The Dose-Dependent Effects of Vascular Risk Factors on Dynamic Compensatory Neural Processes in Mild Cognitive Impairment

Lower cerebrovascular reactivity in prefrontal cortex and weaker negative functional connectivity between prefrontal cortex and insula contribute to white matter hyperintensity-related anxiety or depression

BACKGROUND

White matter hyperintensities (WMHs) are associated with higher anxiety or depression (A/D) incidence. We investigated associations of WMHs with A/D, cerebrovascular reactivity (CVR), and functional connectivity (FC) to identify potential pathomechanisms.

METHODS

Participants with WMH (n = 239) and normal controls (NCs, n = 327) were assessed for A/D using the Hamilton Anxiety Rating Scale (HAMA) and Hamilton Depression Rating Scale (HAMD). The CVR and FC maps were constructed from resting-state functional MRI. Two-way analysis of covariance with fixed factors A/D and WMH was performed to identify regional CVR abnormalities. Seed-based FC analyses were then conducted on regions with WMH × A/D interaction effects on CVR. Logistic regression models were constructed to examine the utility of these measurements for identifying WMH-related A/D.

RESULTS

Participants with WMH related A/D exhibited significantly greater CVR in left insula and lower CVR in right superior frontal gyrus (SFG.R), and HAMA scores were negatively correlated with CVR in SFG.R (r = -0.156, P = 0.016). Insula-SFG.R negative FC was significantly weaker in WMH patients with suspected or definite A/D. A model including CVR plus FC changes identified WMH-associated A/D with highest sensitivity and specificity. In contrast, NCs with A/D exhibited greater CVR in prefrontal cortex and stronger FC within the default mode network (DMN) and between the DMN and executive control network.

LIMITATIONS

This cross-sectional study requires validation by longitudinal and laboratory studies.

CONCLUSIONS

Impaired CVR in SFG.R and weaker negative FC between prefrontal cortex and insula may contribute to WMH-related A/D, providing potential diagnostic imaging markers and therapeutic targets.

Effects of individual metabolic brain network changes co-affected by T2DM and aging on the probabilities of T2DM: protective and risk factors

Neuroimaging markers for risk and protective factors related to type 2 diabetes mellitus are critical for clinical prevention and intervention. In this work, the individual metabolic brain networks were constructed with Jensen-Shannon divergence for 4 groups (elderly type 2 diabetes mellitus and healthy controls, and middle-aged type 2 diabetes mellitus and healthy controls). Regional network properties were used to identify hub regions. Rich-club, feeder, and local connections were subsequently obtained, intergroup differences in connections and correlations between them and age (or fasting plasma glucose) were analyzed. Multinomial logistic regression was performed to explore effects of network changes on the probability of type 2 diabetes mellitus. The elderly had increased rich-club and feeder connections, and decreased local connection than the middle-aged among type 2 diabetes mellitus; type 2 diabetes mellitus had decreased rich-club and feeder connections than healthy controls. Protective factors including glucose metabolism in triangle part of inferior frontal gyrus, metabolic connectivity between triangle of the inferior frontal gyrus and anterior cingulate cortex, degree centrality of putamen, and risk factors including metabolic connectivities between triangle of the inferior frontal gyrus and Heschl's gyri were identified for the probability of type 2 diabetes mellitus. Metabolic interactions among critical brain regions increased in type 2 diabetes mellitus with aging. Individual metabolic network changes co-affected by type 2 diabetes mellitus and aging were identified as protective and risk factors for the likelihood of type 2 diabetes mellitus, providing guiding evidence for clinical interventions.

Distinct reserve capacity impacts on default-mode network in response to left angular gyrus-navigated repetitive transcranial magnetic stimulation in the prodromal Alzheimer disease

