Disrupted brain functional networks in patients with end‐stage renal disease undergoing hemodialysis

Wu, Baolin; Li, Xuekun; Zhang, Meng; Zhang, Feifei; Long, Xipeng; Gong, Qiyong; Jia, Zhiyun

doi:10.1002/jnr.24725

Cited by 15 publications

(27 citation statements)

References 45 publications

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“…This reflects the fact that the overall structure of the small-world network does not reach the optimal state, which further affects the transmission and processing of whole brain information. A study ( Wu et al, 2020 ) revealed that compared with HCs, the sigma of patients on hemodialysis was also significantly reduced, but the reduced Lp and lambda in patients was not consistent with our results. The cognitive function of patients with ESRD is affected by dialysis duration ( Brouhard et al, 2000 ), and the brain network architecture is related to cognitive level ( Liu et al, 2012 ).…”

Section: Discussioncontrasting

confidence: 93%

“…The nodal parameters of the amygdala (including NCp and NLe) in patients on MHD without CI were significantly lower than those in HCs, which is consistent with the results of the previous studies ( Wu et al, 2020 ; Yue et al, 2021 ). The amygdala is an important structure for the regulation and processing of emotions ( Dalton et al, 2005 ).…”

Section: Discussionsupporting

confidence: 91%

“…In addition, compared with HCs, the nodal parameters of the frontal lobe increased and those of the temporal lobe decreased in patients on MHD without CI. This result is similar to the conclusion of a study by Wu et al (2020) that suggested that the nodal degree of the frontal cortex in patients on hemodialysis is higher than that in HCs, and the nodal degree of the temporal lobe is lower than that in HCs. The increase in degree centrality in multiple brain regions, including the middle frontal gyrus, may be an important compensatory mechanism for patients with Alzheimer’s disease to delay dementia ( Behfar et al, 2020 ).…”

Section: Discussionsupporting

confidence: 91%

“…The cognitive function of patients with ESRD is affected by dialysis duration ( Brouhard et al, 2000 ), and the brain network architecture is related to cognitive level ( Liu et al, 2012 ). Given that the duration of hemodialysis among patients with ESRD in this study was longer than that in previous studies ( Wu et al, 2020 ; Yue et al, 2021 ), it is postulated that these inconsistent results may be due to hemodialysis duration. According to the definition of Eloc and gamma ( Sporns and Zwi, 2004 ; Rubinov and Sporns, 2010 ), their decreased values in the patient group reflect the decreased information transmission ability of patients on MHD at the regional level.…”

Section: Discussioncontrasting

confidence: 64%

“…The human brain is a complex network system that can efficiently integrate and transfer information. Recently, a graph theory-based method revealed that the functional brain network in patients with ESRD was damaged, which may affect the cognitive function of patients ( Park et al, 2020 ; Wu et al, 2020 ). However, the difference in brain network architecture between patients on MHD with and without CI remains unclear.…”

Section: Introductionmentioning

confidence: 99%

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Associations of the Disrupted Functional Brain Network and Cognitive Function in End-Stage Renal Disease Patients on Maintenance Hemodialysis: A Graph Theory-Based Study of Resting-State Functional Magnetic Resonance Imaging

Zhang

Chen

Lin

et al. 2021

Front. Hum. Neurosci.

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Objective: Cognitive impairment (CI) is a common neurological complication in patients with end-stage renal disease undergoing maintenance hemodialysis (MHD). Brain network analysis based on graph theory is a promising tool for studying CI. Therefore, the purpose of this study was to analyze the changes of functional brain networks in patients on MHD with and without CI by using graph theory and further explore the underlying neuropathological mechanism of CI in these patients.Methods: A total of 39 patients on MHD (19 cases with CI and 20 without) and 25 healthy controls (HCs) matched for age, sex, and years of education were enrolled in the study. Resting-state functional magnetic resonance imaging (rs-fMRI) and T1-weighted high-resolution anatomical data were obtained, and functional brain networks for each subject were constructed. The brain network parameters at the global and regional levels were calculated, and a one-way analysis of covariance was used to compare the differences across the three groups. The associations between the changed graph-theory parameters and cognitive function scores in patients on MHD were evaluated using Spearman correlation analysis.Results: Compared with HCs, the global parameters [sigma, gamma, and local efficiency (Eloc)] in both patient groups decreased significantly (p < 0.05, Bonferroni corrected). The clustering coefficient (Cp) in patients with CI was significantly lower than that in the other two groups (p < 0.05, Bonferroni corrected). The regional parameters were significantly lower in the right superior frontal gyrus, dorsolateral (SFGdor) and gyrus rectus (REC) of patients with CI than those of patients without CI; however the nodal local efficiency in the left amygdala was significantly increased (all p < 0.05, Bonferroni corrected). The global Cp and regional parameters in the three brain regions (right SFGdor, REC, and left amygdala) were significantly correlated with the cognitive function scores (all FDR q < 0.05).Conclusion: This study confirmed that the topology of the functional brain network was disrupted in patients on MHD with and without CI and the disruption of brain network was more severe in patients with CI. The abnormal brain network parameters are closely related to cognitive function in patients on MHD.

