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Gray Matter Atrophy in the Cortico-Striatal-Thalamic Network and Sensorimotor Network in Relapsing–Remitting and Primary Progressive Multiple Sclerosis

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A Correction to this article was published on 08 April 2021

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Abstract

Gray matter atrophy in multiple sclerosis (MS) is thought to be associated with disability and cognitive impairment, but previous studies have sometimes had discordant results, and the atrophy patterns of relapsing–remitting multiple sclerosis (RRMS) and primary progressive multiple sclerosis (PPMS) remain to be clarified. We conducted a meta-analysis using anisotropic effect-size-based algorithms (AES-SDM) to identify consistent findings from whole-brain voxel-based morphometry (VBM) studies of gray matter volume (GMV) in 924 RRMS patients and 204 PPMS patients. This study is registered with PROSPERO (number CRD42019121319). Compared with healthy controls, RRMS and PPMS patients showed gray matter atrophy in the cortico-striatal-thalamic network, sensorimotor network, and bilateral insula. RRMS patients had a larger GMV in the left insula, cerebellum, right precentral gyrus, and bilateral putamen as well as a smaller GMV in the bilateral cingulate, caudate nucleus, right thalamus, superior temporal gyrus and left postcentral gyrus than PPMS patients. The disease duration, Expanded Disability Status Scale score, Paced Auditory Serial Addition Test z-score, and T2-weighted lesion load were associated with specific gray matter regions in RRMS or PPMS. Alterations in the cortico-striatal-thalamic networks, sensorimotor network, and insula may be involved in the common pathogenesis of RRMS and PPMS. The deficits in the cingulate gyrus and caudate nucleus are more apparent in RRMS than in PPMS. The more severe cerebellum atrophy in PPMS may be a brain feature associated with its neurological manifestations. These imaging biomarkers provide morphological evidence for the pathophysiology of MS and should be verified in future research.

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References

  • Agosta, F., Caso, F., Stankovic, I., Inuggi, A., Petrovic, I., Svetel, M., et al. (2014). Cortico-striatal-thalamic network functional connectivity in hemiparkinsonism. Neurobiology of Aging, 35(11), 2592–2602.

    Article  Google Scholar 

  • Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry–the methods. NeuroImage, 11(6 Pt 1), 805–821. https://doi.org/10.1006/nimg.2000.0582.

    Article  CAS  PubMed  Google Scholar 

  • Audoin, B., Davies, G. R., Finisku, L., Chard, D. T., Thompson, A. J., & Miller, D. H. (2006). Localization of grey matter atrophy in early RRMS : A longitudinal study. Journal of Neurology, 253(11), 1495–1501. https://doi.org/10.1007/s00415-006-0264-2.

    Article  PubMed  Google Scholar 

  • Bakshi, R., Benedict, R. H., Bermel, R. A., & Jacobs, L. (2001). Regional brain atrophy is associated with physical disability in multiple sclerosis: semiquantitative magnetic resonance imaging and relationship to clinical findings. Journal of Neuroimaging, 11(2), 129–136.

    Article  CAS  Google Scholar 

  • Baltruschat, S. A., Ventura-Campos, N., Cruz-Gomez, A. J., Belenguer, A., & Forn, C. (2015). Gray matter atrophy is associated with functional connectivity reorganization during the Paced Auditory Serial Addition Test (PASAT) execution in Multiple Sclerosis (MS). Journal of Neuroradiology. Journal de Neuroradiologie, 42(3), 141–149. https://doi.org/10.1016/j.neurad.2015.02.006.

    Article  PubMed  Google Scholar 

  • Benedict, R. H., Bakshi, R., Simon, J. H., Priore, R., Miller, C., & Munschauer, F. (2002). Frontal cortex atrophy predicts cognitive impairment in multiple sclerosis. The Journal of Neuropsychiatry and Clinical Neurosciences, 14(1), 44–51.

    Article  Google Scholar 

  • Benedict, R. H., & Zivadinov, R. (2011). Risk factors for and management of cognitive dysfunction in multiple sclerosis. Nature Reviews Neurology, 7(6), 332–342. https://doi.org/10.1038/nrneurol.2011.61.

