Subjective Cognitive Decline Modifies the Relationship Between Cerebral Blood Flow and Memory Function in Cognitively Normal Older Adults

Greater subjective cognitive decline severity is associated with worse memory performance and lower entorhinal cerebral blood flow in healthy older adults

OBJECTIVE

Subjective cognitive decline (SCD) is a potential early risk marker for Alzheimer's disease (AD), but its utility may vary across individuals. We investigated the relationship of SCD severity with memory function and cerebral blood flow (CBF) in areas of the middle temporal lobe (MTL) in a cognitively normal and overall healthy sample of older adults. Exploratory analyses examined if the association of SCD severity with memory and MTL CBF was different in those with lower and higher cardiovascular disease (CVD) risk status.

METHODS

Fifty-two community-dwelling older adults underwent magnetic resonance imaging, neuropsychological testing, and were administered the Everyday Cognition Scale (ECog) to measure SCD. Regression models investigated whether ECog scores were associated with memory performance and MTL CBF, followed by similar exploratory regressions stratified by CVD risk status (i.e., lower vs higher stroke risk).

RESULTS

Higher ECog scores were associated with lower objective memory performance and lower entorhinal cortex CBF after adjusting for demographics and mood. In exploratory stratified analyses, these associations remained significant in the higher stroke risk group only.

CONCLUSIONS

Our preliminary findings suggest that SCD severity is associated with cognition and brain markers of preclinical AD in otherwise healthy older adults with overall low CVD burden and that this relationship may be stronger for individuals with higher stroke risk, although larger studies with more diverse samples are needed to confirm these findings. Our results shed light on individual characteristics that may increase the utility of SCD as an early risk marker of cognitive decline.

Subjective Memory Complaints Predict Decline in Memory, Instrumental Activities of Daily Living, and Social Participation in Older Adults: A Fixed-Effects Model

IMPORTANCE

Although subjective memory complaints (SMCs) have been suggested to be associated with future memory impairment, limitations in instrumental activities of daily living (IADLs), and social participation restriction, these associations are still inconclusive.

OBJECTIVE

To determine whether changes in SMCs over time predict decline in memory, IADLs, and social participation in older adults.

DESIGN

Longitudinal study.

SETTING

Community.

PARTICIPANTS

Sample 1 included 2,493 community-dwelling older adults drawn from the Health and Retirement Study (HRS) data collected between 2004 and 2018. Sample 2 included 1,644 community-dwelling older adults drawn from the HRS data collected between 2008 and 2018.

OUTCOMES AND MEASURES

Self-reported SMCs, memory function, self-reported IADL performance, and self-reported social participation.

RESULTS

The mean age of Sample 1 at baseline was 70.16 yr; 1,468 (58.88%) were female. In Sample 1, immediate and delayed memory (all ps < .001) and IADL performance (p < .01) declined over time. Increases in SMCs over time significantly predicted future immediate and delayed memory declines (p < .01 and p < .001, respectively) and future IADL performance decline (p < .001), after controlling for depressive symptoms. The mean age of Sample 2 at baseline was 71.52 yr; 928 (56.45%) were female. In Sample 2, social participation declined over time (all ps < .001). Increases in SMCs over time significantly predicted future social participation decline (p < .05), after controlling for depressive symptoms.

CONCLUSIONS AND RELEVANCE

Increases in SMCs predict future decline in memory, IADL performance, and social participation after accounting for depressive symptoms. What This Article Adds: SMCs can be used as an early indicator of future memory impairment, IADL limitations, and social participation restrictions in older adults. Furthermore, interventions that minimize SMCs may help older adults achieve successful aging.

Recent advances in arterial spin labeling perfusion MRI in patients with vascular cognitive impairment

Cognitive impairment (CI) is a major health concern in aging populations. It impairs patients' independent life and may progress to dementia. Vascular cognitive impairment (VCI) encompasses all cerebrovascular pathologies that contribute to cognitive impairment (CI). Moreover, the majority of CI subtypes involve various aspects of vascular dysfunction. Recent research highlights the critical role of reduced cerebral blood flow (CBF) in the progress of VCI, and the detection of altered CBF may help to detect or even predict the onset of VCI. Arterial spin labeling (ASL) is a non-invasive, non-ionizing perfusion MRI technique for assessing CBF qualitatively and quantitatively. Recent methodological advances enabling improved signal-to-noise ratio (SNR) and data acquisition have led to an increase in the use of ASL to assess CBF in VCI patients. Combined with other imaging modalities and biomarkers, ASL has great potential for identifying early VCI and guiding prediction and prevention strategies. This review focuses on recent advances in ASL-based perfusion MRI for identifying patients at high risk of VCI.

