The subgingival microbiome in patients with established rheumatoid arthritis

Ted R Mikuls; Clay Walker; Fang Qiu; Fang Yu; Geoffrey M Thiele; Barnett Alfant; Eric C Li; Lisa Y Zhao; Gary P Wang; Susmita Datta; Jeffrey B Payne

doi:10.1093/rheumatology/key052

The subgingival microbiome in patients with established rheumatoid arthritis

Rheumatology (Oxford). 2018 Jul 1;57(7):1162-1172. doi: 10.1093/rheumatology/key052.

Authors

Ted R Mikuls^{1

2}, Clay Walker³, Fang Qiu⁴, Fang Yu⁴, Geoffrey M Thiele^{1

2}, Barnett Alfant³, Eric C Li⁵, Lisa Y Zhao⁵, Gary P Wang^{5

6}, Susmita Datta⁷, Jeffrey B Payne^{1

8}

Affiliations

¹ Department of Internal Medicine, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA.
² Medicine, Veterans Affairs Nebraska-Western Iowa Health Care System, Omaha, NE, USA.
³ Department of Oral Biology, College of Dentistry, University of Florida, Gainesville, FL, USA.
⁴ Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA.
⁵ Department of Medicine, College of Medicine, University of Florida, Gainesville, FL, USA.
⁶ Medicine, North Florida/South Georgia Veterans Health System, Gainesville, FL, USA.
⁷ Department of Biostatistics, College of Public Health & Health Professions College of Medicine, University of Florida, Gainesville, FL, USA.
⁸ Department of Surgical Specialties, College of Dentistry, University of Nebraska Medical Center, Lincoln, NE, USA.

PMID: 29562298
DOI: 10.1093/rheumatology/key052

Abstract

Objectives: To profile and compare the subgingival microbiome of RA patients with OA controls.

Methods: RA (n = 260) and OA (n = 296) patients underwent full-mouth examination and subgingival samples were collected. Bacterial DNA was profiled using 16 S rRNA Illumina sequencing. Following data filtering and normalization, hierarchical clustering analysis was used to group samples. Multivariable regression was used to examine associations of patient factors with membership in the two largest clusters. Differential abundance between RA and OA was examined using voom method and linear modelling with empirical Bayes moderation (Linear Models for Microarray Analysis, limma), accounting for the effects of periodontitis, race, marital status and smoking.

Results: Alpha diversity indices were similar in RA and OA after accounting for periodontitis. After filtering, 286 taxa were available for analysis. Samples grouped into one of seven clusters with membership sizes of 324, 223, 3, 2, 2, 1 and 1 patients, respectively. RA-OA status was not associated with cluster membership. Factors associated with cluster 1 (vs 2) membership included periodontitis, smoking, marital status and Caucasian race. Accounting for periodontitis, 10 taxa (3.5% of those examined) were in lower abundance in RA than OA. There were no associations between lower abundance taxa or other select taxa examined with RA autoantibody concentrations.

Conclusion: Leveraging data from a large case-control study and accounting for multiple factors known to influence oral health status, results from this study failed to identify a subgingival microbial fingerprint that could reliably discriminate RA from OA patients.

Keywords: osteoarthritis; periodontitis; rheumatoid arthritis; subgingival microbiome.