Microstructural Brain Pathology in Paranoid Schizophrenia (According to Magnetic Resonance Tractography)

Background: inconsistency of the obtained results of research on the pathology of microstructural connectivity in schizophrenia on the basis of tractography, absence of clinical application of special MRI techniques justify the need to continue scientific search in this direction. Objective: to identify the features of microstructural pathology of the brain in paranoid schizophrenia. Patients and methods: 25 patients diagnosed with paranoid schizophrenia (F20.0) were included in the main group, 30 healthy subjects without neurological and somatic diseases made up the control group. Instrumental studies were carried out on a Philips Ingenia magnetic resonance tomograph (magnetic field strength 1.5 T) using a DTI pulse sequence. Subsequent processing was carried out using “DSI Studio” (software for the analysis of tractor data). Results and discussion: the resulting microstructural brain changes demonstrated differences in the microstructural connectivity of the brain in patients with paranoid schizophrenia compared to the control group. Significant connections were revealed (at the given parameters for constructing connectivity matrices) between the hippocampus and the cingulate gyrus, the hippocampus and thalamus, thalamus and structures of the striopallidar system, and the absence of significant connections between the amygdala in the main group compared to the control group. The results of graph theoretical analysis of neural network indicators of the brain demonstrated higher values of indicators of “clustering” and the “small world” coefficient, characteristic path length, transitivity, density, and lower values of the global efficiency indicator of the main group compared to the control group. Conclusion: the obtained results demonstrate microstructural semiotics of neural network changes of brain in paranoid schizophrenia. Changes in the connectivity of the hippocampus, thalamus, and amygdala appear to be important tractographic semiotic features of the microstructural pathology of the brain in paranoid schizophrenia. The study is one of the stages of the search for a method of objectification and detection of disruption of brain neuroplasticity processes in the endogenous pathology of the schizophrenic spectrum. 

1. Aleksandrovskij JuA, Neznanov NG, red. Psihiatrija: nacional’noe rukovodstvo. M.: GJeOTAR-Media; 2018:1008 p. (In Russ.).

2. Klyushnik TP, Smulevich AB, Zozulya SA, Voronova EI. Neurobiology of Schizophrenia (to the Construction of Clinical and Biological Model). Psychiatry (Moscow) (Psikhiatriya). 2021;19(1):6–15. (In Russ.). doi: 10.30629/2618-6667-2021-19-1-6-15

3. Tarumov DA, Marchenko AA, Trufanov AG, Romanov GG, Lobachev AV, Mavrenkov JeM, Ishakov DN, Zheleznjak IS, Shamrej VK, Trufanov GE, Fisun AJa. Obektivizacija psihicheskih rasstrojstv s primeneniem special’nyh metodik magnitno-rezonansnoj tomografii v sisteme monitoringa psihicheskogo zdorov’ja voennosluzhashhih. Luchevaja diagnostika i terapija. 2019;3(10):60–70. (In Russ.). doi: 10.22328/2079-5343-2019-10-3-60-70

4. Tarumov DA, Trufanov AG, Zheleznjak IS, Shamrej VK, Malahovskij VN. Patologija mikrostrukturnoj konnektivnosti golovnogo mozga pri sindrome zavisimosti ot opioidov i alkogolja. Doktor.Ru. 2020;19(4):35–42. (In Russ.). doi: 10.31550/1727-2378-2020-19-4-35-42

5. Gómez-Gastiasoro A, Zubiaurre-Elorza L, Peña J, Ibarretxe-Bilbao N, Rilo O, Schretlen DJ, Ojeda N. Altered frontal white matter asymmetry and its implications for cognition in schizophrenia: A tractography study. Neuroimage Clin. 2019;22:101781. doi: 10.1016/j.nicl.2019.101781

