The salience network (SN) comprises brain regions that evaluate cues in the external environment in light of internal signals. We examined the SN response to meal intake and potential genetic and acquired influences on SN function.
Monozygotic (MZ; 40 pairs) and dizygotic (15 pairs) twins had body composition and plasma metabolic profile evaluated (glucose, insulin, leptin, ghrelin, and GLP-1). Twins underwent resting-state functional magnetic resonance imaging (fMRI) scans before and after a standardized meal. The strength of SN connectivity was analyzed pre- and post-meal and the percentage change elicited by a meal was calculated. A multi-echo T2 MRI scan measured T2 relaxation time, a radiologic index of gliosis, in the mediobasal hypothalamus (MBH) and control regions. Statistical approaches included intraclass correlations (ICC) to investigate genetic influences and within-pair analyses to exclude genetic confounders.
SN connectivity was reduced by a meal ingestion (β = −0.20; P < 0.001). Inherited influences on both pre- and post-meal connectivity were present (ICC MZ twins 26%, P < 0.05 and 47%, P < 0.001, respectively), but not percentage change in response to the meal. SN connectivity in response to a meal did not differ between participants with obesity and of normal weight (χ2(1) = 0.93; P = 0.33). However, when participants were classified as having high or low signs of MBH gliosis, the high MBH gliosis group failed to reduce the connectivity in response to a meal (z = −1.32; P = 0.19). Excluding genetic confounders, the percentage change in SN connectivity by a meal correlated to body fat percentage (r = 0.24; P < 0.01).
SN connectivity was reduced by a meal, indicating potential participation of the SN in control of feeding. The strength of SN connectivity is inherited, but the degree to which SN connectivity is reduced by eating appears to be influenced by adiposity and the presence of hypothalamic gliosis.
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This work was supported by funding provided by the National Institutes of Health (DK089036, DK098466) and by the American Diabetes Association (ADA 1-17-ICTS-085). Additional assistance was provided by the University of Washington’s Nutrition Obesity Research Center (P30 DK035816), Diabetes Research Center (P30 DK017047), and the Institute of Translational Health Sciences (UL1 TR000423). LES was funded by Sao Paulo Research Foundation Post-Doctoral Fellowship (FAPESP 2017/00657-0).