Background The 2018 NIA-AA framework outlines a six-stage continuum from asymptomatic individuals to severe Alzheimer's disease (AD) dementia, but most Chinese research still focuses on dementia or broad diagnostic categories. Objective To map diagnosis, treatment, and care patterns across all six AD clinical stages in China and identify demographic, clinical, treatment and care-related factors associated with disease stage. Methods We conducted a nationwide, open online survey via official media channels targeting patients with clinician-confirmed AD and their caregivers. Data were collected via Questionnaire Star. Descriptive analyses, group comparisons, and ordinal logistic regression were performed to examine factors associated with NIA-AA stage. Results A total of 1116 valid responses were analyzed. Most participants were at Stage 2 or higher, with distribution of 0.4%, 9.1%, 16.0%, 24.8%, 26.6%, and 23.0%, across Stage 1-6. Overall, 64.5% had been diagnosed within five years. Neurology (66.4%) and memory clinics (19.2%) were the most frequently visited departments. Donepezil (52.2%) and Memantine (38.8%) were the most common medications, while 34.5% reported engaging in non-pharmacological interventions. Only 1.9% of patients receiving professional dementia institutional care. In logistic regression, disease duration (OR = 0.724, p = 0.006), stage at first outpatient visit (OR= 1.843, p < 0.001), and Donepezil use (OR = 1.394, p = 0.003) were independently associated with current NIA-AA stage. Conclusions This study provides the first nationwide, real-world description of diagnosis, treatment, and care across all NIA-AA stages in China. The findings highlight the need for improved primary-care screening, expanded memory-clinic access, and structured caregiver support to promote earlier detection and more equitable, stage-appropriate management of AD.

ABSTRACT Early and accurate diagnosis of Alzheimer's disease (AD) remains a significant challenge due to the multifactorial and dynamic nature of its pathology. Although plasma‐based biomarkers such as amyloid‐β (Aβ) and phosphorylated tau (p‐tau) have shown promise as diagnostic indicators, current single‐biomarker detection techniques lack the requisite sensitivity and specificity for early‐stage diagnosis. Here, we present the development of an ultrasensitive CRISPR‐based multi‐protein detection array (UCMDA) capable of concurrently detecting six core AD biomarkers, including Aβ40, Aβ42, p‐tau181, p‐tau217, p‐tau231, and p‐tau396,404. By integrating antibody pair‐based multiplex recombinase polymerase amplification (RPA) with spatially encoded CRISPR‐Cas12a detection, the UCMDA achieves a detection limit of 1 fg/mL, which is 10 000‐fold more sensitive than conventional ELISA. Clinical validation in a cohort of 155 plasma samples demonstrated that logistic regression (LR)‐based integration of the six biomarkers significantly enhanced diagnostic performance, with the multi‐biomarker model substantially outperforming single‐biomarker approaches in diagnosing AD‐MCI and AD. This platform offers a scalable, cost‐effective, and minimally invasive strategy for early detection and disease monitoring. This work highlights the potential of CRISPR‐based multiplex protein detection technologies combined with machine learning‐assisted analysis to enhance the precision of diagnosing neurodegenerative disorders.

Precision medicine for Alzheimer’s disease (AD) requires the development of a robust management framework grounded in individualized disease staging systems. To date, only a limited number of studies have supplemented the existing AD staging systems. This retrospective study included 7491 MRI examinations from five independent cohorts. We used a novel pseudo-healthy synthesis method to capture individualized brain atrophy patterns. An individualized brain atrophy score (BAS) was computed from the 30 regions with the most severe brain atrophy and used to stratify participants into distinct disease stages. The Jenks natural breaks optimization method was used to determine an optimal number of disease stages based on the individual BAS. BAS exhibited a strong biological basis and revealed a synergistic relationship among biomarker-based staging systems. Four stages were delineated based on the BAS for participants with MCI and clinically diagnosed AD. Stage I showed a slight cognitive decline with only mild hippocampal atrophy evident. Stage II showed mild cognitive decline and mild brain atrophy and shrinkage, extending to the temporal and parietal lobes. Stage III showed moderate cognitive decline and more severe brain atrophy in the temporal lobe, amygdala, hippocampus, parietal lobe, and frontal lobe. Stage IV showed severe mental impairment and diffuse atrophy across the whole brain. The disease stages are associated with dementia severity and abnormalities in AD biomarkers, such as cerebrospinal fluid (CSF) Aβ1–42, CSF total tau, CSF p-tau181, and cognitive scores. Furthermore, those MCI participants at higher disease stages at baseline have a higher risk of progressing to clinically diagnosed AD dementia even under the A/T-negative status. The individualized staging system can accurately assess disease severity, enabling risk stratification at ultra-early pathological stages and facilitating precise AD management.

