A model of clinical symptoms in patients with chronic fatigue syndrome with postCOVID

Lidia Soprun, Natalia Gavrilova, Varavara Ryabkova, Sergey Yastrebov

Saint-Petersburg State University, Saint-Petersburg, Russia;
Saint-Petersburg State University Hospital, Saint-Petersburg, Russia;
Ioffe Physical-Technical Institute of the Russian Academy of Sciences, Saint Petersburg, Russia

Cite: Soprun L., Gavrilova N., Ryabkova V., Yastrebov S. A model of clinical symptoms in patients with chronic fatigue syndrome with postCOVID. JDAH 4(2), 22-30, (2023). https://doi.org/10.33847/2712-8149.4.2_3

Download PDF

Abstract. Post-covid syndrome was defined as the presence of symptoms and/or signs of damage to various organ systems that develop during or after a previous COVID-19 infection persist for more than 12 weeks and cannot be explained by an alternative diagnosis. (A Quick Guide to COVID-19: Managing the Long-term Effects of COVID-19 (NG188). Chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) can be described as a disease of unknown etiology characterized by the presence of permanent fatigue that does not recover after the proper rest, accompanied by various somatic symptoms. Establishment of the diagnosis is based on the analysis of clinical manifestations, however, due to their diversity; it takes a lot of time and medical experience. The application of the statistical analysis may allow simplifying and unifying this task. At the same time, considering diverse manifestations of the CFS/ME, one may allude that there are several different clinical variations of this disease and, therefore, symptoms can be grouped into “clusters”. In this paper a possible correlation was revealed between various clinical symptoms of CFS/ME, using the principal component analysis (PCA) associated with the correlation coefficients of the Pearson’s matrix. A hypothetical physical model of the correlation of immunological symptoms was created. In addition to the positive correlation expected for the symptoms of one disease, negative relationships were also revealed, which may represent some unknown pathophysiological processes of CFS/ME and requires further study. The identification of key symptoms in patients of this group can contribute to the introduction of new diagnostic criteria, which will lead to an improvement in the quality of life and medical care for these patients.
Keywords: Chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME), principal component analysis (PCA), fever, chills, skin rash, flu-like symptoms, swollen lymph nodes, postCOVID, COVID-19.

Acknowledgments

The work was performed at the Department of Healthcare Organization and Medical Law of St. Petersburg State University and Institute of Physics and Ioffe Physical-Technical Institute of the Russian Academy of Sciences under the budgetary financing.
This work was supported by a grant from the Government of the Russian Federation (contract 14.W03.31.0009 dated February 13, 2017) on the allocation of a grant for state support of scientific research conducted under the guidance of leading scientists. The authors contributed equally to the writing of the work.

References

  1. Sotzny F, et al. European Network on ME/CFS (EUROMENE). Myalgic Encephalomyelitis/Chronic Fatigue Syndrome – Evidence for an autoimmune disease. Autoimmun Rev. 2018 Jun;17(6):601-609. doi: 10.1016/j.autrev.2018.01.009. Epub 2018 Apr 7. PMID: 29635081.).
  2. Ryabkova VA, Churilov LP, Shoenfeld Y. Neuroimmunology: What Role for Autoimmunity, Neuroinflammation, and Small Fiber Neuropathy in Fibromyalgia, Chronic Fatigue Syndrome, and Adverse Events after Human Papillomavirus Vaccination? Int J Mol Sci. 2019 Oct 18;20(20):5164. doi: 10.3390/ijms20205164. PMID: 31635218; PMCID: PMC6834318.
  3. Shoenfeld Y, et al. Complex syndromes of chronic pain, fatigue and cognitive impairment linked to autoimmune dysautonomia and small fiber neuropathy. Clin Immunol. 2020 May;214:108384. doi: 10.1016/j.clim.2020.108384. Epub 2020 Mar 17. PMID: 32171889.
  4. Sharif K, et al. On chronic fatigue syndrome and nosological categories. Clin Rheumatol. 2018 May;37(5):1161-1170. doi: 10.1007/s10067-018-4009-2. Epub 2018 Feb 7. PMID: 29417255.
  5. Smith J, et al. Association of chronic fatigue syndrome with human leucocyte antigen class II alleles. J Clin Pathol. 2005;58:860-3.
  6. Ortega-Hernandez OD, Shoenfeld Y. Infection, vaccination, and autoantibodies in chronic fatigue syndrome, cause or coincidence? Annals of the New York Academy of Sciences. 2009;1173:600-9.
  7. Loebel M, et al. Serological profiling of the EBV immune response in Chronic Fatigue Syndrome using a peptide microarray. PloS one. 2017;12:e0179124
  8. Chapenko S, et al. Association of active human herpesvirus-6, -7 and parvovirus b19 infection with clinical outcomes in patients with myalgic encephalomyelitis/chronic fatigue syndrome. Advances in virology. 2012;2012:205085.
  9. Bradley AS, Ford B, Bansal AS. Altered functional B cell subset populations in patients with chronic fatigue syndrome compared to healthy controls. Clinical and experimental immunology. 2013;172:73-80
  10. Brenu EW, et al. Role of adaptive and innate immune cells in chronic fatigue syndrome/myalgic encephalomyelitis. International immunology. 2014;26:233-42.
  11. Curriu M, et al. Screening NK-, B- and T-cell phenotype and function in patients suffering from Chronic Fatigue Syndrome. Journal of translational medicine. 2013;11:68.
  12. Katz BZ, et al. The International Collaborative on Fatigue Following Infection (COFFI). Fatigue 2018; 6: 106–121.
  13. Rasa S, et al. Chronic viral infections in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). J Transl Med. 2018;16(1):268. Published 2018 Oct 1. doi:10.1186/s12967-018-1644-y
  14. Jason LA, Sunnquist M. The Development of the DePaul Symptom Questionnaire: Original, Expanded, Brief, and Pediatric Versions. Front Pediatr. 2018;6:330. Published 2018 Nov 6. doi:10.3389/fped.2018.00330
  15. Berridge M.J. Biochem. J. 2017. Vol. 474. N 8. Р. 1321–1332. DOI: 10.1042/ BCJ20170042
  16. Terenetskaya I.P. Integr. Mol. Med. 2018. Vol. 5. N 2. Р. 1–5. DOI: 10.15761/IMM.1000327 
  17. Szalecki M., Wysocka-Mincewicz M., Ramotowska A., Mazur A., Lisowicz L., Beń-Skowronek I., Sieniawska J., Klonowska B., Charemska D., Nawrotek J., Jałowiec I., Bossowski A., Jamiołkowska M., Pyrżak B., Miszkurka G., Szypowska A. Res. Rev. 2018. Vol. 34. N 2. DOI: 10.1002/dmrr.2962
  18. Principal Component Analysis I.T. Jolliffe. Second Edition, Springer NY.: 2002. 487 p. DOI: 10.1007/b98835
  19. Verstraete L., Leger A. Astron. Astrophys. 1996. Vol. 240. N 1. Р. 55–73. DOI: 10.1007/BF00640196
  20. Guide in Autoimmune Diseases for General medical Practice. Y. Shoenfeld, P.L. Meroni, L.P. Churilov. Saint Petersburg: ELBI-Medkniga, 2017. 416 c.

Published online 13.12.2023