Evaluation of Mental Disorders Using Proton Magnetic Resonance Spectroscopy in Dialysis and Predialysis Patients

End-stage renal disease accompanied by mild cognitive impairment: A study and analysis of trimodal brain network fusion

The function and structure of brain networks (BN) may undergo changes in patients with end-stage renal disease (ESRD), particularly in those accompanied by mild cognitive impairment (ESRDaMCI). Many existing methods for fusing BN focus on extracting interaction features between pairs of network nodes from each mode and combining them. This approach overlooks the correlation between different modal features during feature extraction and the potentially valuable information that may exist between more than two brain regions. To address this issue, we propose a model using a multi-head self-attention mechanism to fuse brain functional networks, white matter structural networks, and gray matter structural networks, which results in the construction of brain fusion networks (FBN). Initially, three networks are constructed: the brain function network, the white matter structure network, and the individual-based gray matter structure network. The multi-head self-attention mechanism is then applied to fuse the three types of networks, generating attention weights that are transformed into an optimized model. The optimized model introduces hypergraph popular regular term and L1 norm regular term, leading to the formation of FBN. Finally, FBN is employed in the diagnosis and prediction of ESRDaMCI to evaluate its classification performance and investigate the correlation between discriminative brain regions and cognitive dysfunction. Experimental results demonstrate that the optimal classification accuracy achieved is 92.80%, which is at least 3.63% higher than the accuracy attained using other methods. This outcome confirms the effectiveness of our proposed method. Additionally, the identification of brain regions significantly associated with scores on the Montreal cognitive assessment scale may shed light on the underlying pathogenesis of ESRDaMCI.

Characterizing Topological Properties of Brain Functional Networks Using Multi-Threshold Derivative for End-Stage Renal Disease with Mild Cognitive Impairment

Patients with end-stage renal disease (ESRD) experience changes in both the structure and function of their brain networks. In the past, cognitive impairment was often classified based on connectivity features, which only reflected the characteristics of the binary brain network or weighted brain network. It exhibited limited interpretability and stability. This study aims to quantitatively characterize the topological properties of brain functional networks (BFNs) using multi-threshold derivative (MTD), and to establish a new classification framework for end-stage renal disease with mild cognitive impairment (ESRDaMCI). The dynamic BFNs (DBFNs) were constructed and binarized with multiple thresholds, and then their topological properties were extracted from each binary brain network. These properties were then quantified by calculating their derivative curves and expressing them as multi-threshold derivative (MTD) features. The classification results of MTD features were compared with several commonly used DBFN features, and the effectiveness of MTD features in the classification of ESRDaMCI was evaluated based on the classification performance test. The results indicated that the linear fusion of MTD features improved classification performance and outperformed individual MTD features. Its accuracy, sensitivity, and specificity were 85.98 ± 2.92%, 86.10 ± 4.11%, and 81.54 ± 4.27%, respectively. Finally, the feature weights of MTD were analyzed, and MTD-cc had the highest weight percentage of 28.32% in the fused features. The MTD features effectively supplemented traditional feature quantification by addressing the issue of indistinct classification differentiation. It improved the quantification of topological properties and provided more detailed features for diagnosing cognitive disorders.

Altered resting-state functional networks in patients with hemodialysis: a graph-theoretical based study

Recent studies have demonstrated that hemodialysis patients exhibit disruptions in functional networks with invisible cerebral alterations. We explored the alterations of functional connectivity in hemodialysis patients using the graph-theory method. A total of 46 hemodialysis patients (53.11 ± 1.58 years, 28 males) and 47 healthy controls (55.57 ± 0.86 years, 22 males) were scanned by using resting-state functional magnetic resonance imaging. The brains of these patients were divided into 90 regions and functional connectivity was constructed with the automatic anatomical labeling atlas. In the defined threshold range, the graph-theory analysis was performed to compare the topological properties including global, regional and edge parameters between the hemodialysis and the healthy control groups. Both hemodialysis patients and healthy control subjects demonstrated common small-world property of the brain functional connections. At the global level, the parameters normalized clustering coefficients and small-worldness were significantly decreased in hemodialysis patients compared with those noted in healthy controls. At the regional level, abnormal nodal metrics (increased or decreased nodal degree, betweenness centrality and efficiency) were widely found in hemodialysis patients compared with those of healthy controls. The network-based statistical method was employed and two disrupted neural circuits with 18 nodes and 19 edges (P = 0.0139, corrected) and 10 nodes and 11 edges (P = 0.0399, corrected) were detected. Of note, the edge-increased functional connectivity was associated with the salience network and the frontal-temporal-basal ganglia connection, whereas the edge-decreased functional connectivity was associated with the frontoparietal network. The graph-theory method may be one of the potential tools to detect disruptions of cerebral functional connectivity and provide important evidence for understanding the neuropathology of hemodialysis patients from the disrupted network organization perspective.

