Микроструктурные изменения белого вещества головного мозга при психических заболеваниях аффективного и шизофренического спектров: обзор данных диффузионной МРТ

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Дудина А.Н., Лебедева И.С. Микроструктурные изменения белого вещества головного мозга при психических заболеваниях аффективного и шизофренического спектров: обзор данных диффузионной МРТ // Российский психиатрический журнал. 2021. №3. С. 76-86.

Аннотация

В научном обзоре с целью обобщения современных данных диффузионной МРТ о микроструктурных нарушениях мозга при психических заболеваниях аффективного и шизофренического спектров и выявления последних тенденций в исследованиях были проанализированы современные отечественные и зарубежные публикации. Рассматривались работы, посвящённые большому депрессивному расстройству, биполярному аффективному расстройству, шизофрении и шизоаффективному расстройству. К настоящему времени накоплен большой массив информации об аномалиях белого вещества при этих заболеваниях, однако данные остаются противоречивыми. Основные современные тренды – продолжение поиска нозологически специфических биомаркёров, определение влияния таких факторов, как проводимая фармакотерапия, длительность заболевания, выраженность психопатологических расстройств, наличие в анамнезе психологических травм и др.

Ключевые слова диффузионная магнитно-резонансная томография; трактография; большое депрессивное расстройство; шизофрения; биполярное аффективное расстройство; шизоаффективное расстройство

