Advertisement

Dysregulation of resting-state functional connectivity in patients with Cushing’s disease

  • Xin Wang
  • Tao Zhou
  • Peng Wang
  • Li Zhang
  • Shiyu Feng
  • Xianghui Meng
  • Xinguang YuEmail author
  • Yanyang ZhangEmail author
Functional Neuroradiology
  • 17 Downloads

Abstract

Purpose

To explore the anatomical distance-dependent functional connectivity patterns in patients with active phase of Cushing’s disease (CD) and to evaluate the associations between hypercortisol exposure and regional normalized functional connectivity strengths (nFCSs).

Methods

Based on the fMRI data in 32 CD patients and 32 healthy controls (HCs), we computed the nFCSs for each voxel in the brain and further divided them into long-range and short-range nFCSs. General linear models was used to investigate between-group differences in these nFCS metrics and the correlations between the nFCSs and clinical variables.

Results

Compared with HC, CD patients showed dysregulation of the nFCSs mainly in the default mode network. They showed an overall higher nFCS in bilateral parahippocampal cortex mainly owing to the disruption of long-range nFCS and a relatively lower nFCS in bilateral posterior cingulate cortex (PCC), bilateral lateral parietal cortex (LP), and right prefrontal cortex (PFC). In addition, their long-range nFCS was lower in the bilateral anterior cingulate cortex, PCC, and LP; short-range nFCS was lower in the bilateral PFC. Notably, the positive correlation between the nFCSs in their right parahippocampal cortex and serum cortisol levels at 08:00 remained significant after taking the anatomical distance into consideration.

Conclusion

The discrepant functional connectivity patterns found in our study indicated a hypercortisol-associated, distance-dependent disruption of resting-state functional connectivity in patients with active CD. We provide novel insights into the impacts of hypercortisol exposure and the pathophysiologic mechanisms of CD, which may facilitate advances in CD intervention ultimately.

Keywords

Cushing’s disease Resting-state Functional connectivity Default mode network Hypercortisol 

Abbreviations

CD

Cushing’s disease

HC

Healthy control

RSFC

Resting-state functional connectivity

nFCS

Normalized functional connectivity strength

DMN

Default mode network

PCC

Posterior cingulate cortex

LP

Lateral parietal cortex

PFC

Prefrontal cortex

ACC

Anterior cingulate cortex;

Notes

Funding

No funding was received for this study.

Compliance with ethical standards

Conflict of interest

We declare that we have no conflict of interest.

Ethical 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.

Informed consent

Written informed consent was obtained from each patient in the study.