Default-mode network (DMN) may be the earliest affected network and is associated with cognitive decline in Alzheimer's disease (AD). Repetitive transcranial magnetic stimulation (rTMS) may help to modulate DMN plasticity. Still, stimulation effects substantially vary across studies and individuals. Global left frontal cortex (gLFC) connectivity, a substitute for reserve capacity, may contribute to the heterogeneous physiological effects of neuro-navigated rTMS. This study investigated the effects of left angular gyrus-navigated rTMS on DMN connectivity in different reserve capacity participants. gLFC connectivity, was computed through resting-state fMRI correlations. Thirty-one prodromal AD patients were divided into low connection group (LCG) and high connection group (HCG) by the median of gLFC connectivity. Distinct reserve capacity impacts on DMN in response to rTMS were identified in these two groups. Then, brain-behavior relationships were examined. gLFC connectivity within a certain range is directly proportional to cognitive reserve ability (i.e., LCG), and the effectiveness of functional connectivity beyond this range decreases (i.e, HCG). Moreover, LCG exhibited increased DMN connectivity and significantly positive memory improvements, while HCG showed a contrary connectivity decline and maintained or slightly improved their cognitive function after neuro-navigated rTMS treatment. The prodromal AD patients with the distinct reserve capacity may benefit differently from left angular gyrus-navigated rTMS, which may lead to increasing attention in defining personalized medicine approach of AD.

Risky drinking and cognitive impairment in community residents aged 50 and over

OBJECTIVES

Alcohol misuse is known to be a risk factor for dementia. This study aimed to explore the association between risky drinking and cognitive impairment in a cohort study of middle aged and older people at risk of dementia.

METHOD

The sample comprised 15,582 people aged 50 and over drawn from the PROTECT study. Risky drinking was defined according to a score of 4 or above on the Alcohol Use Disorders Identification Test (AUDIT). Cognitive function was assessed on visual episodic memory, spatial working memory, verbal working memory and verbal reasoning.

RESULTS

Risky drinkers at baseline were more likely to be younger, male, white British, married, of higher educational status, current or past tobacco smokers and to have moderate to severe depression than non-risky drinkers. Risky drinkers were also more likely to be impaired on self-reported instrumental activities of daily living and subjective cognitive decline. At baseline, risky drinkers were less likely than non-risky drinkers to show impairment on verbal reasoning and spatial working memory but not on visual episodic memory or verbal working memory. Risky drinking at baseline predicted decline in cognitive function on visual episodic memory, verbal reasoning and spatial working memory at 2 year follow-up, but only verbal working memory and spatial working memory remained significant outcomes after controlling for possible confounders.

CONCLUSION

Although of small effect size, the association between risky drinking and impairment on measures of working memory and visuospatial function warrants further examination; particularly given the possibility of partial reversibility in alcohol related cognitive impairment.

Effects of hypertension and aging on brain function in spontaneously hypertensive rats: a longitudinal resting-state functional magnetic resonance imaging study

To investigate the dynamic evolution of brain function under the comorbidities of hypertension and aging. Resting-state functional magnetic resonance imaging scans were longitudinally acquired at 10, 24, and 52 weeks in spontaneously hypertensive rats (SHRs) and Wistar-Kyoto rats. We computed the mean amplitude of low-frequency fluctuation (mALFF), mean regional homogeneity (mReHo), and functional connectivity (FC). There was no interaction between hypertension and aging on brain function. The main effect of aging reflects primarily the cumulative increase of brain activity, especially the increase of mALFF in amygdala and mReHo in cingulate cortex, accompanied by the decrease of brain activity. The main effect of hypertension reflects primarily decreased brain activity in default modal network, accompanied by increased brain activity. The main effect of aging shows reduced brain FC as early as 24 weeks, and the main effect of hypertension shows higher brain FC in SHRs. The novel discovery is that 1 brain FC network increased linearly with age in SHRs, in addition to the linearly decreasing FC. Hypertension and aging independently contribute to spatiotemporal alterations in brain function in SHRs following ongoing progression and compensation. This study provides new insight into the dynamic characteristics of brain function.

Oxidative Stress in the Pathogenesis of Alzheimer's Disease and Cerebrovascular Disease with Therapeutic Implications

The significant gain in life expectancy led to an increase in the incidence and prevalence of dementia. Although vascular risk factors have long and repeatedly been shown to increase the risk of Alzheimer's Disease (AD), translating these findings into effective preventive measures has failed. In addition, the finding that incident ischemic stroke approximately doubles the risk of a patient to develop AD has been recently reinforced. Current knowledge and pathogenetic hypotheses of AD are discussed. The implication of oxidative stress in the development of AD is reviewed, with special emphasis on its sudden burst in the setting of acute ischemic stroke and the possible link between this increase in oxidative stress and consequent cognitive impairment. Current knowledge and future directions in the prevention and treatment of AD are discussed outlining the hypothesis of a possible beneficial effect of antioxidant treatment in acute ischemic stroke in delaying the onset/progression of dementia.

