinal imaging can serve as a reliable non-invasive biomarker for early Alzheimer's disease.

BackgroundDifferentiating subjective cognitive decline (SCD) from mild cognitive impairment (MCI) in amyloid-negative (A-) individuals is clinically relevant for early evaluation along the Alzheimer's disease (AD) pathway.ObjectiveTo assess whether plasma biomarkers discriminate between A-SCD and A-MCI and compare their performance.MethodsWe studied 114 amyloid PET-negative participants (93 A-SCD, 21 A-MCI) aged ≥60 years from multicenter cohorts. Plasma Aβ₄₂/Aβ₄₀ ratio, glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), and phosphorylated tau 181 (pTau181) were measured using Simoa. Associations with MCI were estimated with logistic regression; discrimination was assessed by ROC analysis with AUCs and pairwise AUC comparisons using 1000 bootstrap resamples.ResultsStandardized log (GFAP) was associated with MCI in univariate analysis (OR 2.32; 95% CI 1.35-4.00; p = 0.002) and after adjustment for age and sex (OR 2.45; 1.27-4.74; p = 0.008). GFAP showed moderate discrimination (AUC 0.71; 0.59-0.82), whereas Aβ₄₂/Aβ₄₀, NFL, and pTau181 did not. Pairwise AUC differences favored GFAP over Aβ₄₂/Aβ₄₀ (ΔAUC 0.34; p = 0.020), NFL (0.21; p = 0.032), and pTau181 (0.29; p = 0.005).ConclusionsIn this A- cohort, plasma GFAP was the most informative biomarker for distinguishing MCI from SCD, likely reflecting astrocytic activation. Given modest accuracy and limited disease specificity, GFAP may be most useful as part of a multimodal panel rather than a stand-alone test.

BackgroundEmerging evidence supports the clinical utility of music therapy for Alzheimer's disease (AD), yet robust clinical evidence remains limited.ObjectiveThis study aimed to systematically evaluate the multidimensional effects of music therapy on individuals with AD and to identify optimal intervention parameters and cumulative duration thresholds to guide clinical implementation.MethodsWe conducted a systematic review using RevMan 5.4, analyzing 24 randomized controlled trials (n = 2316) from Chinese and English databases up to January 2025.ResultsCompared to controls, music therapy significantly improved cognition (MD = 2.14, 95%CI = 0.88∼3.41, p = 0.0009), reduced neuropsychiatric symptoms (SMD = -0.55, 95%CI = -0.99∼-0.12, p = 0.01) and anxiety (MD = -4.37, 95%CI = -6.68∼-2.06, p = 0.0002), enhanced quality of life (SMD = 0.51, 95%CI = 0.02∼1.01, p = 0.04), and alleviated caregiver burden (SMD = -0.75, 95%CI = -0.94∼-0.55, p < 0.00001). The optimal regimen involved: frequency >3 sessions/week (p = 0.002), duration <40 min/session (p = 0.03), and intervention period ≥12 weeks (p = 0.002). A staged care model progressing from individual to group-based approaches is recommended (all p < 0.05). Minimum cumulative intervention durations for symptom improvement were: ≥1440 min for quality of life, ≥1800 min for behavioral and psychological symptoms, and ≥3360 min for cognition (all p < 0.05).ConclusionsMusic therapy demonstrates multidimensional benefits for persons living with AD, with distinct cumulative dose thresholds required for improving specific clinical symptoms, providing valuable guidance for clinical practice.

Cognitive composites combine scores from multiple neuropsychological tests and demonstrate greater sensitivity to Alzheimer's disease (AD) related cognitive changes than individual tests. This review examines the development, composition and validity of cognitive composites to detect AD-related cognitive changes. The included cognitive composites were evaluated using four criteria: cognitive domains assessed; neuropsychological tests used, the inclusion of non-neuropsychological measures (e.g., Mini-Mental State Examination) that produce a global score themselves; and statistical methods used to calculate the composite. Existing composites fall into two categories: domain-specific (e.g., episodic memory, executive function, attention) or general composites combining multiple cognitive domains while incorporating clinical and functional measures. Psychometric properties were not consistently reported across all the studies. Therefore, a standardized validation framework is proposed to address these inconsistencies. Future work should focus on systematically evaluating optimized weighting, including data from clinical and functional measures and consistent psychometric reporting for assessing and monitoring cognitive dysfunction in early AD.

BackgroundThe Montreal Cognitive Assessment (MoCA) is widely used for cognitive screening. Despite numerous studies showing that MoCA scores are affected by demographic variables including age, education, and race, the instrument is typically evaluated using a raw score or simple one-point education correction in clinical practice.ObjectiveIn this study, we comprehensively evaluate the diagnostic accuracy of the MoCA in a large cohort of individuals being evaluated for mild cognitive impairment or dementia.MethodsWe used data from the National Alzheimer's Coordinating Center (NACC) database to examine diagnostic accuracy of the MoCA, using both raw scores and Z-scores subject to non-linear demographic correction. We present comprehensive accuracy statistics, concordance with APOE ε4 status, and predictive validity of a mild cognitive impairment classification for the subsequent development of dementia.ResultsWe find that non-linear demographic correction modestly enhances diagnostic performance for individuals with mild cognitive impairment and dementia and results in classifying a higher proportion of APOE ε4 homozygous participants as individuals with dementia as compared to MoCA raw scores.ConclusionsNon-linear demographic correction may improve the diagnostic accuracy of the MoCA and increase concordance with a major known risk factor for Alzheimer's disease (i.e., APOE ε4 status).