    Article  PubMed  Google Scholar 

  • Bermel, R. A., & Bakshi, R. (2006). The measurement and clinical relevance of brain atrophy in multiple sclerosis. The Lancet Neurology, 5(2), 158–170.

    Article  Google Scholar 

  • Bermel, R. A., Innus, M. D., Tjoa, C. W., & Bakshi, R. (2003). Selective caudate atrophy in multiple sclerosis: a 3D MRI parcellation study. NeuroReport, 14(3), 335–339.

    Article  Google Scholar 

  • Bisecco, A., Stamenova, S., Caiazzo, G., d’Ambrosio, A., Sacco, R., Docimo, R., et al. (2018). Attention and processing speed performance in multiple sclerosis is mostly related to thalamic volume. Brain Imaging and Behavior, 12(1), 20–28. https://doi.org/10.1007/s11682-016-9667-6.

    Article  PubMed  Google Scholar 

  • Bodini, B., Khaleeli, Z., Cercignani, M., Miller, D. H., Thompson, A. J., & Ciccarelli, O. (2009). Exploring the relationship between white matter and gray matter damage in early primary progressive multiple sclerosis: an in vivo study with TBSS and VBM. Human Brain Mapping, 30(9), 2852–2861.

    Article  Google Scholar 

  • Borenstein, M., Higgins, J. P., Hedges, L. V., & Rothstein, H. R. (2017). Basics of meta-analysis: I2 is not an absolute measure of heterogeneity. Research synthesis methods, 8(1), 5–18.

    PubMed  Google Scholar 

  • Calabrese, M., Rinaldi, F., Grossi, P., & Gallo, P. (2011). Cortical pathology and cognitive impairment in multiple sclerosis. Expert Review of Neurotherapeutics, 11(3), 425–432. https://doi.org/10.1586/ern.10.155.

    Article  PubMed  Google Scholar 

  • Calabrese, M., Rinaldi, F., Grossi, P., Mattisi, I., Bernardi, V., Favaretto, A., et al. (2010). Basal ganglia and frontal/parietal cortical atrophy is associated with fatigue in relapsing—remitting multiple sclerosis. Multiple Sclerosis Journal, 16(10), 1220–1228.

    Article  Google Scholar 

  • Cavanna, A. E., & Trimble, M. R. (2006). The precuneus: a review of its functional anatomy and behavioural correlates. Brain, 129(3), 564–583.

    Article  Google Scholar 

  • Ceccarelli, A., Rocca, M. A., Pagani, E., Ghezzi, A., Capra, R., Falini, A., et al. (2008). The topographical distribution of tissue injury in benign MS: a 3T multiparametric MRI study. NeuroImage, 39(4), 1499–1509. https://doi.org/10.1016/j.neuroimage.2007.11.002.

    Article  PubMed  Google Scholar 

  • Ceccarelli, A., Rocca, M. A., Valsasina, P., Rodegher, M., Pagani, E., Falini, A., et al. (2009). A multiparametric evaluation of regional brain damage in patients with primary progressive multiple sclerosis. Human Brain Mapping, 30(9), 3009–3019. https://doi.org/10.1002/hbm.20725.

    Article  PubMed  PubMed Central  Google Scholar 

  • Chen, G., Zhou, B., Zhu, H., Kuang, W., Bi, F., Ai, H., et al. (2018). White matter volume loss in amyotrophic lateral sclerosis: A meta-analysis of voxel-based morphometry studies. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 83, 110–117. https://doi.org/10.1016/j.pnpbp.2018.01.007.

    Article  PubMed  Google Scholar 

  • Compston, A., & Coles, A. (2008). Multiple sclerosis. Lancet, 372(9648), 1502–1517. https://doi.org/10.1016/s0140-6736(08)61620-7.

    Article  CAS  PubMed  Google Scholar 

  • Czekóová, K., Shaw, D. J., Saxunová, K., Dufek, M., Mareček, R., Vaníček, J., et al. (2019). Impaired self-other distinction and subcortical grey-matter alterations characterise socio-cognitive disturbances in multiple sclerosis. Frontiers in Neurology, 10, 525.

    Article  Google Scholar 

  • Dalton, C. M., Chard, D. T., Davies, G. R., Miszkiel, K. A., Altmann, D. R., Fernando, K., et al. (2004). Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain, 127(5), 1101–1107.

