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

Hippocampal alterations after SARS-CoV-2 infection: A systematic review

SARS-CoV-2 infection produces a wide range of symptoms. Some of the structural changes caused by the virus in the nervous system are found in the medial temporal lobe, and several neuropsychological sequelae of COVID-19 are related to the function of the hippocampus. The main objective of the systematic review is to update and further analyze the existing evidence of hippocampal and related cortices' structural and functional alterations due to SARS-CoV-2 infection. Both clinical and preclinical studies that used different methodologies to explore the effects of this disease at different stages and grades of severity were considered, besides exploring related cognitive and emotional symptomatology. A total of 24 studies were identified by searching in SCOPUS, Web Of Science (WOS), PubMed, and PsycInfo databases up to October 3rd, 2022. Thirteen studies were performed in clinical human samples, 9 included preclinical animal models, 3 were performed post-mortem, and 1 included both post-mortem and preclinical samples. Alterations in the hippocampus were detected in the acute stage and after several months of infection. Clinical studies revealed alterations in hippocampal connectivity and metabolism. Memory alterations correlated with altered metabolic profiles or changes in grey matter volumes. Hippocampal human postmortem and animal studies observed alterations in neurogenesis, dendrites, and immune response, besides high apoptosis and neuroinflammation. Preclinical studies reported the viral load in the hippocampus. Olfactory dysfunction was associated with alterations in brain functionality. Several clinical studies revealed cognitive complaints, neuropsychological alterations, and depressive and anxious symptomatology.

Altered neurovascular coupling in patients with vascular cognitive impairment: a combined ASL-fMRI analysis

Background and objective

This study aims to examine the role of neurovascular coupling (NVC) in vascular cognitive impairment (VCI) by investigating the relationship between white matter lesion (WML) burden, NVC, and cognitive deficits. Additionally, we aim to explore the potential of NVC as a tool for understanding the neural mechanisms underlying VCI.

Methods

This study included thirty-eight small vessel disease cognitive impairment (SVCI) patients, 34 post-stroke cognitive impairment (PSCI) patients, and 43 healthy controls (HC). Comprehensive assessments, including neuroimaging and neuropsychological testing, were conducted to evaluate cognitive function. WML burden was measured and correlated with NVC coefficients to examine the relationship between white matter pathology and NVC. Mediation analysis was employed to explore the link relationship between NVC, WML burden, and cognitive function.

Results

The present study showed that NVC was significantly reduced in the SVCI and PSCI groups compared with HCs at both whole-brain and brain region level. The analysis revealed notable findings regarding NVC in relation to WML burden and cognitive function in VCI patients. Specifically, reduced NVC coefficients were observed within higher order brain systems responsible for cognitive control and emotion regulation. Mediation analysis demonstrated that NVC played a mediating role in the relationship between WML burden and cognitive impairment.

Conclusion

This study reveals the mediating role of NVC in the relationship between WML burden and cognitive function in VCI patients. The results demonstrate the potential of the NVC as an accurate measure of cognitive impairment and its ability to identify specific neural circuits affected by WML burden.

Convergent and distinct neural structural and functional patterns of mild cognitive impairment: a multimodal meta-analysis

Mild cognitive impairment (MCI) is regarded as a transitional stage between normal aging and Alzheimer's disease. Numerous voxel-based morphometry (VBM) and resting-state fMRI (rs-fMRI) studies have provided strong evidence of abnormalities in the structure and intrinsic function of brain regions in MCI. Studies have recently begun to explore their association but have not employed systematic information in this pursuit. Herein, a multimodal meta-analysis was performed, which included 43 VBM datasets (1,247 patients and 1,352 controls) of gray matter volume (GMV) and 42 rs-fMRI datasets (1,468 patients and 1,605 controls) that combined 3 metrics: amplitude of low-frequency fluctuation, the fractional amplitude of low-frequency fluctuation, and regional homogeneity. Compared to controls, patients with MCI displayed convergent reduced regional GMV and altered intrinsic activity, mainly in the default mode network and salience network. Decreased GMV alone in ventral medial prefrontal cortex and altered intrinsic function alone in bilateral dorsal anterior cingulate/paracingulate gyri, right lingual gyrus, and cerebellum were identified, respectively. This meta-analysis investigated complex patterns of convergent and distinct brain alterations impacting different neural networks in MCI patients, which contributes to a further understanding of the pathophysiology of MCI.

