Preview

Humans and their health

Advanced search

Multivariate analysis in the immune system evaluation in patients with seasonal allergic rhinitis

https://doi.org/10.21626/vestnik/2021-1/04

Abstract

Objective. The paper analyzes the immunological parameters to identify their hidden relationships and informativeness by multivariate analysis in patients with seasonal allergic rhinitis taking into account gender differences.

Materials and methods. The immune status of 112 patients with seasonal allergic rhinitis was examined. The number of eosinophils, the phenotype of lymphocytes (CD3+CD4+; CD3+CD8+; CD3-CD19+), the concentrations of cytokines (IL-1β, IL-4, IL-8, IL-10, IFN-γ), antimicrobial peptide - α-defensin (HNP1-3), and serum immunoglobulin E was investigated. The principal components were analyzed.

Results. The results obtained enabled to identify the most important principal components of immunological parameters, taking into account the magnitude of the correlation coefficients in patients with seasonal allergic rhinitis. The role of various immunity indicators and their contribution to the immune system functioning was studied considering gender differences. In women in the first complex, CD4 (r = -0.75), CD19 (r = -0.70) have the greatest influence, in the second one - Ig E (r = 0.73) and blood eosinophils (r = 0.78). In men in the first complex, a high contribution was made by the serum Ig E concentration (r = 0.87) and the blood eosinophils number (r = 0.82). The high contribution of the serum IL 10 level (r = 0.72) in women is reflected in the fifth complex, where the age was the most significant for men (r = 0.82).

Conclusion. The multivariate analysis method using confirms the possibility of revealing hidden relationships between the studied parameters. The detection of connected combinations between immunological parameters creates the main complexes, taking into account their contribution to the general characteristics of the immune system in patients with seasonal allergic rhinitis.

About the Authors

Svetlana M. Yudina
Kursk State Medical University
Russian Federation

Dr. Sci. (Med.), Professor, Head of the Department of Clinical Immunology, Allergology and Phthisiopulmonology



Olga V. Tarabrina
Kursk State Medical University
Russian Federation

Assistant of the Department of Clinical Immunology, Allergology and Phthisiopulmonology



Alexandra V. Arkhipova
Kursk State Medical University
Russian Federation

Cand. Sci. (Med.), Associate Professor, Associate Professor of the Department of Clinical Immunology, Allergology and Phthisiopulmonology



Inna A. Ivanova
Kursk State Medical University
Russian Federation

Cand. Sci. (Med.), Associate Professor, Associate Professor of the Department of Clinical Immunology, Allergology and Phthisiopulmonology



References

1. Дубровская Л.И., Князев Г.Б. Компьютерная обработка естественнонаучных данных методами многомерной прикладной статистики. Томск: ТМЛ-Пресс, 2011. 120 с.

2. Кузьмина Е.Г., Зацаренко С.В. Многофакторное моделирование иммунного статуса в выявлении вторичных иммунодефицитных состояний и аллергии. Медицинская иммунология. 2017;19(3):275-284. DOI: 10.15789/1563-0625-2017-3-275-284

3. Новиков Д.К., Новиков П.Д., Карпук И.Ю., Смирнова О.В., Выхристенко Л.Р., Величинская О.В. Новые методы диагностики и лечения аллергии. Аллергология и иммунология. 2015:16(4):335-339

4. du Prel J.B., Röhrig B., Hommel G., Blettner M. Choosing statistical tests: part 12 of a series on evaluation of scientific publications. Dtsch Arztebl Int. 2010;107(19):343-348. DOI: 10.3238/arztebl.2010.0343

5. George B.J., Beasley T.M., Brown A.W., Dawson J., Dimova R., Divers J., Goldsby T.U., Heo M. et al. Common scientific and statistical errors in obesity research. Obesity (Silver Spring). 2016;24(4):781-790. DOI: 10.1002/oby.21449

6. Hajian-Tilaki K. Sample size estimation in diagnostic test studies of biomedical informatics. J Biomed Inform. 2014;48:193-204. DOI: 10.1016/j.jbi.2014.02.013

7. Jenssen H., Hamill P., Hancock R.E. Peptide antimicrobial agents. Clin Microbiol Rev. 2006;19(3): 491-511. DOI: 10.1128/CMR.00056-05

8. Malone H.E., Nicholl H., Coyne I. Fundamentals of estimating sample size. Nurse Res. 2016;23(5): 21-25. DOI: 10.7748/nr.23.5.21.s5

9. Monteseirín J. Neutrophils and asthma. J Investig Allergol Clin Immunol. 2009;19(5):340-354

10. Staggs V.S. Pervasive errors in hypothesis testing: Toward better statistical practice in nursing research. Int J Nurs Stud. 2019;98:87-93. DOI: 10.1016/j.ijnurstu.2019.06.012

11. Thiese M.S. Observational and interventional study design types; an overview. Biochem Med (Zagreb). 2014;24(2):199-210. DOI: 10.11613/BM.2014.022


Review

For citations:


Yudina S.M., Tarabrina O.V., Arkhipova A.V., Ivanova I.A. Multivariate analysis in the immune system evaluation in patients with seasonal allergic rhinitis. Humans and their health. 2021;24(1):30-36. (In Russ.) https://doi.org/10.21626/vestnik/2021-1/04

Views: 452


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1998-5746 (Print)
ISSN 1998-5754 (Online)