The introduction of disease-modifying therapies for Alzheimer’s disease (AD-DMTs) is reshaping clinical practice, raising critical questions about patient selection, diagnostic pathways, treatment appropriateness, and equity of access. Frailty, a multidimensional condition of reduced physiological reserve and increased vulnerability to stressors, is common in older adults with AD, yet has not been systematically assessed in AD-DMTs trials, limiting the generalizability of trial findings to real-world populations.In this review, we examine the role of frailty in the emerging era of AD-DMTs, summarizing evidence on its prevalence and prognostic relevance, approaches to its assessment, and its potential impact on treatment safety and effectiveness. We propose that regular frailty assessment should inform decision-making in both clinical trials and clinical practice, while frailty-informed management—including medication review and multidomain interventions—may support more appropriate, individualized care.
Background: Dementia is a major global mortality cause and key driver of disability in older adults, imposing multidimensional burdens. As China's population ages, accurate prevalence estimates and care need assessments are essential for equitable policy planning. This study investigates young- and late-onset dementia prevalence while comparing health service utilization and unmet care needs between affected and unaffected populations.Methods: Utilizing China Mental Health Survey data (2013-2015) with multistage probability sampling, we identified 12,663 nationally representative adults aged ≥55 years. Of these, 10,839 completed Stage I assessments and 2,261 received Stage II evaluations, supplemented by psychiatric assessments of initial non-participants (n=197). Dementia diagnosis followed DSM-IV criteria via validated cognitive/functional instruments. Health service utilization and multidimensional care needs (ADLs/IADLs/safety) were quantified through participant/informant interviews.Results: Among 2 458 participants assessed, dementia prevalence was 2.65% (55-64y) and 5.56% (≥65y). Rural residents showed consistently higher rates than urban counterparts across age groups. Significant education gradients emerged, with urban prevalence decreasing with higher education while rural patterns differed. Individual living with dementia required substantially more care for both samples (55-64 years: 37.4% vs 11..9%, +81.3 monthly hours; 65+ years: 62.6% vs 13.4%, +88.8 monthly hours) without increased health service utilization.Conclusion: This national study reveals substantial dementia burden in China, exposing systemic healthcare deficiencies through misaligned functional care needs and medical engagement. The neglect of chronic disability management in aging populations necessitates urgent integration of prevention strategies and tailored support frameworks within primary care systems.
Brain health refers to optimal brain functioning and integrity, shaped by complex cognitive, psychological, and social determinants. Individuals with mild neurocognitive disorder (mNCD) are at higher risk of developing dementia. Prioritising brain health is essential throughout the lifespan, particularly at midlife when health risks often emerge alongside heavy life responsibilities. International frameworks emphasise addressing modifiable risk factors across the lifespan to reduce dementia risk, yet little is known about the strategies middle-aged individuals with mNCD use to maintain brain health in everyday life. Understanding how people in midlife interpret and act on information about brain health is essential to align clinical care and prevention policies with lived experience. This scoping review followed the Joanna Briggs Institute methodology and mapped data published from August 2015 to 2025 using the 2024 Lancet Commission on dementia and the Cochrane PROGRESS-Plus equity framework. The primary aim of this review was to map the range and characteristics of non-pharmacological brain health strategies used by middle-aged individuals with mNCD to reduce the risks of developing dementia. After screening 6349 records, 17 articles were included. The results are presented in three groups: brain health strategies, facilitators and barriers across strategies, and the equity analysis. Strategies were classified as formalised interventions and self-directed practices. Facilitators and barriers varied according to population characteristics and the strategies used. Equity gaps included limited representation of study participants from rural and low-socioeconomic settings, reduced generalisability to male populations, and underrepresentation of minoritised ethnic groups. Clinicians, service planners, and policymakers should prioritise equity-oriented brain health strategies co-designed with middle-aged individuals. Equity and co-design should be explicitly integrated within global brain health policies and agendas.