    Article  Google Scholar 

  • Di Filippo, M., Portaccio, E., Mancini, A., & Calabresi, P. (2018). Multiple sclerosis and cognition: synaptic failure and network dysfunction. Nature Reviews Neuroscience, 19(10), 599–609.

    Article  Google Scholar 

  • Doche, E., Lecocq, A., Maarouf, A., Duhamel, G., Soulier, E., Confort-Gouny, S., et al. (2017). Hypoperfusion of the thalamus is associated with disability in relapsing remitting multiple sclerosis. Journal of Neuroradiology. Journal de Neuroradiologie, 44(2), 158–164. https://doi.org/10.1016/j.neurad.2016.10.001.

    Article  PubMed  Google Scholar 

  • Donadieu, M., Le Fur, Y., Lecocq, A., Maudsley, A. A., Gherib, S., Soulier, E., et al. (2016). Metabolic voxel-based analysis of the complete human brain using fast 3D-MRSI: Proof of concept in multiple sclerosis. Journal of Magnetic Resonance Imaging, 44(2), 411–419. https://doi.org/10.1002/jmri.25139.

    Article  PubMed  Google Scholar 

  • Duan, Y., Liu, Y., Liang, P., Jia, X., Yu, C., Qin, W., et al. (2012). Comparison of grey matter atrophy between patients with neuromyelitis optica and multiple sclerosis: a voxel-based morphometry study. European Journal of Radiology, 81(2), e110-114. https://doi.org/10.1016/j.ejrad.2011.01.065.

    Article  PubMed  Google Scholar 

  • Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629–634.

    Article  CAS  Google Scholar 

  • Ehling, R., Amprosi, M., Kremmel, B., Bsteh, G., Eberharter, K., Zehentner, M., et al. (2019). Second language learning induces grey matter volume increase in people with multiple sclerosis. PLoS One, 14(12).

  • Ernst, A., Noblet, V., Gounot, D., Blanc, F., de Seze, J., & Manning, L. (2015). Neural correlates of episodic future thinking impairment in multiple sclerosis patients. Journal of Clinical and Experimental Neuropsychology, 37(10), 1107–1123. https://doi.org/10.1080/13803395.2015.1080228.

    Article  PubMed  Google Scholar 

  • Eshaghi, A., Bodini, B., Ridgway, G. R., Garcia-Lorenzo, D., Tozer, D. J., Sahraian, M. A., et al. (2014). Temporal and spatial evolution of grey matter atrophy in primary progressive multiple sclerosis. NeuroImage, 86, 257–264. https://doi.org/10.1016/j.neuroimage.2013.09.059.

    Article  PubMed  Google Scholar 

  • Eshaghi, A., Prados, F., Brownlee, W. J., Altmann, D. R., Tur, C., Cardoso, M. J., et al. (2018). Deep gray matter volume loss drives disability worsening in multiple sclerosis. Annals of Neurology, 83(2), 210–222.

    Article  CAS  Google Scholar 

  • Fan, J., Zhong, M., Gan, J., Liu, W., Niu, C., Liao, H., et al. (2017). Spontaneous neural activity in the right superior temporal gyrus and left middle temporal gyrus is associated with insight level in obsessive-compulsive disorder. Journal of Affective Disorders, 207, 203–211. https://doi.org/10.1016/j.jad.2016.08.027.

    Article  PubMed  Google Scholar 

  • Feigin, V. L., Abajobir, A. A., Abate, K. H., Abd-Allah, F., Abdulle, A. M., Abera, S. F., et al. (2017). Global, regional, and national burden of neurological disorders during 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet Neurology, 16(11), 877–897.

    Article  Google Scholar 

  • Filippi, M., Bar-Or, A., Piehl, F., Preziosa, P., Solari, A., Vukusic, S., et al. (2018). Multiple sclerosis. Nature Reviews Disease Primers, 4(1), 43. https://doi.org/10.1038/s41572-018-0041-4.

    Article  PubMed  Google Scholar 

  • Friend, K. B., Rabin, B. M., Groninger, L., Deluty, R. H., Bever, C., & Grattan, L. (1999). Language functions in patients with multiple sclerosis. The Clinical Neuropsychologist, 13(1), 78–94.