BackgroundPlasma phosphorylated tau isoforms 181 (pTau181) and 217 (pTau217) are promising Alzheimer's disease (AD) biomarkers.ObjectiveWe evaluated the performance of pTau181 and pTau217 in the differential diagnostics between AD, other neurodegenerative diseases and non-neurodegenerative participants.MethodsWe included 104 patients with neurodegenerative diseases (37 with AD, 21 with synucleinopathies [SYNU], 24 with frontotemporal dementia [FTD] and 22 with idiopathic normal-pressure hydrocephalus [iNPH]) and 50 participants without neurodegenerative disorders (33 individuals undergoing knee arthroplasty and 17 with psychiatric diagnoses). pTau181 and pTau217 were measured via single-molecule array.ResultspTau181 differentiated AD patients from psychiatric patients with an area under the curve (AUC) of 0.879 and AD patients from all other participants with an AUC of 0.685. pTau181 was higher in patients with AD compared to FTD, iNPH, and non-neurodegenerative (ND) patients. pTau217 differentiated AD patients from psychiatric patients, with an AUC of 0.998, and AD patients from all other groups, with an AUC of 0.835. pTau217 was higher in AD patients compared to ND, FTD, and SYNU patients, but it did not differ between AD and iNPH patients without adjustment for age as a covariate.ConclusionsOur prospective cohort data indicate that pTau217 differentiates AD patients from psychiatric patients, with an excellent AUC value in receiver operating characteristic analysis. Our study supports the use of pTau217 rather than pTau181 as a minimally invasive tool to differentiate AD from non-neurodegenerative diseases (e.g., psychiatric disorders). Further studies are needed to determine the nature of pTau217 in iNPH.

BackgroundBlood-based biomarkers are increasingly used as scalable front-line tools for Alzheimer's disease amyloid evaluation, but most are validated against amyloid positron emission tomography (PET) and/or cerebrospinal fluid (CSF) rather than neuropathology. In a chained validation cascade (neuropathology→PET→CSF→blood), reported performance may depend strongly on the comparator and on how "gray-zone" (indeterminate) results are handled.ObjectiveTo quantify benchmark dependence and gray-zone policy sensitivity in amyloid biomarker validation and characterize plasma-to-neuropathology performance inference from imperfect proxies.MethodsWe assembled a fully auditable evidence core spanning the amyloid cascade with reconstructable 2 × 2 tables. We recomputed positive percent agreement (PPA) and negative percent agreement (NPA) with 95% Wilson confidence intervals under a prespecified primary policy (exclude indeterminates) and two sensitivity policies (indeterminate→negative; indeterminate→positive). Reference-swap drift across benchmarks was summarized with Monte Carlo uncertainty intervals. For plasma-to-neuropathology inference, we combined plasma-PET agreement with tracer-specific PET-autopsy anchors and reported (i) chained-proxy point implications under conditional independence and (ii) partial-identification bounds without conditional independence across prevalence scenarios (π = 10-50%).ResultsUnder the primary policy, Lumipulse plasma pTau217/Aβ42 showed similar agreement across PET, CSF, and composite comparators (PPA 0.97-0.98; NPA ≈0.91), with drift intervals spanning zero. Indeterminates were frequent (∼19-20%) and dominated apparent shifts: indeterminate→negative reduced PPA by 0.13-0.21, whereas indeterminate→positive reduced NPA by 0.17-0.21. Chained-proxy implications for plasma versus neuropathology varied by PET tracer anchor (sensitivity 0.86-0.96; specificity 0.81-0.91), while bounds were wider (sensitivity 0.83-1.00; specificity 0.81-0.98).ConclusionsGray-zone policy is a first-order driver of reported blood-test performance, and proxy-to-proxy agreement does not uniquely identify plasma-to-neuropathology accuracy without explicit assumptions.

BackgroundAcupuncture has clinical potential in treating Alzheimer's disease (AD) and mild cognitive impairment (MCI), but there is a lack of systematic review and presentation of clinical evidence from the perspective of neuroimaging in this field.ObjectiveTo conduct a systematic review of clinical studies on acupuncture for AD and MCI from the perspective of neuroimaging, and to comprehend the evidence distribution of relevant research.MethodsThis article retrieved all the neuroimaging clinical studies on acupuncture treatment for AD and MCI that were published and included in the seven databases from their establishment until February 22, 2025. It analyzed and organized the data based on the PICOS (Population, Intervention, Comparison, Outcome, Study design) principle, and presented the quality and distribution of evidence.ResultsA total of 58 studies were included. The diagnostic criteria for the research subjects mainly refer to the standards of Western medicine. The task design was mostly two-arm before-and-after comparisons and single-group immediate studies, with the intervention measures mainly including hand acupuncture and electroacupuncture. The study employed 8 neuroimaging techniques and 29 outcome measures, with a primary focus on brain functional activation regions and brain functional connectivity. Included studies had high bias risk in blinding design/implementation; overall evidence quality was acceptable.ConclusionsAcupuncture for AD and MCI demonstrates clear efficacy, which is supported by imaging evidence. In the future, more large-sample, multi-center joint clinical studies using neuroimaging methods will be needed to further investigate AD and MCI, providing more high-quality evidence-based medical evidence in this field.