Background Polygenic risk scores for Alzheimer’s disease (AD-PRS) are widely used to estimate genetic susceptibility to AD, but their relationship with the rate of cognitive decline (CD) after clinical onset remains insufficiently characterized. Objectives To examine the association between AD-PRS and longitudinal CD across the AD spectrum and to evaluate the predictive contribution of individual AD-PRS variants. Design Large longitudinal observational study in a single-center cohort, with an external cohort to assess generalizability. Setting Memory clinic cohort from Ace Alzheimer Center Barcelona (Ace) with external cohort using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Participants The study included 7,233 patients from Ace and 863 from ADNI, with a mean follow-up of 5.4 years in Ace and 3.6 years in ADNI. A biomarker sub-cohort included 1075 participants from Ace and 569 from ADNI. Measurements CD was quantified as the annual change in Mini-Mental State Examination (MMSE) scores estimated using linear mixed-effects models. Associations between AD-PRS and longitudinal MMSE trajectories were tested adjusting for clinical and sociodemographic (CSD) variables and APOE genotype. Machine learning models and SHapley Additive exPlanations (SHAP) were used to evaluate the predictive relevance of individual variants. Results Higher AD-PRS was associated with faster CD in the full clinical cohort and in biomarker subset, independently of APOE genotype. AD-PRS was not associated with baseline MMSE. APOE ε4 was associated with lower baseline MMSE and faster CD only in the full clinical sample. Genetic predictors provided limited improvement beyond CSD variables, and model performance showed limited reproducibility across cohorts. Conclusions AD-PRS is associated with longitudinal CD across the AD spectrum. Although polygenic burden contributes to variability in cognitive trajectories, its added predictive value beyond routinely available clinical variables remains modest.
BACKGROUND:Caring for people with both dementia and advanced care needs is complex. This study aimed to elucidate the prevalence of dementia and behavioral and psychological symptoms of dementia (BPSD) in patients receiving advanced care, including tube feeding, respiratory care, subcutaneous injection, urinary catheter, stoma care or enema, wound care, pain care, or dialysis. METHODS:This study was a nationwide, population-based, cross-sectional survey. A total of 11,297 participants were enrolled between September 2020 and June 2022 using a multistage stratified systematic sampling design. Dementia diagnosis was made by subspecialists during in-home visit or by expert consensus. The presence of BPSD and the use of specific advanced care services were collected by trained interviewers. RESULTS:Overall, 732 (6.5%) participants received at least one item of advanced care and 975 (8.6%) were diagnosed with dementia. Participants receiving advanced care had a higher prevalence of dementia (18.0%vs. 8.0%, p < 0.0001). Subjects receiving stoma or enema care (OR=4.92, 95% CI=2.29-10.59, p < 0.0001), tube feeding (OR=3.20, 95%CI=1.99-5.15, p < 0.0001), dialysis (OR=2.97, 95% CI=1.80-4.92, p < 0.0001), urinary catheterization or intermittent catheterization (OR=2.20, 95% CI=1.32-3.67, p = 0.003), and respiratory care (OR=2.01, 95% CI=1.14-3.57, p = 0.017) had a significantly higher risk of dementia. For BPSD, day-night confusion (42.0%vs. 27.9%, p = 0.002) and care-resistant behaviors (19.8%vs. 12.0%, p = 0.019) were significantly more prevalent in participants receiving advanced care. CONCLUSIONS:This study found that patients receiving advanced care had a significantly higher prevalence of dementia and BPSD in Taiwanese population. Healthcare professionals should be vigilant regarding potential comorbid dementia in patients receiving advanced care and provide more patient-centered approaches or non-pharmacological interventions to alleviate BPSD and reduce care partner's loading.
Amyloid immunotherapy with lecanemab and donanemab has been approved on the basis of statistically significant slowing of cognitive and functional decline in early Alzheimer's disease (1,2). Yet clinicians treating individual patients face the everyday challenge of estimating whether a given patient is declining at the rate that would be expected for them, and whether their trajectory reflects a response to treatment. I argue that this difficulty arises in large part because the field cannot yet routinely stratify patients by tau pathology before treatment, even though tau burden is among the strongest available predictors of both the rate of progression and the magnitude of response to amyloid-targeting therapy. Post-hoc and open-label analyses of the Clarity AD and TRAILBLAZER-ALZ 2 programmes suggest that patients with absent, low, or medium tau burden may constitute a biologically distinct group in whom amyloid clearance is most likely to permit clinical stabilization or measurable functional gain. These observations remain hypotheses, generated largely from subgroup, open-label, and biomarker data rather than from prospective trials designed to test them I propose that tau status should be given strong consideration in patient selection, that tau-guided selection should be evaluated prospectively, and that the access, reimbursement, and standardization barriers to tau positron emission tomography (PET) — together with the promise of scalable plasma tau biomarkers — be addressed deliberately as the field moves toward tau-informed treatment. One tau PET tracer is currently approved by the US Food and Drug Administration, and a regulatory decision on a second is anticipated in 2026.
