Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer's disease – A simultaneous resting-state FDG-PET/fMRI study

Zhang, Miao; Guan, Ziyun; Zhang, Yaoyu; Sun, Wanqing; Li, Wenli; Hu, Jialin; Li, Binyin; Ye, Guanyu; Meng, Hongping; Huang, Xin‐Yun; Lin, Xiaozhu; Wang, Jin; Li, Jun; Li, Biao; Yao, Li

doi:10.1016/j.nicl.2022.102977

Cited by 24 publications

(30 citation statements)

References 69 publications

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“…In this regard, we found a general trend of decreased FDG and FC scores in all three canonical variates in the MCI and AD groups (Figure 4a). Similarly, impaired metabolic-functional coupling has been observed in widespread regions including the subcortical areas, the DMN, the SAL and the FPT in patients at various stages of AD in both resting (Maleki Balajoo et al, 2022;Marchitelli et al, 2018;Zhang et al, 2022) and active states (Y. Zhang, Du, et al, 2021).…”

Section: Discussionmentioning

confidence: 90%

“…On the other hand, Manza et al did not find metabolicfunctional associations in the association or sensorimotor cortices (Manza et al, 2020);and Shokri-Kojori et al demonstrated a mismatch between energy consumption and neuroglial activity in particular brain regions (Shokri-Kojori et al, 2019). Furthermore, several studies, including our previous research, have shown that the metabolicfunctional relationship could be altered during the progression of AD and might exert a detrimental effect on cognitive performance (Ding et al, 2021;Maleki Balajoo et al, 2022;Marchitelli et al, 2018;Martin Scherr et al, 2021;Zhang et al, 2022).…”

Section: Introductionmentioning

confidence: 84%

“…In order to support effective communications between functional hubs, the association cortices are highly energy-demanded, which also makes them vulnerable to neurodegeneration and AD-related pathologies (Badhwar et al, 2017;Manza et al, 2020;Tomasi et al, 2013). As a result, both metabolic and functional alterations have been extensively reported in the DMN (Badhwar et al, 2017;Buckner et al, 2005;Greicius et al, 2004;Sheline & Raichle, 2013), the FPT (Badhwar et al, 2017;Grothe, Teipel, & Initiative, 2016), and the COP/SAL in patients with AD (Brier et al, 2012;Thomas et al, 2014;Zhang et al, 2022). Some of these disruptions were partially attributed to, and further promoted the deposition of amyloid plaques in cortical hubs (Buckner et al, 2005;Drzezga et al, 2011;Grothe et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

“…Participants were required to lay supine with eyes closed and remain awake without systematic thinking during scanning. The PET/MRI imaging protocols was the same as our previous studies (Zhang et al, 2022;M. Zhang, Sun, et al, 2021).…”

Section: Data Acquisitionmentioning

confidence: 99%

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Topographic metabolism‐function relationships in Alzheimer's disease: A simultaneous PET/MRI study

Li,

Zhang,

Huang

et al. 2024

Human Brain Mapping

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Disruptions of neural metabolism and function occur in parallel during Alzheimer's disease (AD). While many studies have shown diverse metabolic‐functional relationships in specific brain regions, much less is known about how large‐scale network‐level functional activity is associated with the topology of metabolism in AD. In this study, we took the advantages of simultaneous PET/MRI and multivariate analyses to investigate the associations between AD‐related stereotypical spatial patterns (topographies) of glucose metabolism, measured by fluorodeoxyglucose PET, and functional connectivity, measured by resting‐state functional MRI. A total of 101 participants, including 37 patients with AD, 25 patients with mild cognitive impairment (MCI), and 39 cognitively normal controls, underwent PET/MRI scans and cognitive assessments. Three pairs of distinct but optimally correlated metabolic and functional topographies were identified, encompassing large‐scale networks including the default‐mode, executive and control, salience, attention, and subcortical networks. Importantly, the metabolic‐functional associations were not only limited to one‐to‐one‐corresponding regions, but also occur in remote and non‐overlapping regions. Furthermore, both glucose metabolism and functional connectivity, as well as their linkages, exhibited various degrees of disruptions in patients with MCI and AD, and were correlated with cognitive decline. In conclusion, our results support distributed and heterogeneous topographic associations between metabolism and function, which are jeopardized by AD. Findings of this study may deepen our understanding of the pathological mechanism of AD through the perspectives of both local energy efficiency and long‐term interactions between synaptic disruption and functional disconnection contributing to the clinical symptomatology in AD.

