MULTIVARIATE MODELLING OF THE IMMUNE STATUS IN DETECTION OF SECONDARY IMMUNODEFICIENCY AND THE ALLERGY

Immune status of healthy people, patients with secondary immunodeficiency and allergic diseases is assessed. To reduce the number of characteristics of immunity (23 indicators) to a number of the generalizing factors the multivariate analysis is used (principal component method). This method consistently reveals the principal components – independent functional complexes of interacting factors, with the characteristic of force of their interrelation. The principal components reflect communications between separate indicators and are located in size of their contribution to the total amount of information. The method is applied to structuring immunological indicators and a possibility of detection of features (distinctions) of the immune status of patients with secondary immunodeficiency and allergic diseases. The method of principal components when it is applied to the assessment of immune status creates welldefined pattern of a functional condition of the immune system, accentuating main types of the reacting immunocompetent cells, their combinations and interaction. In the general immune status of healthy people (blood donors) the T cell compartment (the first and second the principal components) plays the major role. The second in importance components reflect the humoral immunity status. The indicators describing the response of the innate immunity (natural killer cells, the system phagocytic cells), follow them. Mathematical modeling reveals hierarchy of responses of innate and adaptive immunity, which is in agreement with established mechanisms of immune response. Differences of individual indicators of principal components of donors blood (norm), the patients with secondary immunodeficiency and allergic diseases built in the first, second and fourth to the principal components are detected. They group and display the status of 40% of the total amount (dispersion) of immunological information taken in the analysis accentuating quantity and a functionality of T cells subpopulations and to a lesser extent – the level of B cells. In case of secondary immunodeficiency the major part of distribution of values principal individual components is in a zone of negative values, and in case of allergic diseases – in a zone of positive values, indicators of the norm are in the intermediate position. Distribution of the principal component, reflecting immunoregulatory index is similar. The principal component value describing the activation of T cells, exceeded the norm, in case of secondary immunodeficiency, and in case of allergies. Multivariate mathematical analysis of immune status demonstrates its usefulness for differential diagnosis of secondary immunodeficiency and an allergic diseases.

1. Гланц. С. Медико-биологическая статистика / Пер. с англ. Ю.А. Данилова. М.: Практика, 1998. 459 с. [Glantz S. Medicobiological statistics (English Transl. Yu.A. Danilov)]. Moscow: Practice, 1998. 459 p.

2. Дубровская Л.И., Князев Г.Б. Компьютерная обработка естественно-научных данных методами многомерной прикладной статистики. Томск: ТМЛ-Пресс, 2011. 120 с. [Dubrovskaya L.I., Knyazev G.B. Computer processing naturally scientific data by methods of multidimensional applied statistics]. Tomsk: TMLPress 2011. 120 р.

3. Реброва О.Ю. Статистический анализ медицинских данных. М.: МедиаСфера, 2006. 312 с. [Rebrova O. Yu. Statistical analysis of medical data]. Moscow: MediaSfera, 2006. 312 p.

4. Сарап П.В., Винник Ю.С., Останин А.А. Использование факторного анализа для оценки показателей иммунного статуса больных с хирургической патологией // Современные наукоемкие технологии, 2009. № 3. С. 84-85. [Sarap P.V., Vinnik Yu.S., Ostanin A.A. Use of the factorial analysis for an assessment of indicators of the immune status of patients with surgical pathology. Sovremennye naukoemkie tekhnologii = Modern High Technologies, 2009, no. 3, pp. 84-85. (In Russ.)]

5. Халафян А.А. Учебник STATISTICA 6 Статистический анализ данных. М.: Бином, 2007. 503 c. [Khalafyan A.A. Textbook STATISTICA 6 Statistical analysis of data]. Moscow: Binom, 2007. 503 p.

6. Чепелева М.В. Факторный анализ в оценке состояния клеточного иммунитета у пациентов с гнойно-воспалительными заболеваниями длинных трубчатых костей и крупных суставов // Клиническая лабораторная диагностика, 2013. № 11. С. 41-45. [Chepeleva M.V. The factorial analysis in evaluation of cell immunity of patients with pyo-inflammatory diseases of long bones and large joints. Klinicheskaya laboratornaya diagnostika = Russian Clinical Laboratory Diagnostics, 2013, no. 11, pp. 41-45. (In Russ.)]

7. Ярилин А.А. Иммунология. М.: ГЭОТАР-Медиа, 2010. 752 с. [Yarilin A.A. Immunology]. Moscow: GEOTAR-Media, 2010. 752 р