    Article  CAS  Google Scholar 

  • Geisseler, O., Pflugshaupt, T., Bezzola, L., Reuter, K., Weller, D., Schuknecht, B., et al. (2016). Cortical thinning in the anterior cingulate cortex predicts multiple sclerosis patients’ fluency performance in a lateralised manner. Neuroimage Clin, 10, 89–95. https://doi.org/10.1016/j.nicl.2015.11.008.

    Article  PubMed  Google Scholar 

  • Geurts, J. J., Calabrese, M., Fisher, E., & Rudick, R. A. (2012). Measurement and clinical effect of grey matter pathology in multiple sclerosis. The Lancet Neurology, 11(12), 1082–1092.

    Article  Google Scholar 

  • Ghasemi, N., Razavi, S., & Nikzad, E. (2017). Multiple sclerosis: pathogenesis, symptoms, diagnoses and cell-based therapy. Cell Journal (Yakhteh), 19(1), 1.

    Google Scholar 

  • Han, X. M., Tian, H. J., Han, Z., Zhang, C., Liu, Y., Gu, J. B., et al. (2017). Correlation between white matter damage and gray matter lesions in multiple sclerosis patients. Neural Regeneration Research, 12(5), 787–794. https://doi.org/10.4103/1673-5374.206650.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hart, H., Radua, J., Nakao, T., Mataix-Cols, D., & Rubia, K. (2013). Meta-analysis of functional magnetic resonance imaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-specific, stimulant medication, and age effects. JAMA Psychiatry, 70(2), 185–198.

    Article  Google Scholar 

  • Hemmer, B., Kerschensteiner, M., & Korn, T. (2015). Role of the innate and adaptive immune responses in the course of multiple sclerosis. Lancet Neurology, 14(4), 406–419. https://doi.org/10.1016/s1474-4422(14)70305-9.

    Article  CAS  PubMed  Google Scholar 

  • Kato, H., & Izumiyama, M. (2015). Impaired motor control due to proprioceptive sensory loss in a patient with cerebral infarction localized to the postcentral gyrus. Journal of Rehabilitation Medicine, 47(2), 187–190. https://doi.org/10.2340/16501977-1900.

    Article  PubMed  Google Scholar 

  • Khaleeli, Z., Cercignani, M., Audoin, B., Ciccarelli, O., Miller, D. H., & Thompson, A. J. (2007). Localized grey matter damage in early primary progressive multiple sclerosis contributes to disability. NeuroImage, 37(1), 253–261.

    Article  CAS  Google Scholar 

  • Kira, J.-I., Tobimatsu, S., Goto, I., & Hasuo, K. (1993). Primary progressive versus relapsing remitting multiple sclerosis in Japanese patients: a combined clinical, magnetic resonance imaging and multimodality evoked potential study. Journal of the Neurological Sciences, 117(1–2), 179–185.

    Article  CAS  Google Scholar 

  • Lansley, J., Mataix-Cols, D., Grau, M., Radua, J., & Sastre-Garriga, J. (2013). Localized grey matter atrophy in multiple sclerosis: a meta-analysis of voxel-based morphometry studies and associations with functional disability. Neuroscience and Biobehavioral Reviews, 37(5), 819–830. https://doi.org/10.1016/j.neubiorev.2013.03.006.

    Article  CAS  PubMed  Google Scholar 

  • Liu, Y., Liang, P., Duan, Y., Jia, X., Yu, C., Zhang, M., et al. (2011). Brain plasticity in relapsing–remitting multiple sclerosis: Evidence from resting-state fMRI. Journal of the Neurological Sciences, 304(1–2), 127–131.

    Article  Google Scholar 

  • MacKenzie-Graham, A., Kurth, F., Itoh, Y., Wang, H.-J., Montag, M. J., Elashoff, R., et al. (2016). Disability-specific atlases of gray matter loss in relapsing-remitting multiple sclerosis. JAMA Neurology, 73(8), 944–953.

    Article  Google Scholar 

  • Mahad, D. H., Trapp, B. D., & Lassmann, H. (2015). Pathological mechanisms in progressive multiple sclerosis. The Lancet Neurology, 14(2), 183–193.