A novel generation adversarial network framework with characteristics aggregation and diffusion for brain disease classification and feature selection

Imaging genetics provides unique insights into the pathological studies of complex brain diseases by integrating the characteristics of multi-level medical data. However, most current imaging genetics research performs incomplete data fusion. Also, there is a lack of effective deep learning methods to analyze neuroimaging and genetic data jointly. Therefore, this paper first constructs the brain region-gene networks to intuitively represent the association pattern of pathogenetic factors. Second, a novel feature information aggregation model is constructed to accurately describe the information aggregation process among brain region nodes and gene nodes. Finally, a deep learning method called feature information aggregation and diffusion generative adversarial network (FIAD-GAN) is proposed to efficiently classify samples and select features. We focus on improving the generator with the proposed convolution and deconvolution operations, with which the interpretability of the deep learning framework has been dramatically improved. The experimental results indicate that FIAD-GAN can not only achieve superior results in various disease classification tasks but also extract brain regions and genes closely related to AD. This work provides a novel method for intelligent clinical decisions. The relevant biomedical discoveries provide a reliable reference and technical basis for the clinical diagnosis, treatment and pathological analysis of disease.

A diagnostic index based on pseudo-continuous arterial spin labeling and T1-mapping improves efficacy in discriminating Alzheimer’s disease from normal cognition

Background

Pseudo-continuous arterial spin labeling (pCASL) is widely used to quantify cerebral blood flow (CBF) abnormalities in patients with Alzheimer’s disease (AD). T1-mapping techniques assess microstructural characteristics in various pathologic changes, but their application in AD remains in the exploratory stage. We hypothesized that combining quantitative CBF and T1 values would generate diagnostic results with higher accuracy than using either method alone in discriminating AD patients from cognitively normal control (NC) subjects.

Materials and methods

A total of 45 patients diagnosed with AD and 33 NC subjects were enrolled, and cognitive assessment was performed for each participant according to the Chinese version of the Mini-Mental State Examination (MMSE). T1-weighted magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) and pCASL sequence were scanned on a 3T MR scanner. A brain morphometric analysis was integrated into prototype sequence, providing tissue classification and morphometric segmentation results. Quantitative CBF and T1 values of each brain region were automatically generated inline after data acquisition. Independent samples t-test was used to compare regional CBF and T1 values controlled by false discovery rate correction (corrected p < 0.01). The model with combined CBF and T1 values was compared with the individual index by performing receiver operating characteristic curves analysis. The associations between the MMSE score and CBF and T1 values of the brain were investigated using partial correlations.

Results

Cerebral blood flow of the right caudate nucleus (RCc) and left hippocampus (LHc) was significantly lower in the AD group compared with the NC group, while the T1 values of the right caudate nucleus (RCt) and left hippocampus (LHt) increased in the AD group. Prediction accuracies of 73.1, 77.2, 75.9, and 81.3% were achieved for each of the above parameters, respectively. In distinguishing patients from controls using the corresponding optimized cut-off values, most combinations of parameters were elevated (area under curve = 0.775–0.894). The highest area under curve value was 0.944, by combining RCc, LHc, RCt, and LHt.

Conclusion

In this preliminary study, the combined model based on pCASL and T1-mapping improved the diagnostic performance of discriminating AD and NC groups. T1-mapping may become a competitive technique for quantitatively measuring pathologic changes in the brain.

The characteristics of arterial spin labeling cerebral blood flow in patients with subjective cognitive decline: The Chinese imaging, biomarkers, and lifestyle study

Objective

We aimed to characterize the potential risk factors and cerebral perfusion of patients with subjective cognitive decline (SCD).

Methods

This prospective study enrolled consecutive patients from the Chinese Imaging, Biomarkers, and Lifestyle (CIBL) Cohort of Alzheimer’s disease between February 2021 and March 2022. Patients who met the SCD diagnostic criteria were categorized into the SCD group, while those without cognitive complaints or any concerns were assigned to the healthy control (HC) group. The demographic and clinical characteristics and cerebral blood flow (CBF) from pseudo-continuous arterial spin labeling (pCASL) in standard cognitive regions were compared between these two groups. A multivariate analysis was performed to identify independent factors associated with SCD.