Abnormal brain functional networks in end-stage renal disease patients with cognitive impairment

INTRODUCTION

Cognitive impairment (CI) is common in patients with end-stage renal disease (ESRD). Neuroimaging studies have demonstrated structural and functional brain alterations underlying CI in patients with ESRD. However, the patterns of change in whole-brain functional networks in ESRD patients with CI remain poorly understood.

METHODS

We enrolled 66 patients with ESRD (36 patients with CI and 30 patients without CI) and 48 healthy control subjects (HCs). We calculated the topological properties using a graph theoretical analysis. An analysis of covariance (ANCOVA) was used to compare network metrics among the three groups. Moreover, we analyzed the relationships between altered network measures and clinical variables in ESRD patients with CI.

RESULTS

Compared with HCs, both patient groups showed lower local efficiency and small-worldness. ESRD patients had decreased nodal centralities in the default mode regions and right amygdala. Comparison of the two patient groups showed significantly decreased global (small-worldness) and nodal (nodal centralities in the default mode regions) properties in the CI group. Altered nodal centralities in the bilateral medial part of the superior frontal gyrus, left posterior cingulate gyrus, and right precuneus were associated with cognitive performance in the CI group.

CONCLUSION

Disrupted brain functional networks were demonstrated in patients with ESRD, which were more severe in those with CI. Moreover, impaired nodal centralities in the default mode regions might underlie CI in patients with ESRD.

Association between chronic kidney disease and Alzheimer's disease: an update

It has been accepted that kidney function is connected with brain activity. In clinical studies, chronic kidney disease (CKD) patients have been found to be prone to suffering cognitive decline and Alzheimer's disease (AD). The cognitive function of CKD patients may improve after kidney transplantation. All these indicators show a possible link between kidney function and dementia. However, little is known about the mechanism behind the relation of CKD and AD. This review discusses the associations between CKD and AD from the perspective of the pathophysiology of the kidney and complications and/or concomitants of CKD that may lead to cognitive decline in the progression of CKD and AD. Potential preventive and therapeutic strategies for AD are also presented. Further studies are warranted in order to confirm whether the setting of CKD is a possible new determinant for cognitive impairment in AD.

Structural and Functional Alterations in Hemodialysis Patients: A Voxel-Based Morphometry and Functional Connectivity Study

Structural and functional brain alterations have been always observed in end-stage renal disease (ESRD) patients undergoing hemodialysis. The present study aimed to investigate the gray matter volume (GMV) changes in hemodialysis patients compared with those noted in healthy subjects, as well as explore the associated functional connectivity alterations based on the abnormal GMV regions. The experiments revealed the effects of regional morphometry aberrance on the brain functional integrity. A total of 46 hemodialysis patients (53.11 ± 1.58 years, 28 males) and 47 healthy subjects (55.57 ± 0.86 years, 22 males) were enrolled in the present study. All subjects underwent high-resolution T1-weighted imaging, resting-state functional MR imaging, and laboratory examinations were performed in hemodialysis patients. The GMV deficits were analyzed using voxel-based morphometry (VBM) and regions with GMV alteration were defined as seeds for functional connectivity analysis. Correlation analyses between significantly different regions and the results of the blood examination were further performed. We found that bilateral thalamus exhibited significantly increased volumes in the hemodialysis patients compared with those of the healthy subjects. However, the bilateral rectus, bilateral caudate, and bilateral temporal gyrus demonstrated significantly decreased volumes. When the regions with GMV alterations were defined as seeds, the hemodialysis patients exhibited decreased integrations in the thalamo-cortical network and within the basal-ganglia connection. The present study revealed the presence of different types of structural and functional brain impairments in hemodialysis patients.