Литература

1. Almeida PGC, Nani JV, Oses JP, et al. Neuroinflammation and glial cell activation in mental disorders. Brain Behav Immun Health. 2020;2:1–8. DOI: https://doi.org/10.1016/j.bbih.2019.100034 2. Yang E, Nucifora PG, Melhem ER. Diffusion MR imaging: basic principles. Neuroimaging Сlin N Am. 2011;21(1):1–25. DOI: https://doi.org/10.1016/j.nic.2011.02.001; PMID: 21477749 3. Aung WY, Mar S, Benzinger TL. Diffusion tensor MRI as a biomarker in axonal and myelin damage. Imaging Med. 2013;5(5):427–40. DOI: https://doi.org/10.2217/iim.13.49; PMID: 24795779 4. Kimura-Ohba S, Yang Y, Thompson J, et al. Transient increase of fractional anisotropy in reversible vasogenic edema. J Cereb Blood Flow Metab. 2016;36(10):1731–43. DOI: https://doi.org/10.1177/0271678X16630556; PMID: 26865662 5. Simmonds DJ, Hallquist MN, Asato M, et al. Developmental stages and sex differences of white matter and behavioral development through adolescence: a longitudinal diffusion tensor imaging (DTI) study. Neuroimage. 2014;92:356–68. DOI: https://doi.org/10.1016/j.neuroimage; PMID: 24384150 6. Friston K, Brown HR, Siemerkus J, et al. The dysconnection hypothesis (2016). Schizophr Res. 2016;176(2–3):83–94. DOI: https://doi.org/10.1016/j.schres.2016.07.014; PMID: 27450778 7. Andreasen NC, Paradiso S, O'Leary DS. “Cognitive dysmetria” as an integrative theory of schizophrenia: a dysfunction in cortical-subcortical-cerebellar circuitry? Schizophr Bull. 1998;24(2):203–18. DOI: https://doi.org/10.1093/oxfordjournals.schbul.a033321; PMID: 9613621 8. Glenthoj BY, Hemmingsen R. Dopaminergic sensitization: implications for the pathogenesis of schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry. 1997;21(1):23–46. DOI: https://doi.org/10.1016/s0278-5846(96)00158-3; PMID: 9075257 9. Hamoda HM, Makhlouf AT, Fitzsimmons J, et al. Abnormalities in thalamo-cortical connections in patients with first-episode schizophrenia: a two-tensor tractography study. Brain Imaging Behav. 2019;13(2):472–81. DOI: https://doi.org/10.1007/s11682-018-9862-8; PMID: 29667043 10. Tomyshev AS, Lebedeva IS, Akhadov TA, et al. Alterations in white matter microstructure and cortical thickness in individuals at ultra-high risk of psychosis: A multimodal tractography and surface-based morphometry study. Psychiatry Res Neuroimaging. 2019;289:26–36. DOI: https://doi.org/10.1016/j.pscychresns.2019.05.002; PMID: 31132567 11. Gomez-Gastiasoro A, Zubiaurre-Elorza L, Pena J, et al. Altered frontal white matter asymmetry and its implications for cognition in schizophrenia: A tractography study. Neuroimage Clin. 2019;22:101781. DOI: https://doi.org/10.1016/j.nicl.2019.101781; PMID: 30991613 12. Del Re EC, Bouix S, Fitzsimmons J, et al. Diffusion abnormalities in the corpus callosum in first episode schizophrenia: Associated with enlarged lateral ventricles and symptomatology. Psychiatry Res. 2019;277:45–51. DOI: https://doi.org/10.1016/j.psychres.2019.02.038; PMID: 30808608 13. Ji E, Lejuste F, Sarrazin S, et al. From the microscope to the magnet: Disconnection in schizophrenia and bipolar disorder. Neurosci Biobehav Rev. 2019;98:47–57. DOI: https://doi.org/10.1016/j.neubiorev.2019.01.005; PMID: 30629976 14. Ohoshi Y, Takahashi S, Yamada S, et al. Microstructural abnormalities in callosal fibers and their relationship with cognitive function in schizophrenia: A tract-specific analysis study. Brain Behav. 2019;9(8):e01357. DOI: https://doi.org/10.1002/brb3.1357; PMID: 31283112 15. Kirino E, Hayakawa Y, Inami R, et al. Simultaneous fMRI-EEG-DTI recording of MMN in patients with schizophrenia. PLoS One. 2019;14(5):e0215023. DOI: https://doi.org/10.1371/journal.pone.0215023; PMID: 31071097 16. Kraguljac NV, Anthony T, Skidmore FM, et al. Micro- and Macrostructural White Matter Integrity in Never-Treated and Currently Unmedicated Patients With Schizophrenia and Effects of Short-Term Antipsychotic Treatment. Biol Psychiatry Cogn Neurosci Neuroimaging. 2019;4(5):462–71. DOI: https://doi.org/10.1016/j.bpsc.2019.01.002; PMID: 30852126 17. Lee KH, Oh H, Suh JS, et al. Functional and Structural Connectivity of the Cerebellar Nuclei With the Striatum and Cerebral Cortex in First-Episode Psychosis. J Neuropsychiatry Clin Neurosci. 2019;31(2):143–51. DOI: https://doi.org/10.1176/appi.neuropsych.17110276; PMID: 30561280 18. Ho NF, Li Hui Chong P, Lee DR, et al. The Amygdala in Schizophrenia and Bipolar Disorder: A Synthesis of Structural MRI, Diffusion Tensor Imaging, and Resting-State Functional Connectivity Findings. Harv Rev Psychiatry. 2019;27(3):150–64. DOI: https://doi.org/10.1097/HRP.0000000000000207; PMID: 31082993 19. Holleran L, Kelly S, Alloza C, et al. The Relationship Between White Matter Microstructure and General Cognitive Ability in Patients With Schizophrenia and Healthy Participants in the ENIGMA Consortium. Am J Psychiatry. 