Background Although dynamic network reconfiguration is altered in Alzheimer's disease (AD), its pattern in subjective cognitive decline (SCD), an early preclinical stage, remains unclear. Objective This study aims to identify the characteristics of dynamic network reconfiguration in SCD individuals compared to healthy controls (HCs) and AD patients. Methods Time-varying multilayer network models were built for AD (n = 111), SCD (n = 115), and HC (n = 111) groups using the GenLouvain algorithm. We compared dynamic reconfiguration features across groups and examined how abnormal reconfiguration affects the relationship between amyloid-β (Aβ) pathology and cognition. Results SCD individuals showed higher global recruitment and lower global integration than AD patients, and lower integration than HCs. At the nodal level, SCD was marked by increased recruitment and reduced integration in regions mainly within the default mode network (DMN) and somatomotor network (SMN). In SCD, recruitment in the left anterior insula and ventral frontal cortex linked Aβ pathology to memory performance. In AD, integration in the left superior frontal gyrus mediated the effects of Aβ on memory and verbal fluency. The combination of differences in nodal recruitment and integration across groups helped distinguish between healthy, SCD, and AD individuals. Conclusions SCD individuals show distinct patterns of dynamic network reconfiguration, high recruitment, and low integration in DMN and SMN, offering new insights into early AD pathophysiology.

Increasing evidence indicates that blood-based biomarkers, particularly phosphorylated tau (pTau) 217 and the pTau217/amyloid‑β (Aβ) 42 ratio, demonstrate strong diagnostic performance for Alzheimer’s disease (AD) and may offer a minimally invasive alternative to cerebrospinal fluid (CSF) assays and Aβ PET imaging. There is an urgent need to develop local plasma pTau217 and pTau217/Aβ42 ratio assay and to establish population-appropriate diagnostic cutoffs tailored to Chinese populations. This study included 831 individuals from a community-based memory screening cohort and 301 patients from a hospital-based cohort with confirmed Aβ pathology. Plasma pTau217, pTau181, and their ratios to Aβ42 were measured using a high-sensitivity direct chemiluminescence (DCL) immunoassay incorporating proprietary China-developed antibodies. Data-driven Gaussian mixture modeling (GMM) was applied to the community cohort to derive biomarker cutoffs; the diagnostic performance of these cutoffs was validated in the patients with confirmed Aβ pathology. A two-cutoff approach was established in the hospital-based cohort. Multivariate regression analysis was performed to assessed potential confounding effects from routine blood biochemical parameters. GMM identified cutoffs of 4.380 pg/mL for pTau217 and 0.670 for the pTau217/Aβ42 ratio. These values closely matched cutoffs derived from the maximum Youden index (4.296 pg/mL for pTau217 and 0.706 for pTau217/Aβ42) and achieved high diagnostic accuracy (up to 89

Early identification of cerebral small vessel disease related cognitive impairment (CSVD-CI) is crucial for timely clinical intervention. We developed a Transformer-based deep learning model using white matter hyperintensity (WMH) radiomics features from T2-fluid-attenuated inversion recovery images to detect CSVD-CI. A total of 783 subjects (161 longitudinally followed) were enrolled from three centres for model development and external validation, using a domain adaptation strategy. The model achieved AUCs of 0.841 (training) and 0.859/0.749 (validation cohorts), outperforming conventional machine learning models. The gradient-weighted class activation mapping approach highlighted WMH textural features, particularly the logarithm-transformed gray level size zone matrix features, as key contributors. These features were significantly correlated with CSVD macro- and microstructural changes, mediated age-cognition relationships and predicted longitudinal cognitive decline. Our findings indicate that WMH radiomics features, reflecting CI-related biological changes in CSVD, combined with a Transformer-based deep learning model, constitute a feasible, automated, and non-invasive tool for CSVD-CI detection.

