Disrupted White Matter Network and Cognitive Decline in Type 2 Diabetes Patients

Abstract

Abstract. Type 2 diabetes mellitus is accompanied by cognitive impairment and is associated with an increased risk of dementia. Damage to brain structures such as white matter network disruption may underlie this cognitive disturbance. In the present study, 886 non-diabetic and 163 type 2 diabetic participants completed a battery of neuropsychological tests. Among them, 38 diabetic patients and 34 non-diabetic participants that matched the patients for age/sex/education received a magnetic resonance imaging-based diffusion tensor imaging. Then we calculated the topological properties of the white matter network using a graph theoretical method to investigate network efficiency differences between groups. We found that type 2 diabetic patients had inferior performances compared to the non-diabetic controls, in several cognitive domains involving executive function, spatial processing, memory, and attention. We also found that diabetic patients exhibited a disrupted topological organization of the white matter network (including the global network properties, i.e., network strength, global efficiency, local efficiency and shortest path length, and the nodal efficiency of the right rolandic operculum) in the brain. Moreover, those global network properties and the nodal efficiency of the right rolandic operculum both had positive correlations with executive function in the patient group. The results suggest that type 2 diabetes mellitus leads to an alteration in the topological organization of the cortical white matter network and this alteration may account for the observed cognitive decline.

Resveratrol Improves Cognitive Impairment by Regulating Apoptosis and Synaptic Plasticity in Streptozotocin-Induced Diabetic Rats

“…It has been shown that diabetes mellitus is accompanied by cognitive declines and associated with an increased risk of dementia [15]. In the present study, MWM results showed that there are significant differences between normal and diabetic rats, indicating that diabetes is related to cognitive impairment.…”

Altered brain structural topological properties in type 2 diabetes mellitus patients without complications

“…Recently, T2DM‐related structural disconnection has been further supported by WM topological network analyses using graph theory. Three studies on structural network analysis in T2DM patients have detected a weaker small‐world property and decreased local or global efficiency in T2DM patients . However, these studies focused either on elderly patients or on patients with diabetes complications and severe cognitive impairment .…”

“…Three studies on structural network analysis in T2DM patients have detected a weaker small‐world property and decreased local or global efficiency in T2DM patients . However, these studies focused either on elderly patients or on patients with diabetes complications and severe cognitive impairment . However, chronic hyperglycemia could lead to end‐organ damage, whereas cognitive impairments have been found to occur in the early stages of T2DM .…”

Cerebral Pathology and Cognition in Diabetes: The Merits of Multiparametric Neuroimaging

“…Altered network and structural connectivity in type 2 diabetes have been shown using tractography (Reijmer et al, 2013a,b; Hoogenboom et al, 2014; van Bussel et al, 2016b; Yang et al, 2016; Zhang J. et al, 2016). Local and global network properties (i.e., cluster coefficient, global efficiency, path length) were altered and associated with impaired processing speed (Reijmer et al, 2013b).…”

“…Microstructural abnormalities have been published for various brain regions in type 2 diabetes (Yau et al, 2009, 2010; Falvey et al, 2013; Zhang J. et al, 2014, 2016; van Bussel et al, 2016b; Xiong et al, 2016). Reduced FA has been observed in the white matter (Yau et al, 2010; Falvey et al, 2013) mostly concentrated in frontal and temporal regions (Yau et al, 2009), while elevated ADC values were found in a number of brain regions, including the hippocampus (Falvey et al, 2013) and multiple gray matter regions (Yau et al, 2010).…”