Associating brain imaging phenotypes and genetic risk factors via a hypergraph based netNMF method

Abstract

Alzheimer's disease (AD) is a severe neurodegenerative disease for which there is currently no effective treatment. Mild cognitive impairment (MCI) is an early disease that may progress to AD. The effective diagnosis of AD and MCI in the early stage has important clinical significance.

Methods

To this end, this paper proposed a hypergraph-based netNMF (HG-netNMF) algorithm for integrating structural magnetic resonance imaging (sMRI) of AD and MCI with corresponding gene expression profiles.

Results

Hypergraph regularization assumes that regions of interest (ROIs) and genes were located on a non-linear low-dimensional manifold and can capture the inherent prevalence of two modalities of data and mined high-order correlation features of the two data. Further, this paper used the HG-netNMF algorithm to construct a brain structure connection network and a protein interaction network (PPI) with potential role relationships, mine the risk (ROI) and key genes of both, and conduct a series of bioinformatics analyses.

Conclusion

Finally, this paper used the risk ROI and key genes of the AD and MCI groups to construct diagnostic models. The AUC of the AD group and MCI group were 0.8 and 0.797, respectively.

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.

Impairments in the Default Mode and Executive Networks in Methamphetamine Users During Short-Term Abstinence

Purpose

Methamphetamine use may cause severe neurotoxicity and cognitive impairment, leading to addiction, overdose, and high rates of relapse. However, few studies have systematically focused on functional impairments detected by neuroimaging in methamphetamine abstainers (MAs) during short-term abstinence. This study aimed to investigate effective connectivity, resting-state networks, and internetwork functional connectivity in MA brains to improve clinical treatment.

Methods

Twenty MAs and 27 age- and education-matched healthy controls underwent resting-state functional magnetic resonance imaging. The amplitude of low-frequency fluctuations and Granger causality were analyzed to investigate disrupted brain regions and effective connectivity, respectively. Independent component analysis and functional network connectivity were used to identify resting-state networks and internetwork functional connectivity, respectively.

Results

Compared with healthy controls, MAs demonstrated abnormal amplitudes of low-frequency fluctuations in the bilateral precuneus, left posterior cingulate cortex (PCC), left middle frontal gyrus (MFG), left superior parietal lobule, left supplementary motor area (SMA), and left inferior parietal lobule (IPL). Moreover, MAs showed decreased effective connectivity from the left PCC to the left precuneus, increased effective connectivity from the left precuneus to the left MFG and from the right precuneus to the left SMA, and altered functional connectivity within the default mode network (DMN), frontoparietal network, sensorimotor network, ventral attention network, cerebellar network, and visual network. Importantly, hyperconnectivity between the DMN and ventral attention network and hypoconnectivity between the DMN and cerebellar network as well as the DMN and frontoparietal network were demonstrated in MAs.

Conclusion

Our study implies that in short-term methamphetamine abstinence, disruptions to the DMN and executive network may a play key role, providing new insights for early rehabilitation.

An Activation Likelihood Estimation Meta-Analysis of Specific Functional Alterations in Dorsal Attention Network in Mild Cognitive Impairment

Background

Mild cognitive impairment (MCI) is known as the prodromal stage of the Alzheimer’s disease (AD) spectrum. The recent studies have advised that functional alterations in the dorsal attention network (DAN) could be used as a sensitive marker to forecast the progression from MCI to AD. Therefore, our aim was to investigate specific functional alterations in the DAN in MCI.

Methods

We systematically searched PubMed, EMBASE, and Web of Science and chose relevant articles based on the three functional indicators, the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) in the DAN in MCI. Based on the activation likelihood estimation, we accomplished the aggregation of specific coordinates and the analysis of functional alterations.