References

  1. 1.
    Tiemensma J, Kokshoorn NE, Biermasz NR, Keijser BJ, Wassenaar MJ, Middelkoop HA, Pereira AM, Romijn JA (2010) Subtle cognitive impairments in patients with long-term cure of Cushing’s disease. J Clin Endocrinol Metab 95(6):2699–2714.  https://doi.org/10.1210/jc.2009-2032 Google Scholar
  2. 2.
    Pivonello R, Simeoli C, De Martino MC, Cozzolino A, De Leo M, Iacuaniello D, Pivonello C, Negri M, Pellecchia MT, Iasevoli F, Colao A (2015) Neuropsychiatric disorders in Cushing’s syndrome. Front Neurosci 9:129.  https://doi.org/10.3389/fnins.2015.00129 Google Scholar
  3. 3.
    Colao A, Cozzolino A, Pivonello R (2012) Quality of life in patients with Cushing’s disease: a modern approach. Clin Endocrinol 76(6):776–777.  https://doi.org/10.1111/j.1365-2265.2012.04344.x Google Scholar
  4. 4.
    van der Werff SJ, Pannekoek JN, Andela CD, Meijer OC, van Buchem MA, Rombouts SA, van der Mast RC, Biermasz NR, Pereira AM, van der Wee NJ (2015) Resting-state functional connectivity in patients with long-term remission of Cushing’s disease. Neuropsychopharmacology 40(8):1888–1898.  https://doi.org/10.1038/npp.2015.38 Google Scholar
  5. 5.
    Andela CD, van der Werff SJ, Pannekoek JN, van den Berg SM, Meijer OC, van Buchem MA, Rombouts SA, van der Mast RC, Romijn JA, Tiemensma J, Biermasz NR, van der Wee NJ, Pereira AM (2013) Smaller grey matter volumes in the anterior cingulate cortex and greater cerebellar volumes in patients with long-term remission of Cushing’s disease: a case-control study. Eur J Endocrinol 169(6):811–819.  https://doi.org/10.1530/EJE-13-0471 Google Scholar
  6. 6.
    van der Werff SJ, Andela CD, Nienke Pannekoek J, Meijer OC, van Buchem MA, Rombouts SA, van der Mast RC, Biermasz NR, Pereira AM, van der Wee NJ (2014) Widespread reductions of white matter integrity in patients with long-term remission of Cushing’s disease. Neuroimage Clin 4:659–667.  https://doi.org/10.1016/j.nicl.2014.01.017 Google Scholar
  7. 7.
    Bas-Hoogendam JM, Andela CD, van der Werff SJ, Pannekoek JN, van Steenbergen H, Meijer OC, van Buchem MA, Rombouts SA, van der Mast RC, Biermasz NR, van der Wee NJ, Pereira AM (2015) Altered neural processing of emotional faces in remitted Cushing’s disease. Psychoneuroendocrinology 59:134–146.  https://doi.org/10.1016/j.psyneuen.2015.05.001 Google Scholar
  8. 8.
    Barkhof F, Haller S, Rombouts SA (2014) Resting-state functional MR imaging: a new window to the brain. Radiology 272(1):29–49.  https://doi.org/10.1148/radiol.14132388 Google Scholar
  9. 9.
    Maheu FS, Mazzone L, Merke DP, Keil MF, Stratakis CA, Pine DS, Ernst M (2008) Altered amygdala and hippocampus function in adolescents with hypercortisolemia: a functional magnetic resonance imaging study of Cushing syndrome. Dev Psychopathol 20(4):1177–1189.  https://doi.org/10.1017/S0954579408000564 Google Scholar
  10. 10.
    Langenecker SA, Weisenbach SL, Giordani B, Briceno EM, Guidotti Breting LM, Schallmo MP, Leon HM, Noll DC, Zubieta JK, Schteingart DE, Starkman MN (2012) Impact of chronic hypercortisolemia on affective processing. Neuropharmacology 62(1):217–225.  https://doi.org/10.1016/j.neuropharm.2011.07.006 Google Scholar
  11. 11.
    Nieman LK, Biller BMK, Findling JW, Newell-Price J, Savage MO, Stewart PM, Montori VM (2008) The diagnosis of Cushing’s syndrome: an endocrine society clinical practice guideline. J Clin Endocrinol Metab 93(5):1526–1540.  https://doi.org/10.1210/jc.2008-0125 Google Scholar
  12. 12.
    He Y, Chen ZJ, Evans AC (2007) Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cereb Cortex 17(10):2407–2419.  https://doi.org/10.1093/cercor/bhl149 Google Scholar
  13. 13.
    Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10(3):186–198.  https://doi.org/10.1038/nrn2575 Google Scholar
  14. 14.