Results

The frequency of family history of dementia in the SCD group was higher compared with the HC group (p = 0.016). The CBF of left hippocampus (p = 0.023), left parahippocampal gyrus (p = 0.004), left precuneus (p = 0.029), left middle temporal gyrus (p = 0.022), right parahippocampal gyrus (p = 0.018), and right precuneus (p = 0.024) in the SCD group were significantly increased than those in the HC group. The multivariate logistic regression analyses demonstrated that the family history of dementia [OR = 4.284 (1.096–16.747), p = 0.036] and the CBF of left parahippocampal gyrus [OR = 1.361 (1.006–1.840), p = 0.045] were independently associated with SCD.

Conclusion

This study demonstrated that the family history of dementia and the higher CBF within the left parahippocampal gyrus were independent risk factors associated with patients with SCD, which could help in the early identification of the SCD and in intervening during this optimal period.

Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease

Subjective cognitive decline (SCD) is considered to be the preclinical stage of Alzheimer's disease (AD) and has the potential for the early diagnosis and intervention of AD. It was implicated that CSF-tau, which increases very early in the disease process in AD, has a high sensitivity and specificity to differentiate AD from normal aging, and the highly connected brain regions behaved more tau burden in patients with AD. Thus, a highly connected state measured by dynamic functional connectivity may serve as the early changes of AD. In this study, forty-five normal controls (NC), thirty-six individuals with SCD, and thirty-five patients with AD were enrolled to obtain the resting-state functional magnetic resonance imaging scanning. Sliding windows, Pearson correlation, and clustering analysis were combined to investigate the different levels of information transformation states. Three states, namely, the low state, the middle state, and the high state, were characterized based on the strength of functional connectivity between each pair of brain regions. For the global dynamic functional connectivity analysis, statistically significant differences were found among groups in the three states, and the functional connectivity in the middle state was positively correlated with cognitive scales. Furthermore, the whole brain was parcellated into four networks, namely, default mode network (DMN), cognitive control network (CCN), sensorimotor network (SMN), and occipital-cerebellum network (OCN). For the local network analysis, statistically significant differences in CCN for low state and SMN for middle state and high state were found in normal controls and patients with AD. Meanwhile, the differences were also found in normal controls and individuals with SCD. In addition, the functional connectivity in SMN for high state was positively correlated with cognitive scales. Converging results showed the changes in dynamic functional states in individuals with SCD and patients with AD. In addition, the changes were mainly in the high strength of the functional connectivity state.

Progression from Subjective Cognitive Decline to Mild Cognitive Impairment or Dementia: The Role of Baseline Cognitive Performance

Background: Older adults with subjective cognitive decline (SCD) are at an increased risk of progression to mild cognitive impairment (MCI) or dementia. However, few have examined the specific cognitive tests that are associated with progression. Objective: This study examined performance on 18 neuropsychological tests among participants with SCD who later progressed to MCI or dementia. Methods: We included 131 participants from the Czech Brain Aging Study that had SCD at baseline. They completed a comprehensive neuropsychological battery including cognitive tests from the Uniform Data Set 2.0 enriched by the verbal memory test Rey Auditory Verbal Learning Test (RAVLT) and Rey-Osterrieth Complex Figure Test (ROCFT). Results: Fifty-five participants progressed: 53% to non-amnestic MCI (naMCI), 44% to amnestic MCI (aMCI), and 4% to dementia. Scoring one SD below the mean at baseline on the RAVLT 1 and RAVLT 1–5 was associated with 133% (RAVLT 1; HR: 2.33 [1.50, 3.62]) and 122% (RAVLT 1–5; HR: 2.22 [1.55, 3.16]) greater risk of progression to MCI or dementia over 3.84 years on average. Worse performance on the RAVLT 5, RAVLT 1–5, RAVLT 30, and ROCFT–Recall was associated with progression to aMCI whereas worse performance on the RAVLT 1, TMT B, and Boston Naming Test was associated with progression to naMCI. Conclusion: At baseline, lower verbal memory performance was most strongly associated with progression to aMCI whereas lower executive or language performance was most strongly associated with progression to naMCI.