White matter hyperintensities (WMH) often co-exist with β-amyloid (Aβ) and tau tangles in Alzheimer's disease (AD). However, the association of WMH, Aβ plaques, and tau tangles in AD remains elusive. Using two large datasets, this study comprehensively examined the relationship between regional WMH and longitudinal tau accumulation in AD. A total of 951 participants from the ADNI and A4 cohorts with Aβ-PET, fluid-attenuated inversion recovery images (FLAIR), and tau-PET data were included, with Resting-state functional MRI (RS-fMRI) available for a subset of participants. FLAIR images were segmented using a U-Net deep learning model to obtain regional WMH volumes. Tau propagation along connectivity patterns was assessed using connectivity-associated tau spread metrics derived for the whole cortex and specific cortical regions ( β Global , β Frontal , β Parietal , β Temporal , and β Occipital ). We examined the associations between regional WMH, tau accumulation, and connectivity-associated tau spread. Additionally, two cortical tau subtypes were identified: “Occipital > Parietal” and “Parietal > Occipital”, characterized by higher or lower occipital tau relative to parietal tau, and the impact of regional WMH on tau accumulation was assessed within these subtypes. Aβ+ individuals showed higher baseline levels and faster increases in total WMH compared to Aβ- individuals, but no differences were observed between T+ and T- individuals. Among Aβ+ individuals, temporal meta-ROI tau was not associated with faster WMH increases. However, greater total WMH was linked to accelerated temporal meta-ROI tau accumulation (Figure 1), although this relationship did not persist after controlling for Aβ. Greater occipital WMH was associated with faster tau accumulation in occipital regions, particularly the cuneus, and with increasing β Occipital , independent of Aβ (Figure 2). The “Parietal > Occipital” subtype exhibited more rapid tau progression than the “Occipital > Parietal” subtype. In contrast, higher WMH was linked to faster tau increases in the cuneus exclusively within the latter subtype (Figure 3). Greater WMH burden, particularly in the occipital lobe, is associated with faster tau accumulation and spread in posterior cortical regions, independent of Aβ. These findings provide novel insights into understanding how vascular damages reflected by WMH contribute to cortical tau aggregation in the posterior cortical region of AD.

INTRODUCTION:Klotho is a longevity-associated protein with established neuroprotective properties. However, it is unclear how plasma klotho levels relate to Alzheimer's disease (AD) pathologies and cognitive performance. METHODS:In this study, we examined the associations between plasma klotho levels and plasma biomarkers, as well as amyloid beta (Aβ) positron emission tomography (PET), tau PET, neurodegeneration, and cognition, in 354 older adults. Stratified association, interaction, and mediation analyses were conducted to elucidate apolipoprotein E (APOE) ε4-dependent relationships and potential underlying pathways. RESULTS:Higher plasma klotho levels were associated with lower AD-related biomarkers and cognitive decline in APOE ε4 carriers. Plasma klotho and APOE ε4 exhibited significant or marginal interactions with less abnormal changes in plasma phosphorylated tau217, glial fibrillary acidic protein, neurofilament light chain, Aβ PET, and cognition. These AD-related biomarkers mediated the protective effect of plasma klotho on cognitive function in APOE ε4 carriers. DISCUSSION:This study suggests that plasma klotho is an APOE ε4-dependent protective factor, which may attenuate AD-related pathology and improve cognitive performance.