    Wang X, Xia M, Lai Y, Dai Z, Cao Q, Cheng Z, Han X, Yang L, Yuan Y, Zhang Y, Li K, Ma H, Shi C, Hong N, Szeszko P, Yu X, He Y (2014) Disrupted resting-state functional connectivity in minimally treated chronic schizophrenia. Schizophr Res 156(2–3):150–156.  https://doi.org/10.1016/j.schres.2014.03.033 Google Scholar
  15. 15.
    Yan CG, Wang XD, Zuo XN, Zang YF (2016) DPABI: data processing & analysis for (resting-state) brain imaging. Neuroinformatics 14(3):339–351.  https://doi.org/10.1007/s12021-016-9299-4 Google Scholar
  16. 16.
    Ashburner J, Friston KJ (2005) Unified segmentation. NeuroImage 26(3):839–851.  https://doi.org/10.1016/j.neuroimage.2005.02.018 Google Scholar
  17. 17.
    Zhang Y, Mao Z, Feng S, Liu X, Zhang J, Yu X (2018) Monaural-driven functional changes within and beyond the auditory cortical network: evidence from long-term unilateral hearing impairment. Neuroscience 371:296–308.  https://doi.org/10.1016/j.neuroscience.2017.12.015 Google Scholar
  18. 18.
    Zhang Y, Mao Z, Feng S, Wang W, Zhang J, Yu X (2018) Convergent and divergent functional connectivity patterns in patients with long-term left-sided and right-sided deafness. Neurosci Lett 665:74–79.  https://doi.org/10.1016/j.neulet.2017.11.050 Google Scholar
  19. 19.
    Zhang Y, Mao Z, Pan L, Ling Z, Liu X, Zhang J, Yu X (2018) Dysregulation of pain- and emotion-related networks in trigeminal neuralgia. Front Hum Neurosci 12:107.  https://doi.org/10.3389/fnhum.2018.00107 Google Scholar
  20. 20.
    Zalesky A, Solowij N, Yucel M, Lubman DI, Takagi M, Harding IH, Lorenzetti V, Wang R, Searle K, Pantelis C, Seal M (2012) Effect of long-term cannabis use on axonal fibre connectivity. Brain 135 (Pt 7:2245–2255.  https://doi.org/10.1093/brain/aws136 Google Scholar
  21. 21.
    Wang L, Xia M, Li K, Zeng Y, Su Y, Dai W, Zhang Q, Jin Z, Mitchell PB, Yu X, He Y, Si T (2015) The effects of antidepressant treatment on resting-state functional brain networks in patients with major depressive disorder. Hum Brain Mapp 36(2):768–778.  https://doi.org/10.1002/hbm.22663 Google Scholar
  22. 22.
    Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15(1):1–25Google Scholar
  23. 23.
    Eklund A, Nichols TE, Knutsson H (2016) Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci U S A 113(28):7900–7905.  https://doi.org/10.1073/pnas.1602413113 Google Scholar
  24. 24.
    Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL (2001) A default mode of brain function. Proc Natl Acad Sci U S A 98(2):676–682.  https://doi.org/10.1073/pnas.98.2.676 Google Scholar
  25. 25.
    Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 102(27):9673–9678.  https://doi.org/10.1073/pnas.0504136102 Google Scholar
  26. 26.
    Leech R, Sharp DJ (2014) The role of the posterior cingulate cortex in cognition and disease. Brain 137(Pt 1):12–32.  https://doi.org/10.1093/brain/awt162 Google Scholar
  27. 27.
    Khalsa S, Mayhew SD, Chechlacz M, Bagary M, Bagshaw AP (2014) The structural and functional connectivity of the posterior cingulate cortex: comparison between deterministic and probabilistic tractography for the investigation of structure-function relationships. NeuroImage 102(Pt 1):118–127.  https://doi.org/10.1016/j.neuroimage.2013.12.022 Google Scholar
  28. 28.
    van den Heuvel M, Mandl R, Luigjes J, Hulshoff Pol H (2008) Microstructural organization of the cingulum tract and the level of default mode functional connectivity. J Neurosci 28(43):10844–10851.  https://doi.org/10.1523/JNEUROSCI.2964-08.2008 Google Scholar
  29. 29.
    Liang X, Zou Q, He Y, Yang Y (2013) Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain. Proc Natl Acad Sci U S A 110(5):1929–1934.  https://doi.org/10.1073/pnas.1214900110 Google Scholar
  30. 30.
