Cluster analysis of immunological serum markers in patients with Parkinson’s disease

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Abstract

Introduction. The study of patients’ biological features, including their immune responses, in specific diseases, is an important step towards personalized diagnosis and treatment. Parkinson’s disease (PD) is thus of particular interest as one of the most common age-related neurodegenerative diseases.

Study aim – to determine the immunophenotypes of patients with PD using cluster analysis.

Materials and methods. Mathematical analysis was conducted on a database of 46 patients with PD. The levels of the following functionally related inflammatory markers were used as the classification characteristics: the enzymatic activity of leukocyte elastase (LE), the functional activity of α1-proteinase inhibitor (α1-PI), the auto-antibody levels to S-100b and myelin basic protein.

Results. Based on the immunological markers, the use of multiple algorithms in the cluster analysis of the PD database allowed to obtain two consistent clusters. The patients in cluster 1 were characterized by a high level of LE activity and a low level of functional α1-PI activity, which indicates insufficient serum antiproteolytic capacity and is an unfavourable prognostic indicator for further development of the inflammation-associated pathological process in the brain tissue. The patients in cluster 2 were characterized by increased functional α1-PI activity in the serum, increased S-100b antibody levels and a decreased LE activity as compared with cluster 1, which indicates dysregulation of the inflammatory response, associated with insufficient neutrophil degranulation, whereas elevated autoantibody levels to the neural antigen S100b characterize the most severe lesions in the nervous system.

Conclusion. The results of the cluster analysis enable the identification of two immunophenotypes in patients with PD, indicating that a phenotypically similar presentation can be due to a different spectrum of immune markers. The obtained data will serve as a basis for development of an immunological approach to personalized diagnosis and treatment.