Association between alcohol intake, mild cognitive impairment and progression to dementia: a dose-response meta-analysis

BACKGROUND

Mild cognitive impairment (MCI) is a cognitive state falling between normal aging and dementia. The relation between alcohol intake and risk of MCI as well as progression to dementia in people with MCI (PDM) remained unclear.

OBJECTIVE

To synthesize available evidence and clarify the relation between alcohol intake and risk of MCI as well as PDM.

METHOD

We searched electronic databases consisting of PubMed, EMBASE, Cochrane Library, and China Biology Medicine disc (CBM) from inception to October 1, 2019. Prospective studies reporting at least three levels of alcohol exposure were included. Categorical meta-analysis was used for quantitative synthesis of the relation between light, moderate and heavy alcohol intake with risk of MCI and PDM. Restricted cubic spline and fixed-effects dose-response models were used for dose-response analysis.

RESULT

Six cohort studies including 4244 individuals were finally included. We observed an unstable linear relation between alcohol intake (drinks/week) and risk of MCI (P linear = 0.0396). It suggested that a one-drink increment per week of alcohol intake was associated with an increased risk of 3.8% for MCI (RR, 1.038; 95% CI 1.002-1.075). Heavy alcohol intake (> 14 drinks/week) was associated with higher risk of PDM (RR = 1.76; 95% CI 1.10-2.82). And we found a nonlinear relation between alcohol intake and risk of PDM. Drinking more than 16 drinks/week (P nonlinear = 0.0038, HR = 1.42; 95% CI 1.00-2.02), or 27.5 g/day (P nonlinear = 0.0047, HR = 1.46; 95% CI 1.00-2.11) would elevate the risk of PDM.

CONCLUSION

There was a nonlinear dose-response relation between alcohol intake and risk of PDM. Excessive alcohol intake would elevate the risk of PDM.

Structural equation models to estimate dynamic effective connectivity networks in resting fMRI. A comparison between individuals with Down syndrome and controls

Emerging evidence suggests that an effective or functional connectivity network does not use a static process over time but incorporates dynamic connectivity that shows changes in neuronal activity patterns. Using structural equation models (SEMs), we estimated a dynamic component of the effective network through the effects (recursive and nonrecursive) between regions of interest (ROIs), taking into account the lag 1 effect. The aim of the paper was to find the best structural equation model (SEM) to represent dynamic effective connectivity in people with Down syndrome (DS) in comparison with healthy controls. Twenty-two people with DS were registered in a functional magnetic resonance imaging (fMRI) resting-state paradigm for a period of six minutes. In addition, 22 controls, matched by age and sex, were analyzed with the same statistical approach. In both groups, we found the best global model, which included 6 ROIs within the default mode network (DMN). Connectivity patterns appeared to be different in both groups, and networks in people with DS showed more complexity and had more significant effects than networks in control participants. However, both groups had synchronous and dynamic effects associated with ROIs 3 and 4 related to the upper parietal areas in both brain hemispheres as axes of association and functional integration. It is evident that the correct classification of these groups, especially in cognitive competence, is a good initial step to propose a biomarker in network complexity studies.

Aggregation of Vascular Risk Factors Modulates the Amplitude of Low-Frequency Fluctuation in Mild Cognitive Impairment Patients

Background: Several vascular risk factors, including hypertension, diabetes, body mass index, and smoking status are found to be associated with cognitive decline and the risk of Alzheimer's disease (AD). We aimed to investigate whether an aggregation of vascular risk factors modulates the amplitude of low-frequency fluctuation (ALFF) in patients with mild cognitive impairment (MCI).

Methods: Forty-three MCI patients and twenty-nine healthy controls (HCs) underwent resting-state functional MRI scans, and spontaneous brain activity was measured by the ALFF technique. The vascular risk profile was represented with the Framingham Heart Study general cardiovascular disease (FHS-CVD) risk score, and each group was further divided into high and low risk subgroups. Two-way ANOVA was performed to explore the main effects of diagnosis and vascular risk and their interaction on ALFF.

