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Disrupted brain gray matter networks in drug-naïve participants with essential tremor

Research output: Contribution to journalArticlepeer-review

Jing Yang, Du Lei, Jiaxin Peng, Xueling Suo, Walter H.L. Pinaya, Wenbin Li, Junying Li, Graham J. Kemp, Rong Peng, Qiyong Gong

Original languageEnglish
Pages (from-to)1501-1510
Number of pages10
Issue number9
Accepted/In press2021
PublishedSep 2021

Bibliographical note

Funding Information: This study was funded by the National Natural Science Foundation of China (Grant Nos. 81621003, 82027808) and the Functional and Molecular Imaging Key Laboratory of Sichuan Province (FMIKLSP, Grant: 2019JDS0044). Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors


Purpose: To use structural magnetic resonance imaging and graph theory approaches to investigate the topological organization of the brain morphological network based on gray matter in essential tremor, and its potential relation to disease severity. Methods: In this prospective study conducted from November 2018 to November 2019, 36 participants with essential tremor and 37 matched healthy controls underwent magnetic resonance imaging. Brain networks based on the morphological similarity of gray matter across regions were analyzed using graph theory. Nonparametric permutation testing was used to assess group differences in topological metrics. Support vector machine was applied to the gray matter morphological matrices to classify participants with essential tremor vs. healthy controls. Results: Compared with healthy controls, participants with essential tremor showed increased global efficiency (p < 0.01) and decreased path length (p < 0.01); abnormal nodal properties in frontal, parietal, and cerebellar lobes; and disconnectivity in cerebello-thalamo-cortical network. The abnormal brain nodal centralities (left superior cerebellum gyrus; right caudate nucleus) correlated with clinical measures, both motor (Fahn–Tolosa–Marìn tremor rating, p = 0.017, r = − 0.41) and nonmotor (Hamilton depression scale, p = 0.040, r = − 0.36; Hamilton anxiety scale, p = 0.008, r = − 0.436). Gray matter morphological matrices classified individuals with high accuracy of 80.0%. Conclusion: Participants with essential tremor showed randomization in global properties and dysconnectivity in the cerebello-thalamo-cortical network. Participants with essential tremor could be distinguished from healthy controls by gray matter morphological matrices.

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