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Background Subjective cognitive decline (SCD) is a preclinical stage along the Alzheimer’s disease (AD) continuum. However, little is known about the aberrant patterns of connectivity and topological alterations of the brain functional connectome and their diagnostic value in SCD. Methods Resting-state functional magnetic resonance imaging and graph theory analyses were used to investigate the alterations of the functional connectome in 66 SCD individuals and 64 healthy controls (HC). Pearson correlation analysis was computed to assess the relationships among network metrics, neuropsychological performance and pathological biomarkers. Finally, we used the multiple kernel learning-support vector machine (MKL-SVM) to differentiate the SCD and HC individuals. Results SCD individuals showed higher nodal topological properties (including nodal strength, nodal global efficiency and nodal local efficiency) associated with amyloid-β levels and memory function than the HC, and these regions were mainly located in the default mode network (DMN). Moreover, increased local and medium-range connectivity mainly between the bilateral parahippocampal gyrus (PHG) and other DMN-related regions was found in SCD individuals compared with HC individuals. These aberrant functional network measures exhibited good classification performance in the differentiation of SCD individuals from HC individuals at an accuracy up to 79.23%. Conclusion The findings of this study provide insight into the compensatory mechanism of the functional connectome underlying SCD. The proposed classification method highlights the potential of connectome-based metrics for the identification of the preclinical stage of AD.

: Subjective cognitive decline (SCD) is considered a preclinical state of Alzheimer's disease (AD) and may represent a more advanced preclinical status than amnestic mild cognitive impairment (aMCI). Our aim was to explore changes in the white matter (WM) microstructure and their correlation with cognitive function in these AD-spectrum patients. : Diffusion tensor images from 43 individuals with normal cognition (NC), 38 SCD patients, and 36 aMCI patients were compared using an atlas-based segmentation strategy. The correlation between diffusion parameters and cognitive function was further analyzed. : The anatomical pattern of WM impairment was generally similar between SCD and aMCI patients. However, aMCI patients showed significantly lower fractional anisotropy (i.e., corpus callosum forceps major and forceps minor) and increased mean diffusivity [i.e., bilateral anterior thalamic radiation (ATR), left corticospinal tract (CST), forceps minor, left cingulum (cingulate gyrus), left cingulum hippocampus, and left inferior fronto-occipital fasciculus (IFO)] in some tracts than did SCD subjects, indicating a disruption in WM microstructural integrity in the aMCI. Individuals with microstructural disruption in forceps minor, left cingulum (cingulate gyrus), and left cingulum hippocampus tracts performed worse in general cognition and memory function tests, as indicated by line regression analysis. : SCD individuals had extensive WM microstructural damage in a pattern similar to that seen in aMCI, although presenting a cognitive performance comparable with that of cognitively healthy individuals. Our results suggest that WM integrity might precede objectively measurable memory decline and may be a potential early biomarker for AD.

Neuroimaging evidence has suggested white matter microstructure are heavily affected in Alzheimer's disease (AD). However, whether white matter dysfunction is localized at the specific regions of fiber tracts and whether they would be a potential biomarker for AD remain unclear. By automated fiber quantification (AFQ), we applied diffusion tensor images from 25 healthy controls (HC), 24 amnestic mild cognitive impairment (aMCI) patients and 18 AD patients to create tract profiles along 16 major white matter fibers. We compared diffusion metrics [Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR)] between groups. To assess the diagnostic value, we applied a random forest (RF) classifier, a type of machine learning method. In the global tract level, we found that aMCI and AD patients showed higher MD, DA, and DR values in some fiber tracts mostly in the left hemisphere compared to HC. In the point-wise level, widespread disruption were distributed on specific locations of different tracts. The point-wise MD measurements presented the best classification performance with respect to differentiating AD from HC. The two most important variables were localized in the prefrontal potion of left uncinate fasciculus and anterior thalamic radiation. In addition, the point-wise DA in the posterior component of the left cingulum cingulate displayed the most robust discriminative ability to identify AD from aMCI. Our findings provide evidence that white matter abnormalities based on the AFQ method could be as a diagnostic biomarker in AD.

