Periodontitis (PD) has emerged as a risk factor for rheumatoid arthritis (RA). Affecting more than 20% of the general population (1), PD is an inflammatory disorder initiated by bacterial infection, which has a detrimental impact on the integrity of several different oral tissues, including the gingiva, cementum, and periodontal ligament, ultimately leading to tooth loss. PD and RA share several common disease attributes, including chronic tissue inflammation and, in severe cases, marked destruction of the underlying bone. Similarities between PD and RA extend beyond histopathologic and inflammatory features. Both PD and RA share common risk factors for susceptibility, most notably, HLA–DRB1 alleles and, importantly, cigarette smoking (2–9). Moreover, therapies used in RA have been reported to ameliorate the signs and symptoms of PD (10–12).
Several cross-sectional case–control investigations have corroborated the association of PD with RA, although these findings were not replicated in 2 recent studies (13, 14). Compared to controls, RA patients experience more gingival bleeding, more missing teeth, twice as much loss of soft tissue attachment, and increased alveolar bone loss (15, 16). In a recent study, patients with RA were almost twice as likely as those with osteoarthritis to have moderate-to-severe PD, an association that was independent of age, sex, race, and smoking history (17).
While most studies investigating the relationship between PD and RA have focused on shared inflammatory pathways, few have examined the associations of RA with the bacterial infections that initiate PD. A number of gram-negative oral pathogens have been implicated in PD, and several have garnered attention. Chief among the organisms of interest is Porphyromonas gingivalis. P gingivalis has been reported to be the only prokaryote known to express peptidylarginine deiminase (PAD) (18, 19), an enzyme responsible for the posttranslational modification of arginine into citrulline. Given the predominant role of citrullinated proteins in RA pathogenesis, it has been speculated that infection with P gingivalis could facilitate autoantigen presentation and loss of tolerance in RA (19).
Investigations of P gingivalis in RA have primarily involved studies examining RA patients with established disease. Based on these studies alone, it is not possible to know with certainty whether infection with P gingivalis precedes RA onset or whether it occurs subsequent to RA disease incidence. Therefore, in the present study, we sought to examine the association of P gingivalis infection with the presence of RA-related autoantibodies among individuals at increased risk of developing RA but without clinically evident disease. The existence of such an association in the absence of clinically apparent inflammatory arthritis would strongly support the hypothesis that infection precedes disease and is therefore not simply a consequence of established RA or its treatments. The existence of such an association would also strongly support a central role of P gingivalis in the initiation of RA.
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- SUBJECTS AND METHODS
- AUTHOR CONTRIBUTIONS
There were 284 subjects included in the analyses, including 171 autoantibody negative and 113 autoantibody positive individuals. Of the 113 subjects categorized as autoantibody positive, 38 were further categorized as high-risk based on the presence of ACPA or positive findings on ≥2 RF assays. When high-risk status was alternatively defined as positivity for ACPA or ≥2 of 3 RF isotypes (eliminating RF nephelometry from the definition), there were 33 individuals categorized as being high-risk. Group characteristics are summarized in Table 1. Compared to the autoantibody-negative subjects (mean ± SD age 44 ± 14 years), both the autoantibody-positive group (48 ± 15 years of age; P = 0.044) and the high-risk group (51 ± 16 years of age; P = 0.012) were older at enrollment. No other significant differences between the autoantibody-positive or high-risk groups compared to the autoantibody-negative group were noted. Specifically, there were no group differences in the prevalence of known PD risk factors, including HLA–DRB1 SE positivity, smoking status, or diabetes mellitus (Table 1). Relative to the autoantibody- negative group, there were also no significant differences in the prevalence of self-reported signs and symptoms of PD, including gum bleeding, a diagnosis of gum disease or gingivitis, or the presence of deep periodontal pockets, in either the autoantibody-positive group or the high-risk group.
Table 1. Descriptive characteristics and frequency of self-reported signs and symptoms of periodontitis among SERA participants*
| ||Autoantibody negative (n = 171)||Autoantibody positive (n = 113)||High risk (n = 38)|
|Sociodemographic features and RA risk factors|| || || |
| Age, mean ± SD years||44 ± 14||48 ± 15†||51 ± 16†|
| Female, %||69||73||76|
| Caucasian, %||77||82||82|
| Ever smoked cigarettes, %||37||31||29|
| Diabetes mellitus, %||5||4||5|
| More education than high school, %||79||79||73|
| HLA–DRB1 shared epitope positive, %||55||55||58|
|Signs and symptoms of periodontitis, %|| || || |
| Gum bleeding||22||26||19|
| Gum disease or gingivitis||21||23||19|
| Deep periodontal pockets||15||18||20|
Rates of positivity for the different RA-related autoantibodies in the autoantibody-positive and high-risk groups are summarized in Table 2. Eight of the subjects were ACPA positive, comprising 7% of those positive for at least 1 autoantibody and 21% of the high-risk subgroup.