BACKGROUND:Plasma phosphorylated tau 217 (p-tau217) has emerged as a promising Alzheimer's disease (AD) biomarker, yet its longitudinal associations with neurodegeneration and cognitive decline remain inadequately characterized in Chinese populations, and ethnicity-specific diagnostic thresholds are lacking for optimal clinical application. METHODS:A total of 541 participants (402 cognitively unimpaired [CU]; 139 cognitively impaired [CI]) from the Sino Longitudinal Study on Cognitive Decline (SILCODE) cohort were enrolled. Cross-sectional and longitudinal associations of plasma p-tau217 with amyloid-β (Aβ) pathology, neurodegeneration, and cognition were evaluated. Diagnostic thresholds were derived using receiver operating characteristic analysis, and Cox regression assessed prognostic value for clinical progression. RESULTS:Cross-sectionally, baseline p-tau217 was associated with greater Aβ burden, neurodegeneration, and poorer cognition in the whole cohort and CI group; in the CU group, associations were confined to amyloid measures. Longitudinally, accelerated p-tau217 accumulation was associated with faster neurodegeneration and cognitive decline in the whole cohort, with stage-dependent patterns: nominal associations with neurodegenerative markers in CU and prominent cognitive associations in CI. Plasma p-tau217 demonstrated high diagnostic accuracy for amyloid positivity (AUC = 0.891; cutoff: 0.529 pg/mL). Threshold-based stratification effectively differentiated individuals by Aβ burden, neurodegeneration, and cognitive trajectories. Elevated baseline p-tau217 predicted higher progression risk (Whole cohort: HR = 2.66 [1.28-5.53], p = 0.009; CU: HR = 2.44 [1.07-5.59], p = 0.034). CONCLUSION:Plasma p-tau217 serves as a valuable diagnostic and prognostic biomarker for AD, even among CU individuals, and the ethnicity-specific threshold of 0.529 pg/mL enhances its clinical applicability for early detection and risk stratification in Chinese populations.

INTRODUCTION: Mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease (AD), shows pronounced clinical heterogeneity poorly explained by pathology burden, representing a gap complicating prognosis. As the brain operates as a complex network for information integration, we hypothesized that connectome architecture mediates the link between AD pathology and clinical expression. METHODS: We developed a framework integrating structural and functional connectomes from multi-center cohorts, performing connectome-based subtyping in MCI, with analyses of upstream pathology, downstream phenotypes, and transcriptomic associations. RESULTS: This approach identified an "MCI-compromised" (MCI-C) subgroup characterized by extensive structural-functional connectomic disruption and an "MCI-preserved" (MCI-P) subgroup with relatively preserved connectome integrity. Despite comparable pathology, MCI-C demonstrated more severe neurodegeneration, accelerated cognitive decline, and elevated progression risk. Multiscale analyses linked these patterns to transcriptomic profiles of mitochondrial, synaptic, and neuroimmune processes. DISCUSSION: These findings demonstrate that the connectome acts as a critical mediator, rather than a passive endophenotype, shaping AD clinical expression.

INTRODUCTION:Longitudinal diagnostic and prognostic validity of plasma phosphorylated tau217 (p-tau217) in Alzheimer's disease (AD) remains uncertain. METHODS:In this multi-cohort study of 2117 individuals, we established baseline plasma p-tau217 thresholds for amyloid-β-positron emission tomography (Aβ-PET) and assessed their longitudinal classification stability and prognostic relevance for AD-related outcomes. RESULTS:Baseline-defined cutoffs achieved high and sustained accuracy (86%-95%) for Aβ-PET positivity over up to 5 years of follow-up. Longitudinally, most p-tau217-positive individuals remained stable (93%-98%), whereas the intermediate zone group progressed more to positive (44%-78%) than p-tau217-negative individuals (4%-21%). Participants with stable-positive and progress-to-positive p-tau217 profiles more frequently exhibited Aβ abnormalities (90%-100% and 64%-96%, respectively) and experienced accelerated tau accumulation, hippocampal atrophy, and incident dementia compared to those with a stable-negative p-tau217 profile. DISCUSSION:These findings support the high stability and Aβ-PET classification performance of longitudinal plasma p-tau217 monitoring in AD, providing a scalable tool for risk stratification and disease monitoring.

