Potential Alterations of Functional Connectivity Analysis in the Patients with Chronic Prostatitis/Chronic Pelvic Pain Syndrome

Shengyang Ge, Qingfeng Hu, Yijun Guo, Ke Xu, Guowei Xia, Chuanyu Sun, Shengyang Ge, Qingfeng Hu, Yijun Guo, Ke Xu, Guowei Xia, Chuanyu Sun

Abstract

Background: Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is one of the most common diseases in urology, but its pathogenesis remains unclear. As a kind of chronic pain which the patients suffered for more than 3 months, we investigated the influence on patients' brain functional connectivity in resting state.

Methods: We recruited a cohort of 18 right-handed male patients with CP/CPPS and 21 healthy male right-handed age-matched controls. Their resting-state fMRI data and structural MRI data were preprocessed and processed by RESTPlus V1.22. To assess the integrity of the default mode network (DMN), we utilized the voxel-wised analysis that we set medial prefrontal cortex (mPFC) and posterior cingulate gyrus (PCC) as seed points to compare the global functional connectivity (FC) strength.

Results: Compared with healthy control, the FC strength between left mPFC and posterior DMN decreased in the group of CP/CPPS (P < 0.05, GFR correction, voxel P < 0.01, cluster P < 0.05), and the FC strength between the left anterior cerebellar lobe and posterior DMN increased (P < 0.05, GFR correction, voxel P < 0.01, cluster P < 0.05). In the patient group, there was a positive correlation between the increased FC strength and the score of the Hospital Anxiety and Depression Scale (HADS) anxiety subscale (r = 0.5509, P = 0.0178) in the left anterior cerebellar lobe, a negative correlation between the decreased FC strength and the score of the National Institutes of Health Chronic Prostatitis Symptom Index (r = -0.6281, P = 0.0053) in the area of left mPFC, and a negative correlation between the decreased FC strength and the score of HADS anxiety subscale (r = -0.5252, P = 0.0252).

Conclusion: Patients with CP/CPPS had alterations in brain function, which consisted of the default mode network's compromised integrity. These alterations might play a crucial role in the pathogenesis and development of CP/CPPS.

Conflict of interest statement

There is no conflict of interest regarding the publication of this paper.

Copyright © 2021 Shengyang Ge et al.

Figures

Figure 1
Figure 1
Study design flow chart. We initially recruited a cohort of health control (22 persons) and patients (22 persons). However, 1 person in health control and 4 persons in patient cohort were excluded. Their detailed reasons were demonstrated in the flow chart.
Figure 2
Figure 2
The differentiated brain regions with abnormal zFC values: (a) sagittal view; (b) axial view. The red region was positively activated, and the blue region was negatively activated (P < 0.05, voxel ≥ 5, GFR correction, voxel P < 0.01, cluster P < 0.05). Compared to the healthy control group, the patient cohort of CP/CPPS had differentiated brain regions with abnormal zFC values when we set the PCC as the seed point.
Figure 3
Figure 3
The differentiated brain regions with abnormal zFC values and their correlation with HADS anxiety subscale scores and NIH-CPSI scores. (a) Negatively activated clusters. (b) The correlation between the HADS (anxiety) score and the degree of FC in area of negatively activated clusters. (c) The correlation between the CPSI score and the degree of FC in area of negatively activated clusters. (d) Positively activated clusters. (e) The correlation between the HADS (anxiety) score and the degree of FC in area of positively activated clusters.