Spatial variation of perfusion MRI reflects cognitive decline in mild cognitive impairment and early dementia

Cerebral blood flow (CBF) measured with arterial spin labelling (ASL) magnetic resonance imaging (MRI) reflects cerebral perfusion, related to metabolism, and arterial transit time (ATT), related to vascular health. Our aim was to investigate the spatial coefficient of variation (sCoV) of CBF maps as a surrogate for ATT, in volunteers meeting criteria for subjective cognitive decline (SCD), amnestic mild cognitive impairment (MCI) and probable Alzheimer’s dementia (AD). Whole-brain pseudo continuous ASL MRI was performed at 3 T in 122 participants (controls = 20, SCD = 44, MCI = 45 and AD = 13) across three sites in New Zealand. From CBF maps that included all grey matter, sCoV progressively increased across each group with increased cognitive deficit. A similar overall trend was found when examining sCoV solely in the temporal lobe. We conclude that sCoV, a simple to compute imaging metric derived from ASL MRI, is sensitive to varying degrees of cognitive changes and supports the view that vascular health contributes to cognitive decline associated with Alzheimer’s disease.

Relationship between Cerebral Perfusion on Arterial Spin Labeling (ASL) MRI with Brain Volumetry and Cognitive Performance in Mild Cognitive Impairment and Dementia due to Alzheimer's Disease

Context

Cerebral blood flow (CBF) measurement using arterial spin labelling (ASL) MRI sequences has recently emerged as a prominent tool in dementia research.

Aims

To establish association between quantified regional cerebral perfusion and gray matter (GM) volumes with cognitive measures in mild cognitive impairment (MCI) and early Alzheimer's Dementia (AD), using three dimensional fast spin echo pseudo-continuous ASL MRI sequences.

Settings and Design

Hospital-based cross-sectional study.

Methods and Material

Three age-matched groups, i.e., 21 cognitively normal healthy controls (HC), 20 MCI and 19 early AD patients diagnosed using neuropsychological tests and who consented for multimodality 3T MRI were recruited for the study.

Statistical Analysis Used

Statistical parametric mapping and regions of interest (ROI) multivariate analysis of variance was used to ascertain differences between patients and controls on MRI-volumetry and ASL. Linear regression was used to assess relationship between CBF with GM atrophy and neuropsychological test measures.

Results

Compared to HC, patients with MCI and AD had significantly lower quantified perfusion in posterior cingulate and lingual gyri, over hippocampus in MCI, with no differences noted between MCI and AD. Atrophy over the middle temporal gyrus and hippocampus differentiated AD from MCI. No significant positive correlations were noted between perfusion and GM volumes in ROI with the exception of temporal neocortex. Significantly positive coefficient b-value (p < 0.01) were apparent between global cognition with CBF in precuneus, temporal neocortex and precuneus volume, with negative b-values noted between medial temporal CBF for global cognition and recall scores.

Conclusions

ROI-based CBF measurements differentiated MCI and AD from HC; volumetry of medial and neocortical temporal GM separates AD from MCI. Correlations between CBF and neuropsychology are variable and require further longitudinal studies to gauge its predictive utility on cognitive trajectory in MCI.

Impaired cerebral vascular and metabolic responses to parametric N-back tasks in subjective cognitive decline

Previous studies reported abnormally increased and/or decreased blood oxygen level-dependent (BOLD) activations during functional tasks in subjective cognitive decline (SCD). The neurophysiological basis underlying these functional aberrations remains debated. This study aims to investigate vascular and metabolic responses and their dependence on cognitive processing loads during functional tasks in SCD. Twenty-one SCD and 18 control subjects performed parametric N-back working-memory tasks during MRI scans. Task-evoked percentage changes (denoted as δ) in cerebral blood volume (δCBV), cerebral blood flow (δCBF), BOLD signal (δBOLD) and cerebral metabolic rate of oxygen (δCMRO₂) were evaluated. In the frontal lobe, trends of decreased δCBV, δCBF and δCMRO₂ and increased δBOLD were observed in SCD compared with control subjects under lower loads, and these trends increased to significant differences under the 3-back load. δCBF was significantly correlated with δCMRO₂ in controls, but not in SCD subjects. As N-back loads increased, the differences between SCD and control subjects in δCBF and δCMRO₂ tended to enlarge. In the parietal lobe, no significant between-group difference was observed. Our findings suggested that impaired vascular and metabolic responses to functional tasks occurred in the frontal lobe of SCD, which contributed to unusual BOLD hyperactivation and was modulated by cognitive processing loads.

Quantitative Study of the Changes in Cerebral Blood Flow and Iron Deposition During Progression of Alzheimer's Disease

BACKGROUND

Advanced Alzheimer's disease (AD) has no effective treatment, and identifying early diagnosis markers can provide a time window for treatment.