Objective: To characterize earlier damage pattern of white matter (WM) microstructure in cerebral small vessel disease (CSVD) and its relationship with cognitive domain dysfunction. Methods: A total of 144 CSVD patients and 100 healthy controls who underwent neuropsychological measurements and diffusion tensor imaging (DTI) examination were recruited. Cognitive function, emotion, and gait were assessed in each participant. The automated fiber quantification (AFQ) technique was used to extract different fiber properties between groups, and partial correlation and general linear regression analyses were performed to assess the relationship between position-specific WM microstructure and cognitive function. Results: Specific segments in the association fibers, commissural WM regions of interest (ROIs), and projection fibers were damaged in the CSVD group [ P < 0.05, family-wise error (FWE) correction], and these damaged segments showed interhemispheric symmetry. In addition, the damage to specific tract profiles [including the posteromedial component of the right cingulum cingulate (CC), the occipital lobe portion of the callosum forceps major, the posterior portion of the left superior longitudinal fasciculus (SLF), and the bilateral anterior thalamic radiation (ATR)] was related to the dysfunction in specific cognitive domains. Among these tracts, we found the ATR to be the key set of tracts whose profiles were most associated with cognitive dysfunction. The left ATR was a specific fiber bundle associated with episode memory and language function, whereas the fractional anisotropy (FA) values of the intermediate component of the right ATR were negatively correlated with executive function and gait evaluation. It should be noted that the abovementioned relationships could not survive the Bonferroni correction ( p < 0.05/27), so we chose more liberal uncorrected statistical thresholds. Conclusions: Damage to the WM fiber bundles showed extensive interhemispheric symmetry and was limited to particular segments in CSVD patients. Disruption of strategically located fibers was associated with different cognitive deficits, especially the bilateral ATR.

Differentiating between Alzheimer's disease (AD) and frontotemporal dementia (FTD) can be challenging due to overlapping cognitive and behavioral manifestations. Evidence regarding non-invasive and early-stage biomarkers remains limited. Our aim was to identify retinal biomarkers for the risk of AD and FTD in populations without dementia and explore underlying brain structural mechanisms. We included a total of 3,0573 UK Biobank participants without dementia, ocular disorders, and diabetes who underwent baseline retinal optical coherence tomography (OCT) imaging. Cox proportional hazards models were used to estimate the associations between macular OCT parameters and the risk of AD and FTD. Mediation analysis was used to explore the underlying mechanisms affected by brain structures. The mean age at recruitment was 55.27, and 46.10% of the participants were male. During a mean follow-up of 9.15 ± 2.59 years, 148 patients with AD and eight patients with FTD were identified. Reduced thickness of the ganglion cell-inner plexiform layer (GC-IPL) at baseline was associated with an increased risk of AD (HR, 1.033; 95% CI, 1.001-1.066;  = 0.044), while thinner retinal pigment epithelial in the inner superior subfield at baseline was associated with an elevated risk of FTD (HR, 1.409; 95% CI, 1.060-1.871;  = 0.018). Structurally abnormal visual pathways, including cortical and subcortical gray matter volumes, as well as white matter integrity, mediated the association between the GC-IPL thickness and AD risk. Our findings provide preliminary empirical support for a relationship between prodromal changes in retinal layers and a higher risk of AD or FTD, suggesting that macular OCT may serve as a non-invasive, sensitive biomarker of high-risk years before the onset of dementia.

White matter hyperintensity (WMH) is widely observed in the elderly population and serves as a key indicator of cognitive impairment (CI). However, the underlying mechanism remains to be elucidated. Herein, we investigated the topological patterns of resting state functional networks in WMH subjects and the relationship between the topological measures and CI. A graph theory-based analysis was employed in the resting-state functional magnetic resonance scans of 112 subjects (38 WMH subjects with cognitive impairment without dementia (CIND), 36 WMH subjects with normal cognition and 38 healthy controls (HCs), and we found that WMH-CIND subjects displayed decreased global efficiency at the levels of the whole brain, specific subnetworks [fronto-parietal network (FPN) and cingulo-opercular network (CON)] and certain nodes located in the FPN and CON, as well as decreased local efficiency in subnetworks. Our results demonstrated that nodal global efficiency in frontal and parietal regions mediated the impairment of information processing speed related to periventricular WMH (PWMH). Additionally, we performed support vector machine (SVM) analysis and found that altered functional efficiency can identify WMH-CIND subjects with high accuracy, sensitivity and specificity. These findings suggest impaired functional networks in WMH-CIND individuals and that decreased functional efficiency may be a feature of CI in WMH subjects.

Both episodic memory and executive function are impaired in amnestic mild cognitive impairment (aMCI) subjects, but it is unclear if these impairments are independent or interactive. The present study aimed to explore the relationship between episodic memory deficits and executive function deficits, and the underlying functional mechanisms in aMCI subjects. Thirty-one aMCI subjects and 27 healthy subjects underwent neuropsychological tests and multimodal magnetic resonance imaging (MRI) scans. Hippocampal networks and medial prefrontal cortex (MPFC) networks were identified based on resting-sate functional MRI (fMRI) data. AMCI subjects displayed lower episodic memory scores and executive function scores than control subjects, and the episodic memory scores were positively correlated with the executive function scores in aMCI subjects. Brain network analyses showed an interaction between the hippocampal networks and the MPFC networks, and the interaction was significantly associated with the episodic memory scores and the executive function scores. Notably, aMCI subjects displayed higher functional connectivity (FC) of the right hippocampal network with the right prefrontal cortex than did control subjects, but this difference disappeared when controlling for the MPFC networks. Furthermore, the effects of the MPFC networks on the hippocampal networks were significantly associated with the episodic memory scores in aMCI subjects. The present findings suggested that the episodic memory deficits in aMCI subjects could be partially underpinned by the modulation of the MPFC networks on the hippocampal networks.