A central objective in neuroscience is to elucidate how the brain generates complex dynamic activity through the interactions of brain areas. In this study, we utilized the Interaction Network, a graph neural network model, to develop a computational framework for predicting whole-brain cortical blood oxygenation level dependent (BOLD) signals. We derived an Inter-Regional Interactions (IRI) metric to quantify message transmission among brain areas probing the underlying dynamical mechanisms. In addition, the total IRI emitted from each brain region was calculated and defined as the IRI sent by region (RS-IRI). Our model predicted BOLD activity for the following 10 time points from initial BOLD signals, and achieved a mean absolute error of 0.04 (arbitrary units). The predicted functional connectivity (FC) achieves a correlation coefficient of 0.97 compared to the empirical FC. The fluctuation amplitude of the IRI increases with the length of the connection and the largest RS-IRI oscillation amplitude is observed in visual areas. The RS-IRI demonstrates a hierarchical organization, characterized by more concentrated distributions in association regions and larger fluctuation amplitudes in unimodal regions. Applying our approach to Alzheimer’s disease (AD), we demonstrate that the frequency-specific amplitudes of IRI oscillations discriminate AD patients from healthy controls and correlate with Mini-Mental State Examination scores. Together, this work presents a deep learning–based framework for modeling brain dynamics as well as a quantitative index of inter-areal interactions, and offers a new perspective for disease characterization.

Both Apolipoprotein E-ε4 (APOE-ε4) and astrocytic activation, as measured by glial fibrillary acidic protein (GFAP), play critical roles in Alzheimer's disease (AD). However, the influence of astrocytic activation on the relationship between APOE-ε4 and AD pathologies remains unclear. This study investigates the interrelationships among astrocytic activation, APOE-ε4, and AD pathophysiology in 529 participants who underwent plasma biomarker measurements, APOE genotyping, and cognitive testing. Additionally, 277, 284, and 104 underwent structural magnetic resonance imaging (MRI), amyloid-β (Aβ) positron emission tomography (PET), and tau PET, respectively. The associations of plasma GFAP, APOE-ε4, and AD-related biomarkers, as well as whether plasma GFAP mediates APOE-ε4-related effects on AD, were investigated. Higher plasma GFAP and APOE-ε4 were independently associated with more severe Aβ and tau aggregation, as well as cognitive decline. Mediation analyses showed a significant indirect effect of APOE-ε4 on plasma p-tau biomarkers (21.1%-24.9%), Aβ PET (16.4%), and cognition (19.6%), while the indirect effect on tau PET was trend-level (29.1%, pFDR = 0.051). These findings highlight the central role of astrocytic activation in AD pathogenesis and underscore plasma GFAP as a promising biomarker for risk stratification and therapeutic targeting.

Biological sex fundamentally shapes human brain organization, but sex-specific normative neuroanatomical trajectories across the lifespan remain largely uncharted. Here, we constructed independent, sex-specific lifespan brain charts using structural neuroimaging data from 59,915 healthy individuals (29,760 males and 30,155 females) ranging in age from 266 postconception days to 100 years. By examining 296 structural phenotypes across global, cortical, and subcortical measures, these models revealed widespread sex differences in maturational timing, with males reaching peak milestones later than females. These trajectories demonstrate that sex differences evolve dynamically, with phenotype-specific windows of emergence and maximal separation. Compared with conventional sex-pooled references, sex-specific models achieved superior predictive accuracy and reduced misestimation of individual deviations in healthy populations. Across five neuropsychiatric conditions, sex-specific models improved the detection of extreme deviations and revealed both shared and sex-dependent patterns of disorder-related neuroanatomical abnormalities. These sex-specific charts establish tailored normative references for assessing brain development, ageing, and disease.

