Advertisement

Brain Imaging and Behavior

, Volume 12, Issue 6, pp 1544–1555 | Cite as

Disrupted topological organization of the frontal-mesolimbic network in obese patients

  • Qianqian Meng
  • Yu Han
  • Gang JiEmail author
  • Guanya Li
  • Yang Hu
  • Li Liu
  • Qingchao Jin
  • Karen M. von Deneen
  • Jizheng Zhao
  • Guangbin Cui
  • Huaning Wang
  • Dardo Tomasi
  • Nora D. Volkow
  • Jixin Liu
  • Yongzhan Nie
  • Yi ZhangEmail author
  • Gene-Jack WangEmail author
Original Research

Abstract

Neuroimaging studies have revealed brain functional abnormalities in frontal-mesolimbic regions in obesity. However, the effects of obesity on brain network topology remains largely unknown. In the current study, we employed resting-state functional magnetic resonance imaging and graph theory methods to investigate obesity-related changes in brain network topology in 26 obese patients and 28 normal weight subjects. Results revealed that the whole-brain networks of the two groups exhibited typical features of small-world topology. Obese patients showed significantly increased shortest path length (Lp) and decreased global efficiency (Eglob). Moreover, decreased nodal-degree/efficiency was found in frontal (medial orbitofrontal cortex-mOFC, rostral anterior cingulate cortex-rACC), striatal (caudate/nucleus accumbens) and limbic regions (insula, amygdala, hippocampus/parahippocampal gyrus) and thalamus in obese patients. Network-based statistics showed that a sub-network, composed of 31 nodes and 30 edges, was significantly disrupted in obese patients; 29 out of 30 connections were associated with the right rACC. In the obese group, Lp and Eglob were negatively correlated with body mass index (BMI, P < 0.005), and BMI was negatively correlated with nodal-degree/efficiency of the mOFC (P < 0.001). Findings suggest disruption of the small-world organization and a global reduction of integration of functional brain networks involving the right rACC in obesity and implicating the mOFC in mediating severity.

Keywords

Brain connectome Frontal-mesolimbic Obesity Resting-state fMRI 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant Nos. 81271549, 81470816, 61431013, 81501543, 81730016, 81601563, 81371530, 81571751, and 81571753, National Clinical Research Center for Digestive Diseases, Xi’an, China under Grant No. 2015BAI13B07, and in part by the Intramural Research Program of the United States National Institute on Alcoholism and Alcohol Abuse, Z01AA3009 (DT, NDV, GJW).

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Ethical statements

Informed consent was obtained from all patients included in the study.

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Supplementary material

11682_2017_9802_MOESM1_ESM.doc (2.6 mb)
Supplementary material 1 (DOC 2616 KB)
11682_2017_9802_MOESM2_ESM.tif (139 kb)
Supplementary material 2 (TIF 139 KB)
11682_2017_9802_MOESM3_ESM.tif (3.8 mb)
Supplementary material 3 (TIF 3840 KB)
11682_2017_9802_MOESM4_ESM.tif (3.5 mb)
Supplementary material 4 (TIF 3537 KB)
11682_2017_9802_MOESM5_ESM.tif (143 kb)
Supplementary material 5 (TIF 143 KB)
11682_2017_9802_MOESM6_ESM.tif (2.2 mb)
Supplementary material 6 (TIF 2292 KB)
11682_2017_9802_MOESM7_ESM.tif (3.3 mb)
Supplementary material 7 (TIF 3355 KB)
11682_2017_9802_MOESM8_ESM.tif (103 kb)
Supplementary material 8 (TIF 103 KB)

