A1 Journal article (refereed)
Aberrant brain functional networks in type 2 diabetes mellitus : A graph theoretical and support-vector machine approach (2022)
Lin, L., Zhang, J., Liu, Y., Hao, X., Shen, J., Yu, Y., Xu, H., Cong, F., Li, H., & Wu, J. (2022). Aberrant brain functional networks in type 2 diabetes mellitus : A graph theoretical and support-vector machine approach. Frontiers in Human Neuroscience, 16, Article 974094. https://doi.org/10.3389/fnhum.2022.974094
JYU authors or editors
Publication details
All authors or editors: Lin, Lin; Zhang, Jindi; Liu, Yutong; Hao, Xinyu; Shen, Jing; Yu, Yang; Xu, Huashuai; Cong, Fengyu; Li, Huanjie; Wu, Jianlin
Journal or series: Frontiers in Human Neuroscience
eISSN: 1662-5161
Publication year: 2022
Publication date: 12/10/2022
Volume: 16
Article number: 974094
Publisher: Frontiers Media SA
Publication country: Switzerland
Publication language: English
DOI: https://doi.org/10.3389/fnhum.2022.974094
Publication open access: Openly available
Publication channel open access: Open Access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/84210
Publication is parallel published: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9597867/
Abstract
Methods: A total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were analyzed using a graph-theoretic approach, the FC and topological characteristics of the network were compared between T2DM and HC using a general linear model, and correlations between networks and clinical and cognitive characteristics were identified. The support vector machine (SVM) model was used to identify differences between T2DM and HC.
Results: In patients with T2DM, FC was higher in two core regions [precuneus/posterior cingulated cortex (PCC)_1 and later prefrontal cortex_1] in the default mode network and lower in bilateral superior parietal lobes (within dorsal attention network), and decreased between the right medial frontal cortex and left auditory cortex. The FC of the right frontal medial-left auditory cortex was positively correlated with the Montreal Cognitive Assessment scales and negatively correlated with the blood glucose levels. Long-range connectivity between bilateral auditory cortex was missing in the T2DM. The nodal degree centrality and efficiency of PCC were higher in T2DM than in HC (P < 0.005). The nodal degree centrality in the PCC in the SVM model was 97.56% accurate in distinguishing T2DM patients from HC, demonstrating the reliability of the prediction model.
Conclusion: Functional abnormalities in the auditory cortex in T2DM may be related to cognitive impairment, such as memory and attention, and nodal degree centrality in the PCC might serve as a potential neuroimaging biomarker to predict and identify T2DM.
Keywords: adult-onset diabetes; cognitive skills; biomarkers; neural networks (biology); cerebral cortex; magnetic resonance imaging; machine learning
Free keywords: type 2 diabetes mellitus; cognitive function; auditory cortex; resting-state MRI; support vector machine; topological properties
Contributing organizations
Ministry reporting: Yes
Reporting Year: 2022
JUFO rating: 1