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Salience network connectivity is reduced by a meal and influenced by genetic background and hypothalamic gliosis



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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  1. 1.

    Damoiseaux JS, Rombouts SARB, Barkhof F, Scheltens P, Stam CJ, Smith SM, et al. Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA. 2006;103:13848–53.

  2. 2.

    Power JD, Cohen AL, Nelson SM, Wig GS, Barnes KA, Church JA, et al. Functional network organization of the human brain. Neuron. 2011;72:665–78.

  3. 3.

    Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007;27:2349–56.

  4. 4.

    Bressler SL, Menon V. Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn Sci. 2010;14:277–90.

  5. 5.

    Rolls ET. Reward systems in the brain and nutrition. Annu Rev Nutr. 2016;36:435–70.

  6. 6.

    MenonV. Salience network. In: Toga AW (ed). Brain Mapping: An Encyclopedic Reference. vol. 2. Academic Press, Elsevier; 2015. pp. 597–611.

  7. 7.

    Lips MA, Wijngaarden MA, Van Der Grond J, Van Buchem MA, De Groot GH, Rombouts S. et al. Resting-state functional connectivity of brain regions involved in cognitive control, motivation, and reward is enhanced in obese females. Am J Clin Nutr. 2014;100:524–31.

  8. 8.

    Ryan JP, Karim HT, Aizenstein HJ, Helbling NL, Toledo FGS. Insulin sensitivity predicts brain network connectivity following a meal. Neuroimage. 2018;171:268–76.

  9. 9.

    Paolini BM, Laurienti PJ, Norris J, Jack Rejeski W. Meal replacement: calming the hot-state brain network of appetite. Front Psychol. 2014;5:1–13.

  10. 10.

    Kullmann S, Heni M, Veit R, Ketterer C, Schick F, Häring HU, et al. The obese brain: association of body mass index and insulin sensitivity with resting state network functional connectivity. Hum Brain Mapp. 2012;33:1052–61.

  11. 11.

    van Opstal AM, Hafkemeijer A, van den Berg-Huysmans AA, Hoeksma M, Blonk C, Pijl H, et al. Brain activity and connectivity changes in response to glucose ingestion. Nutr Neurosci. 2018;0:1–8.

  12. 12.

    Doucet GE, Rasgon N, McEwen BS, Micali N, Frangou S. Elevated body mass index is associated with increased integration and reduced cohesion of sensory-driven and internally guided resting-state functional brain networks. Cereb Cortex. 2018;28:988–97.

  13. 13.

    García-García I, Jurado MÁ, Garolera M, Segura B, Sala-Llonch R, Marqués-Iturria I, et al. Alterations of the salience network in obesity: a resting-state fMRI study. Hum Brain Mapp. 2013;34:2786–97.

  14. 14.

    Nummenmaa L, Hirvonen J, Hannukainen JC, Immonen H, Lindroos MM, Salminen P, et al. Dorsal striatum and its limbic connectivity mediate abnormal anticipatory reward processing in obesity. PLoS One. 2012;7:e31089.

  15. 15.

    Figley CR, Asem JSA, Levenbaum EL, Courtney SM. Effects of body mass index and body fat percent on default mode, executive control, and salience network structure and function. Front Neurosci. 2016;10:1–23.

  16. 16.

    Gupta A, Mayer EA, Hamadani K, Bhatt R, Fling C, Alaverdyan M, et al. Sex differences in the influence of body mass index on anatomical architecture of brain networks. Int J Obes. 2017;41:1185–95.

  17. 17.

    Thaler JP, Yi C, Schur EA, Guyenet SJ, Hwang BH, Dietrich MO, et al. Obesity is associated with hypothalamic injury in rodents and humans. J Clin Investig. 2012;122:153–62.

  18. 18.

    Douglass JD, Dorfman MD, Fasnacht R, Shaffer LD, Thaler JP. Astrocyte IKKβ/NF-κB signaling is required for diet-induced obesity and hypothalamic inflammation. Mol Metab. 2017;6:366–73.

  19. 19.