6. Seitz J, Zuo JX, Lyall AE, Makris N, Kikinis Z, Bouix S, Pasternak O, Fredman E, Duskin J, Goldstein JM, Petryshen TL, Mesholam-Gately RI, Wojcik J, McCarley RW, Seidman LJ, Shenton ME, Koerte IK, Kubicki M. Tractography Analysis of 5 White Matter Bundles and Their Clinical and Cognitive Correlates in Early-Course Schizophrenia. Schizophr Bull. 2016;42(3):762–771. doi: 10.1093/schbul/sbv171

7. Voineskos AN, Lobaugh NJ, Bouix S, Rajji TK, Miranda D, Kennedy JL, Mulsant BH, Pollock BG, Shenton ME. Diffusion tensor tractography findings in schizophrenia across the adult lifespan. Brain. 2010;133(Pt 5):1494–1504. doi: 10.1093/brain/ awq040

8. Chawla N, Deep R, Khandelwal SK, Garg A. 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;44:179–186. doi: 10.1016/j. ajp.2019.07.043

9. Geoffroy PA, Houenou J, Duhamel A, Amad A, De Weijer AD, Curčić-Blake B, Linden DE, Thomas P, Jardri R. The Arcuate Fasciculus in auditory-verbal hallucinations: a meta-analysis of diffusion-tensor-imaging studies. Schizophr Res. 2014;159(1):234–237. doi: 10.1016/j.schres.2014.07.014 Epub 2014 Aug 10. PMID: 25112160.

10. Cavelti M, Kircher T, Nagels A, Strik W, Homan P. Is formal thought disorder in schizophrenia related to structural and functional aberrations in the language network? A systematic review of neuroimaging findings Schizophr Res. 2018;199:2–16. doi: 10.1016/j. schres.2018.02.051

11. Zhu T, Zhou C, Fang X, Huang C, Xie C, Ge H, Yan Z, Zhang X, Chen J. Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation Front Psychiatry. 2022;(13):957685. doi: 10.3389/fpsyt.2022.957685

12. Zhao W, Guo S, He N, Yang AC, Lin CP, Tsai SJ. Callosal and subcortical white matter alterations in schizophrenia: A diffusion tensor imaging study at multiple levels. Neuroimage Clin. 2018;20:594–602. doi: 10.1016/j.nicl.2018.08.027

13. Li S., Hu N, Zhang W, Tao B, Dai J, Gong Y, Tan Y, Cai D, Lui S. Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity. Front Psychiatry. 2019;(10):482. doi: 10.3389/fpsyt.2019.00482

14. Koshiyama D, Fukunaga M, Okada N, Morita K, Nemoto K, Usui K, Yamamori H, Yasuda Y, Fujimoto M, Kudo N, Azechi H, Watanabe Y, Hashimoto N, Narita H, Kusumi I, Ohi K, Shimada T, Kataoka Y, Yamamoto M, Ozaki N, Okada G, Okamoto Y, Harada K, Matsuo K, Yamasue H, Abe O, Hashimoto R, Takahashi T, Hori T, Nakataki M, Onitsuka T, Holleran L, Jahanshad N, van Erp TGM, Turner J, Donohoe G, Thompson PM, Kasai K, Hashimoto R. White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals. Mol Psychiatry. 2020;4(25):883–895. doi: 10.1038/ s41380-019-0553-7

15. Zhao G., Lau WKW, Wang C, Yan H, Zhang C, Lin K, Qiu S, Huang R, Zhang R. A Comparative Multimodal Meta-analysis of Anisotropy and Volume Abnormalities in White Matter in People Suffering from Bipolar Disorder or Schizophrenia. Schizophr Bull. 2022;1(48):69–79. doi: 10.1093/schbul/sbab093

16. Kristensen TD, Mandl RCW, Jepsen JRM, Rostrup E, Glenthoj LB, Nordentoft M, Glenthoj BY, Ebdrup BH. Non-pharmacological modulation of cerebral white matter organization: A systematic review of non-psychiatric and psychiatric studies Neuroscience & Biobehavioral Reviews. 2018;(88):84–97. doi: 10.1016/j. neubiorev.2018.03.013