The human cortical functional hierarchy, spanning from primary sensorimotor to transmodal association regions, represents a fundamental principle of brain organisation. Here, we show lifespan changes in the sensorimotor-association (S-A) gradient in the cortical functional hierarchy using multimodal neuroimaging data from 33,247 participants aged 32 postmenstrual weeks to 80 years. We identify three critical neurodevelopmental milestones: initiation (third trimester to perinatal period), establishment (infancy to early childhood), and expansion-stabilisation (late childhood to adulthood). Pronounced gradient changes are predominantly observed during the first decade, with continued refinement extending into mid-adulthood. Spatiotemporally heterogeneous growth patterns in functional gradients align with evolutionary hierarchies, segregation-integration dynamics, structural maturation, and cognitive spectrum development, proceeding along a dominant S-A growth axis. These findings establish a unified neurodevelopmental framework that links connectome gradient dynamics to multifaceted functional and structural properties, advancing our understanding of cortical hierarchy maturation across the lifespan.

Fluid biomarkers in plasma and cerebrospinal fluid (CSF) are crucial for Alzheimer's disease (AD) diagnosis. Emerging evidence suggests a link between kidney function and these biomarkers, but the relationship remains unclear. This study provides a systematic review and meta-analysis of the effect of renal function indicators (eGFR and serum creatinine) on AD fluid biomarkers in older adults. We searched PubMed, Cochrane, Web of Science, and EMBASE databases on July 4, 2025. Eligible studies were selected, and data were extracted for meta-analysis. Correlation coefficients were aggregated using a random-effects model. Our search yielded 11,057 articles, with 25 studies included in the meta-analysis of 9 plasma biomarkers. Lower eGFR (indicating worse renal function) was significantly associated with elevated plasma levels of neurofilament light chain (NfL) (r = −0.40), amyloid-β (Aβ)42 (r = −0.37), Aβ40 (r = −0.46), phosphorylated tau (p-tau)181 (r = −0.22), p-tau217 (r = −0.32), total tau (t-tau) (r = −0.38), and glial fibrillary acidic protein (GFAP) (r = −0.26). It was also associated with a lower plasma Aβ42/Aβ40 ratio (r = 0.06). No significant association was found for plasma p-tau231. An additional 18 articles were included in the qualitative review. Our findings demonstrate significant associations between renal function indicators and AD fluid biomarkers, particularly in plasma. However, given that approximately 80

Background: The association between whole-brain cerebral perfusion and glymphatic function has not been fully elucidated in Alzheimer’s disease (AD). Methods: The study enrolled 59 cognitively normal individuals without AD biomarkers (CN_A–), 31 cognitively normal (CN_A+), and 29 cognitively impaired individuals (CI_A+) with positive AD biomarkers. All participants underwent clinical and neuropsychological assessments, multimodal MRI, and plasma biomarker assays; amyloid positron emission tomography (PET) was available for a subset. Cerebral blood flow (CBF), choroid plexus (CP) volume and perfusion, and glymphatic markers were quantified. Relationships among perfusion, glymphatic function, and cognition were examined using correlation and mediation analyses. Findings: Widespread cortical hypoperfusion across temporo-limbic and cingulate regions was already evident in CN_A+ individuals compared with CN_A–, with no further decline in CI_A+. Cortical CBF was strongly correlated with CP perfusion across all regions (partial r = 0.715–0.825). Among biomarker-positive participants, higher CBF in the right temporal and hippocampal regions was associated with better cognitive performance, whereas larger CP volume correlated with lower MoCA-B scores. CP perfusion fully mediated the association between left middle cingulate cortex CBF and global cognition. CP volume was significantly enlarged only in CI_A+, whereas glymphatic markers declined progressively across the AD continuum. Interpretation: These results delineate a potential sequential vascular-CP-glymphatic axis in AD continuum. Cerebral perfusion may be an early functional biomarker and promising therapeutic target for preclinical AD.