    Schur EA, Melhorn SJ, Oh S-K, Lacy JM, Berkseth KE, Guyenet SJ, et al. Radiologic evidence that hypothalamic gliosis is associated withobesity and insulin resistance in humans. Obesity. 2015;23:2142–8.

  20. 20.

    Kreutzer C, Peters S, Schulte DM, Fangmann D, Türk K, Wolff S, et al. Hypothalamic inflammation in human obesity is mediated by environmental and genetic factors. Diabetes. 2017;66:2407–15.

  21. 21.

    Baufeld C, Osterloh A, Prokop S, Miller KR, Heppner FL. High-fat diet-induced brain region-specific phenotypic spectrum of CNS resident microglia. Acta Neuropathol. 2016;132:361–75.

  22. 22.

    Sewaybricker LE, Schur EA, Melhorn SJ, Campos BM, Askren MK, Nogueira GAS, et al. Initial evidence for hypothalamic gliosis in children with obesity by quantitative T2 MRI and implications for blood oxygen-level dependent response to glucose ingestion. Pediatr Obes. 2019;14:e12486.

  23. 23.

    Burda JE, Sofroniew MV. Reactive gliosis and the multicellular response to CNS damage and disease. Neuron. 2014;81:229–48.

  24. 24.

    Schwartz MW, Seeley RJ, Zeltser LM, Drewnowski A, Ravussin E, Redman LM, et al. Obesity pathogenesis: an endocrine society scientific statement. Endocr Rev. 2017;38:267–96.

  25. 25.

    Kelley AE, Baldo Ba, Pratt WE, Will MJ. Corticostriatal-hypothalamic circuitry and food motivation: integration of energy, action and reward. Physiol Behav. 2005;86:773–95.

  26. 26.

    Fu Y, Ma Z, Hamilton C, Liang Z, Hou X, Ma X, et al. Genetic influences on resting-state functional networks: a twin study. Hum Brain Mapp. 2015;36:3959–72.

  27. 27.

    Glahn DC, Winkler AM, Kochunov P, Almasy L, Duggirala R, Carless MA, et al. Genetic control over the resting brain. Proc Natl Acad Sci USA. 2010;107:1223–8.

  28. 28.

    Yang Z, Zuo X-N, McMahon KL, Craddock RC, Kelly C, de Zubicaray GI, et al. Genetic and environmental contributions to functional connectivity architecture of the human brain. Cereb Cortex. 2016;26:2341–52.

  29. 29.

    Boomsma D, Busjahn A, Peltonen L. Classical twin studies and beyond. Nat Rev Genet. 2002;3:872–82.

  30. 30.

    Strachan E, Hunt C, Afari N, Duncan G, Noonan C, Schur E, et al. University of Washington Twin registry: poised for the next generation of twin research. Twin Res Hum Genet. 2013;16:455–62.

  31. 31.

    Melhorn SJ, Mehta S, Kratz M, Tyagi V, Webb MF, Noonan CJ, et al. Brain regulation of appetite in twins. Am J Clin Nutr. 2016;103:314–22.

  32. 32.

    Mifflin MD, St Jeor ST, Hill La, Scott BJ, Daugherty Sa, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990;51:241–7.

  33. 33.

    Melhorn SJ, Askren MK, Chung WK, Kratz M, Bosch TA, Tyagi V, et al. FTO genotype impacts food intake and corticolimbic activation. Am J Clin Nutr. 2018;107:145–54.

  34. 34.

    Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9.

  35. 35.

    Behzadi Y, Restom K, Liau J, Liu TT. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage. 2007;37:90–101.

  36. 36.

    Jenkinson M. Fast, automated, N-dimensional phase-unwrapping algorithm. Magn Reson Med. 2003;49:193–7.

  37. 37.

    Greve DN, Fischl B. Accurate and robust brain image alignment using boundary-based registration. Neuroimage. 2009;48:63–72.

  38. 38.

    Avants BB, Tustison NJ, Song G, Cook PA, Klein A, Gee JC. A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage. 2011;54:2033–44.

  39. 39.

    Carlin JB, Gurrin LC, Sterne JAC, Morley R, Dwyer T. Regression models for twin studies: a critical review. Int J Epidemiol. 2005;34:1089–99.

  40. 40.