References

  1. Alba-Ferrara, L., Muller-Oehring, E. M., Sullivan, E. V., Pfefferbaum, A., & Schulte, T. (2016). Brain responses to emotional salience and reward in alcohol use disorder. Brain Imaging Behavior, 10(1), 136 – 46.CrossRefGoogle Scholar
  2. Atalayer, D., Pantazatos, S. P., Gibson, C. D., McOuatt, H., Puma, L., Astbury, N. M., & Geliebter, A. (2014). Sexually dimorphic functional connectivity in response to high vs. low energy-dense food cues in obese humans: an fMRI study. Neuroimage, 100, 405 – 13.CrossRefGoogle Scholar
  3. Baek, K., Morris, L. S., Kundu, P., & Voon, V. (2017). Disrupted resting-state brain network properties in obesity: decreased global and putaminal cortico-striatal network efficiency. Psychological Medicine, 47(4), 585–596.CrossRefGoogle Scholar
  4. Batterink, L., Yokum, S., & Stice, E. (2010). Body mass correlates inversely with inhibitory control in response to food among adolescent girls: an fMRI study. Neuroimage, 52(4), 1696 – 703.CrossRefGoogle Scholar
  5. Benedict, C., Brooks, S. J., O’Daly, O. G., Almen, M. S., Morell, A., Aberg, K., Gingnell, M., Schultes, B., & Hallschmid, M. Broman JE and others. 2012. Acute sleep deprivation enhances the brain’s response to hedonic food stimuli: an fMRI study. Journal Clinical Endocrinology and Metabolism, 97(3), E443–E447.Google Scholar
  6. Blechert, J., Klackl, J., Miedl, S. F., & Wilhelm, F. H. (2016). To eat or not to eat: Effects of food availability on reward system activity during food picture viewing. Appetite, 99, 254–261.CrossRefGoogle Scholar
  7. Blechert, J., Meule, A., Busch, N. A., & Ohla, K. (2014). Food-pics: an image database for experimental research on eating and appetite. Frontiers in Psychology, 5, 617.CrossRefGoogle Scholar
  8. Bohon, C. (2014). Greater emotional eating scores associated with reduced frontolimbic activation to palatable taste in adolescents. Obesity (Silver Spring), 22(8), 1814–1820.CrossRefGoogle Scholar
  9. Breckel, T. P., Thiel, C. M., Bullmore, E. T., Zalesky, A., Patel, A. X., & Giessing, C. (2013). Long-term effects of attentional performance on functional brain network topology. PLoS One, 8(9), e74125.CrossRefGoogle Scholar
  10. Bullmore, E. T., Suckling, J., Overmeyer, S., Rabe-Hesketh, S., Taylor, E., & Brammer, M. J. (1999). Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain. IEEE Transactions on Medical Imaging, 18(1), 32–42.CrossRefGoogle Scholar
  11. Cao, R., Wu, Z., Li, H., Xiang, J., & Chen, J. (2014). Disturbed connectivity of EEG functional networks in alcoholism: a graph-theoretic analysis. Biomedical Materials Engineering, 24(6), 2927–2936.PubMedGoogle Scholar
  12. Chanraud, S., Pitel, A. L., Pfefferbaum, A., & Sullivan, E. V. (2011). Disruption of functional connectivity of the default-mode network in alcoholism. Cerebral Cortex, 21(10), 2272–2281.CrossRefGoogle Scholar
  13. Cohen, M. X., Heller, A. S., & Ranganath, C. (2005). Functional connectivity with anterior cingulate and orbitofrontal cortices during decision-making. Brain Research Cognitive Brain Research, 23(1), 61–70.CrossRefGoogle Scholar
  14. Collaboration, N. (2016). Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants. LANCET, 387(387), 1377–1396.Google Scholar