17. Ushakov VL, Malashenkova IK, Kostyuk GP, Zakharova NV, Krynskiy SA, Kartashov SI, Ogurtsov DP, Bravve LV, Kaydan MA, Hailov NA, Chekulaeva EI, Didkovsky NA. The relationship between inflammation, cognitive disorders and neuroimaging data in schizophrenia. S.S. Korsakov Journal of Neurology and Psychiatry/Zhurnal Nevrologii i Psikhiatrii imeni S.S. Korsakova. 2020;120(11):70–78. (In Russ.). doi: 10.17116/jnevro202012011170

18. Zaharova NV, Chekulaeva EI, Krynskij SA, Ushakov VL, Kurmyshev MV, Kostjuk GP, Bravve LV, Mamedova GSh, Kartashov SI, Ogurcov DP, Kajdan MA, Orlov VA, Hajlov NA, Malashenkova IK. Immunological status and basic structures of the human brain in norm and in patients with schizophrenia. Vestnik RFFI. 2021;4(112):60–77. (In Russ.). doi: 10.22204/24104639-2021-112-04-60-77

19. Lebedeva IS, Karelin SA, Ahadov TA, Tomyshev AS, Ublinskij MV, Semenova NA, Barhatova AN, Kaleda VG. Mikrostrukturnye anomalii mozolistogo tela i krjuchkovidnogo puchka i processy obrabotki sluhovoj informacii u bol’nyh junosheskoj pristupoobraznoj shizofreniej. Fiziologija cheloveka. 2016;42(4):27–31. (In Russ.). doi: 10.7868/S0131164616040123

20. Ushakov VL, Malahov DG, Orlov VA, Kartashov SI, Korosteleva AN, Skiteva LI, Velichkovskij BM, Maslennikova AV, Arhipov AJu, Strelec VB, Vartanov AV, Zaharova NV, Reznik AM, Morozova AJu, Kostjuk GP. fMRT i traktograficheskie issledovanija bol’nyh shizofreniej. In: Klinicheskaja psihiatrija XXI veka: integracija innovacij i tradicij dlja diagnostiki i optimizacii terapii psihicheskih rasstrojstv: materialy Vserossijskoj nauchno-prakticheskoj konferencii s mezhdunarodnym uchastiem, posvjashhennoj pamjati professora Ruslana Jakovlevicha Vovina (90-letiju so dnja rozhdenija). Jelektronnoe izdanie, Saint Petersburg, 17–18 maja 2018 goda. SPb.: Al’ta Astra, 2018:342–345. (In Russ.). https://www.elibrary.ru/ item.asp?id=46297497

21. Stahl SM. Symptoms and circuits, part 3: schizophrenia. J Clin Psychiatry. 2004;65(1):8–9. doi: 10.4088/ jcp.v65n0102

22. Purves D, Augustine GJ, Fitzpatrick D, Hall WC, Moone ML, LaMantia A-S, Platt ML, White LE. Neuroscience. 6th ed. Sunderland (MA): Sinauer Associates; 2018.

23. Kay SR, Fiszbein A, Opler LA. The Positive and Negative Syndrome Scale (PANSS) for Schizophrenia. Schizophr Bull. 1987;2(13):261–276. doi: 10.1093/ schbul/13.2.261

24. Kraguljac NV, McDonald WM, Widge AS, Rodriguez CI, Tohen M, Nemeroff CB. Neuroimaging Biomarkers in Schizophrenia. Am J Psychiatry. 2021;178(6):509–521. doi: 10.1176/appi.ajp.2020.20030340

25. Tregellas JR, Smucny J, Harris JG, Olincy A, Maharajh K, Kronberg E, Eichman LC, Lyons E, Freedman R. Intrinsic hippocampal activity as a biomarker for cognition and symptoms in schizophrenia. Am J Psychiatry. 2014;171(5):549–556. doi: 10.1176/appi. ajp.2013.13070981

26. Heckers S, Konradi C. GABAergic mechanisms of hippocampal hyperactivity in schizophrenia. Schizophr Res. 2015;167(1–3):4–11. doi: 10.1016/j. schres.2014.09.041