Lecanemab, a humanized IgG1 monoclonal antibody that targets soluble aggregated Aβ species (protofibrils), has demonstrated robust brain fibrillar amyloid reduction and slowing of clinical decline in early Alzheimer's disease(AD) and received its approval for this indication in the USA 2023 and China 2024. However, reports published of real-world data on this therapy are still very limited, espcially in China. LEAD is an investigator- led, multicenter, prospective, real-world study in 20 hospitals in Jiangsu Province, China. The primary objective was to assess the effectiveness of lecanemab under real-world clinical practice in early Alzheimer's diseasepatients in China. The secondary objectives included evaluating the safety of lecanemab in Chinese patients. This prospective cohort trial included early AD (mild cognitive impairment or mild dementia due to AD) patients having an indication for lecanemab. Each participant had evidence of amyloid on positronemission tomography (PET) or by cerebrospinal fluid testing. Baseline data on demographics, medical history, cognitive score, plasma biomarkers, Apoe and MR indicators were assessed and a treatment with intravenous lecanemab (10 mg per kilogram of body weight each 2 weeks) was started. The patients will be followed up, attend safety visits, provide blood samples to measure AD biomarkers at months 3, 6 and 12. AD blood biomarkers was detected using chemiluminescence. All cognitive assessments will be repeated at month 6 and 12, structural MR will be noted at month 1,1.5,3.5 and 6. The last study visit will be at month 12, when all baseline measurements will be repeated. The study was approved by the Drum Tower Hospital Research Ethics Committee (2024-746-01). This study is onging, 90 subjects have been recruited. Currently in the data extraction phase. Baseline data collection of the subjects is shown in Table 1. All patients will complete 6 months of treatment in July 2025. Updated result will be available for the conference. The LEAD project is a multi-center, real-world study that will determine the therapeutic efficacy of lecanemab in alleviating clinical symptoms and pathological aspects in Alzheimer's disease patients in Jiangsu, China, as well as monitor adverse effects, in order to assist the treatment of more Asian AD patients.

APOEε4 allele has an increased risk of Alzheimer's disease(AD) compared to others. Functional connectivity gradients are a novel hierarchical design of functional connectivity patterns in brain networks that captures the spatial correlations between connectivity patterns in various locations. The aim of this research is how the APOE ε4 affects the functional connectivity gradients of the default mode network (DMN) in AD and how it correlates with cognitive function. From September 2022 to September 2024, 271 subjects were recruited from memory clinic of Drum Tower Hospital, Nanjing University Medical School. The study included 108 healthy controls(HC) APOE ε4 non-carriers, 25 HC APOE ε4 carriers, 81 AD APOE ε4 non-carriers, and 57 AD APOE ε4 carriers. All individules underwent cognitive function testing, blood test of AD biomarkers and resting-state functional magnetic resonance imaging (rs-fMRI). A two-factor ANOVA and Correlation tests were utilized to examine the relationship between APOE ε4, functional gradients and cognitive function in four groups. Intermediary analysis was used to investigate the relationship between the DMN functional gradient and blood AD biomarkers. After controlling for sex, age, and years of education, there was an interaction between the presence of the APOE ε4 gene and the functional gradient in the right temporal lobe of DMN in two groups; In APOE ε4 non-carriers, the DMN functional gradient was significantly higher in AD compared to HC ( p  < 0.001), while in APOE ε4 carriers it was significantly lower in AD ( p  = 0.031); Among AD subjects, APOE-ε4 carriers showed a significant decrease in the default network functional gradient compared to non-carriers ( p  <0.001); APOE-ε4 carriers showed a positive correlation between DMN functional gradient in the right temporal lobe and several ognitive domains; Mediation analyses revealed that AD markers affect DMN resting-state functional connectivity by altering DMN functional gradients. The APOEε4 gene impacts the functional connectivity gradient of the default network, especially in the right temporal lobe in AD patients. They are more likely than non-carriers to experience functional network gradient derangement, which is linked to cognitive deterioration. This effect may be related to blood AD markers altering the DMN functional gradient affecting DMN resting-state functional connectivity.