  15. Comte, M., Schon, D., Coull, J. T., Reynaud, E., Khalfa, S., Belzeaux, R., Ibrahim, E. C., Guedj, E., & Blin, O. Weinberger, D. R., et al. (2016). Dissociating bottom-up and top-down mechanisms in the cortico-limbic system during emotion processing. Cerebral Cortex, 26(1), 144 – 55.CrossRefGoogle Scholar
  16. Craig, A. D. (2011). Significance of the insula for the evolution of human awareness of feelings from the body. Annals of the New York Academy of Sciences, 1225, 72–82.CrossRefGoogle Scholar
  17. DelParigi, A., Chen, K., Salbe, A. D., Reiman, E. M., & Tataranni, P. A. (2005). Sensory experience of food and obesity: a positron emission tomography study of the brain regions affected by tasting a liquid meal after a prolonged fast. Neuroimage, 24(2), 436 – 43.CrossRefGoogle Scholar
  18. Fan, L., Li, H., Zhuo, J., Zhang, Y., Wang, J., Chen, L., Yang, Z., Chu, C., & Xie, S. Laird A. R., et al. (2016). The human brainnetome atlas: a new brain atlas based on connectional architecture. Cerebral Cortex, 26(8), 3508–3526.CrossRefGoogle Scholar
  19. Farr, O. M., Li, C. S., & Mantzoros, C. S. (2016). Central nervous system regulation of eating: Insights from human brain imaging. Metabolism, 65(5), 699–713.CrossRefGoogle Scholar
  20. Frank, S., Kullmann, S., & Veit, R. (2013). Food related processes in the insular cortex. Frontiers in Human Neuroscience, 7, 499.CrossRefGoogle Scholar
  21. Fransson, P., & Marrelec, G. (2008). The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis. Neuroimage, 42(3), 1178–1184.CrossRefGoogle Scholar
  22. Gautier, J. F., Chen, K., Uecker, A., Bandy, D., Frost, J., Salbe, A. D., Pratley, R. E., Lawson, M., Ravussin, E., Reiman, E. M. et al. (1999). Regions of the human brain affected during a liquid-meal taste perception in the fasting state: a positron emission tomography study. The American Journal of Clinical Nutrition, 70(5), 806 – 10.CrossRefGoogle Scholar
  23. Gearhardt, A. N., Corbin, W. R., & Brownell, K. D. (2009). Preliminary validation of the Yale food addiction scale. Appetite, 52(2), 430–436.CrossRefGoogle Scholar
  24. Gearhardt, A. N., Yokum, S., Orr, P. T., Stice, E., Corbin, W. R., & Brownell, K. D. 2011. Neural correlates of food addiction. Archives of General Psychiatry, 68(8), 808 – 16.CrossRefGoogle Scholar
  25. Giessing, C., & Thiel, C. M. (2012). Pro-cognitive drug effects modulate functional brain network organization. Frontiers in Behavior Neuroscience, 6, 53.Google Scholar
  26. Golchert, J., Smallwood, J., Jefferies, E., Liem, F., Huntenburg, J. M., Falkiewicz, M., Lauckner, M. E., Oligschlager, S., Villringer, A., & Margulies, D. S. (2017). In need of constraint: Understanding the role of the cingulate cortex in the impulsive mind. Neuroimage, 146, 804–813.CrossRefGoogle Scholar
  27. Hamilton, M. (1959). The assessment of anxiety states by rating. The British Journal of Medical Psychology, 32(1), 50 – 5.CrossRefGoogle Scholar
  28. Hamilton, M. (1960). A rating scale for depression. Journal of Neurology Neurosurgery, and Psychiatry, 23, 56–62.CrossRefGoogle Scholar
  29. Hare, T. A., Camerer, C. F., & Rangel, A. (2009). Self-control in decision-making involves modulation of the vmPFC valuation system. Science, 324(5927), 646–648.CrossRefGoogle Scholar
  30. Hare, T. A., O’Doherty, J., Camerer, C. F., Schultz, W., & Rangel, A. (2008). Dissociating the role of the orbitofrontal cortex and the striatum in the computation of goal values and prediction errors. Journal of Neuroscience, 28(22), 5623–5630.CrossRefGoogle Scholar