Introduction The choroid plexus (CP) increases in volume across the Alzheimer’s disease (AD) continuum, suggesting its potential as a clearance-related biomarker. However, few studies have examined ante-mortem CP volume in relation to post-mortem AD pathology, the gold standard for diagnosis. Methods Participants who had structural magnetic resonance imaging and post-mortem pathology, with an interval of ≤ 5 years between imaging and death, were examined. Normalized CP volume (NCPV) was semi-automatically segmented from the lateral ventricles and analyzed using Bayesian linear regression to estimate associations with cognitive impairment (CI), AD pathology, and relevant clinical/demographic data. Results Intermediate and high levels of AD pathology and CI were associated with larger NCPV, whereas female sex was associated with lower NCPV. Subgroup analyses showed larger NCPV in individuals with greater CI despite comparable levels of AD pathology. Discussion These findings link CP enlargement to neuropathologically confirmed AD burden and CI, supporting further investigation of CP structure and function in AD.
BACKGROUND:Social determinants of health (SDOH) are increasingly recognized as important drivers of cognitive outcomes. However, most existing evidence focuses on individual SDOH components and older populations. OBJECTIVES:To develop a comprehensive SDOH index and examine its association with subsequent changes in cognitive function and structural brain measures in midlife. DESIGN:Prospective cohort study with repeated measures of cognition and brain imaging. SETTING:Community-based cohort from the Coronary Artery Risk Development in Young Adults (CARDIA) study. PARTICIPANTS:A total of 3488 participants with SDOH data in early midlife (mean age 40.0 ± 3.6 years); 645 participants had repeated brain magnetic resonance imaging (MRI) data. MEASUREMENTS:A weighted aggregate SDOH index was constructed from 12 items across 5 domains: economic stability, community and social context, education, neighborhood and built environment, and health care access. Cognitive function was assessed using the Digit Symbol Substitution Test (DSST), Stroop Test, and Rey Auditory Verbal Learning Test (RAVLT). Brain MRI outcomes included white matter hyperintensities (WMHs) and total gray matter (GM) volume. Mixed linear regression models examined associations between SDOH quartiles and longitudinal cognitive and MRI outcomes, adjusting for demographics, vascular risk factors, depression, and intracranial volume (for MRI). RESULTS:At baseline, participants in the most disadvantaged SDOH quartile performed worse across all cognitive tests compared with the least disadvantaged quartile (p < 0.001). Over time, the most disadvantaged quartile showed steeper decline in DSST performance (adj. mean change: -0.72, 95% CI: -0.93 to -0.52 vs. -0.55, 95% CI: -0.76 to -0.34, p = 0.013), greater WMH accumulation (ratio: 1.07, 95% CI: 1.05 to 1.09 vs. 1.04, 95% CI: 1.03 to 1.05, p = 0.007), and steeper decline in total GM volume (-2.02 cm³, 95% CI: -2.39 to -1.65 vs. -1.46 cm³, 95% CI: -1.71 to -1.20, p = 0.011) per 5-year interval compared to the least disadvantaged quartile. CONCLUSIONS:Greater social disadvantage in midlife is associated with worse baseline cognition and accelerated decline in cognitive function and brain integrity. These findings highlight the importance of SDOH as key determinants of brain health in midlife and suggest that strategies to mitigate social disadvantage may help preserve cognitive and brain health.
