By combining DTI and rs-fMRI with graph theoretical analysis, in this study, we investigated the topological alterations of both the structural and functional connectomes in T2DM patients with and without MCI. We made several observations. First, both the structural and functional networks showed alterations in patients with T2DM, including during the normal-cognition stage. However, the network changes appeared more pronounced in the DM-MCI group compared to the DM-NC group. Second, the decreased nodal efficiencies of the structural and functional networks were detected in frontoparietal, temporal and occipital lobes, whereas the nodal efficiencies of functional network showed increased changes in the T2DM groups within several brain regions, suggesting a possible compensatory mechanism of the functional network in the stage of cognition decline. Third, the extent of network changes was correlated with disease severity in patients with T2DM. Some previous studies [24] have also explored the topological alterations of the brain’s functional network in T2DM patients using graph theory approaches. There are some differences in our study. First, we conducted a combination analysis including both the structural and functional networks within the same cohort of T2DM patients, providing a comparative analysis of the variations between them. Second, in the correlation analysis with clinical variables, we expanded the scope to include global network properties (Eglob, Eloc, Cp and Lp) as well as nodal efficiencies, with all the T2DM patients, including those with normal cognition, brought into the correlation analysis.

Although the small-world properties were preserved in the DM-MCI patients, some global network properties of the structural networks were significantly altered compared to the controls. The decreased Eglob and Eloc and increased Lp of the DTI networks exhibited in the DM-MCI group implied that the cognitive impairment stage of patients with T2DM was characterized by disrupted topological organization and integration in the structural connectome, underpinning changes in the functional connectome. Similar topological abnormalities in T2DM were discovered in earlier studies using graph analysis based on DTI networks [25, 26]. Furthermore, we included the DM-NC group, whose cognition status and scores were normal in clinical assessments. In these patients, the structural network properties exhibited intermediate values between the DM-MCI and controls. In previous study we detected WM alterations in DM-NC patients [27]. We concluded that WM alternations and decreased global/local efficiency had been emerging, although the between-group difference in network metrics had not reached statistical significance.

Unlike the consistent findings in the structural network by previous studies, the analyses of the functional network showed inconsistent results. Decreased Eglob and increased Lp measurements revealed a decreased network efficiency [28]. Moreover, an increased efficiency (measured by increased Eglob, Eloc, and Cp) in the functional network has been reported in T2DM [13, 19,20,21]. According to our findings, the DM-MCI group showed significantly elevated Eloc and Cp compared to the controls. The combination of higher Eloc and Cp reflects high local specialization of the brain in information processing, as well as greater efficiency in synchronizing neuronal activity. The finding that the functional networks were “better” organized in T2DM than controls is not unique [13, 19,20,21]. This suggests a compensatory mechanism of the whole-brain functional network during the stage of cognition decline, which was associated with functional plasticity and increased connections.

In addition to the global network metrics, the analyses of nodal properties also provided some insights, particularly between DM-NC and controls, where the global network properties did not exhibit a significant difference. Decreased nodal efficiencies in the structural network were observed in brain regions, such as the middle frontal gyrus and posterior cingulate gyrus, which were part of the default-mode network (DMN) and may involve cognitive functions [29]. The reduced nodal efficiency may assist with the early identification of T2DM-related MCI before it is reflected by neuropsychological assessments. In contrast to the continually decreased nodal efficiencies in the structural network, in the functional network, some regions with increased nodal efficiencies were detected in both DM-NC and DM-MCI patients. We speculated that at (or even before) the emergence of clinically apparent MCI, the brain functional network may have already been reorganized as a compensatory mechanism to counteract the slight cognitive decrements.

Currently, the diagnosis of diabetes-related MCI is primarily made based on the clinical symptoms and neuropsychological tests. However, the commonly used neuropsychological scales in the clinical diagnosis of T2DM-related MCI lacks specificity and sensitivity, and is likely biased by the patient’s educational background, degree of cooperation, and the subjectivity of the clinicians [30]. Therefore, biomarkers that effectively suggest the existence of MCI will help to identify and intervene at early stage of MCI, delay the occurrence of dementia, and improve the quality of life of patients with T2DM.

This study has several limitations that warrant discussion. First, the sample size was relatively moderate, which may limit generalization of the results. Second, this study was a single time-point and cross-sectional. Given the dynamic development of MCI, a longitudinal study tracking the same patients with T2DM would be better able to demonstrate the dynamic network changes to potentially predict the cognitive decline. Finally, despite finding alterations in global network metrics and nodal efficiency in some regions, it remains difficult to develop a classifier to identify an individual with MCI due to the high inter-subject variability in the network metrics and regions with altered nodal efficiency. We are enlisting more volunteers to gain a more comprehensive conclusion.