  31. He, Y., Chen, Z., & Evans, A. (2008). Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer’s disease. Journal of Neuroscience, 28(18), 4756–4766.CrossRefGoogle Scholar
  32. Hendrick, O. M., Luo, X., Zhang, S., & Li, C. S. (2012). Saliency processing and obesity: a preliminary imaging study of the stop signal task. Obesity (Silver Spring), 20(9), 1796 – 802.CrossRefGoogle Scholar
  33. Hu, S., Ide, J. S., Zhang, S., & Li, C. S. (2015). Anticipating conflict: neural correlates of a Bayesian belief and its motor consequence. Neuroimage, 119, 286 – 95.CrossRefGoogle Scholar
  34. Ide, J. S., Shenoy, P., Yu, A. J., & Li, C. S. (2013). Bayesian prediction and evaluation in the anterior cingulate cortex. Journal of Neuroscience, 33(5), 2039–2047.CrossRefGoogle Scholar
  35. Jiang, G., Wen, X., Qiu, Y., Zhang, R., Wang, J., Li, M., Ma, X., Tian, J., & Huang, R. (2013). Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study. PLoS One, 8(12), e82715.CrossRefGoogle Scholar
  36. Killgore, W. D., Young, A. D., Femia, L. A., Bogorodzki, P., Rogowska, J., & Yurgelun-Todd, D. A. (2003). Cortical and limbic activation during viewing of high- versus low-calorie foods. Neuroimage, 19(4), 1381–1394.CrossRefGoogle Scholar
  37. Kullmann, S., Heni, M., Veit, R., Ketterer, C., Schick, F., Haring, H. U., Fritsche, A., & Preissl, H. (2012). The obese brain: association of body mass index and insulin sensitivity with resting state network functional connectivity. Human Brain Mapping, 33(5), 1052–1061.CrossRefGoogle Scholar
  38. Levitan, R. D., Rivera, J., Silveira, P. P., Steiner, M., Gaudreau, H., Hamilton, J., Kennedy, J. L., Davis, C., Dube, L., Fellows, L. et al. (2015). Gender differences in the association between stop-signal reaction times, body mass indices and/or spontaneous food intake in pre-school children: an early model of compromised inhibitory control and obesity. International Journal of Obesity (London), 39(4), 614–619.CrossRefGoogle Scholar
  39. Liu, J., Liang, J., Qin, W., Tian, J., Yuan, K., Bai, L., Zhang, Y., Wang, W., Wang, Y., Li, Q. et al. (2009). Dysfunctional connectivity patterns in chronic heroin users: an fMRI study. Neuroscience Letters 460(1):72 – 7.CrossRefGoogle Scholar
  40. Manza, P., Hu, S., Chao, H. H., Zhang, S., Leung, H. C., & Li, C. S. (2016). A dual but asymmetric role of the dorsal anterior cingulate cortex in response inhibition and switching from a non-salient to salient action. Neuroimage, 134, 466 – 74.CrossRefGoogle Scholar
  41. Pelchat, M. L., Johnson, A., Chan, R., Valdez, J., & Ragland, J. D. (2004). Images of desire: food-craving activation during fMRI. Neuroimage, 23(4), 1486–1493.CrossRefGoogle Scholar
  42. Peng, Z., Shi, F., Shi, C., Yang, Q., Chan, R. C., & Shen, D. (2014). Disrupted cortical network as a vulnerability marker for obsessive-compulsive disorder. Brain Structure and Function, 219(5), 1801–1812.CrossRefGoogle Scholar
  43. Pepino, M. Y., Finkbeiner, S., & Mennella, J. A. (2009). Similarities in food cravings and mood states between obese women and women who smoke tobacco. Obesity (Silver Spring), 17(6), 1158–1163.Google Scholar
  44. Petrovich, G. D. (2011). Learning and the motivation to eat: forebrain circuitry. Physiology and Behavior, 104(4), 582–589.CrossRefGoogle Scholar