    Article  CAS  Google Scholar 

  • Mainero, C., Caramia, F., Pozzilli, C., Pisani, A., Pestalozza, I., Borriello, G., et al. (2004). fMRI evidence of brain reorganization during attention and memory tasks in multiple sclerosis. NeuroImage, 21(3), 858–867.

    Article  Google Scholar 

  • Mallik, S., Muhlert, N., Samson, R. S., Sethi, V., Wheeler-Kingshott, C. A., Miller, D. H., et al. (2015). Regional patterns of grey matter atrophy and magnetisation transfer ratio abnormalities in multiple sclerosis clinical subgroups: a voxel-based analysis study. Multiple Sclerosis, 21(4), 423–432. https://doi.org/10.1177/1352458514546513.

    Article  PubMed  Google Scholar 

  • Mesaros, S., Rocca, M. A., Absinta, M., Ghezzi, A., Milani, N., Moiola, L., et al. (2008). Evidence of thalamic gray matter loss in pediatric multiple sclerosis. Neurology, 70(13 Pt 2), 1107–1112. https://doi.org/10.1212/01.wnl.0000291010.54692.85.

    Article  CAS  PubMed  Google Scholar 

  • Meyer-Moock, S., Feng, Y. S., Maeurer, M., Dippel, F. W., & Kohlmann, T. (2014). Systematic literature review and validity evaluation of the Expanded Disability Status Scale (EDSS) and the Multiple Sclerosis Functional Composite (MSFC) in patients with multiple sclerosis. BMC Neurology, 14, 58. https://doi.org/10.1186/1471-2377-14-58.

    Article  PubMed  PubMed Central  Google Scholar 

  • Migliore, S., Ghazaryan, A., Simonelli, I., Pasqualetti, P., Landi, D., Palmieri, M. G., et al. (2016). Validity of the minimal assessment of cognitive function in multiple sclerosis (MACFIMS) in the Italian population. Neurological Sciences, 37(8), 1261–1270. https://doi.org/10.1007/s10072-016-2578-x.

    Article  PubMed  Google Scholar 

  • Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine, 151(4), 264–269.

    Article  Google Scholar 

  • Morgen, K., Sammer, G., Courtney, S. M., Wolters, T., Melchior, H., Blecker, C. R., et al. (2006). Evidence for a direct association between cortical atrophy and cognitive impairment in relapsing-remitting MS. NeuroImage, 30(3), 891–898. https://doi.org/10.1016/j.neuroimage.2005.10.032.

    Article  PubMed  Google Scholar 

  • Nakagawa, S., Takeuchi, H., Taki, Y., Nouchi, R., Kotozaki, Y., Shinada, T., et al. (2017). Lenticular nucleus correlates of general self-efficacy in young adults. Brain Structure & Funct, 222(7), 3309–3318. https://doi.org/10.1007/s00429-017-1406-2.

    Article  Google Scholar 

  • Nebel, K., Wiese, H., Seyfarth, J., Gizewski, E. R., Stude, P., Diener, H.-C., et al. (2007). Activity of attention related structures in multiple sclerosis patients. Brain Research, 1151, 150–160.

    Article  CAS  Google Scholar 

  • Ontaneda, D., Thompson, A. J., Fox, R. J., & Cohen, J. A. (2017). Progressive multiple sclerosis: prospects for disease therapy, repair, and restoration of function. Lancet, 389(10076), 1357–1366. https://doi.org/10.1016/s0140-6736(16)31320-4.

    Article  Google Scholar 

  • Pantano, P., Iannetti, G. D., Caramia, F., Mainero, C., Di Legge, S., Bozzao, L., et al. (2002). Cortical motor reorganization after a single clinical attack of multiple sclerosis. Brain, 125(7), 1607–1615.

    Article  Google Scholar 

  • Peron, J., Cekic, S., Haegelen, C., Sauleau, P., Patel, S., Drapier, D., et al. (2015). Sensory contribution to vocal emotion deficit in Parkinson’s disease after subthalamic stimulation. Cortex, 63, 172–183. https://doi.org/10.1016/j.cortex.2014.08.023.

