1
|
Liu Y, Wang H, Sha G, Cao Y, Chen Y, Chen Y, Zhang J, Chai C, Fan Q, Xia S. The covariant structural and functional neuro-correlates of cognitive impairments in patients with end-stage renal diseases. Front Neurosci 2024; 18:1374948. [PMID: 38686326 PMCID: PMC11056510 DOI: 10.3389/fnins.2024.1374948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 04/03/2024] [Indexed: 05/02/2024] Open
Abstract
Introduction Cognitive impairment (CI) is a common complication of end-stage renal disease (ESRD) that is associated with structural and functional changes in the brain. However, whether a joint structural and functional alteration pattern exists that is related to CI in ESRD is unclear. Methods In this study, instead of looking at brain structure and function separately, we aim to investigate the covariant characteristics of both functional and structural aspects. Specifically, we took the fusion analysis approach, namely, multimodal canonical correlation analysis and joint independent component analysis (mCCA+jICA), to jointly study the discriminative features in gray matter volume (GMV) measured by T1-weighted (T1w) MRI, fractional anisotropy (FA) in white matter measured by diffusion MRI, and the amplitude of low-frequency fluctuation (ALFF) measured by blood oxygenation-level-dependent (BOLD) MRI in 78 ESRD patients versus 64 healthy controls (HCs), followed by a mediation effect analysis to explore the relationship between neuroimaging findings, cognitive impairments and uremic toxins. Results Two joint group-discriminative independent components (ICs) were found to show covariant abnormalities across FA, GMV, and ALFF (all p < 0.05). The most dominant joint IC revealed associative patterns of alterations of GMV (in the precentral gyrus, occipital lobe, temporal lobe, parahippocampal gyrus, and hippocampus), alterations of ALFF (in the precuneus, superior parietal gyrus, and superior occipital gyrus), and of white matter FA (in the corticospinal tract and inferior frontal occipital fasciculus). Another significant IC revealed associative alterations of GMV (in the dorsolateral prefrontal and orbitofrontal cortex) and FA (in the forceps minor). Moreover, the brain changes identified by FA and GMV in the above-mentioned brain regions were found to mediate the negative correlation between serum phosphate and mini-mental state examination (MMSE) scores (all p < 0.05). Conclusion The mCCA+jICA method was demonstrated to be capable of revealing covariant abnormalities across neuronal features of different types in ESRD patients as contrasted to HCs, and joint brain changes may play an important role in mediating the relationship between serum toxins and CIs in ESRD. Our results show the mCCA+jICA fusion analysis approach may provide new insights into similar neurobiological studies.
Collapse
Affiliation(s)
- Yuefan Liu
- Department of Biomedical Engineering, Medical College, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
| | - Huiying Wang
- Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Guanchen Sha
- Department of Biomedical Engineering, Medical College, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
| | - Yutong Cao
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
- Intelligent Medical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Yongsheng Chen
- Department of Neurology, Wayne State University School of Medicine, Detroit, MI, United States
| | - Yuanyuan Chen
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
- Intelligent Medical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Jingyi Zhang
- Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Chao Chai
- Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Qiuyun Fan
- Department of Biomedical Engineering, Medical College, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
- Intelligent Medical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Shuang Xia
- Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| |
Collapse
|