References

    1. Schneider H., Ludwig M., Hossain H. M., Diemer T., Weidner W. The 2001 Giessen Cohort Study on patients with prostatitis syndrome--an evaluation of inflammatory status and search for microorganisms 10 years after a first analysis. Andrologia. 2003;35(5):258–262.
    1. Krieger J. N., Nyberg L., Jr., Nickel J. C. NIH consensus definition and classification of prostatitis. JAMA. 1999;282(3):236–237. doi: 10.1001/jama.282.3.236.
    1. Passavanti M. B., Pota V., Sansone P., Aurilio C., De Nardis L., Pace M. C. Chronic pelvic pain: assessment, evaluation, and objectivation. Pain Research and Treatment. 2017;2017:15. doi: 10.1155/2017/9472925.9472925
    1. Pontari M. A., Ruggieri M. R. Mechanisms in prostatitis/chronic pelvic pain syndrome. The Journal of Urology. 2008;179(5 Suppl):S61–S67. doi: 10.1016/j.juro.2008.03.139.
    1. Kwon J. K., Chang I. H. Pain, catastrophizing, and depression in chronic prostatitis/chronic pelvic pain syndrome. International Neurourology Journal. 2013;17(2):48–58. doi: 10.5213/inj.2013.17.2.48.
    1. Loeser J. D., Melzack R. Pain: an overview. Lancet. 1999;353(9164):1607–1609. doi: 10.1016/S0140-6736(99)01311-2.
    1. Davis K. D., Moayedi M. Central mechanisms of pain revealed through functional and structural MRI. Journal of Neuroimmune Pharmacology. 2013;8(3):518–534. doi: 10.1007/s11481-012-9386-8.
    1. Bach J. P., Lupke M., Dziallas P., et al. Auditory functional magnetic resonance imaging in dogs--normalization and group analysis and the processing of pitch in the canine auditory pathways. BMC Veterinary Research. 2016;12(1):p. 32. doi: 10.1186/s12917-016-0660-5.
    1. Chen Y. C., Xia W., Luo B., et al. Frequency-specific alternations in the amplitude of low-frequency fluctuations in chronic tinnitus. Frontiers in Neural Circuits. 2015;9:p. 67. doi: 10.3389/fncir.2015.00067.
    1. Kutch J. J., Yani M. S., Asavasopon S., et al. Altered resting state neuromotor connectivity in men with chronic prostatitis/chronic pelvic pain syndrome: a Mapp: research network neuroimaging study. NeuroImage: Clinical. 2015;8:493–502. doi: 10.1016/j.nicl.2015.05.013.
    1. Raichle M. E., Snyder A. Z. A default mode of brain function: a brief history of an evolving idea. NeuroImage. 2007;37(4):1083–1090. doi: 10.1016/j.neuroimage.2007.02.041.
    1. Andrews-Hanna J. R., Reidler J. S., Sepulcre J., Poulin R., Buckner R. L. Functional-anatomic fractionation of the brain’s default network. Neuron. 2010;65(4):550–562. doi: 10.1016/j.neuron.2010.02.005.
    1. Litwin M. S., McNaughton-Collins M., FJ F., Jr., et al. The National Institutes of Health chronic prostatitis symptom index: development and validation of a new outcome MEASURE. The Journal of Urology. 1999;162(2):369–375. doi: 10.1016/S0022-5347(05)68562-X.
    1. Snaith R. P. The hospital anxiety and depression scale. Health and Quality of Life Outcomes. 2003;1(1):p. 29. doi: 10.1186/1477-7525-1-29.
    1. Andrade F. A., Pereira L. V., Sousa F. A. Pain measurement in the elderly: a review. Revista Latino-Americana de Enfermagem. 2006;14(2):271–276. doi: 10.1590/S0104-11692006000200018.
    1. Alshelh Z., Marciszewski K. K., Akhter R., et al. Disruption of default mode network dynamics in acute and chronic pain states. NeuroImage: Clinical. 2018;17:222–231. doi: 10.1016/j.nicl.2017.10.019.
    1. Mulders P. C., van Eijndhoven P. F., Schene A. H., Beckmann C. F., Tendolkar I. Resting-state functional connectivity in major depressive disorder: a review. Neuroscience and Biobehavioral Reviews. 2015;56:330–344. doi: 10.1016/j.neubiorev.2015.07.014.