The aim of this study was to explore the correlation between brain functional alterations and cerebrospinal fluid (CSF) pathological biomarkers in Alzheimer's disease (AD) patients. A total of 39 individuals were recruited, including 23 AD patients and 16 control subjects. All subjects underwent a battery of neuropsychological examinations, CSF measurement and multimodal magnetic resonance imaging scans. Independent component analysis was used to investigate the variations of functional connectivity (FC) between the two groups by utilizing the resting-sate functional MRI (RS-fMRI) data. Differences in ALFF and ReHo between the two groups were also calculated. Then correlation analyses were used to estimate the possible association between functional alterations and CSF β-amyloid (Aβ 1-42 .) and tau. Multiple inter- and intra-network functional connections were altered in AD patients compared to the Non ADCI group. In the AD group, ALFF decreased in the right Superior Frontal Gyrus, Middle Frontal Gyrus, left superior temporal gyrus. and increased in the right cerebellum anterior lobe, and caudate nucleus as compared to Non-AD CI group (p < 0.001). In addition, ReHo decreased in the right insula and left middle temporal gyrus (p < 0.001). Dynamic fluctuations of CSF Tau were observed to be associated with changes in FC between VN and PCC, FC of SMN, as well as the altered ReHo in the right insula and left middle temporal gyrus. Compared the AD group with the non-AD CI group, the aforementioned altered functional brain connectivity, with the exception of FC in the PCC and VN, was significantly associated with a decrease in CSF Aβ 1-42 . AD patients have exhibited functional changes in more than one brain region. These changes are linked to the variations of Tau protein and Aβ 1-42 in CSF, with Aβ 1-42 having a particularly large impact on brain network function. From an imaging standpoint, this study validated the impact of pathological changes on brain function in AD.

Polycystic ovary syndrome (PCOS) is a common reproductive and metabolic disorder in the reproductive-age women. The international evidence-based guideline for the assessment and management of PCOS 2023 now suggests raising the follicle number per ovary (FNPO) threshold from 12 to 20 to define its key feature, polycystic ovarian morphology (PCOM). However, understanding of low- and high-FNPO PCOS cases defined in this cutoff is very limited. Given that the measures of lipoprotein subfractions are the biomarkers of several common diseases, this study aims to explore clinical characteristics and lipoprotein subfractions in low- and high-FNPO PCOS, and develop a diagnostic model. A total of 1918 women including 792 low- and 182 high-FNPO PCOS cases, met the international evidence-based guideline 2023, and 944 controls were collected for clinical data analysis. Plasma samples of 66 low-FNPO and 24 high-FNPO PCOS cases and 22 controls matched with BMI and age were utilized for the measurement of 112 lipoprotein subfractions by nuclear magnetic resonance spectroscopy. Partial least squares discriminant analysis (PLS-DA) and logistic regression analysis were used to identify key lipoprotein subfractions. Ten machine learning algorithms and recursive feature elimination with logistic regression were used to construct the effective model to predict PCOM based on the new guideline. Models were validated with bootstrap resampling. High-FNPO PCOS cases presented worse lipid parameters compared with low-FNPO cases and controls. Based on the results of PLS-DA and logistic regression analysis, seven key lipoprotein subfractions were selected, including V2TG, V3TG, V4TG, V2CH, V3CH, V3PL, and V4PL. The addition of them into the anti-Müllerian hormone (AMH) models for predicting high-FNPO PCOS resulted in a significantly improved model performance (AUC increased from 0.750 to 0.874). Even if the only V3TG was added into the AMH model, the AUC increased to 0.807. Lipid metabolism, particularly seven key lipoprotein subfractions, has been identified as a major risk factor for high-FNPO PCOS cases. Among these, V3TG subfraction warrants special attention, both from the perspective of disease risk and precision diagnosis. Due to the lack of effective external validation at this stage, validation of larger sample sizes is necessary before generalizing the application.