Background Predicting cognitive decline as a continuum, from healthy age-related decline to mild cognitive impairment and dementia, enables more precise individual-level predictions. However, the practical value of such models for early intervention and prevention depends on their ability to generalize to independent cohorts, a property that is often not evaluated. Objectives This study investigated whether adding structural magnetic resonance imaging (MRI) to non-brain data improved machine learning predictions of continuous cognitive decline and analyzed the models’ generalizability. Design Multi-target random forest regression models predicted annual decline in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SOB) and Mini-Mental State Examination (MMSE) using non-brain data, structural MRI data, or their combination from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 1237) and Open Access Series of Imaging Studies (OASIS-3; N = 662) datasets. Cross-site generalizability was evaluated. Setting Data from ADNI and OASIS-3 were used for this study. Participants A total of 1899 participants who had demographic, clinical, and brain imaging data from a baseline session and clinical data from at least 2 follow-up sessions were included. Measurements Baseline non-brain (demographics, clinical and neuropsychological scores, information on APOE genotype, cognitive diagnosis, health, and number of sessions before baseline) and/or structural MRI data were used to predict the yearly rate of change in CDR-SOB and MMSE scores. Results Including structural MRI data improved prediction of CDR-SOB and MMSE change, reaching respective R2 values of .41 and .33 in ADNI and .42 and .33 in OASIS-3. Model performance for across-dataset predictions was reduced (R2 between .18 and .35), unexplained by distributional shifts of target variables. Models using only top predictive features performed similarly to full models when tested externally (R2 between .18 and .34), suggesting predictor redundancy. Conclusions Incorporating structural MRI data enhances within-dataset prediction of continuous cognitive decline, allowing for more precise individual-level prediction and advancing towards precision medicine. Even though external validation remains limited, quantifying the generalizability gap is a crucial step towards the responsible use of ML models in clinical intervention and prevention.
INTRODUCTION:We aimed to estimate the cost-effectiveness of the patient-centered special care unit for behavioral and psychological symptoms of dementia (SCU-B) in the Respectful Caring for the Agitated Elderly (RECage) study. METHODS:A health-economic evaluation was performed alongside a controlled European multicenter three-year longitudinal cohort study enrolling 508 participants in a non-SCU-B cohort and SCU-B cohort. Health service resource use, costs, quality-adjusted life years (QALYs), and incremental cost per QALY gained were assessed. RESULTS:Total QALYs were lower (-0.13; bootstrap-interval -0.23 to -0.02) and total costs were higher (€24,960; bootstrap-interval 14,870 to 35,090) in the SCU-B cohort. Base case and sensitivity analyses indicated the SCU-B was likely not cost-effective. DISCUSSION:Widespread implementation as well as disinvestment of SCU-B cannot be recommended, given the uncertainty of the study results. We recommend a randomized study stratified by (local/county) region for conclusive evidence.
Background Epigenetic modification is a hallmark of aging that encloses physiological information relevant to health and longevity and has been used to construct epigenetic clocks that estimate epigenetic age acceleration (EAA) to monitor population health across the life span. Psychological adversities (PA) are recognized contributors to poor health; however, their potential role in EAA remains insufficiently understood in older adults. Objective This study systematically reviews and meta-analyzes the association between PA and EAA from midlife onward. Methods Eligible literatures were indexed in five databases up to July 2025. Study quality was assessed using an adapted Newcastle-Ottawa scale. Meta-analyses were performed using random-effects models, followed by post hoc and sensitivity analyses to assess robustness. Results Twenty-two studies were included, of which fifteen were classified as high quality. Irrespective of the type of psychological adversity, positive associations were consistently observed for second-generation epigenetic clocks (PhenoAge and GrimAge). Meta-analyses revealed that greater loneliness (β = 0.07, 95 % CI [0.06, 0.08], I2 = 0 %, p = 0.002), depression (β = 0.08, 95 % CI [0.04, 0.13], I2 = 55.2 %, p = 0.003), and stress (β = 0.10, 95 % CI [0.03, 0.16], I2 = 68.4 %, p = 0.009) were each associated with higher EAA. Conclusions Psychosocial stress, depression, and loneliness are each associated with accelerated aging from midlife onward. Notable gaps include the lack of studies examining anxiety and underrepresentation of non-Western population. Whether alleviating psychological adversities translates into decelerated aging trajectories requests future intervention studies.
