The use of autoimmunological parameters to evaluate the results of osteopathic correction: pilot study

Introduction. Osteopathic correction (OC) is aimed to eliminate somatic dysfunctions, which are reversible structural and functional disorders of tissue mobility. Adaptation mechanisms of the organism imply structural 

The aim of the study is to investigate the fundamental possibility of using functional (not nosological) autoimmunological indicators to evaluate the results of osteopathic correction.

Materials and methods. The prospective study was conducted on the basis of the Department of Osteopathy of the Mechnikov NWSMU and the Institute of Osteopathy (Saint-Petersburg) in 2020–2021. 10 young and middle-aged people (20–52 years old) were examined. Patients underwent osteopathic correction in the amount of 2–3 sessions. Patients were examined according to the algorithms of osteopathic diagnostics; the ratio of antibody titers to 24 autoantigens of various body tissues and organs was evaluated using the ELI-Viscero-Test-24 method before and after the OC courses.

Results. The relative content of autoantibodies to the main connective tissue protein collagen significantly (p=0,037) increased from a median value of 6 % (Q1–Q3 2–9 %) to 11 % (Q1–Q3 2–22 %). The other autoimmunological indicators varied in different directions.

Conclusion. It is likely that OC triggers the processes of connective tissue restructuring, which are reflected in an increase in the indicators of auto-AT to collagen. Changes in other autoimmunological indicators require more detailed studies on a larger sample.

1. Aruin L. I., Babaeva A. G., Gel′fand V. B., Glumova V. A., Efi mov E. A., Zotikov E. A., Tumanov V. P. Structural bases of adaptation and compensation of disturbed functions. M.: Medicine; 1987; 448 p. (in russ.).

2. Potekhina Yu. P., Tregubova E. S., Mokhov D. E. The phenomenon of somatic dysfunction and the mechanisms of osteopathic treatment. Med. News North Caucasus. 2020; 15 (1): 145–152 (in russ.). https://doi.org/10.14300/mnnc.2020.15036

3. Poletaev A. B. The main principles of adaptive immune system function: self-recognition, self-interaction, and self-maintenance // In: Physiologic Autoimmunity and Preventive Medicine / Ed. A. B. Poletaev. Bentham Science; 2013: 3–20. https://doi.org/10.2174/97816080572451130101

4. Poletaev A. B. Antibodies to insulin receptors as a biomarker of the precursor of diabetes mellitus type 2. Terra Medica. 2013; 1 (71): 22–26 (in russ.).

5. Elkon K., Casali P. Nature and functions of autoantibodies. Nature clin. Pract. Rheumatol. 2008; 4 (9): 491–498. https://doi.org/10.1038/ncprheum0895

6. Metchnikoff E., Mečnikov I. The evolutionary biology papers of Elie Metchnikoff. Springer Science & Business Media; 2000; 212 p.

7. Poletaev A. B. Physiological immunology (natural autoantibodies and problems of nanomedicine). M.: Miklosh; 2010; 218 p. (in russ.).

8. Zaichik A. M., Poletaev A. B., Churilov L. P. Natural autoantibodies, immunological theories and preventive medicine. Vestn. Saint-Petersburg University. Medicine. 2013; (2): 3–16 (in russ.).

9. Poletaev A., Osipenko L. General network of natural autoantibodies as immunological homunculus (Immunculus). Autoimmun. Rev. 2003; 2 (5): 264–271. https://doi.org/10.1016/S1568-9972(03)00033-8

10. Poletaev A. B., Stepanyuk V. L., Gershwin M. E. Integrating immunity: the immunculus and self-reactivity. J. Autoimmun. 2008; 30 (1–2): 68–73. https://doi.org/10.1016/j.jaut.2007.11.012

11. Bizzaro N. Autoantibodies as predictors of disease: the clinical and experimental evidence. Autoimmun. Rev. 2007; 6 (6): 325-–333. https://doi.org/10.1016/j.autrev.2007.01.006

12. Agrawal S., Misra R., Aggarwal A. Autoantibodies in rheumatoid arthritis: association with severity of disease in established RA. Clin. Rheumatol. 2007; 26 (2): 201–204. https://doi.org/10.1007/s10067-006-0275-5

13. Caforio A. L., Mahon N. G., Baig M. K., Tona F., Murphy R. T., Elliott P. M., McKenna W. J. Prospective familial assessment in dilated cardiomyopathy: cardiac autoantibodies predict disease development in asymptomatic relatives. Circulation. 2007; 115 (1): 76–83. https://doi.org/10.1161/CIRCULATIONAHA.106.641472