BackgroundApolipoprotein E (APOE) ε4 is the most significant genetic risk factor for sporadic Alzheimer's disease (AD). However, its impact on the dynamic changes in resting-state functional connectivity (FC), particularly concerning network formation, interaction, and dissolution over time, remains largely unexplored in AD.ObjectiveThis study aims to explore the effect of APOE ε4 on dynamic FC (dFC) variability and cognitive performance in AD.MethodsWe analyzed the dFC of AD patients, comparing APOE ε4 carriers (n = 33) with non-carriers (n = 41). The whole-brain dFC was assessed by calculating dynamic fractional amplitude of low-frequency fluctuations (dfALFF) and dynamic regional homogeneity (dReHo). To further explore the relationship between cognitive function and dFC in AD patients, we conducted a correlation analysis. Mediation analysis was also performed to determine whether dFC mediates the link between the APOE ε4 and cognitive decline in AD patients.ResultsAD patients carrying the APOE ε4 exhibited more severe cognitive impairment, along with reduced dReHo and dfALFF in both the left and right posterior cerebellar lobes. In these carriers, the dFC analysis showed lower dFC between the left posterior cerebellar lobe and the left middle temporal gyrus, which was positively correlated with executive function and information processing speed. Additionally, mediation analysis indicated that APOE ε4 influences dFC in this brain region, contributing to executive dysfunction in AD.ConclusionsThese findings offer preliminary evidence that APOE ε4 modulates fluctuating communication within the cerebellar lobe and the dFC between the cerebellar lobe and the temporal gyrus in AD.

Previous studies on gait changes in mild cognitive impairment (MCI) are inconsistent. Alzheimer’s disease (AD) plasma biomarkers, amyloid beta (Aβ) and phosphorylated-tau (p-tau), are relevant to gait disorders. This study explores gait changes in MCI and the relationship between gait performance and AD plasma biomarkers. 231 participants were recruited and stratified based on p-tau181 levels into: low p-tau181 with normal cognition (lT-NC), low p-tau181 with MCI (lT-MCI), and high p-tau181 with MCI (hT-MCI). The same cohort was subsequently stratified by Aβ42/Aβ40 levels into: high Aβ42/Aβ40 with normal cognition (hA-NC), high Aβ42/Aβ40 with MCI (hA-MCI), and low Aβ42/Aβ40 with MCI (lA-MCI). Demographic, cognitive and gait data were compared across groups. The hT-MCI and lA-MCI groups were older than the other groups. Significant differences in stride length were found between lT-NC and hT-MCI, lT-MCI and hT-MCI, but not between lT-NC and lT-MCI. Neuropsychological assessments revealed poorer performance in hT-MCI and lT-MCI groups relative to lT-NC, while global cognitive function was comparable between hT-MCI and lT-MCI groups. No such associations were observed between stride length and Aβ42/Aβ40 levels. Decreased stride length, which is generally considered to be indicative of poorer gait, was significantly associated with elevated p-tau181 levels and independent of global cognitive status. These findings highlight the potential of p-tau181 as a biomarker for tau-related motor dysfunction in MCI.

BACKGROUND:APOEε4 allele has an increased risk of Alzheimer's disease(AD) compared to others. Functional connectivity gradients are a novel hierarchical design of functional connectivity patterns in brain networks that captures the spatial correlations between connectivity patterns in various locations. The aim of this research is how the APOE ε4 affects the functional connectivity gradients of the default mode network (DMN) in AD and how it correlates with cognitive function. METHOD:From September 2022 to September 2024, 271 subjects were recruited from memory clinic of Drum Tower Hospital, Nanjing University Medical School. The study included 108 healthy controls(HC) APOE ε4 non-carriers, 25 HC APOE ε4 carriers, 81 AD APOE ε4 non-carriers, and 57 AD APOE ε4 carriers. All individules underwent cognitive function testing, blood test of AD biomarkers and resting-state functional magnetic resonance imaging (rs-fMRI). A two-factor ANOVA and Correlation tests were utilized to examine the relationship between APOE ε4, functional gradients and cognitive function in four groups. Intermediary analysis was used to investigate the relationship between the DMN functional gradient and blood AD biomarkers. RESULT:After controlling for sex, age, and years of education, there was an interaction between the presence of the APOE ε4 gene and the functional gradient in the right temporal lobe of DMN in two groups; In APOE ε4 non-carriers, the DMN functional gradient was significantly higher in AD compared to HC (p < 0.001), while in APOE ε4 carriers it was significantly lower in AD (p = 0.031); Among AD subjects, APOE-ε4 carriers showed a significant decrease in the default network functional gradient compared to non-carriers (p <0.001); APOE-ε4 carriers showed a positive correlation between DMN functional gradient in the right temporal lobe and several ognitive domains; Mediation analyses revealed that AD markers affect DMN resting-state functional connectivity by altering DMN functional gradients. CONCLUSION:The APOEε4 gene impacts the functional connectivity gradient of the default network, especially in the right temporal lobe in AD patients. They are more likely than non-carriers to experience functional network gradient derangement, which is linked to cognitive deterioration. This effect may be related to blood AD markers altering the DMN functional gradient affecting DMN resting-state functional connectivity.