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Section: Discussioncontrasting

confidence: 93%

Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

Section: Discussioncontrasting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Associations of the Disrupted Functional Brain Network and Cognitive Function in End-Stage Renal Disease Patients on Maintenance Hemodialysis: A Graph Theory-Based Study of Resting-State Functional Magnetic Resonance Imaging

Zhang

Chen

Lin

et al. 2021

Front. Hum. Neurosci.

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Multiparameter neuroimaging study of neurovascular coupling changes in patients with end‐stage renal disease

Sun,

Li,

Jiao

et al. 2024

Brain and Behavior

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PurposeTo assess changes in neurovascular coupling (NVC) by evaluating the relationship between cerebral perfusion and brain connectivity in patients with end‐stage renal disease (ESRD) undergoing hemodialysis versus in healthy control participants. And by exploring brain regions with abnormal NVC associated with cognitive deficits in patients, we aim to provide new insights into potential preventive and therapeutic interventions.Materials and methodsA total of 45 patients and 40 matched healthy controls were prospectively enrolled in our study. Montreal Cognitive Assessment (MoCA) was used to assess cognitive function. Arterial spin labeling (ASL) was used to calculate cerebral blood flow (CBF), and graph theory–based analysis of results from resting‐state functional magnetic resonance imaging (rs‐fMRI) was used to calculate brain network topological parameters (node betweenness centrality [BC], node efficiency [Ne], and node degree centrality [DC]). Three NVC biomarkers (CBF‐BC, CBF‐Ne, and CBF‐DC coefficients) at the whole brain level and 3 NVC biomarkers (CBF/BC, CBF/Ne, and CBF/DC ratios) at the local brain region level were used to assess NVC. Mann–Whitney U tests were used to compare the intergroup differences in NVC parameters. Spearman's correlation analysis was used to evaluate the relationship among NVC dysfunctional pattern, cognitive impairment, and clinical characteristics multiple comparisons were corrected using a voxel‐wise false‐discovery rate (FDR) method (p < .05).ResultsPatients showed significantly reduced global coupling coefficients for CBF‐Ne (p = .023) and CBF‐BC (p = .035) compared to healthy controls. Coupling ratios at the local brain region level were significantly higher in patients in 33 brain regions (all p values < .05). Coupling ratio changes alone or accompanied by changes in CBF, node properties, or both CBF and node properties were identified. In patients, negative correlations were seen between coupling ratios and MoCA scores in many brain regions, including the left dorsolateral superior frontal gyrus, the bilateral median cingulate and paracingulate gyri, and the right superior parietal gyrus. The correlations remained even after adjusting for hemoglobin and hematocrit levels.ConclusionDisrupted NVC may be one mechanism underlying cognitive impairment in dialysis patients.

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Global iterative optimization framework for predicting cognitive function statuses of patients with end‐stage renal disease

Sheng

Zhang

Shi

et al. 2023

Int J Imaging Syst Tech

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The existing methods to determine the cognitive function level of end-stage renal disease (ESRD) are not only inaccurate but also susceptible to the influence of the patient's education level, emotional state, and examination environment. We proposed a global iterative optimization framework (GIO) to accurately predict cognitive function statuses of ESRD patients without being affected by the above factors. First, the functional magnetic resonance imaging (fMRI) data preprocessed and the time series were extracted to construct brain functional networks. Secondly, the areas under curve (AUC) of topological attribute parameters in the brain functional networks were extracted as features. After statistical analysis, the global efficiency, the characteristic path length, and the shortest path length in the small-world network were selected as features for linear fusion. Finally, the support vector regression (SVR) was used as the basis of GIO framework, and the global iterative search strategy was introduced to find out the most appropriate penalty factor and radial basis function parameters. Achieving the objective of accurately predicting the cognitive function status of patients with end-stage renal disease. Since this framework uses SVR which has special advantages in processing small sample data, and introduces appropriate parameter selection method, the prediction ability of GIO framework has been significantly improved. Experimental results demonstrate that the final prediction accuracy of the proposed framework is significantly better than those of SVR, LSSVR, GMO-SVR, GMO-LSSVR, and PSO-SVR. The mean absolute error (MAE) and the mean absolute percentage error (MAPE) of the proposed framework are 0.55% and 2.58%, respectively. It is suggested that this framework is more convenient to determine the current level of cognitive function in ESRD patients and is conducive to the early prevention of cognitive dysfunction in ESRD patients.

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Disrupted brain functional networks in patients with end‐stage renal disease undergoing hemodialysis

Cited by 15 publications

References 45 publications

Associations of the Disrupted Functional Brain Network and Cognitive Function in End-Stage Renal Disease Patients on Maintenance Hemodialysis: A Graph Theory-Based Study of Resting-State Functional Magnetic Resonance Imaging

Associations of the Disrupted Functional Brain Network and Cognitive Function in End-Stage Renal Disease Patients on Maintenance Hemodialysis: A Graph Theory-Based Study of Resting-State Functional Magnetic Resonance Imaging

Multiparameter neuroimaging study of neurovascular coupling changes in patients with end‐stage renal disease

Global iterative optimization framework for predicting cognitive function statuses of patients with end‐stage renal disease

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