    Article  PubMed  Google Scholar 

  • Petracca, M., Zaaraoui, W., Cocozza, S., Vancea, R., Howard, J., Heinig, M. M., et al. (2018). An MRI evaluation of grey matter damage in African Americans with MS. Multiple Sclerosis and Related Disorders, 25, 29–36. https://doi.org/10.1016/j.msard.2018.06.007.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pokryszko-Dragan, A., Bladowska, J., Zimny, A., Slotwinski, K., Zagrajek, M., Gruszka, E., et al. (2014). Magnetic resonance spectroscopy findings as related to fatigue and cognitive performance in multiple sclerosis patients with mild disability. Journal of the Neurological Sciences, 339(1–2), 35–40.

    Article  Google Scholar 

  • Popescu, V., Agosta, F., Hulst, H. E., Sluimer, I. C., Knol, D. L., Sormani, M. P., et al. (2013). Brain atrophy and lesion load predict long term disability in multiple sclerosis. Journal of Neurology, Neurosurgery and Psychiatry, 84(10), 1082–1091. https://doi.org/10.1136/jnnp-2012-304094.

    Article  PubMed  Google Scholar 

  • Prakash, R. S., Snook, E. M., Motl, R. W., & Kramer, A. F. (2010). Aerobic fitness is associated with gray matter volume and white matter integrity in multiple sclerosis. Brain Research, 1341, 41–51. https://doi.org/10.1016/j.brainres.2009.06.063.

    Article  CAS  PubMed  Google Scholar 

  • Preziosa, P., Rocca, M. A., Pagani, E., Stromillo, M. L., Enzinger, C., Gallo, A., et al. (2016). Structural MRI correlates of cognitive impairment in patients with multiple sclerosis: A Multicenter Study. Human Brain Mapping, 37(4), 1627–1644. https://doi.org/10.1002/hbm.23125.

    Article  PubMed  PubMed Central  Google Scholar 

  • Prinster, A., Quarantelli, M., Lanzillo, R., Orefice, G., Vacca, G., Carotenuto, B., et al. (2010). A voxel-based morphometry study of disease severity correlates in relapsing– remitting multiple sclerosis. Multiple Sclerosis, 16(1), 45–54. https://doi.org/10.1177/1352458509351896.

    Article  CAS  PubMed  Google Scholar 

  • Prinster, A., Quarantelli, M., Orefice, G., Lanzillo, R., Brunetti, A., Mollica, C., et al. (2006). Grey matter loss in relapsing-remitting multiple sclerosis: a voxel-based morphometry study. NeuroImage, 29(3), 859–867. https://doi.org/10.1016/j.neuroimage.2005.08.034.

    Article  CAS  PubMed  Google Scholar 

  • Radua, J., Mataix-Cols, D., Phillips, M. L., El-Hage, W., Kronhaus, D., Cardoner, N., et al. (2012). A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. European Psychiatry, 27(8), 605–611.

    Article  CAS  Google Scholar 

  • Radua, J., van den Heuvel, O. A., Surguladze, S., & Mataix-Cols, D. (2010). Meta-analytical comparison of voxel-based morphometry studies in obsessive-compulsive disorder vs other anxiety disorders. Archives of General Psychiatry, 67(7), 701–711.

    Article  Google Scholar 

  • Rashid, W., Parkes, L., Ingle, G., Chard, D., Toosy, A., Altmann, D., et al. (2004). Abnormalities of cerebral perfusion in multiple sclerosis. Journal of Neurology, Neurosurgery & Psychiatry, 75(9), 1288–1293.

    Article  CAS  Google Scholar 

  • Riccitelli, G., Rocca, M. A., Forn, C., Colombo, B., Comi, G., & Filippi, M. (2011). Voxelwise assessment of the regional distribution of damage in the brains of patients with multiple sclerosis and fatigue. AJNR. American Journal of Neuroradiology, 32(5), 874–879. https://doi.org/10.3174/ajnr.A2412.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Riccitelli, G., Rocca, M. A., Pagani, E., Martinelli, V., Radaelli, M., Falini, A., et al. (2012). Mapping regional grey and white matter atrophy in relapsing-remitting multiple sclerosis. Multiple Sclerosis, 18(7), 1027–1037. https://doi.org/10.1177/1352458512439239.