BackgroundAlzheimer's disease (AD) involves Aβ and tau pathology, initiating years before symptoms. the apolipoprotein E ε4 allele (APOE ε4) is the major genetic risk factor, influencing neurodegeneration and functional network disruption. This study investigates how APOE ε4 modulates the default mode network (DMN)'s hierarchical organization to accelerate cognitive decline.ObjectiveThis study aimed to elucidate how APOE ε4 accelerates AD pathological progression by altering the functional gradient hierarchy of DMN, and to evaluate the potential of DMN gradient abnormalities as an early diagnostic biomarker for AD.MethodsWe enrolled 271 participants, categorized by diagnosis and APOE ε4 status. All underwent neuropsychological assessment, plasma Aβ42/40 measurement, and resting-state functional MRI. DMN functional gradients were quantified using the BrainSpace toolbox. Statistical analyses included a 2 × 2 factorial design, mediation analysis, and correlation testing with cognitive scores.ResultsA significant Group × Genotype interaction was identified in the right inferior temporal gyrus (RITG). AD patients with APOE ε4 showed the most severe gradient attenuation, while non-carrier patients exhibited compensatory elevation. The RITG gradient correlated with multiple cognitive domains exclusively in APOE ε4 carriers. Altered connectivity between the left superior frontal gyrus (LSFG) and RITG mediated the effect of Aβ burden on gradient disruption.ConclusionsAPOE ε4 accelerates cognitive decline in AD by specifically disrupting the DMN functional gradient hierarchy, particularly within the right ITG. Amyloid-β deposition contributes to macro-scale DMN topological disorganization by impairing LSFG-RITG functional connectivity. DMN functional gradient mapping provides a sensitive biomarker for early AD diagnosis and a novel target for APOE ε4-targeted interventions.

Chronic cerebral hypoperfusion (CCH) leads to white matter injury (WMI), a key contributor to the development of vascular cognitive impairment (VCI). Beraprost sodium (BPS) is a chemically stable and orally active prostaglandin I2 (PGI2) analog, while the role and mechanism of BPS in VCI have not been well understood. In this study, we used a mouse model of bilateral carotid artery stenosis (BCAS mice) and demonstrated that BPS treatment facilitated the proliferation and differentiation of oligodendrocyte precursor cells (OPCs), potentially via PDGFR-α pathway modulation. This intervention promoted remyelination and attenuated WMI and cognitive dysfunction in BCAS mice. Collectively, our results suggested that BPS mitigates chronic ischemic WMI by targeting OPC development, providing a potential therapeutic avenue for VCI.

Diabetes causes cognitive impairment, and the hippocampus is important for long-term and permanent memory function. However, the mechanism of their interaction is still unclear. In this study, rat models of diabetes mellitus were generated by a single injection of streptozotocin (STZ). This study aims to explore the changes in myelinated fibers in the hippocampus of type 1 diabetic rats. The unbiased stereological methods and transmission electron microscopy were used to obtain the total volume of the hippocampus, the total volume of the myelin sheath, the total length of the myelinated nerve fibers, the distribution of the length with different diameters of the myelinated fibers, and the distribution of the length with different thickness of the myelin sheath. Stereological analysis revealed that, compared to that of the control group, the total myelinated fibers volumes and the total myelinated fibers length were decreased slightly, while the total volume and the thickness of myelin sheaths were significantly decreased in the diabetic group. Finally, when compared with the control group, the total length of myelinated fibers in the diabetes group was significantly reduced, with diameters ranging from 0.7 to 1.1 μm and thicknesses of myelin sheaths from 0.15 to 0.17 μm. This study provides the first experimental evidence by stereological means to demonstrate that myelinated nerve fibers may be the key factor in cognitive dysfunction in diabetes.