Table 2. Frequency of RA-related autoantibodies in study participants classified as autoantibody positive or high risk*
| ||Autoantibody positive (n = 113)||High risk (n = 38)|
|ACPA, no. (%)||8 (7)||8 (21)|
|RF, no. (%)|| || |
| Nephelometry||38 (34)||18 (47)|
| ELISA|| || |
| IgA||26 (23)||16 (42)|
| IgM||36 (32)||25 (66)|
| IgG||60 (53)||26 (68)|
Concentrations (log-transformed) of circulating IgG antibody to P gingivalis, P intermedia, and F nucleatum in each study group are shown in Figure 1. Anti–P gingivalis antibody concentrations were significantly correlated with both anti–P intermedia (r = 0.60, P < 0.001) and anti–F nucleatum (r = 0.45, P < 0.001). Log-transformed anti–P gingivalis concentrations were higher in those with at least 1 autoantibody than in those with no autoantibodies (mean ± SD 4.89 ± 1.00 versus 4.59 ± 0.88; P = 0.010), a difference that was numerically greater in high-risk individuals (5.03 ± 1.11 versus 4.59 ± 0.88; P = 0.011).
Figure 1. Log-transformed concentrations of antibody to Porphyromonas gingivalis, Prevotella intermedia, and Fusobacterium nucleatum based on autoantibody-positive (Ab+; n = 113), high-risk (HR; n = 38), or autoantibody-negative (Ab−; n = 171) status. Autoantibody-positive subjects were those positive for ≥1 rheumatoid arthritis– related autoantibody. High-risk subjects were those positive for anti–citrullinated protein antibody or for rheumatoid factor on ≥2 assays (by nephelometry or enzyme-linked immunosorbent assay for IgA, IgM, or IgG isotype). Each data point represents a single subject; horizontal lines and error bars show the mean ± SD. ∗ = P = 0.010; ∗∗ = P = 0.011.
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In contrast, there were no significant differences in anti–P intermedia concentrations among those with at least 1 autoantibody (5.46 ± 0.70; P = 0.564) or in high-risk individuals (5.57 ± 0.48; P = 0.191) as compared to autoantibody-negative individuals (5.42 ± 0.66). Likewise, there was no difference in anti–F nucleatum antibody concentrations among autoantibody-positive individuals (4.49 ± 0.82, P = 0.59) or high-risk individuals (4.48 ± 0.90, P = 0.80) compared to autoantibody-negative individuals (4.44 ± 0.84) (Figure 1). There were no significant differences in the findings on any of the bacterial serologies, including anti–P gingivalis, in comparisons of ACPA-positive subjects (n = 8) with autoantibody-negative subjects (data not shown).
Univariate and adjusted associations of log-transformed anti–P gingivalis, anti–P intermedia, and anti–F nucleatum concentrations with the presence of at least 1 RA-related autoantibody and with high- risk status (versus autoantibody-negative controls) are summarized in Table 3. In unadjusted analyses, anti–P gingivalis concentrations (per log unit increase) were significantly associated with autoantibody-positive status (ORunadj 1.41 [95% CI 1.08–1.85], P = 0.011), but anti– P intermedia (ORunadj 1.11 [95% CI 0.78–1.59], P = 0.563) and anti–F nucleatum (ORunadj 1.08 [95% CI 0.81–1.45], P = 0.594) concentrations were not. Unadjusted associations of anti–P gingivalis with high-risk status (ORunadj 1.68 [95% CI 1.12–2.52], P = 0.012) were also significant, whereas the associations of anti–P intermedia with high-risk status were not significant (ORunadj 1.51 [95% CI 0.82–2.80], P = 0.188). Anti–F nucleatum antibody showed no association with high-risk status, and these results did not change following multivariable adjustment.