BACKGROUND:About one third of amyloid positive, cognitively normal individuals develop mild cognitive impairment or clinical Alzheimer dementia (AD) over 5 years of follow-up. Sensitive cognitive measures, in addition to biomarkers of amyloid pathology, add to the efficiency of secondary prevention trials by identifying cognitively normal individuals at greatest risk of clinical progression. The Stages of Objective Memory Impairment (SOMI) system, based on the picture version of the Free and Cued Selective Reminding Test with immediate recall (pFCSRT+IR), predicted clinical progression in two observational studies. OBJECTIVE:Our objective was to extend SOMI's findings to clinical trials using participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's(A4) study. METHODS:Eligible participants were cognitively normal, had a Clinical Dementia Rating (CDR) =0, an elevated amyloid level, the pFCSRT+IR, pTau217, and longitudinal data on the CDR. Cox proportional hazards model was used to assess the association of baseline SOMI stage for clinical progression defined by time to the first of 2 consecutive CDRs > 0 or CDR>0 at last assessment. The sample was censored at 4.5 years of follow-up. RESULTS:Of the 911 eligible participants, mean age was 72 years, 59% were female, 62% were APOE ε4 carriers, and 37% progressed over 4.5 years. Hazard ratios (HR) for progression were estimated with follow-up time as the timescale and the SOMI 0 group as the reference. The HRs for progression across SOMI stage increased from 1.48(1.15-1.92 p=.003) for SOMI-1, to 1.83 (1.32-2.54, p ≤ 0.001) for SOMI-2, and to 3.04 (1.97-4.68, p ≤ 0.001) for SOMI 3/4. SOMI remained an independent and significant predictor when pTau217 was added to the model. CONCLUSION:SOMI's risk profile in A4 was similar to prior findings in observational cohorts. SOMI provides a low-cost, non-invasive enrichment tool for identifying individuals at risk for early cognitive decline in secondary prevention trials.
BACKGROUND:Cardiovascular disease (CVD) is a major risk factor for cognitive decline and dementia. We examined whether a higher atherosclerotic cardiovascular disease (ASCVD) risk is associated with faster cognitive decline in Project FRONTIER, a rural cohort. METHODS:Participants were aged ≥40 years without baseline CVD and completed two study visits. Primary outcomes were the RBANS Total Score and its domains; secondary outcomes were Executive Interview 25, verbal fluency, Clock Drawing Test (CLOX), and Trail Making Test (TMT) A and B. Primary exposure was the 10-year ASCVD risk per AHA PREVENT equations. We fitted Bayesian mixed-effects models to estimate the interaction between time (in years) and ASCVD risk, adjusting for covariates using brms package in R. RESULTS:We analyzed data of 383 participants (age 57.74 ± 11.4 years; 75.5 % female; 59.8 % Hispanic; median follow-up 3.00 years, IQR: 2.67-3.64). The time×ASCVD risk interaction for RBANS Total was credibly negative (β = -1.22 points/year per 10 % higher risk, 95 % CrI -1.87 to -0.58). Strongest domain-specific effects were for attention (β = -1.25; 95 % CrI -2.14 to -0.37) and delayed memory (β = -1.36; 95 % CrI -2.16 to -0.05). CLOX suggested a credibly negative interaction (β = -0.39; 95 % CrI -0.62 to -0.16), and TMT-A showed a credibly positive interaction (β = +2.85 s/year; 95 % CrI 1.28 to 4.41). DISCUSSION:In this rural cohort, a higher 10-year ASCVD risk was associated with faster decline in global cognition, particularly attention and delayed memory, supporting the potential value of cardiovascular risk monitoring and modification to preserve cognitive function.
BACKGROUND:Population ageing is driving a global surge in cognitive impairment. While late-life decline is well-characterized, the onset of measurable cognitive changes across the full adult lifespan remains uncertain. We aimed to estimate the age at which detectable decline begins using longitudinal data from three population-based cohorts from three countries spanning three continents. METHODS:We analyzed participant-level longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS; China), Midlife in the United States (MIDUS; USA), and Kardiovize (KV; Czech Republic). Cognitive performance was assessed using validated instruments (TICS, BTACT, and MoCA). Scores were harmonized using the percent of maximum possible method (0-100 metric). Linear mixed-effects models, adjusted for age group, sex, and education estimated change over an average 7-9-year follow-up. FINDINGS:In pooled sample of 14,389 participants (baseline age 22-94 years), a detectable decline in total cognition first emerged in the 31-40 age group (mean change -1.2 points, 95% CI -2.1 to -0.3). Decline magnitude increased progressively with age, reaching -11.4-points in the oldest strata (all p<0.001). Non-memory domains showed earlier vulnerability (detectable from age 31), while significant memory decline emerged after age 50. Individual trajectories showed substantial heterogeneity, suggesting that chronological age is not a deterministic proxy for decline. INTERPRETATION:Population-level cognitive decline became detectable in early midlife, decades before the traditional clinical focus on older age. Across three population-based cohorts from Asia, North America, and Europe, we observed consistent early decline in non-memory domains followed by later memory decline. These findings support evaluation of midlife cognitive monitoring and life-course approaches to brain health. FUNDING:European Union Next Generation EU; European Regional Development Fund; European Social Fund; Barrow Neurological Foundation; NIH.