2020;177(6):537–47. DOI: https://doi.org/10.1176/appi.ajp.2019.19030225; PMID: 32212855 20. Koshiyama D, Fukunaga M, Okada N, et al. White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals. Mol Psychiatry. 2020;25(4):883–95. DOI: https://doi.org/10.1038/s41380-019-0553-7; PMID: 31780770 21. Chawla N, Deep R, Khandelwal SK, et al. Reduced integrity of superior longitudinal fasciculus and arcuate fasciculus as a marker for auditory hallucinations in schizophrenia: A DTI tractography study. Asian J Psychiatr. 2019;44:179–86. DOI: https://doi.org/10.1016/j.ajp.2019.07.043; PMID: 31398683 22. Asmal L, Kilian S, du Plessis S, et al. Childhood Trauma Associated White Matter Abnormalities in First-Episode Schizophrenia. Schizophr Bull. 2019;45(2):369–76. DOI: https://doi.org/10.1093/schbul/sby062; PMID: 29860345 23. Liang S, Wang Q, Kong X, et al. White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging. Neurosci Bull. 2019;35(5):867–76. DOI: https://doi.org/10.1007/s12264-019-00381-w; PMID: 31062333 24. Repple J, Zaremba D, Meinert S, et al. Time heals all wounds? A 2-year longitudinal diffusion tensor imaging study in major depressive disorder. J Psychiatry Neuroscience. 2019;44(6):407–13. DOI: https://doi.org/10.1503/jpn.180243; PMID: 31094489 25. Doolin K, Andrews S, Carballedo A, et al. Longitudinal diffusion weighted imaging of limbic regions in patients with major depressive disorder after 6 years and partial to full remission. Psychiatry Res Neuroimaging. 2019;287:75–86. DOI: https://doi.org/10.1016/j.pscychresns.2019.04.004; PMID: 31004996 26. Nugent AC, Farmer C, Evans JW, et al. Multimodal imaging reveals a complex pattern of dysfunction in corticolimbic pathways in major depressive disorder. Hum Brain Mapp. 2019;40(13):3940–50. DOI: https://doi.org/10.1002/hbm.24679; PMID: 31179620 27. Zheng K, Wang H, Li J, et al. Structural networks analysis for depression combined with graph theory and the properties of fiber tracts via diffusion tensor imaging. Neurosci Lett. 2019;694:34–40. DOI: https://doi.org/10.1016/j.neulet.2018.11.025; PMID: 30465819 28. van Velzen LS, Kelly S, Isaev D, et al. White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group. Mol Psychiatry. 2020;25(7):1511–25. DOI: https://doi.org/10.1038/s41380-019-0477-2; PMID: 31471575 29. Heij GJ, Penninx B, van Velzen LS, et al. White matter architecture in major depression with anxious distress symptoms. Prog Neuropsychopharmacol Biol Psychiatry. 2019;94:109664. DOI: https://doi.org/10.1016/j.pnpbp.2019.109664; PMID: 31158389 30. Coloigner J, Batail JM, Commowick O, et al. White matter abnormalities in depression: A categorical and phenotypic diffusion MRI study. NeuroImage Clinical. 2019;22:101710. DOI: https://doi.org/10.1016/j.nicl.2019.101710; PMID: 30849644 31. Wang S, Leri F, Rizvi SJ. Anhedonia as a central factor in depression: Neural mechanisms revealed from preclinical to clinical evidence. Prog Neuropsychopharmacol Biol Psychiatry. 2021;110:110289. DOI: https://doi.org/10.1016/j.pnpbp.2021.110289; PMID: 33631251 32. Lyon M, Welton T, Varda A, et al. Gender-specific structural abnormalities in major depressive disorder revealed by fixel-based analysis. Neuroimage Clin. 2019;21:101668. DOI: https://doi.org/10.1016/j.nicl.2019.101668; PMID: 30690418 33. Meinert S, Repple J, Nenadic I, et al. Reduced fractional anisotropy in depressed patients due to childhood maltreatment rather than diagnosis. Neuropsychopharmacology. 2019;44(12):2065–72. DOI: https://doi.org/10.1038/s41386-019-0472-y; PMID: 31382267 34. Graziano RC, Bruce SE, Paul RH, et al. The effects of bullying in depression on white matter integrity. Behav Brain Res. 2019;363:149–54. DOI: https://doi.org/10.1016/j.bbr.2019.01.054; PMID: 30710613 35. Kang SG, Cho SE. Neuroimaging Biomarkers for Predicting Treatment Response and Recurrence of Major Depressive Disorder. Int J Mol Sci. 2020;21(6):2148. DOI: https://doi.org/10.3390/ijms21062148; PMID: 32245086 36. Yang C, Li L, Hu X, et al. Psychoradiologic abnormalities of white matter in patients with bipolar disorder: diffusion tensor imaging studies using tract-based spatial statistics. J Psychiatry Neuroscience. 2019;44(1):32–44. DOI: https://doi.org/10.1503/jpn.170221; PMID: 30565904 37. Ota M, Noda T, Sato N, et al. The use of diffusional kurtosis imaging and neurite orientation dispersion and density imaging of the brain in bipolar disorder. J Affect Disord. 2019;251:231–4. DOI: https://doi.org/10.1016/j.jad.2019.03.068; PMID: 30928862 38. Favre P, Pauling M, Stout J, et al. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals. Neuropsychopharmacology. 2019;44(13):2285–93. DOI: https://doi.org/10.1038/s41386-019-0485-6; PMID: 31434102 39. Reich R, Gilbert A, Clari R, et al. A preliminary investigation of impulsivity, aggression and white matter in patients with bipolar disorder and a suicide attempt history. J Affect Disord. 