Purpose: The aim of this study was to explore the correlation between brain functional network alterations and cerebrospinal fluid (CSF) pathological biomarkers in Alzheimer’s disease (AD)-spectrum patients. Method: A total of 39 individuals were recruited, including 23 AD patients and 16 control subjects. All subjects underwent a battery of neuropsychological examinations, CSF measurement and multimodal magnetic resonance imaging scans. Independent component analysis was used to investigate the differences of functional connectivity（FC）among the two groups based on the resting-sate functional MRI (fMRI) data. Then correlation analyses were used to estimate the potential relationship between functional network alterations and cerebral amyloid and tau burden. Result: Multiple inter- and intra-network functional connections were altered in AD patients compared to the Non ADCI group. Alterations in FC between VN and PCC, as well as the functional connections of SMN were found to be associated with the dynamic changes of CSF Tau. Compared the AD group with the non-AD CI group, the aforementioned altered functional brain connectivity, with the exception of FC in the PCC and VN, was significantly associated with a decrease in CSF Aβ Conclusion: This study provides provisional evidence that the brain functional network alterations was closely associated with CSF pathological characteristics, and these exploratory results support new research ideas for the early diagnosis of AD.

Introduction: Early identification of white matter hyperintensity-related cognitive impairment (WMH-CI) through normal MRI images is of great significance for early clinical intervention to reduce the occurrence of dementia. The aim of this study was to develop a generalizable and interpretable deep learning model for screening WMH-related CI using radiomic features (RFs) from T2 fluid-attenuated inversion recovery (T2-FLAIR) images. Methods: A total of 783 subjects were enrolled from three medical centres. RFs for WMH lesions were extracted from T2-FLAIR images in each subject. A deep learning model with a hierarchical transformer architecture was used to leverage all extracted RFs, instead of feature selection, to develop and cross-validate the diagnostic model for cognitive dysfunction. Unsupervised domain adaptation was used to address the cross-centre data inconsistencies without labelling the outer centre data. A gradient-weighted class activation mapping approach was adopted to identify the RFs that contributed most to the diagnosis. Subgroup analysis, correlation analysis and mediation analysis were performed to confirm the clinical relevance of the model. Besides, we also verify the clinical importance of the model by microstructural pathology of WMH detected by diffusion tensor imaging. Results: The deep learning model showed robust diagnostic power for WMH related CI, with an area under the receiver operating curve (AUC) of 0.841±0.016 in the development cohort. The prediction accuracy, sensitivity, specificity, precision and recall were 0.793 ± 0.108, 0.798 ± 0.021, 0.800 ± 0.065, 0.716±0.055 and 0.793 ± 0.108, respectively. The model generalized well across different subgroups. It also performed well in other two external verification cohorts, with an AUC of 0.859 and 0.749, respectively. The visual representation showed that the most important features were textural features, which were also significantly correlated with clinical assessment scale and diffusion parameters. Conclusions: This study presents a non-invasive imaging biomarker that can identify WMH-CI patients and is applicable to all levels of hospitals since only conventional MRI images are needed.

Mild cognitive impairment (MCI), regarded as the prodromal stage before the clinical phase of Alzheimer’s disease (AD), has been considered for early differential diagnosis. Patients with amnestic mild cognitive impairment (aMCI), an important subtype of MCI, are more likely to progress to clinical Alzheimer disease (AD). To examine the structural and functional connectome in both kinds of MCI and found differences in structural connectivity (SC)-functional connectivity (FC) coupling. Fifty-nine individuals with aMCI, non-amnestic mild cognitive impairment (naMCI) and healthy controls (NC) underwent resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI). Brains were parcellated into functional modules according to the FC networks of NC, and individual FC and SC within modules as well as average FC, average SC and average SC-FC correlation values in each module among groups were analyzed, while logistic regression was used to find predictive factors. After controlling for age, sex, and education, the FC values in the temporal-occipital module and the SC-FC correlation values in the temporal-occipital and the default mode module appeared associated with the prediction of aMCI. These modular connectivity values can be used for further study of MCI subtypes.