About the authors

Tatyana P. Klyushnik

Research Center for Mental Health

Email: simonov1951@rambler.ru
Россия, Moscow

Anatoly N. Simonov

Research Center for Mental Health

Author for correspondence.
Email: simonov1951@rambler.ru
Россия, Moscow

Lyubov V. Androsova

Research Center for Mental Health

Email: simonov1951@rambler.ru
Россия, Moscow

Natalia V. Ponomareva

Research Center of Neurology

Email: simonov1951@rambler.ru
Россия, Moscow

Sergey N. Illarioshkin

Research Center of Neurology

Email: simonov1951@rambler.ru
Россия, Moscow

References

  1. Sita G., Hrelia P., Tarozzi A. Morroni F. Isothiocyanates are promising compounds against oxidative stress, neuroinflammation and cell death that may benefit neurodegeneration in Parkinson's disease. Int J Mol Sci 2016; 17: pii: E1454. doi: 10.3390/ijms17091454. PMID: 27598127.
  2. Xu L., He D., Bai Y. Microglia-mediated inflammation and neurodegenerative disease. Mol Neurobiol 2016; 53: 6709–6715. doi: 10.1007/s12035-015-9593-4. PMID: 26659872.
  3. Del-Bel E., Bortolanza M., Dos-Santos-Pereira M. et al. L-DOPA-induced dyskinesia in Parkinson's disease: Are neuroinflammation and astrocytes key elements? Synapse 2016; 70: 479–500. doi: 10.1002/syn.21941. PMID: 27618286.
  4. De Virgilio A., Greco A., Fabbrini G. et al. Parkinson's disease: Autoimmunity and neuroinflammation. Autoimmun Rev 2016; 15: 1005–1011. doi: 10.1016/j.autrev.2016.07.022. PMID: 27497913.
  5. Zhou S., Du X., Xie J., Wang J. Interleukin-6 regulates iron-related proteins through c-Jun N-terminal kinase activation in BV2 microglial cell lines. PLoS One 2017; 12: e0180464. doi: 10.1371/journal.pone.0180464. PMID: 28672025.
  6. Chen L., Mo M., Li G. et al. The biomarkers of immune dysregulation and inflammation response in Parkinson disease. Transl Neurodegener 2016; 5: 16. doi: 10.1186/s40035-016-0063-3. PMID: 27570618.
  7. Dzamko N., Gysbers A., Perera G. et al. Toll-like receptor 2 is increased in neurons in Parkinson's disease brain and may contribute to alpha-synuclein pathology. Acta Neuropathol 2017; 133: 303–319. doi: 10.1007/s00401-016-1648-8. PMID: 27888296.
  8. Wang W., Nguyen L.T., Burlak C.et al.Caspase-1 causes truncation and aggregation of the Parkinson's disease-associated protein α-synuclein. Proc Natl Acad Sci USA 2016; 113: 9587–9592. doi: 10.1073/pnas.1610099113. PMID: 27482083.
  9. Zhang G., Xia Y., Wan F. et al. New perspectives on roles of alpha-synuclein in Parkinson's disease. Front Aging Neurosci 2018; 10: 370. doi: 10.3389/fnagi.2018.00370. PMID: 30524265.
  10. Ransohoff R.M. How neuroinflammation contributes to neurodegeneration. Science 2016; 353: 777–783. doi: 10.1126/science.aag2590. PMID: 27540165.
  11. Kustrimovic N., Marino F., Cosentino M. Peripheral immunity, immunoaging and neuroinflammation in Parkinson's disease. Curr Med Chem 2018. doi: 10.2174/0929867325666181009161048. PMID: 30306855.
  12. Alam Q., Alam M.Z., Mushtaq G. et al. Inflammatory process in Alzheimer's and Parkinson's diseases: central role of cytokines. Curr Pharm Des 2016; 22: 541–548. PMID: 26601965.
  13. Kim R., Kim H.J., Kim A. et al. Peripheral blood inflammatory markers in early Parkinson's disease. J Clin Neurosci 2018; 58: 30–33. doi: 10.1016/j.jocn.2018.10.079. PMID: 30454693.
  14. Klyushnik T.P., Androsova L.V., Mikhaylova N.M. et al. [Systemic inflammatory markers in age-associated cognitive impairment and Alzheimer’s disease]. Zhurnal nevrologii i psikhiatrii im. S.S. Korsakova 2017; 117(7): 74–79. doi: 10.17116/jnevro20171177174-79. PMID: 28805765. (In Russ.)
  15. Dotsenko V.L., Neshkova E.A., Yarovaya G.A. [Detection of leukocyte elastase from complex with plasma α1-proteinase inhibitor by it enzymatic activity with a synthetic substrate]. Voprosy meditsinskoy khimii 1994; 40(3): 20–25. (In Russ.)
  16. Nartikova V.F., Paskhina T.S. [A unified method for assay of alpha-1-antitrypsin and alpha-2-macroglobulin activity in human serum (plasma)].Voprosy meditsinskoy khimii 1979; 25(4): 494–499. (In Russ.)
  17. Dyuran B., Odell P. [Cluster Analysis]. Moscow, 1977. 128 p. (In Russ.)
  18. Aivazyan S.A., Bukhshtaber V.M., Enyukov I.S., Meshalkin L.D. [Applied Statistics: Classification and Dimension Reduction]. Moscow, 1989. 607 p. (In Russ.)
  19. Shitikov V.K., Mastitsky S.E. [Classification, regression, and other data mining algorithms using R] [Electronic resource]. 2017. URL: https://github.com/ranalytics/data-mining (In Russ.)
  20. Klyushnik T.P., Androsova L.V., Zozulya S.A. et al. [Comparative analysis of inflammatory markers in endogenous and non-psychotic mental disorders]. Sibirskij vestnik psikhiatrii i narkologii 2018; 2(99): 64–69. (In Russ.)
  21. Mantovani A., Cassatella M.A., Costantini C., Jaillon S. Neutrophils in the activation and regulation of innate and adaptive immunity. Nat Rev Immunol 2011; 11: 519–531. doi: 10.1038/nri3024. PMID: 21785456.
  22. Kolaczkowska E., Kubes P. Neutrophil recruitment and function in health and inflammation. Nat Rev Immunol 2013; 13: 159–175. doi: 10.1038/nri3399. PMID: 23435331.
  23. Mayadas T.N., Cullere X., Lowell C.A. The multifaceted functions of neutrophils. Annu Rev Pathol 2014; 9: 181–218. doi: 10.1146/annurev-pathol-020712-164023. PMID: 24050624.
  24. Hampton H.R., Chtanova T. The lymph node neutrophil. Semin Immunol 2016; 28: 129–136. doi: 10.1016/j.smim.2016.03.008. PMID: 27025975.
  25. Pham C.T. Neutrophil serine proteases fine-tune the inflammatory response. Int J Biochem Cell Biol 2008; 40: 1317–1333. doi: 10.1016/j.biocel.2007.11.008. PMID: 18180196.
  26. Kravtsov A.L., Shmel'kova T.P. [Secretory neutrophil degranulation as a trigger for inflammation and an immune response regulator: the role of serine leukocyte proteases and proteolytically activated receptors]. Epidemiologiya i vaktsinoprofilaktika 2011; 1(56): 79–87. (In Russ.)
  27. Simonov A.N., Klyushnik T.P., Androsova L.V. et al. [Cluster analysis of inflammatory markers in disorders of adaptation]. Zhurnal nevrologii i psikhiatrii im. S.S. Korsakova 2018; 118(7): 59–66 (In Russ.) doi: 10.17116/jnevro20181187159. PMID: 30132459.
  28. Klyushnik T.P., Zozulya S.A., Androsova L.V. et al. [Laboratory diagnostics in monitoring patients with endogenous psychosis (“Neuro-Immuno-Test”)]. Moscow, 2016. 32 p. (In Russ.)

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Copyright (c) 2019 Klyushnik T.P., Simonov A.N., Androsova L.V., Ponomareva N.V., Illarioshkin S.N.

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