Background Composite dietary antioxidant index (CDAI) is a critical metric for assessing antioxidant‐rich diets. However, the relationship between the CDAI and dementia has not yet been explored. This study aimed to investigate the association between CDAI and the risk of dementia and dementia subtypes, as well as the underlying mechanisms involved. Methods A total of 157,742 dementia‐free participants from the UK Biobank were prospectively analyzed. CDAI was calculated based on the intake of six dietary antioxidants derived from dietary information using a 24‐hour recall questionnaire. Cox proportional hazards models were used to investigate the associations between CDAI and the risk of all‐cause dementia, Alzheimer's disease (AD), and vascular dementia (VD). Restricted cubic splines were used to examine potential non‐linear correlations. Multivariable linear regression and mediation analyses were conducted to explore the underlying mechanisms, focusing on blood inflammation markers and brain structures. Results During a median follow‐up of 13.39 years, 1,822 participants (1.16%) were diagnosed with dementia, including 791 cases of AD and 322 cases of VD. After multivariable adjustment, higher CDAI scores were significantly associated with a decreased risk of all‐cause dementia and AD. An L‐shaped nonlinear association was found between CDAI scores and both all‐cause dementia and AD, with inflection points at 1.579 for all‐cause dementia and 0.848 for AD. Below the inflection points, each unit increase in CDAI was associated with a 6.3% reduced risk of all‐cause dementia (HR, 0.937; 95% CI: 0.907‐0.968, p < 0.001) and a 6.5% reduced risk of AD (HR, 0.935; 95% CI: 0.897‐0.974, p = 0.001). Blood inflammation markers partially mediate the relationship between CDAI and all‐cause dementia and AD. CDAI was positively associated with cortical and subcortical volumes in the lower CDAI group after Bonferroni correction. No mediating effects of the brain volume were observed. Conclusions There was an L‐shaped nonlinear association between CDAI scores and the risk of all‐cause dementia and AD. The CDAI has potential value as a biomarker for dementia and a dietary intervention target for reducing dementia risk. The beneficial effects of CDAI on inflammatory markers and brain structure provide valuable insights into the underlying mechanisms. However, further studies are required to confirm these results.

Let →G be a finite simple directed graph with n vertices, and let Γ be a finite abelian group of order n . A Γ -distance magic labeling is a bijection φ:V(→G)⟶Γ for which there exists c∈Γ such that ∑y∈N+(x)φ(y)−∑y∈N−(x)φ(y)=c for any x∈V(→G) , where N+(x) and N−(x) denote the set of the head and the tail of x , respectively. In this paper, we obtain a necessary and sufficient condition for that there exists a Γ-distance magic labeling for the Cartesian products of two directed cycles.

Background Insulin resistance, a manifestation of insulin signaling pathway disorders, can induce neuroinflammation by interacting with Alzheimer's disease (AD) pathology. The triglyceride‐glucose (TyG) index provides an effective method to reflect insulin resistance levels. However, the role of insulin resistance in the pathophysiology of AD remains unclear. This study aimed to investigate the association between TyG index and cognitive function in patients with AD. Method A total of 1029 participants with positive β‐amyloid biomarkers were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI), according to the amyloid PET or cerebrospinal fluid Aβ42 levels. Triglyceride‐glucose (TyG) index was calculated using fasting blood glucose and triglyceride levels. Comprehensive cognitive level was represented by the global Clinical Dementia Scale (CDR‐G), CDR‐sum of boxes (CDR‐SB), Mini‐Mental State Examination (MMSE), and Preclinical Alzheimer's Cognitive Composite (PACC). Multivariate linear regression analysis was used to examine the association between TyG index and cognitive function, adjusting for age, gender, education, race, marriage, smoking and drinking history, apolipoprotein E genotype, BMI, hypertension and diabetes history. Result Patients with AD in the highest TyG quartile group demonstrated the worst Clinical Dementia Rating‐Sum of Boxes (CDR‐SB) scores (p = 0.035). A higher TyG index was correlated with higher CDR‐SB (r=0.065, p = 0.035), lower PACC (r=‐0.048, p = 0.022), and lower MMSE (r=‐0.052, p = 0.018) scores. Multivariate regression analysis confirmed that TyG index remained independently associated with higher CDR‐SB scores (β = 0.02, 95% CI = [0.01, 0.04], p = 0.041) after adjusting for age, gender, education, race, marriage, smoking and drinking history, apolipoprotein E genotype, BMI, hypertension and diabetes history. Conclusion Our findings indicate a significant association between insulin resistance and cognitive impairment in patients with Alzheimer's disease, suggesting the potential importance of insulin resistance in AD pathophysiology.