Results: The main effect of diagnosis on ALFF was found in left middle temporal gyrus (LMTG) and left superior parietal gyrus (LSPG), and the main effect of risk on ALFF was detected in left fusiform gyrus (LFFG), left precuneus (LPCUN), and left cerebellum posterior lobe (LCPL). Patients with MCI exhibited increased ALFF in the LMTG and LSPG than HCs, and participants with high vascular risk showed increased ALFF in the LFFG and LCPL, while decreased ALFF in the LPCUN. An interaction between diagnosis (MCI vs. HC) and FHS-CVD risk (high vs. low) regarding ALFF was observed in the left hippocampus (LHIP). HCs with high vascular risk showed significantly increased ALFF in the LHIP than those with low vascular risk, while MCI patients with high vascular risk showed decreased ALFF in the LHIP than HCs with high vascular risk. Interestingly, the mean ALFF of LHIP positively correlated with word recall test in HCs with high vascular risk (rho = 0.630, P = 0.016), while negatively correlated with the same test in MCI patients with high vascular risk (rho = −0.607, P = 0.001).

Conclusions: This study provides preliminary evidence highlighting that the aggregation of vascular risk factors modulates the spontaneous brain activity in MCI patients, and this may serve as a potential imaging mechanism underlying vascular contribution to AD.

Neurologic Factors in Patients with Vascular Mild Cognitive Impairment Based on fMRI

This study focused on the application of functional magnetic resonance imaging and neuropsychology in diagnosis of vascular mild cognitive impairment (MCI) and the exploration of its relevant factors. The study enrolled 28 patients with vascular MCI in an observation group and 30 healthy individuals in a control group. All patients underwent magnetic resonance imaging. An automatic segmentation algorithm based on graph theory was adopted to process the images. Age, sex, disease course, Montreal Cognitive Assessment score, regional homogeneity, and amplitude of low-frequency fluctuation levels were recorded. There were no significant differences in age, gender, and course of disease between the observation group and the control group (P > 0.05). The level of regional homogeneity in the left posterior cerebellum in the observation group was significantly higher than that in the control group (P < 0.05).The regional homogeneity level of bilateral cingulate cortex was negatively correlated with Montreal Cognitive Assessment score (P < 0.05). The amplitude of low-frequency fluctuation of bilateral inferior parietal lobe, parietal lobe, and prefrontal lobe in the observation group was significantly lower than that in the control group, and the amplitude of low-frequency fluctuation of bilateral anterior cingulate gyrus, superior medial frontal gyrus, orbital frontal gyrus, right middle frontal gyrus, and right auxiliary motor area was higher than that in the control group (P < 0.05). Heart disease, such as myocardial infarction and atrial fibrillation, is a high risk factor for vascular MCI. Functional magnetic resonance imaging combined with an automatic segmentation algorithm can noninvasively observe the changes of a patient's brain tissue, which can be used in the recognition of vascular MCI. The global network attributes of patients with depression tend to be more randomized and have stronger resilience under targeted attacks.

Aberrant White Matter Microstructure as a Potential Diagnostic Marker in Alzheimer's Disease by Automated Fiber Quantification

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.

The compensatory phenomenon of the functional connectome related to pathological biomarkers in individuals with subjective cognitive decline

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.

Serine hydroxymethyltransferase 1 promoter hypermethylation increases the risk of essential hypertension

BACKGROUND

Serine hydroxymethyltransferase 1 (SHMT1) is an enzyme involved in folic acid metabolism and is known to contribute to the development of hypertension. We evaluated the relationship between SHMT1 promoter methylation and essential hypertension (EH).

METHODS

Quantitative methylation-specific polymerase chain reaction was used to measure the SHMT1 promoter methylation level in 241 EH patients and 288 age- and gender-matched healthy individuals. The diagnostic value of SHMT1 promoter hypermethylation was analyzed using a receiver operating characteristic (ROC) curve. The Gene Expression Omnibus (GEO) database and dual-luciferase reporter assay were used to validate our findings.

RESULTS

Compared with the control group, significant differences in SHMT1 promoter methylation were found in both EH and hyperhomocysteinemia groups (P < 0.001 and P = 0.029, respectively). The area under the curve of the diagnosis of SHMT1 promoter hypermethylation for EH was 0.808, with a sensitivity and specificity of 73.9% and 77.8%, respectively. The risk of SHMT1 promoter hypermethylation was significantly higher in the >65-year group than in the ≤65-year group (odds ratio = 3.925; 95% confidence interval = 2.141-7.196). In addition, GEO database analysis showed that 5-aza-deoxycytidine increased gene expression in several carotid endothelial cell lines. A dual-luciferase reporter assay revealed that the target sequence in the SHMT1 promoter upregulated gene expression.

CONCLUSION

Our findings indicate that SHMT1 promoter hypermethylation increases the risk of EH and may be a promising biomarker for EH.