Rheumatoid arthritis (RA) is a common, chronic autoimmune disease that causes joint damage and deformity associated with an increased disability risk and shortened life expectancy (1). New treatment methods have significantly improved disease control, but remission is still difficult to be achieved, so new and improved treatment and diagnostic options are needed for patients stratification and prognosis. To achieve this goal, the proposed study will be aimed at studying RA main factors' relationship. The project's central theme is that microbial dysbiosis is a critical determinant of RA pathogenesis, and the interaction between human factors and the microbiome contributes to the disease risk and it's activity.
The microbiome plays a fundamental role in diseases and human health. Technological advances in recent decades have expanded our understanding of microbes and their ability to form innate and acquired human immune responses. Advances in understanding the microbiome's impact on human immunity, along with the realization that inflammatory processes underlie a number of common diseases, including RA, necessitates an interdisciplinary approach to studying the interaction of humans and microbes at various levels. Modern sequencing technologies and new tools development for analyzing metagenomic data allow us to understand better the complex relationship between the dynamic microbes community inhabiting mucous tissues and the human immune system. Such analysis is especially relevant in Central Asia, since the investigators not only identified ethnic differences in risk loci, but also found that the composition of the intestinal and oral microbiota of Kazakhs is unique and significantly differs from the corresponding microbiota in other world regions, due to lifestyle factors characteristic of Kazakhstan and common to the whole Central Asia. The main research's purpose is to study the complex relationship between microbiome dysbiosis, local and systemic inflammation in relation to RA pathogenesis and the disease activity in the Kazakhstan population. The investigators assume that patients with RA have greater dysbiosis (local microbiota violation) in the intestine and oral cavity compared to the control group, and that it is due to a greater inflammatory response and disease activity. To consider this hypothesis, microbiome biomarkers of the oral cavity and gut in RA will be identified, RA patients immunological parameters in blood, stool and saliva samples will be analyzed, an dynamics assessment of the microbiome and immunological profile against the probiotic therapy background and an analysis of the relationships between microbiome and immunological profiles will be carried out. The research's scientific novelty and significance consist in the study of the local and general immune status in combination with the microbiomes of the oral cavity and gut in RA. The results are likely not only to give a new insight into the relationship between human factors and pathogenic factors, but may also affect the RA diagnosis, the disease activity prognosis and inform preventive strategies. Thus, a better understanding of the complex microbial interactions with the immune system of the mucous membrane in RA can advance our understanding of RA pathophysiology, help predict future relapses, develop strategies for prevention and early diagnosis, and lead to new therapeutic directions' development aimed at the microbiome. The results impact on the science and technology development contribute to the first comprehensive study of the RA pathogenesis in the Central Asian population. The investigators expect not only to receive important new information about the RA etiopathogenesis, but also the complex interaction that determines the pathogenesis and disease activity. The proposed study has the potential not only to improve the methods of diagnosis and monitoring of RA patients in Kazakhstan, but also can contribute to a better RA understanding in general, paving the way for personalized diagnosis and treatment of rheumatic diseases.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
50
probiotic including bifidobacterium
the oral cavity and gut microbiome
An analysis of the biodiversity of the oral cavity and intestine will be carried out against the background of probiotic therapy: Alpha and Betta diversity according to the main indices: Chao1, Shannon, Simpson etc. The number of taxa associated with the severity of RA will be estimated using LDA. It will be analyzed to what extent probiotic therapy corrects the functional profile of the oral and intestinal microbiomes.
Time frame: Change from Baseline the oral cavity and gut microbiome immediately after probiotic therapy
the oral cavity and gut microbiome
An analysis of the biodiversity of the oral cavity and intestine will be carried out against the background of probiotic therapy: Alpha and Betta diversity according to the main indices: Chao1, Shannon, Simpson etc. The number of taxa associated with the severity of RA will be estimated using LDA. It will be analyzed to what extent probiotic therapy corrects the functional profile of the oral and intestinal microbiomes.
Time frame: Change from Baseline the oral cavity and gut microbiome at 1 month
the immunological profile
the levels of the following inflammatory cytokines, chemokines and immunoglobulins will be measured in stool samples, oral swabs and blood: sCD40L (pg/mL) , EGF (pg/mL), Eotaxin/CCL11(pg/mL), FGF-2 (pg/mL), Flt-3 ligand (pg/mL), Fractalkine (pg/mL), G-CSF (pg/mL), GM-CSF (pg/mL), GRO (pg/mL), IFN-α2 (pg/mL), IFN-γ (pg/mL), IL-1α (pg/mL), IL-1β (pg/mL), IL-1ra (pg/mL), IL-2 (pg/mL), IL-3 (pg/mL), IL-4 (pg/mL), IL-5 (pg/mL), IL-6 (pg/mL), IL-7(pg/mL), IL-8(pg/mL), IL-9(pg/mL), IL-10(pg/mL), IL-12 (p40)(pg/mL), IL-12 (p70)(pg/mL), IL-13(pg/mL), IL-15(pg/mL), IL-17A(pg/mL), IP-10(pg/mL), MCP-1(pg/mL), MCP-3(pg/mL), MDC (CCL22)(pg/mL), MIP-1α(pg/mL), MIP-1β(pg/mL), PDGF-AA(pg/mL), PDGF-AB/BB(pg/mL), RANTES(pg/mL), TGF-α(pg/mL), TNF-α(pg/mL), TNF-β(pg/mL), VEGF(pg/mL), IgA (g/L), IgG1-G4 (g/L), IgM (g/L).
Time frame: Change from Baseline the oral cavity and gut microbiome immediately after probiotic therapy
the immunological profile
the levels of the following inflammatory cytokines, chemokines and immunoglobulins will be measured in stool samples, oral swabs and blood: sCD40L (pg/mL) , EGF (pg/mL), Eotaxin/CCL11(pg/mL), FGF-2 (pg/mL), Flt-3 ligand (pg/mL), Fractalkine (pg/mL), G-CSF (pg/mL), GM-CSF (pg/mL), GRO (pg/mL), IFN-α2 (pg/mL), IFN-γ (pg/mL), IL-1α (pg/mL), IL-1β (pg/mL), IL-1ra (pg/mL), IL-2 (pg/mL), IL-3 (pg/mL), IL-4 (pg/mL), IL-5 (pg/mL), IL-6 (pg/mL), IL-7(pg/mL), IL-8(pg/mL), IL-9(pg/mL), IL-10(pg/mL), IL-12 (p40)(pg/mL), IL-12 (p70)(pg/mL), IL-13(pg/mL), IL-15(pg/mL), IL-17A(pg/mL), IP-10(pg/mL), MCP-1(pg/mL), MCP-3(pg/mL), MDC (CCL22)(pg/mL), MIP-1α(pg/mL), MIP-1β(pg/mL), PDGF-AA(pg/mL), PDGF-AB/BB(pg/mL), RANTES(pg/mL), TGF-α(pg/mL), TNF-α(pg/mL), TNF-β(pg/mL), VEGF(pg/mL), IgA (g/L), IgG1-G4 (g/L), IgM (g/L).
Time frame: Change from Baseline the oral cavity and gut microbiome at 1 month
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