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Zhang P, He Z, Mao Y, Sun R, Qu Y, Chen L, Ma P, Yin S, Yin T, Zeng F. Aberrant resting-state functional connectivity and topological properties of the subcortical network in functional dyspepsia patients. Front Mol Neurosci 2022; 15:1001557. [PMCID: PMC9606653 DOI: 10.3389/fnmol.2022.1001557] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
Functional dyspepsia (FD) is a disorder of gut-brain interaction. Previous studies have demonstrated a wide range of abnormalities in functional brain activity and connectivity patterns in FD. However, the connectivity pattern of the subcortical network (SCN), which is a hub of visceral information transmission and processing, remains unclear in FD patients. The study compared the resting-state functional connectivity (rsFC) and the global and nodal topological properties of SCN between 109 FD patients and 98 healthy controls, and then explored the correlations between the connectivity metrics and clinical symptoms in FD patients. The results demonstrated that FD patients manifested the increased rsFC in seventeen edges among the SCN, decreased small-worldness and local efficiency in SCN, as well as increased nodal efficiency and nodal degree centrality in the anterior thalamus than healthy controls (p < 0.05, false discovery rate corrected). Moreover, the rsFC of the right anterior thalamus-left nucleus accumbens edge was significantly correlated with the NDSI scores (r = 0.255, p = 0.008, uncorrected) and NDLQI scores (r = −0.241, p = 0.013, uncorrected), the nodal efficiency of right anterior thalamus was significantly correlated with NDLQI scores (r = 0.204, p = 0.036, uncorrected) in FD patients. This study indicated the abnormal rsFC pattern, as well as global and nodal topological properties of the SCN, especially the bilateral anterior thalamus in FD patients, which enhanced our understanding of the central pathophysiology of FD and will lay the foundation for the objective diagnosis of FD and the development of new therapies.
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Affiliation(s)
- Pan Zhang
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhaoxuan He
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yangke Mao
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Ruirui Sun
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yuzhu Qu
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Li Chen
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Peihong Ma
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China
| | - Shuai Yin
- First Affiliated Hospital, Henan University of Traditional Chinese Medicine, Zhengzhou, Henan, China
| | - Tao Yin
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- *Correspondence: Tao Yin,
| | - Fang Zeng
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Fang Zeng,
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Yin T, Sun R, He Z, Chen Y, Yin S, Liu X, Lu J, Ma P, Zhang T, Huang L, Qu Y, Suo X, Lei D, Gong Q, Liang F, Li S, Zeng F. Subcortical-Cortical Functional Connectivity as a Potential Biomarker for Identifying Patients with Functional Dyspepsia. Cereb Cortex 2021; 32:3347-3358. [PMID: 34891153 DOI: 10.1093/cercor/bhab419] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 10/21/2021] [Accepted: 10/22/2021] [Indexed: 02/05/2023] Open
Abstract
The diagnosis of functional dyspepsia (FD) presently relies on the self-reported symptoms. This study aimed to determine the potential of functional brain network features as biomarkers for the identification of FD patients. Firstly, the functional brain Magnetic Resonance Imaging data were collected from 100 FD patients and 100 healthy subjects, and the functional brain network features were extracted by the independent component analysis. Then, a support vector machine classifier was established based on these functional brain network features to discriminate FD patients from healthy subjects. Features that contributed substantially to the classification were finally identified as the classifying features. The results demonstrated that the classifier performed pretty well in discriminating FD patients. Namely, the accuracy of classification was 0.84 ± 0.03 in cross-validation set and 0.80 ± 0.07 in independent test set, respectively. A total of 15 connections between the subcortical nucleus (the thalamus and caudate) and sensorimotor cortex, parahippocampus, orbitofrontal cortex were finally determined as the classifying features. Furthermore, the results of cross-brain atlas validation showed that these classifying features were quite robust in the identification of FD patients. In summary, the current findings suggested the potential of using machine learning method and functional brain network biomarkers to identify FD patients.
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Affiliation(s)
- Tao Yin
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Ruirui Sun
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Zhaoxuan He
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China.,Key Laboratory of Sichuan Province for Acupuncture and Chronobiology, Chengdu, Sichuan 610075, China
| | - Yuan Chen
- International Education College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Shuai Yin
- First Affiliated Hospital, Henan University of Traditional Chinese Medicine, Zhengzhou, Henan 450002, China
| | - Xiaoyan Liu
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Jin Lu
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Peihong Ma
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China.,School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Tingting Zhang
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Liuyang Huang
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Yuzhu Qu
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Xueling Suo
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Du Lei
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Qiyong Gong
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Fanrong Liang
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Shenghong Li
- State Key Laboratory of Southwestern Chinese Medicine Resources, Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Fang Zeng
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China.,Key Laboratory of Sichuan Province for Acupuncture and Chronobiology, Chengdu, Sichuan 610075, China
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