The vaginal bacterial dysbiosis severity predicting model according to the normobiota index

Abstract

The local and systemic immunodeficiency is the main mechanism for vaginal bacterial dysbiosis and its extreme manifestation – bacterial vaginosis (BV) development. The complex immune response study and the establishment of the main mechanisms and factors, reflecting it and corresponding to the microbiocenosis severity disorder are relevant. Aim – to develop a neural network model of the severity of vaginal bacterial dysbiosis based on the assessment of normobiota. Divided into the following groups according to the Conditionally pathogenic microflora index (CPMI) and normobiota index (NBI): normocenosis (n=53), dysbiosis I (n=128) and II degree (n=117) among the latter 83 patients with PNB>1 lg GE/sample were identified, in whom BV was established. Molecular genetic studies of the epithelium scraping from the vagina posterolateral wall were carried out by Polymerase chain reaction (“DNK-Technologiia” LLC, RF). Facultative and obligate anaerobes, myco- and ureplasmas, and yeast-like fungi were quantified. The content of immunoglobulins, lysozyme, cytokines, complement, phagocytosis activity of leukocytes, hormones, the number of lymphocytes and their fractions, as well as the vaginal discharge pH (a total of 58 indexes) were identified in blood and vaginal discharge. For statistical and mathematical analysis, the Statistica 10 software (StatSoft, Inc., USA) was used. Using neural network modeling, it was revealed that among all the factorial signs for determining the bacterial dysbiosis degree, the complement component C4 and γ-INF content in the vaginal discharge and circulating immune complexes (CIC) and TNFα in the blood were important. A linear neural network model was built on the selected set of factor signs (the Cohen’s kappa coefficient consent index on the training set was k=0.87 (95% CI 0.82-0.91) for confirming plurality – k=0.89 (95% CI 0.77-1.00). With normocenosis, the complement activation PNB was decreased, and γ-INF and TNFα content was increased. The CIC levels blood increase corresponded to the opportunistic microflora growth and reflected the humoral immune response activation, which suggests that this indicator is an early dysbiosis marker. With I degree dysbiosis all factors had positive relationship with NBI, which reflected the immune system stress state. In case of II degree dysbiosis, NBI had a negative relationship with γ-INF content in the vaginal discharge, and CIC in the blood, while positive – with C4 content in vaginal discharge, and TNFα in the blood, which proved the immune system dysregulation and caused its further suppression with the BV-association immunodeficiency development. The immune system reaction during the BV development evolved from non-specific resistance reactions to cytokine-induced reactions of specific humoral immunity in response to the BV-associated microbiota growth, which subsequently experienced depletion and loss of immune control.