  45. Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage, 59, 2142–2154.CrossRefGoogle Scholar
  46. Rothemund, Y., Preuschhof, C., Bohner, G., Bauknecht, H. C., Klingebiel, R., Flor, H., & Klapp, B. F. (2007). Differential activation of the dorsal striatum by high-calorie visual food stimuli in obese individuals. Neuroimage, 37(2), 410 – 21.CrossRefGoogle Scholar
  47. Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: uses and interpretations. Neuroimage, 52(3), 1059–1069.CrossRefGoogle Scholar
  48. Sjoerds, Z., Stufflebeam, S. M., Veltman, D. J., Van den Brink, W., Penninx, B. W., & Douw, L. (2017). Loss of brain graph network efficiency in alcohol dependence. Addiction Biology, 22(2), 523–534.CrossRefGoogle Scholar
  49. Stoeckel, L. E., Weller, R. E., Cook, E. R., Twieg, D. B., Knowlton, R. C., & Cox, J. E. (2008). Widespread reward-system activation in obese women in response to pictures of high-calorie foods. Neuroimage, 41(2), 636 – 47.CrossRefGoogle Scholar
  50. Suo, X., Lei, D., Li, K., Chen, F., Li, F., Li, L., Huang, X., Lui, S., & Li, L. Kemp, G. J., et al. (2015). Disrupted brain network topology in pediatric posttraumatic stress disorder: a resting-state fMRI study. Human Brain Mapping, 36(9), 3677–3686.CrossRefGoogle Scholar
  51. Tracy, A. L., Wee, C. J., Hazeltine, G. E., & Carter, R. A. (2015). Characterization of attenuated food motivation in high-fat diet-induced obesity: Critical roles for time on diet and reinforcer familiarity. Physiology and Behavior, 141, 69–77.CrossRefGoogle Scholar
  52. Volkow, N. D., & Fowler, J. S. 2000. Addiction, a disease of compulsion and drive: involvement of the orbitofrontal cortex. Cerebral Cortex, 10(3), 318 – 25.CrossRefGoogle Scholar
  53. Volkow, N. D., Wang, G. J., & Baler, R. D. (2011). Reward, dopamine and the control of food intake: implications for obesity. Trends in Cognitive Sciences, 15(1), 37–46.CrossRefGoogle Scholar
  54. Volkow, N. D., Wang, G. J., Telang, F., Fowler, J. S., Thanos, P. K., Logan, J., Alexoff, D., Ding, Y. S., Wong, C., Ma, Y. and others (2008). Low dopamine striatal D2 receptors are associated with prefrontal metabolism in obese subjects: possible contributing factors. Neuroimage, 42(4), 1537–1543.CrossRefGoogle Scholar
  55. Wang, G. J., Tomasi, D., Backus, W., Wang, R., Telang, F., Geliebter, A., Korner, J., Bauman, A., & Fowler, J. S. Thanos, P. K., et al. (2008). Gastric distention activates satiety circuitry in the human brain. Neuroimage, 39(4), 1824–1831.CrossRefGoogle Scholar
  56. Wang, G. J., Yang, J., Volkow, N. D., Telang, F., Ma, Y., Zhu, W., Wong, C. T., Tomasi, D., Thanos, P. K., & Fowler, J. S. (2006). Gastric stimulation in obese subjects activates the hippocampus and other regions involved in brain reward circuitry. Proceeding of the National Academy Sciences United States of America, 103(42), 15641–15645.CrossRefGoogle Scholar
  57. Wang, J., Zuo, X., Dai, Z., Xia, M., Zhao, Z., Zhao, X., Jia, J., Han, Y., & He, Y. 2013. Disrupted functional brain connectome in individuals at risk for Alzheimer’s disease. Biological Psychiatry, 73(5), 472 – 81.CrossRefGoogle Scholar
  58. Wang, Z., Faith, M., Patterson, F., Tang, k, Kerrin, K., Wileyto, E. P., Detre, J. A., & Lerman, C. (2007). Neural substrates of abstinence-induced cigarette cravings in chronic smokers. Journal of Neurosciences, 27(51), 14035–14040.Google Scholar