OBJECTIVE

To quantify the changes in cerebral blood flow (CBF) and iron deposition during progression of AD.

METHODS

94 subjects underwent brain imaging on a 3.0-T MRI scanner with techniques of three-dimensional arterial spin labeling (3D-ASL) and quantitative susceptibility mapping (QSM). The subjects included 22 patients with probable AD, 22 patients with mild cognitive impairment (MCI), 25 patients with subjective cognitive decline (SCD), and 25 normal controls (NC). The CBF and QSM values were obtained using a standardized brain region method based on the Brainnetome Atlas. The differences in CBF and QSM values were analyzed between and within groups using variance analysis and correlation analysis.

RESULTS

CBF and QSM identified several abnormal brain regions of interest (ROIs) at different stages of AD (p < 0.05). Regionally, the CBF values in several ROIs of the AD and MCI subjects were lower than for NC subjects (p < 0.001). Higher QSM values were observed in the globus pallidus. The CBF and QSM values in multiple ROI were negatively correlated, while the putamen was the common ROI of the three study groups (p < 0.05). The CBF and QSM values in hippocampus were cross-correlated with scale scores during the progression of AD (p < 0.05).

CONCLUSION

Iron deposition in the basal ganglia and reduction in blood perfusion in multiple regions existed during the progression of AD. The QSM values in putamen can be used as an imaging biomarker for early diagnosis of AD.

Regional hyperperfusion in older adults with objectively-defined subtle cognitive decline

Although cerebral blood flow (CBF) alterations are associated with Alzheimer's disease (AD), CBF patterns across prodromal stages of AD remain unclear. Therefore, we investigated patterns of regional CBF in 162 Alzheimer's Disease Neuroimaging Initiative participants characterized as cognitively unimpaired (CU; n = 80), objectively-defined subtle cognitive decline (Obj-SCD; n = 31), or mild cognitive impairment (MCI; n = 51). Arterial spin labeling MRI quantified regional CBF in a priori regions of interest: hippocampus, inferior temporal gyrus, inferior parietal lobe, medial orbitofrontal cortex, and rostral middle frontal gyrus. Obj-SCD participants had increased hippocampal and inferior parietal CBF relative to CU and MCI participants and increased inferior temporal CBF relative to MCI participants. CU and MCI groups did not differ in hippocampal or inferior parietal CBF, but CU participants had increased inferior temporal CBF relative to MCI participants. There were no CBF group differences in the two frontal regions. Thus, we found an inverted-U pattern of CBF signal across prodromal AD stages in regions susceptible to early AD pathology. Hippocampal and inferior parietal hyperperfusion in Obj-SCD may reflect early neurovascular dysregulation, whereby higher CBF is needed to maintain cognitive functioning relative to MCI participants, yet is also reflective of early cognitive inefficiencies that distinguish Obj-SCD from CU participants.

Microstructural and Cerebral Blood Flow Abnormalities in Subjective Cognitive Decline Plus: Diffusional Kurtosis Imaging and Three-Dimensional Arterial Spin Labeling Study

Objective: To explore microstructural and cerebral blood flow (CBF) abnormalities in individuals with subjective cognitive decline plus (SCD plus) using diffusional kurtosis imaging (DKI) and three-dimensional (3D) arterial spin labeling (ASL). Methods: Twenty-seven patients with SCD plus, 31 patients with amnestic mild cognitive impairment (aMCI), and 33 elderly controls (ECs) were recruited and underwent DKI and 3D ASL using a GE 3.0-T MRI. Mean kurtosis (MK), fractional anisotropy (FA), mean diffusivity (MD), and CBF values were acquired from 24 regions of interest (ROIs) in the brain, including the bilateral hippocampal (Hip) subregions (head, body, and tail), posterior cingulate cortex (PCC), precuneus, dorsal thalamus subregions (anterior nucleus, ventrolateral nucleus, and medial nucleus), lenticular nucleus, caput nuclei caudati, white matter (WM) of the frontal lobe, and WM of the occipital lobe. Pearson's correlation analysis was performed to assess the relationships among the DKI-derived parameters, CBF values, and key neuropsychological tests for SCD plus. Results: Compared with ECs, participants with SCD plus showed a significant decline in MK and CBF values, mainly in the Hip head and PCC, and participants with aMCI exhibited more significant abnormalities in the MK and CBF values than individuals with ECs and SCD plus in multiple regions. Combined MK values showed better discrimination between patients with SCD plus and ECs than that obtained using CBF levels, with areas under the receiver operating characteristic (ROC) curve (AUC) of 0.874 and 0.837, respectively. Similarly, the AUC in discriminating SCD plus from aMCI patients obtained using combined MK values was 0.823, which was also higher than the combined AUC of 0.779 obtained using CBF values. Moreover, MK levels in the left Hip (h) and left PCC positively correlated with the auditory verbal learning test-delayed recall (AVLT-DR) score in participants with SCD plus. By contrast, only the CBF value in the left Hip head positively correlated with the AVLT-DR score. Conclusions: Our results provide new evidence of microstructural and CBF changes in patients with SCD plus. MK may be used as an early potential neuroimaging biomarker and may be a more sensitive DKI parameter than CBF at the very early stage of Alzheimer's disease (AD).

Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease

Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer’s disease (AD) continuum. Investigating populations with SCD is important for understanding the early pathological mechanisms of AD and identifying SCD-related biomarkers, which are critical for the early detection of AD. With the advent of advanced neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), accumulating evidence has revealed structural and functional brain alterations related to the symptoms of SCD. In this review, we summarize the main imaging features and key findings regarding SCD related to AD, from local and regional data to connectivity-based imaging measures, with the aim of delineating a multimodal imaging signature of SCD due to AD. Additionally, the interaction of SCD with other risk factors for dementia due to AD, such as age and the Apolipoprotein E (ApoE) ɛ4 status, has also been described. Finally, the possible explanations for the inconsistent and heterogeneous neuroimaging findings observed in individuals with SCD are discussed, along with future directions. Overall, the literature reveals a preferential vulnerability of AD signature regions in SCD in the context of AD, supporting the notion that individuals with SCD share a similar pattern of brain alterations with patients with mild cognitive impairment (MCI) and dementia due to AD. We conclude that these neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential for identifying the underlying pathological alterations associated with SCD. More longitudinal studies with larger sample sizes combined with more advanced imaging modeling approaches such as artificial intelligence are still warranted to establish their clinical utility.

A Novel Connectome-Based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer's Disease by Using Resting-State High-Density EEG EGI GES 300

Aim: To investigate for the first time the brain network in the Alzheimer’s disease (AD) spectrum by implementing a high-density electroencephalography (HD-EEG - EGI GES 300) study with 256 channels in order to seek if the brain connectome can be effectively used to distinguish cognitive impairment in preclinical stages. Methods: Twenty participants with AD, 30 with mild cognitive impairment (MCI), 20 with subjective cognitive decline (SCD) and 22 healthy controls (HC) were examined with a detailed neuropsychological battery and 10 min resting state HD-EEG. We extracted correlation matrices by using Pearson correlation coefficients for each subject and constructed weighted undirected networks for calculating clustering coefficient (CC), strength (S) and betweenness centrality (BC) at global (256 electrodes) and local levels (29 parietal electrodes). Results: One-way ANOVA presented a statistically significant difference among the four groups at local level in CC [F (3, 88) = 4.76, p = 0.004] and S [F (3, 88) = 4.69, p = 0.004]. However, no statistically significant difference was found at a global level. According to the independent sample t-test, local CC was higher for HC [M (SD) = 0.79 (0.07)] compared with SCD [M (SD) = 0.72 (0.09)]; t (40) = 2.39, p = 0.02, MCI [M (SD) = 0.71 (0.09)]; t (50) = 0.41, p = 0.004 and AD [M (SD) = 0.68 (0.11)]; t (40) = 3.62, p = 0.001 as well, while BC showed an increase at a local level but a decrease at a global level as the disease progresses. These findings provide evidence that disruptions in brain networks in parietal organization may potentially represent a key factor in the ability to distinguish people at early stages of the AD continuum. Conclusions: The above findings reveal a dynamically disrupted network organization of preclinical stages, showing that SCD exhibits network disorganization with intermediate values between MCI and HC. Additionally, these pieces of evidence provide information on the usefulness of the 256 HD-EEG in network construction.