    1. Baliki M. N., Geha P. Y., Apkarian A. V., Chialvo D. R. Beyond feeling: chronic pain hurts the brain, disrupting the default-mode network dynamics. Journal of Neuroscience. 2008;28(6):1398–1403. doi: 10.1523/JNEUROSCI.4123-07.2008.
    1. Baliki M. N., Mansour A. R., Baria A. T., Apkarian A. V. Functional reorganization of the default mode network across chronic pain conditions. PLoS One. 2014;9(9, article e106133) doi: 10.1371/journal.pone.0106133.
    1. Hagmann P., Cammoun L., Gigandet X., et al. Mapping the structural core of human cerebral cortex. PLoS Biology. 2008;6(7, article e159) doi: 10.1371/journal.pbio.0060159.
    1. Greicius M. D., Supekar K., Menon V., Dougherty R. F. Resting-state functional connectivity reflects structural connectivity in the default mode network. Cerebral Cortex. 2009;19(1):72–78. doi: 10.1093/cercor/bhn059.
    1. Leech R., Sharp D. J. The role of the posterior cingulate cortex in cognition and disease. Brain. 2014;137(1):12–32. doi: 10.1093/brain/awt162.
    1. Buckner R. L., Andrews-Hanna J. R., Schacter D. L. The brain’s default network. Annals of the New York Academy of Sciences. 2008;1124(1):1–38. doi: 10.1196/annals.1440.011.
    1. Zhang D., Raichle M. E. Disease and the brain’s dark energy. Nature Reviews Neurology. 2010;6(1):15–28. doi: 10.1038/nrneurol.2009.198.
    1. Kucyi A., Moayedi M., Weissman-Fogel I., et al. Enhanced medial prefrontal-default mode network functional connectivity in chronic pain and its association with pain rumination. Journal of Neuroscience. 2014;34(11):3969–3975. doi: 10.1523/JNEUROSCI.5055-13.2014.
    1. Hilton L., Hempel S., Ewing B. A., et al. Mindfulness meditation for chronic pain: systematic review and meta-analysis. Annals of Behavioral Medicine. 2017;51(2):199–213. doi: 10.1007/s12160-016-9844-2.
    1. Radzicki D., Pollema-Mays S. L., Sanz-Clemente A., Martina M. Loss of M1 receptor dependent cholinergic excitation contributes to mPFC deactivation in neuropathic pain. Journal of Neuroscience. 2017;37(9):2292–2304. doi: 10.1523/JNEUROSCI.1553-16.2017.
    1. Ong W. Y., Stohler C. S., Herr D. R. Role of the prefrontal cortex in pain processing. Molecular Neurobiology. 2019;56(2):1137–1166. doi: 10.1007/s12035-018-1130-9.
    1. Kunz M., Mylius V., Schepelmann K., Lautenbacher S. Loss in executive functioning best explains changes in pain responsiveness in patients with dementia-related cognitive decline. Behavioural Neurology. 2015;2015:7. doi: 10.1155/2015/878157.878157
    1. Du Y., Pearlson G. D., Yu Q., et al. Interaction among subsystems within default mode network diminished in schizophrenia patients: a dynamic connectivity approach. Schizophrenia Research. 2016;170(1):55–65. doi: 10.1016/j.schres.2015.11.021.
    1. Elsenbruch S., Wolf O. T. Could stress contribute to pain-related fear in chronic pain? Frontiers in Behavioral Neuroscience. 2015;9:p. 340. doi: 10.3389/fnbeh.2015.00340.
    1. Vlaeyen J. W., Linton S. J. Fear-avoidance and its consequences in chronic musculoskeletal pain: a state of the art. Pain. 2000;85(3):317–332. doi: 10.1016/S0304-3959(99)00242-0.
    1. Tseng M. T., Kong Y., Eippert F., Tracey I. Determining the neural substrate for encoding a memory of human pain and the influence of anxiety. Journal of Neuroscience. 2017;37(49):11806–11817. doi: 10.1523/JNEUROSCI.0750-17.2017.
    1. Stoodley C. J., Schmahmann J. D. Evidence for topographic organization in the cerebellum of motor control versus cognitive and affective processing. Cortex. 2010;46(7):831–844. doi: 10.1016/j.cortex.2009.11.008.