Background: European approval of lecanemab and donanemab has shifted anti-amyloid monoclonal antibodies from trial evidence to health-system implementation. In Italy, reimbursement decisions are pending, and real-world estimates of treatment-ready eligibility under Italian appropriate use recommendations (AUR) incorporating European Medicines Agency (EMA) restrictions are needed. Methods: We conducted a retrospective cohort study at the Cognitive Neurology Clinic of the University Hospital of Modena, embedded in the provincial dementia-care network. All patients with at least one visit between Jan 1, 2024, and Dec 31, 2025, were included. Eligibility for lecanemab and donanemab was assessed through a sequential algorithm based on Italian AUR, applying EMA product-label restrictions. Eligibility was estimated across three denominators: the service cohort, the clinical cohort with MCI or mild AD dementia, and the clinical-biological AD cohort. Findings: Among 1080 patients, 596 had MCI or mild AD dementia, and 230 had clinical-biological AD. After all eligibility steps, 50 patients were treatment-ready. Eligibility was 4·6% of the service cohort (50/1080; 95% CI 3·5–6·1%), 8·4% of the clinical cohort (50/596; 6·3–10·9%), and 21·7% of the clinical-biological AD cohort (50/230; 16·6–27·6%). After biomarker testing, the largest attrition points were clinical stage, care-context readiness, MRI findings, and APOE-related criteria. Interpretation: Even in a biomarker-enabled Italian cognitive neurology network, treatment-ready eligibility is 4·6% of all seen patients. These findings may contribute to the creation of equitable referral pathways by providing empirical denominators for reimbursement assessment and service planning.
Background: Although blood-based biomarkers are now available for diagnosing Alzheimer’s disease (AD), the best biomarker for AD-specific neurodegeneration and cognitive decline remains unclear. This study aimed to determine the relative importance of four plasma biomarkers—phosphorylated tau (p-tau) 217, p-tau181, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP)—in AD-specific neurodegeneration and cognition. Methods: We analyzed cross-sectional data from two independent, ethnically distinct cohorts spanning the clinical spectrum from cognitively unimpaired to dementia: 150 participants from the SAMD cohort (100% Asian) and 284 participants from the ADNI cohort (94.0% White). Plasma biomarker levels were quantified using Single-Molecule Array (Simoa) assays. We employed dominance analysis to determine the hierarchical contributions of these biomarkers to AD signature regions of interest (ROI) thickness (entorhinal, inferior temporal, middle temporal, and fusiform regions), total cognition, and memory, stratified by amyloid-PET status. Three sensitivity analyses were further conducted to validate the findings across these cohorts, mitigating potential biases arising from differences in demographic characteristics and clinical severity. All analyses were adjusted for age, sex, education, and APOE ε4 status. Results: The dominance hierarchy differed markedly according to the amyloid status. Plasma GFAP and p-tau217 emerged as the dominant predictors for AD signature ROI thickness and cognitive impairment in amyloid-positive participants. Specifically, GFAP demonstrated superior dominance in explaining cortical atrophy within the SAMD cohort, whereas p-tau217 was the dominant predictor in the ADNI cohort. P-tau217 generally outperformed the others in explaining total cognition and memory in the amyloid (+) group. In contrast, among amyloid (−) participants, plasma NfL showed greater explanatory power than GFAP for both neurodegeneration and cognitive decline across both cohorts. Conclusion: The efficacy of plasma biomarkers in reflecting AD-related neurodegeneration varies significantly depending on the presence of amyloid pathology. While GFAP and p-tau217 are robust indicators of AD-associated changes linked to plaque pathology, NfL better reflects non-specific neurodegeneration involving axonal damage. Consequently, a stratified approach based on amyloid status is essential for the optimal application of blood-based biomarkers in monitoring disease progression and evaluating therapeutic efficacy in future clinical trials and precision medicine.