GJ-4 alleviates Aβ25-35-induced memory dysfunction in mice through protecting the neurovascular unit

Alzheimer's disease (AD) is the most common neurodegenerative disease. AD has become an important social health problem but there are few therapeutic drugs. Many researchers devote to the development of drugs for the treatment of AD. GJ-4 is crocin enrichments from Gardenia jasminoides J. Ellis, and our previous studies have shown GJ-4 had potent neuroprotective effects on several AD animal models. However, the underlying mechanisms have not been fully elucidated. The aim of the present study was to explore the mechanism of GJ-4 on a Aβ_25-35-intoxicated mouse model. The results demonstrated that GJ-4 treatment significantly improved spatial learning and memory abilities of the AD mice challenged by Aβ_25-35. Mechanistic study indicated that GJ-4 could alleviate endothelial dysfunction, as GJ-4 markedly reduced endothelial cell edema, as well as improved tight junction structures by up-regulating Zonula occludens-1 (ZO-1), Claudin-5 and Occludin expressions. Moreover, GJ-4 markedly reduced receptor for advanced glycation end products (RAGE) expression and increased low-density lipoprotein receptor-related protein-1 (LRP-1) expression, suggesting endothelial transduction and clearance of toxic species capabilities improved by GJ-4 treatment. The results also indicated that GJ-4 significantly decreased IL-6 and IL-1β mRNA expressions, as well as intercellular adhesion molecule 1 (ICAM-1) and vascular cell adhesion molecule 1 (VCAM-1) expressions, implying the inhibition of glial activation and vascular inflammation by GJ-4 treatment. Furthermore, GJ-4 treatment inhibited glial activation mediated neuroinflammation through inhibiting high-mobility group box protein 1(HMGB-1)/RAGE/NF-κB signaling pathway, which might confer to the neuroprotection. In conclusion, our present study proved GJ-4 could protect the neurovascular unit (NVU), through attenuating endothelial cell damage, enhancing tight junction function, inhibiting of glial activation and protecting of neurons. This study provided evidence that the beneficial effects of GJ-4 on AD might be owing to its protection on NVU.

Aerobic Exercise Training Improves Cerebral Blood Flow and Executive Function: A Randomized, Controlled Cross-Over Trial in Sedentary Older Men

Background

Physical activity may attenuate age-related cognitive decline by improving cerebrovascular function. The aim of this study was therefore to investigate effects of aerobic exercise training on cerebral blood flow (CBF), which is a sensitive physiological marker of cerebrovascular function, in sedentary older men.

Methods

Seventeen apparently healthy men, aged 60–70 years and with a BMI between 25 and 35 kg/m², were included in a randomized, controlled cross-over trial. Study participants were randomly allocated to a fully-supervised, progressive, aerobic exercise training or no-exercise control period for 8 weeks, separated by a 12-week wash-out period. Measurements at the end of each period included aerobic fitness evaluated using peak oxygen consumption during incremental exercise (VO_2peak), CBF measured with pseudo-continuous arterial spin labeling magnetic resonance imaging, and post-load glucose responses determined using an oral glucose tolerance test (OGTT). Furthermore, cognitive performance was assessed in the domains of executive function, memory, and psychomotor speed.

Results

VO_2peak significantly increased following aerobic exercise training compared to no-exercise control by 262 ± 236 mL (P < 0.001). CBF was increased by 27% bilaterally in the frontal lobe, particularly the subcallosal and anterior cingulate gyrus (cluster volume: 1008 mm³; P < 0.05), while CBF was reduced by 19% in the right medial temporal lobe, mainly temporal fusiform gyrus (cluster volume: 408 mm³; P < 0.05). Mean post-load glucose concentrations determined using an OGTT decreased by 0.33 ± 0.63 mmol/L (P = 0.049). Furthermore, executive function improved as the latency of response was reduced by 5% (P = 0.034), but no changes were observed in memory or psychomotor speed.

Conclusion

Aerobic exercise training improves regional CBF in sedentary older men. These changes in CBF may underlie exercise-induced beneficial effects on executive function, which could be partly mediated by improvements in glucose metabolism. This clinical trial is registered on ClinicalTrials.gov as NCT03272061.

Dose-dependent association of accelerometer-measured physical activity and sedentary time with brain perfusion in aging

INTRODUCTION

Age-related decreases in cerebral blood flow (CBF) may lead to cognitive decline, while physical activity (PA) can maintain CBF and cognition in aging. The intensity of PA needed to affect CBF in aging, and the independent effects of sedentary time on CBF are currently unknown. Moreover, research conducted in free-living environments with objective measures of PA (e.g., accelerometry) is lacking.