Study Objectives:By examining spontaneous activity changes of sleep-related networks in patients with the Alzheimer's disease (AD) spectrum with or without insomnia disorder (ID) over time via neuro-navigated repetitive transcranial magnetic stimulation (rTMS), we revealed the effect and mechanism of rTMS targeting the left-angular gyrus in improving the comorbidity symptoms of the AD spectrum with ID.Methods:A total of 34 AD spectrum patients were recruited in this study, including 18 patients with ID and the remaining 16 patients without ID. All of them were measured for cognitive function and sleep by using the cognitive and sleep subscales of the neuropsychiatric inventory. The amplitude of low-frequency fluctuation changes in sleep-related networks was revealed before and after neuro-navigated rTMS treatment between these two groups, and the behavioral significance was further explored.Results:Affective auditory processing and sensory-motor collaborative sleep-related networks with hypo-spontaneous activity were observed at baseline in the AD spectrum with ID group, while substantial increases in activity were evident at follow-up in these subjects. In addition, longitudinal affective auditory processing, sensory-motor and default mode collaborative sleep-related networks with hyper-spontaneous activity were also revealed at follow-up in the AD spectrum with ID group. In particular, longitudinal changes in sleep-related networks were associated with improvements in sleep quality and episodic memory scores in AD spectrum with ID patients.Conclusion:We speculated that left angular gyrus-navigated rTMS therapy may enhance the memory function of AD spectrum patients by regulating the spontaneous activity of sleep-related networks, and it was associated with memory consolidation in the hippocampus-cortical circuit during sleep.Clinical Trial Registration:The study was registered at the Chinese Clinical Trial Registry, registration ID: ChiCTR2100050496, China.

Background Neuro-navigated repetitive transcranial magnetic stimulation (rTMS) is potentially effective in enhancing cognitive performance in the spectrum of Alzheimer’s disease (AD). We explored the effect of rTMS-induced network reorganization and its predictive value for individual treatment response. Methods Sixty-two amnestic mild cognitive impairment (aMCI) and AD patients were recruited. These subjects were assigned to multimodal magnetic resonance imaging scanning before and after a 4-week stimulation. Then, we investigated the neural mechanism underlying rTMS treatment based on static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) analyses. Finally, the support vector regression was used to predict the individual rTMS treatment response through these functional features at baseline. Results We found that rTMS at the left angular gyrus significantly induced cognitive improvement in multiple cognitive domains. Participants after rTMS treatment exhibited significantly the increased sFNC between the right frontoparietal network (rFPN) and left frontoparietal network (lFPN) and decreased sFNC between posterior visual network and medial visual network. We revealed remarkable dFNC characteristics of brain connectivity, which was increased mainly in higher-order cognitive networks and decreased in primary networks or between primary networks and higher-order cognitive networks. dFNC characteristics in state 1 and state 4 could further predict individual higher memory improvement after rTMS treatment (state 1, R = 0.58; state 4, R = 0.54). Conclusion Our findings highlight that neuro-navigated rTMS could suppress primary network connections to compensate for higher-order cognitive networks. Crucially, dynamic regulation of brain networks at baseline may serve as an individualized predictor of rTMS treatment response. Relevance statement Dynamic reorganization of brain networks could predict the efficacy of repetitive transcranial magnetic stimulation in the spectrum of Alzheimer’s disease. Key points • rTMS at the left angular gyrus could induce cognitive improvement. • rTMS could suppress primary network connections to compensate for higher-order networks. • Dynamic reorganization of brain networks could predict individual treatment response to rTMS. Graphical Abstract