Table 3. Associations of antibodies to Porphyromonas gingivalis, Prevotella intermedia, and Fusobacterium nucleatum with the presence of RA-related autoantibodies among SERA participants*
|Bacterial IgG antibody||Autoantibody positive versus control||High risk versus control|
|Univariate||Multivariable model A†||Multivariable model B†||Univariate||Multivariable model A†||Multivariable model B†|
|Anti–P gingivalis|| || || || || || |
| OR (95% CI)||1.41 (1.08–1.85)||1.56 (1.10–2.22)||1.39 (1.00–1.92)||1.68 (1.12–2.52)||1.72 (1.01–2.95)||1.70 (1.05–2.74)|
|Anti–P intermedia|| || || || || || |
| OR (95% CI)||1.11 (0.78–1.59)||0.76 (0.47–1.23)||–||1.51 (0.82–2.80)||0.97 (0.42–2.27)||–|
|Anti–F nucleatum|| || || || || || |
| OR (95% CI)||1.08 (0.81–1.45)||–||0.98 (0.67–1.43)||1.06 (0.69–1.62)||–||1.01 (0.57–1.76)|
The findings of the univariate analyses were not substantially changed following multivariable adjustment referent to anti–P gingivalis concentrations, which remained significant. In contrast, associations of anti–P intermedia concentrations with high-risk status were completely attenuated following multivariable adjustment (ORadj 0.97 [95% CI 0.42–2.27], P = 0.953) (Table 3).
In multivariable analyses that included results from all 3 bacterial serologies in addition to the aforementioned covariates, the association of anti–P gingivalis with autoantibody positivity (ORadj 1.51 [95% CI 1.04–2.20], P = 0.032) and high-risk status (ORadj 1.64 [95% CI 0.94–2.89], P = 0.083) did not change substantially, although the association did not reach statistical significance for high-risk status. Of the covariates examined, including age, sex, race, smoking, HLA–DRB1 SE status, diabetes mellitus, and education, only older age was significantly associated with autoantibody-positive and high-risk status in multivariable models (data not shown). Associations of anti–P gingivalis antibody with high-risk status were also unchanged and remained significant when an alternative definition of high-risk status, consisting of positivity to either ACPA or 2 of the 3 RF isotypes, was used (data not shown).
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Although associations between RA and PD have been noted for several decades (38), the mechanisms underpinning this relationship have not been clearly elucidated. Recent studies, including one from our group (27, 39, 40), have suggested that infection with P gingivalis is a cofactor in the development and progression of RA. We previously observed that antibodies to P gingivalis are found in significantly higher concentrations among patients with RA than among healthy controls recruited from the community (27). Furthermore, in patients with RA, anti–P gingivalis antibody concentrations have been shown to correlate with the presence of ACPA (27, 40). Of 11 different oral bacteria examined in a recent study (41), P gingivalis was shown to be the only organism capable of endogenously citrullinating both fibrinogen and enolase. This is important because autoantibodies directed against the citrullinated form of these antigens are highly specific for RA and have been speculated to play a pathogenic role in disease progression (42). It has been hypothesized that the dual expression of gingipains (lysine- and arginine-specific proteases expressed by several oral bacteria) and PAD by P gingivalis acts in concert in RA, the former producing a carboxy-terminal arginine residue that then serves as a target for bacterially expressed PAD (18). Citrullination by bacterial PAD appears to be distinct from mammalian PAD that more efficiently citrullinates internal arginine residues (43).
In addition to associations with ACPA, P gingivalis along with other oral pathogens have also been speculated to play a role in RF expression. Patients with PD are more likely than controls to be RF-seropositive, and RF has been identified in the gingival tissue and subgingival plaque of patients with PD (44). Because lysine and arginine residues exist in the Fc region of IgG (45), it has been suggested that modification of these domains by bacterially expressed gingipains leads to targeting and binding with RF (19). Whether the association of P gingivalis with RA operates directly through effects on RF or ACPA generation in the oral cavity or in related lymphatic structures remains unknown and needs further study.
The timing and development of RF and ACPA in relationship to each other in the development of RA are also unknown; some studies suggest that ACPAs are generated prior to RF (25, 26), although conversely, a study using samples from the US Department of Defense Serum Repository showed that RF positivity often precedes ACPA expression (46). This area of study is particularly relevant when trying to understand the mechanisms by which PD and infection with P gingivalis may lead to the development of RA-related autoimmunity. For example, given the association of PD with elevations of RF levels in the oral cavity and the association in our study of elevated levels of antibody to P gingivalis in subjects that predominantly had only circulating elevations of RF, P gingivalis infection may initially lead to the development of RF, followed by the generation of ACPAs. Investigations into this area are planned in further studies of longitudinal samples from the SERA project.