BackgroundSubjective cognitive decline (SCD) is a common early complaint in mild cognitive impairment (MCI). Evidence for the 21-item SCD-Questionnaire (SCD-Q21) to discriminate MCI from normal controls (NCs) is limited.ObjectiveTo investigate the discrimination performance of Chinese SCD-Q21 and compare it with SCD-Q9 for community-based MCI early detection, assess the added value of simple covariates, and determine an optimal SCD-Q21 cut-off.Methods294 NCs and 83 people with MCI were assessed and collected demographic and clinical data. Participants completed SCD-Q21, SCD-Q9, Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD) scale; clinical adjudication used Montreal Cognitive Assessment-Basic, Clinical Dementia Rating, and Activities of Daily Living. Group comparison, logistic regression and ROC analyses were applied. Optimal cut-offs were derived using the Youden index and AUCs were compared using DeLong tests. Within-MCI analyses contrasted screen-positive versus screen-negative subgroups.ResultsTotal SCD-Q21 scores were higher in MCI, although five items [question 1 (Q1), Q2, Q3, Q11, and Q17] did not differ between groups. In multivariable binary logistic regression models, lower education (OR = 0.786), higher body mass index (BMI) (OR = 17.874), and higher SCD-Q21 total scores (OR = 1.114) were independently associated with MCI, whereas SCD-Q9 was not. Standalone AUCs were 0.662 (SCD-Q21) and 0.640 (SCD-Q9). Combing age, sex, education, BMI, and HAMA/HAMD with SCD instrument yielded AUC ∼0.91. SCD-Q21 ≥ 7 gave 69.88% sensitivity and 62.93% specificity. Screen-negative MCI cases showed lower vascular/metabolic comorbidity and lower HAMA/HAMD scores.ConclusionsSCD-Q21 provides independent information but modest stand-alone discrimination. As part of a brief multivariable triage including education, BMI, vascular risk review, and anxiety rating, it supports efficient case-finding in community settings.

Amyloid-β (Aβ) PET is crucial for diagnosing and monitoring Alzheimer’s disease (AD), but its high cost and radiation exposure limit its use. Deep learning techniques make it possible to generate PET from structured MRI data. In this study, we built a deep learning model to generate 3D synthetic Aβ PET images from structural MRI. The generative adversarial network with share parameters (ShareGAN) model was trained and tested with 1009 Aβ PET and paired MRI images from the Alzheimer’s Disease Neuroimaging Initiative database and three tertiary hospitals in China. The 3D synthetic model operates on the whole volume rather than 2D image slices, realistically reproducing minor discrepancies between neighboring image planes. ShareGAN-based PET images were evaluated using quantitative metrics and visual assessment. Pearson correlation coefficient and Bland–Altman analyses were used to assess the correlation and concordance between synthetic and real PETs. 3D Synthetic PET images showed high similarity and correlation with real Aβ PET in external testing sets 1 and 2 in terms of structural similarity index measure (0.898, 0.899), peak signal-to-noise ratio (34.690, 34.725), mean absolute error (0.031, 0.031), and standardized uptake value ratio (R = 0.758, 0.828). The diagnostic accuracy of PET positive or negative status in external testing sets 1 and 2 was 88.5

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by an insidious onset and gradual deterioration. Clinically, it manifests as cognitive decline and behavioral changes rather than only as generalized dementia. Currently, the diagnostic accuracy of AD remains limited due to the nonspecific clinical manifestations and the low specificity of conventional examinations such as neuropsychological assessments, electroencephalography (EEG), computed tomography (CT), and magnetic resonance imaging (MRI). Positron emission tomography/computed tomography (PET/CT) provides detailed structural and functional information along with specific molecular distributions, making it increasingly valuable for the diagnosis and research of AD. We performed PET/CT scans using the radiotracers 18F-AV-45 (florbetapir) and 18F-AV-1451 (flortaucipir). The key distinction between these tracers lies in their molecular targets: 18F-AV-45 binds to β-amyloid (Aβ), whereas 18F-AV-1451 specifically targets tau protein. This study elaborates on the protocol for the combined use of both tracers in AD diagnosis, encompassing patient preparation procedures, image acquisition techniques, interpretation standards, and the clinical significance of their joint application. This dual-tracer protocol provides a sensitive, comprehensive, and non-invasive method for detecting both amyloid and tau pathology, enhancing early diagnosis, disease staging, and research on disease progression.