    1. Turk D. C., Wilson H. D. Fear of pain as a prognostic factor in chronic pain: conceptual models, assessment, and treatment implications. Current Pain and Headache Reports. 2010;14(2):88–95. doi: 10.1007/s11916-010-0094-x.
    1. Baumann O., Borra R. J., Bower J. M., et al. Consensus paper: the role of the cerebellum in perceptual processes. Cerebellum. 2015;14(2):197–220. doi: 10.1007/s12311-014-0627-7.
    1. Bocci T., De Carolis G., Ferrucci R., et al. Cerebellar transcranial direct current stimulation (Ctdcs) ameliorates phantom limb pain and non-painful phantom limb sensations. Cerebellum. 2019;18(3):527–535. doi: 10.1007/s12311-019-01020-w.
    1. Schmahmann J. D., Pandya D. N. Anatomic organization of the basilar pontine projections from prefrontal cortices in rhesus monkey. Journal of Neuroscience. 1997;17(1):438–458. doi: 10.1523/JNEUROSCI.17-01-00438.1997.
    1. Welman F. H. S. M., Smit A. E., Jongen J. L. M., Tibboel D., van der Geest J. N., Holstege J. C. Pain experience is somatotopically organized and overlaps with pain anticipation in the human cerebellum. Cerebellum. 2018;17(4):447–460. doi: 10.1007/s12311-018-0930-9.
    1. Fields H. L. Pain modulation: expectation, opioid analgesia and virtual pain. Progress in Brain Research. 2000;122:245–253. doi: 10.1016/S0079-6123(08)62143-3.
    1. Borsook D., Moulton E. A., Tully S., Schmahmann J. D., Becerra L. Human cerebellar responses to brush and heat stimuli in healthy and neuropathic pain subjects. Cerebellum. 2008;7(3):252–272. doi: 10.1007/s12311-008-0011-6.
    1. Moulton E. A., Schmahmann J. D., Becerra L., Borsook D. The cerebellum and pain: passive integrator or active participator? Brain Research Reviews. 2010;65(1):14–27. doi: 10.1016/j.brainresrev.2010.05.005.
    1. Nakamura Y., Nojiri K., Yoshihara H., et al. Significant differences of brain blood flow in patients with chronic low back pain and acute low back pain detected by brain SPECT. Journal of Orthopaedic Science. 2014;19(3):384–389. doi: 10.1007/s00776-014-0534-2.
    1. Liu H.-Y., Lee P.-L., Chou K.-H., et al. The cerebellum is associated with 2-year prognosis in patients with high-frequency migraine. Journal of Headache and Pain. 2020;21(1):p. 29. doi: 10.1186/s10194-020-01096-4.
    1. Salomons T. V., Moayedi M., Erpelding N., Davis K. D. A brief cognitive-behavioural intervention for pain reduces secondary hyperalgesia. Pain. 2014;155(8):1446–1452. doi: 10.1016/j.pain.2014.02.012.
    1. Yoshino A., Okamoto Y., Okada G., et al. Changes in resting-state brain networks after cognitive-behavioral therapy for chronic pain. Psychological Medicine. 2018;48(7):1148–1156. doi: 10.1017/S0033291717002598.
    1. Greenwald J. D., Shafritz K. M. An integrative neuroscience framework for the treatment of chronic pain: from cellular alterations to behavior. Frontiers in Integrative Neuroscience. 2018;12:p. 18. doi: 10.3389/fnint.2018.00018.
    1. Seminowicz D. A., Shpaner M., Keaser M. L., et al. Cognitive-behavioral therapy increases prefrontal cortex gray matter in patients with chronic pain. The Journal of Pain. 2013;14(12):1573–1584. doi: 10.1016/j.jpain.2013.07.020.
    1. Kabat-Zinn J., Lipworth L., Burney R. The clinical use of mindfulness meditation for the self-regulation of chronic pain. Journal of Behavioral Medicine. 1985;8(2):163–190. doi: 10.1007/BF00845519.
    1. Yang H., Long X. Y., Yang Y., et al. Amplitude of low frequency fluctuation within visual areas revealed by resting-state functional MRI. NeuroImage. 2007;36(1):144–152. doi: 10.1016/j.neuroimage.2007.01.054.

Source: PubMed

Sponsorer og samarbeidspartnere

Medisinsk tilstand

Legemiddelintervensjoner

3
Abonnere