The structural covariance of connected gray matter has been demonstrated valuable in inferring large-scale structural brain networks. The alterations of grey matter structural covariance networks in prediabetes remains unclear. In this study, the topological features and robustness of gray matter structural covariance networks in prediabetes were examined. Results showed that the prediabetes group retained the small-worldness characteristics. The prediabetes group showed higher clustering coefficient, higher local efficiency and more vulnerable to random failure than healthy controls (HCs) group, suggesting that prediabetes disturbed the segregation of gray matter structural covariance networks, which provided new insights into the pathophysiology of this disease
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