2019;247:88–96. DOI: https://doi.org/10.1016/j.jad.2019.01.001; PMID: 30658245 40. Zhuang H, Liu R, Wu C, et al. Multimodal classification of drug-naive first-episode schizophrenia combining anatomical, diffusion and resting state functional resonance imaging. Neurosci Lett. 2019;705:87–93. DOI: https://doi.org/10.1016/j.neulet.2019.04.039; PMID: 31022433 41. Liang S, Li Y, Zhang Z, et al. Classification of First-Episode Schizophrenia Using Multimodal Brain Features: A Combined Structural and Diffusion Imaging Study. Schizophr Bull. 2019;45(3):591–9. DOI: https://doi.org/10.1093/schbul/sby091; PMID: 29947804 42. Stolicyn A, Harris MA, Shen X, et al. Automated classification of depression from structural brain measures across two independent community-based cohorts. Hum Brain Mapp. 2020;41(14):3922–37. DOI: https://doi.org/10.1002/hbm.25095; PMID: 32558996 43. Maglanoc LA, Kaufmann T, Jonassen R, et al. Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis. Hum Brain Mapp. 2020;41(1):241–55. DOI: https://doi.org/10.1002/hbm.24802; PMID: 31571370 44. Achalia R, Sinha A, Jacob A, et al. A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder. Asian J Psychiatr. 2020;50:101984. DOI: https://doi.org/10.1016/j.ajp.2020.101984; PMID: 32143176 45. Han W, Sorg C, Zheng C, et al. Low-rank network signatures in the triple network separate schizophrenia and major depressive disorder. Neuroimage Clin. 2019;22:101725. DOI: https://doi.org/10.1016/j.nicl.2019.101725; PMID: 30798168 46. Rashid B, Calhoun V. Towards a brain-based predictome of mental illness. Hum Brain Mapp. 2020;41(12):3468–535. DOI: https://doi.org/10.1002/hbm.25013; PMID: 32374075 47. Ochi R, Noda Y, Tsuchimoto S, et al. White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study. Prog Neuropsychopharmacol Biol Psychiatry. 2020;100:109871. DOI: https://doi.org/10.1016/j.pnpbp.2020.109871; PMID: 31962187 48. Kraguljac NV, Anthony T, Monroe WS, et al. A longitudinal neurite and free water imaging study in patients with a schizophrenia spectrum disorder. Neuropsychopharmacology. 2019;44(11):1932–9. DOI: https://doi.org/10.1038/s41386-019-0427-3; PMID: 31153156 49. Barth C, Lonning V, Gurholt TP, et al. Exploring white matter microstructure and the impact of antipsychotics in adolescent-onset psychosis. PLoS One. 2020;15(5):e0233684. DOI: https://doi.org/10.1371/journal.pone.0233684; PMID: 32470000 50. Davis AD, Hassel S, Arnott SR, et al. White Matter Indices of Medication Response in Major Depression: A Diffusion Tensor Imaging Study. Biol Psychiatry Cogn Neurosci Neuroimaging. 2019;4(10):913–24. DOI: https://doi.org/10.1016/j.bpsc.2019.05.016; PMID: 31471185 51. Matsuoka K, Morimoto T, Matsuda Y, et al. Computer-assisted cognitive remediation therapy for patients with schizophrenia induces microstructural changes in cerebellar regions involved in cognitive functions. Psychiatry Res Neuroimaging. 2019;292:41–6. DOI: https://doi.org/10.1016/j.pscychresns.2019.09.001; PMID: 31521942 52. McClure MM, Graff FS, Triebwasser J, et al. Neuroimaging predictors of response to cognitive remediation and social skills training: A pilot study in veterans with schizophrenia. Psychiatry Res Neuroimaging. 2019;293:110988. DOI: https://doi.org/10.1016/j.pscychresns.2019.110988; PMID: 31655369 53. Niznikiewicz MA. Neurobiological approaches to the study of clinical and genetic high risk for developing psychosis. Psychiatry Res. 2019;277:17–22. DOI: https://doi.org/10.1016/j.psychres.2019.02.009; PMID: 30926150 54. Tomyshev AS, Lebedeva IS, Kananovich PS, et al. [Mul'timodal'noe MRT issledovanie osobennostej provodjashhih putej i anatomii serogo veshhestva golovnogo mozga pri semejnom riske rasstrojstv affektivnogo spektra i shizofrenii]. Bjulleten' jeksperimental'noj biologii i mediciny [Bulletin of Experimental Biology and Medicine]. 2020;169(5):542–6. (In Russ.) 55. Chang X, Mandl RCW, Pasternak O, et al. Diffusion MRI derived free-water imaging measures in patients with schizophrenia and their non-psychotic siblings. Prog Neuropsychopharmacol Biol Psychiatry. 2021;109:110238. DOI: https://doi.org/10.1016/j.pnpbp.2020.110238; PMID: 33400942 56. Jin J, Delaparte L, Chen HW, et al. Structural connectivity between rostral anterior cingulate cortex and amygdala predicts first onset of depressive disorders in adolescence. Biol Psychiatry Cogn Neurosci Neuroimaging. 2021;1–20. DOI: https://doi.org/10.1016/j.bpsc.2021.01.012; PMID: 33610811 57. Toenders YJ, van Velzen LS, Heideman IZ, et al. Neuroimaging predictors of onset and course of depression in childhood and adolescence: A systematic review of longitudinal studies. Dev Cogn Neurosci. 2019;39:100700. DOI: https://doi.org/10.1016/j.dcn.2019.100700; PMID: 31426010 58. Vanes LD, Dolan RJ. Transdiagnostic neuroimaging markers of psychiatric risk: A narrative review. Neuroimage Clin. 2021;30:102634. DOI: https://doi.org/10.1016/j.nicl.2021.102634; PMID: 33780864



DOI: http://dx.doi.org/10.47877/1560-957Х-2021-10308

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