    Schur E, Carnell S. What twin studies tell us about brain responses to food cues. Curr Obes Rep. 2017;6:371–9.

  41. 41.

    Craig ADB. How do you feel—now? The anterior insula and human awareness. Nat Rev Neurosci. 2009;10:59–70.

  42. 42.

    Shehzad Z, Kelly AMC, Reiss PT, Gee DG, Gotimer K, Uddin LQ, et al. The resting brain: unconstrained yet reliable. Cereb Cortex. 2009;19:2209–29.

  43. 43.

    Guo CC, Kurth F, Zhou J, Mayer EA, Eickhoff SB, Kramer JH, et al. One-year test-retest reliability of intrinsic connectivity network fMRI in older adults. Neuroimage. 2012;61:1471–83.

  44. 44.

    Andermann ML, Lowell BB. Toward a wiring diagram understanding of appetite control. Neuron. 2017;95:757–78.

  45. 45.

    Menon V, Uddin LQ. Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct. 2010;214:655–67.

  46. 46.

    Seeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD. Neurodegenerative diseases target large-scale human brain networks. Neuron. 2009;62:42–52.

  47. 47.

    Uddin LQ, Menon V. The anterior insula in autism: under-connected and under-examined. Neurosci Biobehav Rev. 2009;33:1198–203.

  48. 48.

    Woolley JD, Gorno-Tempini ML, Seeley WW, Rankin K, Lee SS, Matthews BR, et al. Binge eating is associated with right orbitofrontal-insular-striatal atrophy in frontotemporal dementia. Neurology. 2007;69:1424–33.

  49. 49.

    Frank S, Linder K, Kullmann S, Heni M, Ketterer C, Çavuşoǧlu M, et al. Fat intake modulates cerebral blood flow in homeostatic and gustatory brain areas in humans. Am J Clin Nutr. 2012;95:1342–9.

  50. 50.

    Martin LE, Holsen LM, Chambers RJ, Bruce AS, Brooks WM, Zarcone JR, et al. Neural mechanisms associated with food motivation in obese and healthy weight adults. Obesity. 2010;18:254–60.

  51. 51.

    Poldrack RA, Baker CI, Durnez J, Gorgolewski KJ, Matthews PM, Munafò MR, et al. Scanning the horizon: towards transparent and reproducible neuroimaging research. Nat Rev Neurosci. 2017;18:115–26.

  52. 52.

    Doornweerd S, van Duinkerken E, de Geus EJ, Arbab-Zadeh P, Veltman DJ, Ijzerman RG. Overweight is associated with lower resting state functional connectivity in females after eliminating genetic effects: a twin study. Hum Brain Mapp. 2017;38:5069–81.

  53. 53.

    Valdearcos M, Douglass JD, Robblee MM, Dorfman MD, Stifler DR, Bennett ML, et al. Microglial inflammatory signaling orchestrates the hypothalamic immune response to dietary excess and mediates obesity susceptibility. Cell Metab. 2017;26:185–197.e3.

  54. 54.

    Tomasi D, Volkow ND. Gender differences in brain functional connectivity density. Hum Brain Mapp. 2012;33:849–60.

  55. 55.

    Biswal BB, Mennes M, Zuo X-N, Gohel S, Kelly C, Smith SM, et al. Toward discovery science of human brain function. Proc Natl Acad Sci USA. 2010;107:4734–9.

  56. 56.

    Jamadar SD, Sforazzini F, Raniga P, Ferris NJ, Paton B, Bailey MJ, et al. Sexual dimorphism of resting-state network connectivity in healthy ageing. J Gerontol B Psychol Sci Soc Sci. 2018;00:1–11.

  57. 57.

    Weissman-Fogel I, Moayedi M, Taylor KS, Pope G, Davis KD. Cognitive and default-mode resting state networks: do male and female brains “rest” differently? Hum Brain Mapp. 2010;31:1713–26.

  58. 58.

    Rossi MA, Stuber GD. Overlapping brain circuits for homeostatic and hedonic feeding. Cell Metab. 2018;27:42–56.

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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).

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The authors declare that they have no conflict of interest.

Correspondence to Ellen A. Schur.

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