    Sepulcre J, Liu H, Talukdar T, Martincorena I, Yeo BT, Buckner RL (2010) The organization of local and distant functional connectivity in the human brain. PLoS Comput Biol 6(6):e1000808.  https://doi.org/10.1371/journal.pcbi.1000808 Google Scholar
  31. 31.
    Mesulam MM (1998) From sensation to cognition. Brain 121(Pt 6):1013–1052Google Scholar
  32. 32.
    Phillips ML, Drevets WC, Rauch SL, Lane R (2003) Neurobiology of emotion perception I: the neural basis of normal emotion perception. Biol Psychiatry 54(5):504–514Google Scholar
  33. 33.
    Quirk GJ, Beer JS (2006) Prefrontal involvement in the regulation of emotion: convergence of rat and human studies. Curr Opin Neurobiol 16(6):723–727.  https://doi.org/10.1016/j.conb.2006.07.004 Google Scholar
  34. 34.
    Starkman MN, Giordani B, Gebarski SS, Berent S, Schork MA, Schteingart DE (1999) Decrease in cortisol reverses human hippocampal atrophy following treatment of Cushing’s disease. Biol Psychiatry 46(12):1595–1602Google Scholar
  35. 35.
    Starkman MN, Giordani B, Gebarski SS, Schteingart DE (2003) Improvement in learning associated with increase in hippocampal formation volume. Biol Psychiatry 53(3):233–238Google Scholar
  36. 36.
    Bourdeau I, Bard C, Noel B, Leclerc I, Cordeau MP, Belair M, Lesage J, Lafontaine L, Lacroix A (2002) Loss of brain volume in endogenous Cushing’s syndrome and its reversibility after correction of hypercortisolism. J Clin Endocrinol Metab 87(5):1949–1954.  https://doi.org/10.1210/jcem.87.5.8493 Google Scholar
  37. 37.
    Simmons NE, Do HM, Lipper MH, Laws ER Jr (2000) Cerebral atrophy in Cushing’s disease. Surg Neurol 53(1):72–76Google Scholar
  38. 38.
    Campbell S, Marriott M, Nahmias C, MacQueen GM (2004) Lower hippocampal volume in patients suffering from depression: a meta-analysis. Am J Psychiatry 161(4):598–607.  https://doi.org/10.1176/appi.ajp.161.4.598 Google Scholar
  39. 39.
    Colla M, Kronenberg G, Deuschle M, Meichel K, Hagen T, Bohrer M, Heuser I (2007) Hippocampal volume reduction and HPA-system activity in major depression. J Psychiatr Res 41(7):553–560.  https://doi.org/10.1016/j.jpsychires.2006.06.011 Google Scholar
  40. 40.
    Gurvits TV, Shenton ME, Hokama H, Ohta H, Lasko NB, Gilbertson MW, Orr SP, Kikinis R, Jolesz FA, McCarley RW, Pitman RK (1996) Magnetic resonance imaging study of hippocampal volume in chronic, combat-related posttraumatic stress disorder. Biol Psychiatry 40(11):1091–1099.  https://doi.org/10.1016/s0006-3223(96)00229-6 Google Scholar
  41. 41.
    Kitayama N, Vaccarino V, Kutner M, Weiss P, Bremner JD (2005) Magnetic resonance imaging (MRI) measurement of hippocampal volume in posttraumatic stress disorder: a meta-analysis. J Affect Disord 88(1):79–86.  https://doi.org/10.1016/j.jad.2005.05.014 Google Scholar
  42. 42.
    Cole J, Costafreda SG, McGuffin P, Fu CH (2011) Hippocampal atrophy in first episode depression: a meta-analysis of magnetic resonance imaging studies. J Affect Disord 134(1–3):483–487.  https://doi.org/10.1016/j.jad.2011.05.057 Google Scholar
  43. 43.
    Admon R, Leykin D, Lubin G, Engert V, Andrews J, Pruessner J, Hendler T (2013) Stress-induced reduction in hippocampal volume and connectivity with the ventromedial prefrontal cortex are related to maladaptive responses to stressful military service. Hum Brain Mapp 34(11):2808–2816.  https://doi.org/10.1002/hbm.22100 Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xin Wang
    • 1
    • 2
  • Tao Zhou
    • 2
  • Peng Wang
    • 2
  • Li Zhang
    • 3
  • Shiyu Feng
    • 2
  • Xianghui Meng
    • 2
  • Xinguang Yu
    • 1
    • 2
    Email author
  • Yanyang Zhang
    • 2
    Email author
  1. 1.School of MedicineNankai UniversityTianjinChina
  2. 2.Department of NeurosurgeryThe First Medical Center of Chinese PLA General HospitalBeijingChina
  3. 3.Department of RadiologyThe First Medical Center of Chinese PLA General HospitalBeijingChina

Personalised recommendations