Hitchon and colleagues (39) recently examined the association of P gingivalis antibody with the presence of RA-related autoantibodies in a North American native (NAN) population, a study that included patients with RA, unaffected relatives (FDRs), and controls. That study showed that antibodies specific to P gingivalis were found in higher concentrations in both ACPA-positive RA patients and ACPA-positive FDRs as compared to ACPA-negative RA patients and ACPA-negative FDRs, respectively. In addition to important differences in the target populations and the techniques used for the measurement of bacterial serology values (a lipopolysaccharide-based assay in that study versus whole lysate–based approach in our study), other aspects distinguish these efforts. ACPA positivity was relatively infrequent in our study population (2.8%), precluding meaningful analyses of this subgroup. This rate of ACPA positivity is much lower than the prevalence of 19% reported among NAN FDRs. While this may relate to differences in the background prevalence of disease risk factors such as HLA–DRB1 SE (73% for NAN FDRs versus 55% in our study population), this discrepancy is largely attributable to the different definitions used for ACPA positivity. In the present study, individuals were considered to be ACPA positive based solely on results of the anti–CCP-2 ELISA, since previous reports demonstrated a substantially increased risk of developing RA in patients seropositive by this assay (25, 26). In contrast, NAN RA cases and NAN FDRs in the study by Hitchon et al were considered ACPA positive if they were seropositive by either the anti–CCP-2 assay (5% positive) or any anti–CCP-2 isotype assay (IgG1–IgG4, IgA, or IgM). As pointed out by those authors (39), the prognostic implications of anti–CCP-2 isotype positivity among unaffected relatives remain unclear. In addition to ACPA positivity, our high-risk group included individuals seropositive on ≥2 RF assays, a definition that was not operant in the prior NAN investigation, but one that has been shown to portend disease risk in other unaffected populations. For example, positivity for ≥2 RF isotypes has been shown to have a specificity of 98% for the development of RA (24).
Our results complement and extend previous reports in several meaningful ways. For each log-fold increase in anti–P gingivalis antibody concentration, individuals in our study were 40–70% more likely to be seropositive for RA-related autoantibodies. These associations were independent of all other RA and PD risk factors examined. To our knowledge, ours is the first study to simultaneously examine associations of P gingivalis and alternative oral pathogens with autoantibody expression in individuals at increased risk of RA. Recognizing that P intermedia and other oral bacteria frequently coaggregate with P gingivalis in PD-related biofilms (35), the observed correlations between bacterial antibody concentrations were expected. Importantly, the results of multivariable regression that simultaneously included antibody to P gingivalis and an alternative oral pathogen (in addition to antibodies to all 3 organisms examined) as independent variables showed that associations with the presence of RA-related autoantibodies were specific for P gingivalis and did not extend to at least 2 other oral pathogens frequently implicated in PD. Similar rates of self-reported signs and symptoms of PD reported across the study groups further support, but do not prove, the contention that infection with P gingivalis drives the observed associations with RA-related autoantibody expression, rather than disease-related autoantibody production being a consequence of nonspecific periodontal inflammation. Recognizing only modest sensitivities and moderate predictive values for self-reported PD (23), it would have been optimal to have had results from periodontal examinations. However, results from standardized oral assessments were not part of this study, although such assessments are planned for ongoing studies.
Additional studies with longer followup times and larger sample sizes will be needed to more clearly define the epidemiologic links between P gingivalis infection and RA onset. It will be essential that future efforts be designed to more precisely detail the temporal relationship of this infection with the immunologic responses that follow, including the formation of RA-related autoantibodies. Although our study included simultaneous examinations of P gingivalis and 2 other oral pathogens, additional efforts will be needed to examine the many other oral pathogens that have been identified but were not included in this study in addition to the complex interactions that are likely to exist between pathogens comprising oral and subgingival microbiomes. Regardless, these results demonstrate that associations of P gingivalis infection with RA-related autoantibody expression exist among individuals without clinically apparent RA but with a higher background risk of developing the disease. Furthermore, based on these observations, it is unlikely that established RA serves as the initiating event in this relationship. Specifically, these results refute speculation that PD (and infection with P gingivalis) simply represents a consequence of severe RA or an “opportunistic” product of immunosuppressive therapy. Importantly, these results provide insight into a potentially critical environmental trigger in the pathogenesis of RA, one that could be targeted in future interventions aimed at disease prevention.
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- SUBJECTS AND METHODS
- AUTHOR CONTRIBUTIONS
All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Mikuls had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study conception and design. Mikuls, Thiele, Deane, O'Dell, Weisman, Derber, Holers, Norris.
Acquisition of data. Mikuls, Deane, O'Dell, Weisman, Gregersen, Buckner, Keating, Derber, Holers.
Analysis and interpretation of data. Mikuls, Thiele, Deane, Payne, O'Dell, Yu, Sayles, Weisman, Derber, Robinson, Holers.