  59. Wee, C. Y., Zhao, Z., Yap, P. T., Wu, G., Shi, F., Price, T., Du, Y., Xu, J., Zhou, Y., & Shen, D. (2014). Disrupted brain functional network in internet addiction disorder: a resting-state functional magnetic resonance imaging study. PLoS One, 9(9), e107306.CrossRefGoogle Scholar
  60. Wilson, S. J., Sayette, M. A., & Fiez, J. A. (2012). Quiting-unmotivated and quiting-motivated cigarette smokers exhibit different patterns of cue-elicited brain activation when anticipating an opportunity to smoke. Journal of Abnormal Psychology, 121(1), 198–211.CrossRefGoogle Scholar
  61. Yi, L. Y., Liang, X., Liu, D. M., Sun, B., Ying, S., Yang, D. B., Li, Q. B., Jiang, C. L., & Han, Y. 2015. Disrupted topological organization of resting-state functional brain network in subcortical vascular mild cognitive impairment. CNS Neuroscience and Therapeutics, 21(10), 846 – 54.CrossRefGoogle Scholar
  62. Yuan, K., Qin, W., Liu, J., Guo, Q., Dong, M., Sun, J., Zhang, Y., Liu, P., Wang, W., Wang, Y. et al. (2010). Altered small-world brain functional networks and duration of heroin use in male abstinent heroin-dependent individuals. Neuroscience Letters, 477(1), 37–42.CrossRefGoogle Scholar
  63. Zalesky, A., Fornito, A., & Bullmore, E. T. (2010). Network-based statistic: identifying differences in brain networks. Neuroimage, 53(4), 1197 – 207.CrossRefGoogle Scholar
  64. Zhang, J., Wang, J., Wu, Q., Kuang, W., Huang, X., He, Y., & Gong, Q. (2011). Disrupted brain connectivity networks in drug-naive, first-episode major depressive disorder. Biological Psychiatry, 70(4), 334 – 42.CrossRefGoogle Scholar
  65. Zhang, R., Jiang, G., Tian, J., Qiu, Y., Wen, X., Zalesky, A., Li, M., Ma, X., Wang, J., Li, S. et al. (2016). Abnormal white matter structural networks characterize heroin-dependent individuals: a network analysis. Addiction Biology, 21(3), 667 – 78.CrossRefGoogle Scholar
  66. Zhang, Y., Ji, G., Xu, M., Cai, W., Zhu, Q., Qian, L., Zhang, Y. E., Yuan, K., Liu, J., Li, Q. et al. (2016). Recovery of brain structural abnormalities in morbidly obese patients after bariatric surgery. International Journal of Obesity (London), 40(10), 1558–1565.CrossRefGoogle Scholar
  67. Zhang, Y., Li, M., Wang, R., Bi, Y., Li, Y., Yi, Z., Liu, J., Yu, D., & Yuan, K. 2017. Abnormal brain white matter network in young smokers: a graph theory analysis study. Brain Imaging Behavior.Google Scholar
  68. Zhang, Y., Wang, J., Zhang, G., Zhu, Q., Cai, W., Tian, J., Zhang, Y. E., Miller, J. L., & Wen, X. Ding, M., et al. (2015). The neurobiological drive for overeating implicated in Prader-Willi syndrome. Brain Research, 1620, 72–80.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Center for Brain Imaging, School of Life Science and TechnologyXidian UniversityXi’anChina
  2. 2.Department of Radiology, Tangdu HospitalFourth Military Medical UniversityXi’anChina
  3. 3.Xijing Gastrointestinal HospitalThe Fourth Military Medical UniversityXi’anChina
  4. 4.College of Mechanical and Electronic EngineeringNorthwest A&F UniversityYanglingChina
  5. 5.Department of Psychiatry, Xijing HospitalFourth Military Medical UniversityXi’anChina
  6. 6.Laboratory of NeuroimagingNational Institute on Alcohol Abuse and AlcoholismBethesdaUSA

Personalised recommendations