Insulin resistance, which is one of the causes of type 2 diabetes, may cause structural and functional abnormalities of the human brain, but the mechanisms are not well understood. In this study, we used data from the Bunkyo Health Study, a cohort study of elderly Japanese subjects, to investigate the relationship between gray matter volume (GMV) and insulin resistance. Using data from 1609 subjects with no missing data, we examined the relationship between the GMV and homeostasis model assessment for insulin resistance (HOMA-IR). We identified the precuneus, superior frontal gyrus, and ventral medial frontal cortex as brain regions where gray matter volume correlated negatively with HOMA-IR (p-uncorrected < 0.001 at voxel-level, p-FWE-corrected < 0.05 at cluster level) (Figure 1A). Of the cerebrocortical networks, the default-mode network accounted for approximately 60% of voxels in the detected clusters (Figure 1B). Next, using resting-state functional images of the Human Connectome Project (HCP) (N = 418), we examined functional connectivity of five hypothalamic nuclei (paraventricular nucleus, arch nucleus (PVH), arcuate nucleus (ARC), dorsal medial nucleus (DMH), ventral medial nucleus (VMH), and lateral hypothalamic area(LHA)) with the default-mode regions. The PVH showed stronger functional connectivity to the default-mode regions than the other nuclei (all p < 0.001) (Figure 1C). These results suggest that the development of insulin resistance is associated with reduced GMV in the default-mode regions and those functional interactions with the hypothalamus.
Ogawa et al. (Thu,) studied this question.