    Article  PubMed  Google Scholar 

  • Rimkus, C. M., Schoonheim, M. M., Steenwijk, M. D., Vrenken, H., Eijlers, A. J., Killestein, J., et al. (2019). Gray matter networks and cognitive impairment in multiple sclerosis. Multiple Sclerosis Journal, 25(3), 382–391.

    Article  Google Scholar 

  • Rocca, M. A., Amato, M. P., De Stefano, N., Enzinger, C., Geurts, J. J., Penner, I. K., et al. (2015). Clinical and imaging assessment of cognitive dysfunction in multiple sclerosis. Lancet Neurol, 14(3), 302–317. https://doi.org/10.1016/s1474-4422(14)70250-9.

    Article  PubMed  Google Scholar 

  • Rocca, M. A., Mesaros, S., Pagani, E., Sormani, M. P., Comi, G., & Filippi, M. (2010). Thalamic damage and long-term progression of disability in multiple sclerosis. Radiology, 257(2), 463–469.

    Article  Google Scholar 

  • Sanchis-Segura, C., Cruz-Gomez, A. J., Belenguer, A., Fittipaldi Marquez, M. S., Avila, C., & Forn, C. (2016). Increased regional gray matter atrophy and enhanced functional connectivity in male multiple sclerosis patients. Neuroscience Letters, 630, 154–157. https://doi.org/10.1016/j.neulet.2016.07.028.

    Article  CAS  PubMed  Google Scholar 

  • Sander, D., Grandjean, D., Pourtois, G., Schwartz, S., Seghier, M. L., Scherer, K. R., et al. (2005). Emotion and attention interactions in social cognition: brain regions involved in processing anger prosody. NeuroImage, 28(4), 848–858. https://doi.org/10.1016/j.neuroimage.2005.06.023.

    Article  PubMed  Google Scholar 

  • Sepulcre, J., Sastre-Garriga, J., Cercignani, M., Ingle, G. T., Miller, D. H., & Thompson, A. J. (2006). Regional gray matter atrophy in early primary progressive multiple sclerosis: a voxel-based morphometry study. Archives of Neurology, 63(8), 1175–1180. https://doi.org/10.1001/archneur.63.8.1175.

    Article  PubMed  Google Scholar 

  • Tavazzi, E., Lagana, M. M., Bergsland, N., Tortorella, P., Pinardi, G., Lunetta, C., et al. (2015). Grey matter damage in progressive multiple sclerosis versus amyotrophic lateral sclerosis: a voxel-based morphometry MRI study. Neurological Sciences, 36(3), 371–377. https://doi.org/10.1007/s10072-014-1954-7.

    Article  PubMed  Google Scholar 

  • Tsagkas, C., Chakravarty, M. M., Gaetano, L., Naegelin, Y., Amann, M., Parmar, K., et al. (2020). Longitudinal patterns of cortical thinning in multiple sclerosis. Human Brain Mapping.

  • Vercellino, M., Plano, F., Votta, B., Mutani, R., Giordana, M. T., & Cavalla, P. (2005). Grey matter pathology in multiple sclerosis. Journal of Neuropathology & Experimental Neurology, 64(12), 1101–1107.

    Article  Google Scholar 

  • Wang, T., Liu, J., Zhang, J., Zhan, W., Li, L., Wu, M., et al. (2016). Altered resting-state functional activity in posttraumatic stress disorder: A quantitative meta-analysis. Sci Rep, 6(1), 1–14.

    Article  Google Scholar 

  • Wang, X. W., Luo, Q. L., Tian, F. T., Cheng, B. C., Qiu, L. Q., Wang, S. W., et al. (2018). Brain grey-matter volume alteration in adult patients with bipolar disorder under different conditions: a voxel-based meta-analysis. Journal Psychiatry Neuroscience, 44(1), https://doi.org/10.1503/jpn.180002.

  • Wollman, S. C., Alhassoon, O. M., Hall, M. G., Stern, M. J., Connors, E. J., Kimmel, C. L., et al. (2017). Gray matter abnormalities in opioid-dependent patients: A neuroimaging meta-analysis. American Journal of Drug and Alcohol Abuse, 43(5), 505–517. https://doi.org/10.1080/00952990.2016.1245312.