27. Medoff DR, Holcomb HH, Lahti AC, Tamminga CA. Probing the human hippocampus using rCBF: contrasts in schizophrenia. Hippocampus. 2001;11(5):543–50. doi: 10.1002/hipo.1070

28. Rahm C, Liberg B, Reckless G, Ousdal O, Melle I, Andreassen OA, Agartz I. Negative symptoms in schizophrenia show association with amygdala volumes and neural activation during affective processing. Acta Neuropsychiatr. 2015;27(4):213–220. doi: 10.1017/neu.2015.11

29. Rasetti R, Mattay VS, Wiedholz LM, Kolachana BS, Hariri AR, Callicott JH, Meyer-Lindenberg A, Weinberger DR. Evidence that altered amygdala activity in schizophrenia is related to clinical state and not genetic risk. Am J Psychiatry. 2009;166(2):216–225. doi: 10.1176/appi.ajp.2008.08020261

30. Pinkham AE, Loughead J, Ruparel K, Overton E, Gur RE, Gur RC. Abnormal modulation of amygdala activity in schizophrenia in response to directand averted-gaze threat-related facial expressions. Am J Psychiatry. 2011;168(3):293–301. doi: 10.1176/appi. ajp.2010.10060832

31. Rubinov M, Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage. 2010;52(3):1059–1069. doi: 10.1016/j.neuroimage.2009.10.003

32. Bassett DS, Bullmore E. Small-world brain networks. Neuroscientist. 2006;12(6):512–523. doi: 10.1177/1073858406293182

33. Sporns O, Honey CJ. Small worlds inside big brains. Proc Natl Acad Sci U S A. 2006;103(51):19219-19220. doi: 10.1073/pnas.0609523103

34. Cohen JR, D’Esposito M. The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition. J Neurosci. 2016;36(48):12083–12094. doi: 10.1523/JNEUROSCI.2965-15.2016

35. Zhang R, Wei Q, Kang Z, Zalesky A, Li M, Xu Y, Li L, Wang J, Zheng L, Wang B, Zhao J, Zhang J, Huang R. Disrupted brain anatomical connectivity in medication-naïve patients with first-episode schizophrenia. Brain Struct Funct. 2015; 220(2):1145–1159. doi: 10.1007/s00429-014-0706-z

36. Zhang Y, Lin L, Lin CP, Zhou Y, Chou KH, Lo CY, Su TP, Jiang T. Abnormal topological organization of structural brain networks in schizophrenia. Schizophr Res. 2012;141(23):109–118. doi: 10.1016/j. schres.2012.08.021

37. Zhao W, Guo S, He N, Yang AC, Lin CP, Tsai SJ. Callosal and subcortical white matter alterations in schizophrenia: A diffusion tensor imaging study at multiple levels. Neuroimage Clin. 2018;20:594–602. doi: 10.1016/j.nicl.2018.08.027

38. Sexton CE, Walhovd KB, Storsve AB, Tamnes CK, Westlye LT, Johansen-Berg H, Fjell AM. Accelerated Changes in White Matter Microstructure during Aging: A Longitudinal Diffusion Tensor Imaging Study. J Neurosci. 2014;46(34):15425–15436. doi: 10.1523/ JNEUROSCI.0203-14.2014

39. Leroux E, Vandevelde A, Tréhout M, Dollfus S. Abnormalities of fronto-subcortical pathways in schizophrenia and the differential impacts of antipsychotic treatment: a DTI-based tractography study. Psychiatry Res Neuroimaging. 2018;(280):22–29. doi: 10.1016/j.pscychresns.2018.08.008

40. Ozcelik-Eroglu E, Ertugrul A, Oguz KK, Has AC, Karahan S, Yazici MK. Effect of clozapine on white matter integrity in patients with schizophrenia: A diffusion tensor imaging study. Psychiatry Res Neuroimaging. 2014;3(223):226–235. doi: 10.1016/j.pscychresns.2014.06.001