Results

A total of 38 studies were involved in our meta-analysis. By summing up included articles, we acquired specific brain region alterations in the DAN mainly in the superior temporal gyrus (STG), middle temporal gyrus (MTG), superior frontal gyrus (SFG), middle frontal gyrus (MFG), inferior frontal gyrus (IFG), precentral gyrus (preCG), inferior parietal lobule (IPL), superior parietal lobule (SPL). At the same time, the key area that shows anti-interaction with default mode network included the IPL in the DAN. The one showing interactions with executive control network was mainly in the MFG. Finally, the frontoparietal network showed a close connection with DAN especially in the IPL and IFG.

Conclusion

This study demonstrated abnormal functional markers in the DAN and its interactions with other networks in MCI group, respectively. It provided the foundation for future targeted interventions in preventing the progression of AD.

Systematic Review Registration

[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42021287958].

Neuroinflammation in perioperative neurocognitive disorders: From bench to the bedside

The perioperative neurocognitive disorders (PNDs) are one of the most common complications in elderly patients characterized by various forms of cognitive decline after anesthesia and surgery. Although the etiology for PNDs remained unclear, neuroinflammation has been characterized as one of the major causes, especially in the elderly patients. The activation of glial cells including microglia and astrocytes plays a significant role in the inflammatory responses in central nerve system (CNS). Although carefully designed, clinical studies on PNDs showed controversial results. Meanwhile, preclinical studies provided evidence from various levels, including behavior performance, protein levels, and gene expression. In this review, we summarize high‐quality studies and recent advances from both clinical and preclinical studies and provide a broad view from the onset of PNDs to its potential therapeutic targets. Future studies are needed to investigate the signaling pathways in PNDs for prevention and treatment, as well as the relationship of PNDs and future neurocognitive dysfunction.

Altered Patterns of Amplitude of Low-Frequency Fluctuations and Fractional Amplitude of Low-Frequency Fluctuations Between Amnestic and Vascular Mild Cognitive Impairment: An ALE-Based Comparative Meta-Analysis

Background: Changes in the amplitude of low-frequency fluctuations (ALFF) and the fractional amplitude of low-frequency fluctuations (fALFF) have provided stronger evidence for the pathophysiology of cognitive impairment. Whether the altered patterns of ALFF and fALFF differ in amnestic cognitive impairment (aMCI) and vascular mild cognitive impairment (vMCI) is largely unknown. The purpose of this study was to explore the ALFF/fALFF changes in the two diseases and to further explore whether they contribute to the diagnosis and differentiation of these diseases.

Methods: We searched PubMed, Ovid, and Web of Science databases for articles on studies using the ALFF/fALFF method in patients with aMCI and vMCI. Based on the activation likelihood estimation (ALE) method, connectivity modeling based on coordinate meta-analysis and functional meta-analysis was carried out.

Results: Compared with healthy controls (HCs), patients with aMCI showed increased ALFF/fALFF in the bilateral parahippocampal gyrus/hippocampus (PHG/HG), right amygdala, right cerebellum anterior lobe (CAL), left middle temporal gyrus (MTG), left cerebrum temporal lobe sub-gyral, left inferior temporal gyrus (ITG), and left cerebrum limbic lobe uncus. Meanwhile, decreased ALFF/fALFF values were also revealed in the bilateral precuneus (PCUN), bilateral cuneus (CUN), and bilateral posterior cingulate (PC) in patients with aMCI. Compared with HCs, patients with vMCI predominantly showed decreased ALFF/fALFF in the bilateral CUN, left PCUN, left PC, and right cingulate gyrus (CG).

Conclusions: The present findings suggest that ALFF and fALFF displayed remarkable altered patterns between aMCI and vMCI when compared with HCs. Thus, the findings of this study may serve as a reliable tool for distinguishing aMCI from vMCI, which may help understand the pathophysiological mechanisms of these diseases.

