Changes in MEG resting-state networks are related to cognitive decline in type 1 diabetes mellitus patients

Abstract

Objective: Integrity of resting-state functional brain networks (RSNs) is important for proper cognitive functioning. In type 1 diabetes mellitus (T1DM) cognitive decrements are commonly observed, possibly due to alterations in RSNs, which may vary according to microvascular complication status. Thus, we tested the hypothesis that functional connectivity in RSNs differs according to clinical status and correlates with cognition in T1DM patients, using an unbiased approach with high spatio-temporal resolution functional network.

Methods: Resting-state magnetoencephalographic (MEG) data for T1DM patients with (n = 42) and without (n = 41) microvascular complications and 33 healthy participants were recorded. MEG time-series at source level were reconstructed using a recently developed atlas-based beamformer. Functional connectivity within classical frequency bands, estimated by the phase lag index (PLI), was calculated within eight commonly found RSNs. Neuropsychological tests were used to assess cognitive performance, and the relation with RSNs was evaluated.

Results: Significant differences in terms of RSN functional connectivity between the three groups were observed in the lower alpha band, in the default-mode (DMN), executive control (ECN) and sensorimotor (SMN) RSNs. T1DM patients with microvascular complications showed the weakest functional connectivity in these networks relative to the other groups. For DMN, functional connectivity was higher in patients without microangiopathy relative to controls (all p < 0.05). General cognitive performance for both patient groups was worse compared with healthy controls. Lower DMN alpha band functional connectivity correlated with poorer general cognitive ability in patients with microvascular complications.

Discussion: Altered RSN functional connectivity was found in T1DM patients depending on clinical status. Lower DMN functional connectivity was related to poorer cognitive functioning. These results indicate that functional connectivity may play a key role in T1DM-related cognitive dysfunction.

Keywords: Functional connectivity; Magnetoencephalography; Oscillations; Phase Lag Index (PLI); Resting-state networks; Type 1 diabetes mellitus.

Fig. 1

Left panels: Average (and 2 standard errors) connectivity (lower alpha band, log-transformed) within resting-state networks that showed a significant group effect. Note that for all these networks the functional connectivity was significantly lower for the patient group with microvascular complications (T1DM⁺) than for the patient group without microvascular complications (T1DM⁻), as well as in the sensorimotor network (SMN) for the T1DM⁺ group compared to controls. In the default mode network (DMN), the PLI was significantly higher for the T1DM⁻ group than for the controls. Right panels show the areas for the relevant RSN (highlighted in blue) on a template brain (see also Appendix A). Here, cold colours indicate low PLI, hot colours indicate high PLI.