14. Eckstein A. K., Plicht M., Lax H., Neuhäuser M., Mann K., Lederbogen S., Heckmann C., Esser J., Morgenthaler N. G. Thyrotropin receptor autoantibodies are independent risk factors for Graves′ ophthalmopathy and help to predict severity and outcome of the disease. J. clin. Endocr. Metab. 2006; 91 (9): 3464–3470. https://doi.org/10.1210/jc.2005-2813

15. Parikka V., Näntö-Salonen K., Saarinen M., Simell T., Ilonen J., Hyöty H., Veijola R., Knip M., Simell O. Early seroconversion and rapidly increasing autoantibody concentrations predict prepubertal manifestation of type 1 diabetes in children at genetic risk. Diabetologia. 2012; 55 (7): 1926–1936. https://doi.org/10.1007/s00125-012-2523-3

16. Werb Z. ECM and cell surface proteolysis: regulating cellular ecology. Cell. 1997; 91 (4): 439–442. https://doi.org/10.1016/S0092-8674(00)80429-8

17. Lukashev M. E., Werb Z. ECM signalling: orchestrating cell behaviour and misbehaviour. Trends cell Biol. 1998; 8 (11): 437–441. https://doi.org/10.1016/S0962-8924(98)01362-2

18. Varner J. A., Cheresh D. A. Integrins and cancer. Curr. Opin. cell Biol. 1996; 8 (5): 724–730. https://doi.org/10.1016/S0955-0674(96)80115-3

19. Poletaev A. B., Churilov L. P., Stroev Yu. I., Agapov M. M. Immunophysiology versus immunopathology: Natural autoimmunity in human health and disease. Pathophysiology. 2012; 19 (3): 221–231. https://doi.org/10.1016/j.pathophys.2012.07.003

20. Mokhov D. E., Tregubova E. S., Belash V. O., Yushmanov I. G. A modern view of the osteopathy methodology. Manual Ther. J. 2014; 4 (56): 59–65 (in russ.)].

21. Malinovsky E. L., Novoseltsev S. V., Ivashkevich L. A. Models of organism′s adaptive reactions to the osteopathictreatment. Overview of methods and possibilities. Russian Osteopathic Journal. 2011; 1–2: 117–129 (in russ.)].

22. Mokhov D. E., Aptekar I. A., Belash V. O., Litvinov I. A., Mogelnitsky A. S., Potekhina Yu. P., Tarasov N. A., Tarasova V. V., Tregubova E. S., Ustinov A. V. The basics of osteopathy: A textbook for residents. M.: GEOTAR-Media; 2020; 400 p. (in russ.)].

23. Chen C. S., Mrksigh M., Huang S., Whitesides G. M., Ingber D. E. Geometric control of cell life and death. Science. 1997; 276 (5317): 1425–1428. https://doi.org/10.1126/science.276.5317.1425

24. Ingber D. E. Cellular basis of mechanotransduction. Biologic. Bull. 1998; 194 (3): 323–327. https://doi.org/10.2307/1543102

25. Wang N., Tytell J. D., Ingber D. E. Mechanotransduction at a distance: mechanically coupling the extracellular matrix with the nucleus. Nature Rev. molec. cell Biol. 2009; 10 (1): 75–82. https://doi.org/10.1038/nrm2594

26. McGaw W. T. The effect of tension on collagen remodelling by fi broblasts: a stereological ultrastructural study. Connect. Tiss. Res. 1986; 14 (3): 229–235. https://doi.org/10.3109/03008208609014263

27. Langevin H. M., Sherman K. J. Pathophysiological model for chronic low back pain integrating connective tissue and nervous system mechanisms. Med. Hypothes. 2007; 68 (1): 74–80. https://doi.org/10.1016/j.mehy.2006.06.033

28. Aptekar A. I., Kostolomova E. G., Sukhovey Y. G. Сhange in the functional activity of fi broblasts in the process of modelling of compression, hypercapnia and hypoxia. Russian Osteopathic Journal. 2019; 1–2: 72–84 (in russ.)]. https://doi.org/10.32885/2220-0975-2019-1-2-72-

29. Potehina Yu. P. Role of Connective Tissue in the Body. Russian Osteopathic Journal. 2015; 3–4: 92–104 (in russ.)]. https://doi.org/10.32885/2220-0975-2015-3-4-92-104

30. Schleip R. Fascial plasticity — a new neurobiological explanation: Part 1. J. Bodywork movement Ther. 2003; 7 (1): 11–19. https://doi.org/10.1016/S1360-8592(02)00067-0