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Section: Discussionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 84%

Section: Discussionmentioning

confidence: 99%

Section: Data Acquisitionmentioning

confidence: 99%

See 2 more Smart Citations

Topographic metabolism‐function relationships in Alzheimer's disease: A simultaneous PET/MRI study

Li,

Zhang,

Huang

et al. 2024

Human Brain Mapping

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“…Further, a custom MATLAB program was utilized to modify the 90 functional region of interest atlas from the functional imaging in neuropsychiatric dis-orders lab 47 for generating eight functional neural network masks associated with MCI and AD. The selected neural networks for complexity analysis included basal ganglia (motor symptoms and amyloid-β deposition), 48 default mode (dorsal and ventral default mode associated with amyloid-β and tau pathology and episodic memory), [49][50][51][52][53] central executive (right and left executive control associated with executive and compensatory cognitive control), 49,54,55 language (amyloid-β and tau pathology), 56 precuneus (disruption of functional connectivity due to AD), 56,57 salience (anterior and posterior salience with altered brain function due to AD), 58,59 sensorimotor (connectively alterations due to AD), 49,60,61 and visuospatial (amyloid-β and tau pathology) 56 networks for complexity analysis. The average MSE was calculated for two similar trials (average of Trials 1 and 2 for Cog 1 and Trials 3 and 4 for Cog 2-see Figure 1) for all MSE maps created.…”

Section: Sample Entropy and Multiscale Entropy Analysismentioning

confidence: 99%

Brain function complexity during dual‐tasking is associated with cognitive impairment and age

Peña

Petrillo

Bosset

et al. 2022

Journal of Neuroimaging

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Background and Purpose Early diagnosis of cognitive impairment is important because symptoms can be delayed through therapies. Synaptic disconnections are the key characteristics of dementia, and through nonlinear complexity analysis of brain function, it is possible to identify long‐range synaptic disconnections in the brain. Methods We investigated the capability of a novel upper‐extremity function (UEF) dual‐task paradigm in the functional MRI (fMRI) setting, where the participant flexes and extends their arm while counting, to differentiate between cognitively normal (CN) and those with mild cognitive impairment (MCI). We used multiscale entropy (MSE) complexity analysis of the blood oxygen‐level dependent time‐series across neural networks and brain regions. Outside of the fMRI, we used the UEF dual‐task test, while the elbow kinematics were measured using motion sensors, to record the motor function score. Results Results showed 34% lower MSE values in MCI compared to CN (p<.04 for all regions and networks except cerebellum when counting down by one; effect size = 1.35±0.15) and a negative correlation between MSE values and age (average r2 of 0.30 for counting down by one and 0.36 for counting backward by three). Results also showed an improvement in the logistic regression model sensitivity by 14‐24% in predicting the presence of MCI when brain function measure was added to the motor function score (kinematics data). Conclusions Current findings suggest that combining measures of neural network and motor function, in addition to neuropsychological testing, may provide an accurate tool for assessing early‐stage cognitive impairment and age‐related decline in cognition.

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Advancing Alzheimer's research: Radiomics visualization of the default mode network in cerebral perfusion imaging

Fang,

Zhou,

Xiong

et al. 2024

J Applied Clin Med Phys

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ObjectiveAlzheimer's disease, an irreversible neurological condition, demands timely diagnosis for effective clinical intervention. This study employs radiomics analysis to assess image features in default mode network cerebral perfusion imaging among individuals with cognitive impairment.MethodsA radiomics analysis of cerebral perfusion imaging was conducted on 117 patients with cognitive impairment. They were divided into training and validation sets in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest were employed to select and model image features, followed by logistic regression analysis of LASSO and Random Forest results. Diagnostic performance was assessed by calculating the area under the curve (AUC).ResultsIn the training set, LASSO achieved AUC of 0.978, Random Forest had an AUC of 0.933. In the validation set, LASSO had AUC of 0.859, Random Forest had AUC of 0.986. By conducting Logistic Regression analysis in combination with LASSO and Random Forest, we identified a total of five radiomics features, with four related to morphology and one to textural features, originating from the medial prefrontal cortex and middle temporal gyrus. In the training set, Logistic Regression achieved AUC of 0.911, while in the validation set, it attained AUC of 0.925.ConclusionThe medial prefrontal cortex and middle temporal gyrus are the two brain regions within the default mode network that hold the highest significance for Alzheimer's disease diagnosis. Radiomics analysis contributes to the clinical assessment of Alzheimer's disease by delving into image data to extract deeper layers of information.

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Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer's disease – A simultaneous resting-state FDG-PET/fMRI study

Cited by 24 publications

References 69 publications

Topographic metabolism‐function relationships in Alzheimer's disease: A simultaneous PET/MRI study

Topographic metabolism‐function relationships in Alzheimer's disease: A simultaneous PET/MRI study

Brain function complexity during dual‐tasking is associated with cognitive impairment and age

Advancing Alzheimer's research: Radiomics visualization of the default mode network in cerebral perfusion imaging

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