Abstract
BackgroundPrevious diabetes mellitus studies of cognitive impairments in the early stages have focused on changes in brain structure and function, and more recently the focus has shifted to the relationships between encephalic regions and diversification of network topology. However, studies examining network topology in diabetic brain function are still limited.MethodsThe study included 102 subjects; 55 type 2 diabetes mellitus (T2DM) patients plus 47 healthy controls. All subjects were examined by resting-state functional magnetic resonance imaging (rs-fMRI) scan. According to Automated Anatomical Labeling, the brain was divided into 90 anatomical regions, and every region corresponds to a brain network analysis node. The whole brain functional network was constructed by thresholding the correlation matrices of the 90 brain regions, and the topological properties of the network were computed based on graph theory. Then, the topological properties of the network were compared between different groups by using a non-parametric test. Finally, the associations between differences in topological properties and the clinical indicators were analyzed.ResultsThe brain functional networks of both T2DM patients and healthy controls were found to possess small-world characteristics, i.e., normalized clustering coefficient (γ) > 1, and normalized characteristic path length (λ) close to 1. No significant differences were found in the small-world characteristics (σ). Second, the T2DM patient group displayed significant differences in node properties in certain brain regions. Correlative analytic results showed that the node degree of the right inferior temporal gyrus (ITG) and the node efficiencies of the right ITG and superior temporal gyrus of T2DM patients were positively correlated with body mass index.ConclusionThe brain network of T2DM patients has the same small-world characteristics as normal people, but the normalized clustering coefficient is higher and the normalized characteristic path length is lower than that of the normal control group, indicating that the brain function network of the T2DM patients has changed. The changes of node properties were mostly concentrated in frontal lobe, temporal lobe and posterior cingulate gyrus. The abnormal changes in these indices in T2DM patients might be explained as a compensatory behavior to reduce cognitive impairments, which is achieved by mobilizing additional neural resources, such as the excessive activation of the network and the efficient networking of multiple brain regions.
Highlights
Diabetes is a metabolic disease characterized by long-term hyperglycemia, which may cause various complications such as microvascular disease, retinopathy, kidney disease and peripheral neuropathy
There were no significant differences between the Type 2 diabetes mellitus (T2DM) and T2HC groups in gender, age, body mass index (BMI), total cholesterol (TCHOL), TG, or low density lipoprotein (LDL), but there were differences between the groups in high density lipoprotein (HDL) and Montreal Cognitive Assessment Scale (MoCA) scores
In contrast to the results of the aforementioned study, in the present study we found that T2DM patients have higher normalized cluster coefficient and lower characteristic path length, which are typical features of a small-world network
Summary
Diabetes is a metabolic disease characterized by long-term hyperglycemia, which may cause various complications such as microvascular disease, retinopathy, kidney disease and peripheral neuropathy. In China, the rate of diabetes cases has approximately doubled in the last 10 years. The incidence of diabetes in China is 11.6% and the number of diabetics is more than 100 million, both of which are the highest in the world. Type 2 diabetes mellitus (T2DM) patients account for around 90% of cases of diabetes mellitus (Holman et al, 2015), the morbidity of which has been increasing over the years. Previous diabetes mellitus studies of cognitive impairments in the early stages have focused on changes in brain structure and function, and more recently the focus has shifted to the relationships between encephalic regions and diversification of network topology. Studies examining network topology in diabetic brain function are still limited
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