ArticleCommunications biology2025
Brain connectome gradient dysfunction in patients with end-stage renal disease and its association with clinical phenotype and cognitive deficits.
Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Cingulate Gradient Dysfunction in End-Stage Renal Disease: Associations With Clinical Phenotypes and Exploratory Transcriptomic Signatures.CNS neuroscience & therapeutics · 2026Article
- Cortical gradient compression links cognition and transcriptomic signatures in primary angle-closure glaucoma.Communications biology · 2026Article
- Structural Connectivity Disruption and Structural-Functional Decoupling in Working Memory Networks Across Pre-Dialysis and Maintenance Hemodialysis End-Stage Renal Disease Patients.CNS neuroscience & therapeutics · 2026Observational
- Cortical morphometric gradients reveal molecular and cognitive underpinnings of bipolar disorder.Psychological medicine · 2025Article
- Structural connectome gradients and their relationship to IQ in childhood.Frontiers in human neuroscience · 2025Article
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Authors and funding
10 authors.
Funding
Abstract
A cortical hierarchical architecture is vital for encoding and integrating sensorimotor-to-cognitive information. However, whether this gradient structure is disrupted in end-stage renal disease (ESRD) patients and how this disruption provides valuable information for potential clinical symptoms remain unknown. We prospectively enrolled 77 ESRD patients and 48 healthy controls. Using resting-state functional magnetic resonance imaging, we studied ESRD-related hierarchical alterations. The Neurosynth platform and machine-learning models with 10-fold cross-validation were applied. ESRD patients had abnormal gradient metrics in core regions of the default mode network, sensorimotor network, and frontoparietal network. These changes correlated with creatinine, depression, and cognitive functions. A logistic regression classifier achieved a maximum performance of 84.8% accuracy and 0.901 area under the ROC curve (AUC). Our results highlight hierarchical imbalances in ESRD patients that correlate with diverse cognitive deficits, which may be used as potential neuroimaging markers for clinical symptoms.
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Registered trials
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