METHODS

This cross-sectional study used accelerometry to objectively measure sedentary time, all light PA [AllLightPA], moderate-to-vigorous PA [MVPA], and total activity counts [TAC] in 52 cognitively healthy older adults. Robust linear regressions investigated the association of CBF (using arterial spin labeling magnetic resonance imaging) in frontal and medial temporal regions, with each PA intensity and sedentary time.

RESULTS

Greater sedentary time was significantly associated with lower CBF in lateral and medial frontal regions after adjusting for MVPA, while higher AllLightPA (adjusted for MVPA), MVPA (adjusted for AllLightPA), and TAC were associated with greater CBF in lateral and medial frontal regions.

DISCUSSION

Lighter activities, as well as MVPA, are beneficial to CBF in brain regions typically affected by the aging process and malleable to exercise interventions (i.e., the frontal lobes), whereas sedentary time is an independent risk factor for neurovascular dysregulation in normal aging.

Is brain connectome research the future frontier for subjective cognitive decline? A systematic review

OBJECTIVE

We performed a systematic literature review on Subjective Cognitive Decline (SCD) in order to examine whether the resemblance of brain connectome and functional connectivity (FC) alterations in SCD with respect to MCI, AD and HC can help us draw conclusions on the progression of SCD to more advanced stages of dementia.

METHODS

We searched for studies that used any neuroimaging tool to investigate potential differences/similarities of brain connectome in SCD with respect to HC, MCI, and AD.

RESULTS

Sixteen studies were finally included in the review. Apparent FC connections and disruptions were observed in the white matter, default mode and gray matter networks in SCD with regards to HC, MCI, and AD. Interestingly, more apparent connections in SCD were located over the posterior regions, while an increase of FC over anterior regions was observed as the disease progressed.

CONCLUSIONS

Elders with SCD display a significant disruption of the brain network, which in most of the cases is worse than HC across multiple network parameters.

SIGNIFICANCE

The present review provides comprehensive and balanced coverage of a timely target research activity around SCD with the intention to identify similarities/differences across patient groups on the basis of brain connectome properties.

Precision Aging: Applying Precision Medicine to the Field of Cognitive Aging

The current "one size fits all" approach to our cognitive aging population is not adequate to close the gap between cognitive health span and lifespan. In this review article, we present a novel model for understanding, preventing, and treating age-related cognitive impairment (ARCI) based on concepts borrowed from precision medicine. We will discuss how multiple risk factors can be classified into risk categories because of their interrelatedness in real life, the genetic variants that increase sensitivity to, or ameliorate, risk for ARCI, and the brain drivers or common mechanisms mediating brain aging. Rather than providing a definitive model of risk for ARCI and cognitive decline, the Precision Aging model is meant as a starting point to guide future research. To that end, after briefly discussing key risk categories, genetic risks, and brain drivers, we conclude with a discussion of steps that must be taken to move the field forward.

Current understanding of magnetic resonance imaging biomarkers and memory in Alzheimer's disease

Alzheimer's disease (AD) is caused by a cascade of changes to brain integrity. Neuroimaging biomarkers are important in diagnosis and monitoring the effects of interventions. As memory impairments are among the first symptoms of AD, the relationship between imaging findings and memory deficits is important in biomarker research. The most established magnetic resonance imaging (MRI) finding is hippocampal atrophy, which is related to memory decline and currently used as a diagnostic criterion for AD. While the medial temporal lobes are impacted early by the spread of neurofibrillary tangles, other networks and regional changes can be found quite early in the progression. Atrophy in several frontal and parietal regions, cortical thinning, and white matter alterations correlate with memory deficits in early AD. Changes in activation and connectivity have been detected by functional MRI (fMRI). Task-based fMRI studies have revealed medial temporal lobe hypoactivation, parietal hyperactivation, and frontal hyperactivation in AD during memory tasks, and activation patterns of these regions are also altered in preclinical and prodromal AD. Resting state fMRI has revealed alterations in default mode network activity related to memory in early AD. These studies are limited in part due to the historic inclusion of patients who had suspected AD but likely did not have the disorder. Modern biomarkers allow for more diagnostic certainty, allowing better understanding of neuroimaging markers in true AD, even in the preclinical stage. Larger patient cohorts, comparison of candidate imaging biomarkers to more established biomarkers, and inclusion of more detailed neuropsychological batteries to assess multiple aspects of memory are needed to better understand the memory deficit in AD and help develop new biomarkers. This article reviews MRI findings related to episodic memory impairments in AD and introduces a new study with multimodal imaging and comprehensive neuropsychiatric evaluation to overcome current limitations.