    Article  Google Scholar 

  • Zhang, X., Zhang, F., Huang, D., Wu, L., Ma, L., Liu, H., et al. (2016). Contribution of Gray and White Matter Abnormalities to Cognitive Impairment in Multiple Sclerosis. Intenational Journal of Molecular Sciences, 18(1), https://doi.org/10.3390/ijms18010046.

  • Zivadinov, R., & Bakshi, R. (2004). Central nervous system atrophy and clinical status in multiple sclerosis. Journal of Neuroimaging, 14, 27S-35S.

    Article  Google Scholar 

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Funding

This study was supported by the National Natural Science Foundation of China (Grant Nos. 81771812 and 81971595 ), the Innovation Spark Project of Sichuan University (Grant No. 2019SCUH0003) and the 1·3·5 Project for Disciplines of Excellence–Clinical Research Incubation Project, West China Hospital, Sichuan University (Grant No. 2020HXFH005).

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Contributions

Y.C. wrote the first draft of the paper; F.Q.Z, F.F.T., W.D., L.C.H and Z.Y.J. edited the paper;,Y.C., W.D., F.Q.Z., L.C.H., and Z.Y.J. designed research; Y.C., W.D., F.F.T. X.P.L and F.F.Z. performed research; Y.C., W.D., F.F.T., X.P.L, and F.F.Z analyzed data.

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Correspondence to Zhiyun Jia.

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The original online version of this article was revised: Unfortunately, an Acknowledgement section was inadvertently included in the paper. The section was deleted.

Supplementary Information

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11065_2021_9479_MOESM1_ESM.tif

Supplementary file1 Supplementary Fig. 1. The funnel plots showing the publication bias for each altered brain region in RRMS compared with healthy controls. RRMS < healthy controls: Funnel plot of superior temporal gyri, Egger’s test p = 0.165; Funnel plot of left striatum, Egger’s test p = 0.145; Funnel plot of insula, Egger’s test p = 0.052; Funnel plot of cingulate gyrus, Egger’s test p = 0.055; Funnel plot of thalamus, Egger’s test p = 0.096; Funnel plot of striatum, Egger’s test p = 0.345; Funnel plot of postcentral gyrus, Egger’s test p = 0.036; Funnel plot of inferior frontal gyrus s, Egger’s test p = 0.08. (TIF 170 KB)

11065_2021_9479_MOESM2_ESM.tif

Supplementary file2 Supplementary Fig. 2. The funnel plots showing the publication bias for each altered brain region in PPMS compared with healthy controls. PPMS < healthy controls: Funnel plot of insula, Egger’s test p = 0.944; Funnel plot of striatum, Egger’s test p = 0.071; Funnel plot of left thalamus, Egger’s test p = 0.539; Funnel plot of postcentral gyrus, Egger’s test p = 0.007. (TIF 103 KB)

11065_2021_9479_MOESM3_ESM.tif

Supplementary file3 Supplementary Fig. 3. The funnel plots showing the publication bias for each altered brain region in RRMS compared with PPMS. RRMS > PPMS: Funnel plot of left insula, Egger’s test p = 0.179; Funnel plot of right precentral gyrus, Egger’s test p = 0.30; Funnel plot of lenticular nucleus, putamen, Egger’s test p = 0.284; Funnel plot of left cerebellum, crus II, Egger’s test p = 0.894. RRMS < PPMS: Funnel plot of cingulate gyrus, Egger’s test p = 0.056; Funnel plot of left postcentral gyrus, Egger’s test p = 0.004; Funnel plot of right caudate nucleus, Egger’s test p = 0.729. Funnel plot of the right thalamus, Egger’s test p = 0.894; funnel plot of the left caudate nucleus, Egger’s test p = 0.081. Funnel plot of the right superior temporal gyrus, Egger’s test p = 0.399. (TIF 267 KB)

Supplementary file4 (DOCX 40 KB)

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Cao, Y., Diao, W., Tian, F. et al. Gray Matter Atrophy in the Cortico-Striatal-Thalamic Network and Sensorimotor Network in Relapsing–Remitting and Primary Progressive Multiple Sclerosis. Neuropsychol Rev 31, 703–720 (2021). https://doi.org/10.1007/s11065-021-09479-3

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