Salivary Microbiota and Host-Inflammatory Responses in Periodontitis Affected Individuals With and Without Rheumatoid Arthritis

• Published in: Frontiers in cellular and infection microbiology Vol. 12; p. 841139
• Main Authors: Eriksson, Kaja, Lundmark, Anna, Delgado, Luis F., Hu, Yue O. O., Fei, Guozhong, Lee, Linkiat, Fei, Carina, Catrina, Anca I., Jansson, Leif, Andersson, Anders F., Yucel-Lindberg, Tülay
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 14.03.2022
• Subjects: Arthritis, Rheumatoid; Cellular and Infection Microbiology; Chronic Periodontitis; cytokines; host inflammatory mediators; Humans; Inflammation Mediators; machine learning; Microbiota; periodontitis; rheumatoid arthritis; RNA, Ribosomal, 16S - genetics; saliva; microbiota; saliva; host inflammatory mediators; periodontitis; cytokines; machine learning; rheumatoid arthritis
• ISSN: 2235-2988; 2235-2988
• DOI: 10.3389/fcimb.2022.841139

Periodontitis and rheumatoid arthritis (RA) are two widespread chronic inflammatory diseases with a previously suggested association. The objective of the current study was to compare the oral microbial composition and host´s inflammatory mediator profile of saliva samples obtained from subjects with periodontitis, with and without RA, as well as to predict biomarkers, of bacterial pathogens and/or inflammatory mediators, for classification of samples associated with periodontitis and RA. Salivary samples were obtained from 53 patients with periodontitis and RA and 48 non-RA with chronic periodontitis. The microbial composition was identified using 16S rRNA gene sequencing and compared across periodontitis patients with and without RA. Levels of inflammatory mediators were determined using a multiplex bead assay, compared between the groups and correlated to the microbial profile. The achieved data was analysed using PCoA, DESeq2 and two machine learning algorithms, OPLS-DA and sPLS-DA. Differential abundance DESeq2 analyses showed that the four most highly enriched (log2 FC >20) amplicon sequence variants (ASVs) in the non-RA periodontitis group included sp., sp., sp., and sp. whereas sp., sp., sp., and were the most highly enriched ASVs (log2 FC >20) in the RA group. OPLS-DA with log2 FC analyses demonstrated that the top ASVs with the highest importance included sp. having a positive correlation with non-RA group, and seven ASVs belonging to , sp., , , spp. and with a positive correlation with RA group. Among the detected inflammatory mediators in saliva samples, TWEAK/TNFSF12, IL-35, IFN-α2, pentraxin-3, gp130/sIL6Rb, sIL-6Ra, IL-19 and sTNF-R1 were found to be significantly increased in patients with periodontitis and RA compared to non-RA group with periodontitis. Moreover, correlations between ASVs and inflammatory mediators using sPLS-DA analysis revealed that TWEAK/TNFSF12, pentraxin-3 and IL-19 were positively correlated with the ASVs sp., , sp., and sp. Our results suggest that the combination of microbes and host inflammatory mediators could be more efficient to be used as a predictable biomarker associated with periodontitis and RA, as compared to microbes and inflammatory mediators alone.