Functional MRI-Specific Alterations in Salience Network in Mild Cognitive Impairment: An ALE Meta-Analysis

Background Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Amnestic MCI (aMCI) and non-amnestic MCI are the two subtypes of MCI with the former having a higher risk for progressing to Alzheimer's disease (AD). Compared with healthy elderly adults, individuals with MCI have specific functional alterations in the salience network (SN). However, no consistent results are documenting these changes. This meta-analysis aimed to investigate the specific functional alterations in the SN in MCI and aMCI. Methods: We systematically searched PubMed, Embase, and Web of Science for scientific neuroimaging literature based on three research methods, namely, functional connectivity (FC), regional homogeneity (ReHo), and the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF). Then, we conducted the coordinate-based meta-analysis by using the activation likelihood estimation algorithm. Results: In total, 30 functional neuroimaging studies were included. After extracting the data and analyzing it, we obtained specific changes in some brain regions in the SN including decreased ALFF/fALFF in the left superior temporal gyrus, the insula, the precentral gyrus, and the precuneus in MCI and aMCI; increased FC in the thalamus, the caudate, the superior temporal gyrus, the insula, and the cingulate gyrus in MCI; and decreased ReHo in the anterior cingulate gyrus in aMCI. In addition, as to FC, interactions of the SN with other networks including the default mode network and the executive control network were also observed mainly in the middle frontal gyrus and superior frontal gyrus in MCI and inferior frontal gyrus in aMCI. Conclusions: Specific functional alternations in the SN and interactions of the SN with other networks in MCI could be useful as potential imaging biomarkers for MCI or aMCI. Meanwhile, it provided a new insight in predicting the progression of health to MCI or aMCI and novel targets for proper intervention to delay the progression. Systematic Review Registration: [PROSPERO], identifier [No. CRD42020216259].

Management Based on Multimodal Brain Monitoring May Improve Functional Connectivity and Post-operative Neurocognition in Elderly Patients Undergoing Spinal Surgery

Perioperative neurocognitive disorder (PND) is a common condition in elderly patients undergoing surgery. Sedation, analgesia, regional cerebral oxygen saturation (rSO₂), and body temperature are known to be associated with PND, but few studies have examined the contribution of these factors combined in detail. This prospective, randomized, controlled, double-blinded study investigated whether anesthesia management based on multimodal brain monitoring—an anesthesia management algorithm designed by our group—could improve the post-operative cognitive function and brain functional connectivity (FC) in elderly patients undergoing elective spinal surgery with general anesthesia. The patients (aged ≥65 years) were randomized into two groups [control (Group C), n = 12 and intervention (Group I), n = 14]. Patients in Group I were managed with multimodal brain monitoring (patient state index, spectral edge frequency, analgesia nociception index, rSO₂, and temperature), and those in Group C were managed with routine anesthesia management. All patients were pre- and post-operatively evaluated (7 days after surgery) with the Montreal Cognitive Assessment (MoCA). Amplitude of low-frequency fluctuation (ALFF) and FC were analyzed after resting-state functional MRI. Serum C-reactive protein (CRP) and lipopolysaccharide levels were measured, and the correlation between FC and changes in inflammatory marker levels was analyzed. Mean post-operative MoCA score was higher in Group I (24.80 ± 2.09) than in Group C (22.56 ± 2.24) (p = 0.04), with no difference in PND incidence between groups (28.57 vs. 16.67%; p = 0.47). Group I also showed significantly increased ALFF values in several brain regions after surgery (p < 0.05), and FC between the left hippocampus and left orbital inferior frontal gyrus (FG), left middle FG, left superior temporal gyrus, and left precentral gyrus was enhanced (p < 0.05), which was negatively correlated with the change in serum CRP (pre vs. post-intervention) (R = −0.58, p = 0.01). These results suggest that management of elderly patients undergoing surgery by multimodal brain monitoring may improve post-operative neurocognition and FC by reducing systemic inflammation.

Clinical Trial Registration:http://www.chictr.org.cn/index.aspx, identifier: ChiCTR1900028024.