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Frontiers in Medicine logoLink to Frontiers in Medicine
. 2022 Jul 22;9:899063. doi: 10.3389/fmed.2022.899063

Examining the association between serum IgG of oral bacteria and metabolic syndrome

Zhe-Yu Yang 1,2, Wen-Hui Fang 1,2,3, Chia-Chun Kao 4, Wei-Liang Chen 1,2,3,5,*
PMCID: PMC9353261  PMID: 35935796

Abstract

Aim

This investigation explored the relationship between oral bacteria and metabolic syndrome (METS).

Materials and Methods

There were 4,882 subjects enrolled in this cross-sectional study from the NHANES III database. The severity of periodontitis was classified into mild, moderate and severe. We measured oral bacterial antibodies. We examined the relationship between serum immunoglobulin G (IgG) antibodies of oral bacteria and METS via performing multivariate regression analysis. Mediation analysis of oral bacteria on the correlation between periodontitis and METS was also executed.

Results

After adjusting for covariates, the serum IgG antibodies of P. nigrescens, E. corrodens, and E. nodatum were associated with the presence of METS (p = 0.006, p = 0.014 and p = 0.018, respectively). Furthermore, serum IgG antibodies of P. intermedia, T. forsythia and V. parvula were positively associated with the presence of METS (p = 0.001, p = 0.011, and p = 0.002, respectively) and ≥4 features of METS (p = 0.019, p = 0.025, and p = 0.02, respectively). P. intermedia IgG mediated 11.2% of the relationship between periodontitis and METS.

Conclusion

Serological markers of oral pathogens were correlated with the presence and the number of METS features after multivariable adjustment. Oral bacteria acted as a mediator of the correlation between periodontitis and METS. Our study provided a biologically plausible explanation for the association between periodontitis and METS, which provides a comprehensive evaluation of periodontitis.

Keywords: periodontitis, periodontal bacteria, metabolic syndrome, EPI—epidemiology, multivariate analysis

Introduction

Periodontitis, a chronic inflammatory disease, affects 10–15% of the global population and results in gingival recession, alveolar bone destruction, and tooth loss (1). Dental plaque biofilms formed by periodontal microorganisms are possibly the major etiologic factors (2). Numerous periodontopathic bacteria, rather than a single periodontal pathogen, may contribute to periodontitis (2). Particular periodontal bacteria, such as Porphyromonas gingivalis, Prevotella intermedia, Tannerella forsythia, Aggregatibacter actinomycetemcomitans, and Treponema denticola, are crucial causative pathogens (3). Periodontal bacterial infection may elicit a serum immunoglobulin G (IgG) antibody response. The presence of antibodies to specific periodontal species may represent the clinical periodontal status (4).

Metabolic syndrome (METS) is an emerging public health disorder worldwide (5). Multiple factors such as sociodemographic, environmental, and genetic features influence METS (6). It is well-established that METS is associated with increased odds of cardiovascular disease, diabetes, cancer, and all-cause mortality (7). Several hypotheses, including endothelial disruption, chronic inflammation, visceral fat accumulation, and insulin resistance have been proposed as possible mechanisms (8). Endothelial dysfunction was observed in Zucker obese rats, a model of METS (9). Excessive inflammatory biomarkers were linked to the development of METS (10). Tumor necrosis factor alpha (TNF-α) may interfere with insulin signaling in human skeletal muscle (11). A case control study revealed higher interleukin-6 (IL-6) levels in subjects with METS (12). Adipokine derangement and adipocyte inflammation were implicated in the pathogenesis of METS (13). Thus, METS is considered as a chronic low-grade inflammatory status (14).

Studies reveal that periodontitis is correlated with obesity, hypertension, diabetes mellitus, and cardiovascular diseases (15–17). Several possible pathways, including endothelial dysfunction, an imbalanced immune response and oxidative stress have been presented (18, 19). Epidemiological research has examined the relationship between periodontitis and METS (20). Previous investigations indicate that periodontitis and METS are both associated with systemic inflammation, suggesting a similar pathophysiological mechanism linking these two diseases (15). However, few reports have conducted a comprehensive analysis between oral bacteria and METS. This study's objectives were to investigate the correlation between the serologic markers of 19 oral bacteria and METS and to ascertain the mediation effect of oral bacteria on the correlation between periodontitis and METS.

Methods

Study design and participants

Data were retrieved from the Third National Health and Nutrition Examination Survey (NHANES III) and examined for this cross-sectional study. NHANES III, an observational survey of a non-institutionalized population from the United States, was conducted by the Centers for Disease Control and Prevention and the National Center for Health Statistics between October of 1988 and October of 1994. The survey consisted of sociodemographic information, a clinical examination, medical history and laboratory data. The NHANES III survey had National Center for Health Statistics Institutional Review Board approval and details of its study protocols and consent documents were available on the NHANES website. We excluded subjects without complete information regarding the severity of periodontitis, serum IgG antibody titers against the 19 oral pathogens, the number of METS features, laboratory data, and past history. A total of 4,882 suitable subjects were initially recruited in our study.

Definition of periodontitis

The definition and severity of periodontitis were assessed by the pocket depth and attachment loss (21). Table 1 shows the four categories of periodontitis severity.

Table 1.

Severity of periodontitis and definition of metabolic syndrome.

Periodontal status Definition
No No evidence of mild, moderate, and severe periodontitis
Mild periodontitis ≥two interproximal sites with attachment loss (AL) ≥3 and <4 mm and ≥two interproximal sites with probing depth (PD) ≥4 mm not on the same tooth, or one site with PD ≥ 5 mm
Moderate periodontitis ≥two interproximal sites with AL ≥ 4 and <6 mm not on the same tooth or ≥two interproximal sites with PD ≥ 5 mm not on the same tooth
Severe periodontitis ≥two interproximal sites with AL ≥ 6 mm not on the same tooth and ≥one or more interproximal sites with PD ≥ 5 mm
Criteria Definition
Abdominal obesity Waist circumference ≥102 cm in men and ≥88 cm in women
Hypertriglyceridemia ≥150 mg/dL (≥1.69 mmol/L)
Reduced HDL cholesterol <40 mg/dL (1.03 mmol/L) for men and <50mg/dL (1.29 mmol/L) for women
Elevated blood pressure Systolic blood pressure (SBP) ≥130 mm Hg or diastolic blood pressure (DBP) ≥85 mmHg
Elevated fasting glucose ≥100 mg/dL (5.6 mmol/L)

Serum IgG antibody measurement of oral pathogens

The level of serum IgG antibodies of 19 oral pathogens was determined using a rapid checkerboard immunoblotting technique (22). Table 2 shows the 19 oral bacterial species and strains. The bacterial IgG titers are presented as Elisa Units (EU).

Table 2.

Nineteen periodontal bacterial species and strains.

Periodontal bacteria species Periodontal bacterial strains
P. gingivalis ATCC #33277 and #53978
P. intermedia ATCC #25611
P. nigrescens ATCC #33563
T. forsythia ATCC #43037
A. actinomycetemcomitans ATCC strains #43718, #29523, and #33384
F. nucleatum ATCC #10953
S. oralis ATCC #35037
M. micros ATCC #33270
C. rectus ATCC #33238
E. corrodens ATCC #23834
E. nodatum ATCC #33099
S. intermedius ATCC #27335
C. ochracea ATCC #33624
V. parvula ATCC #10790
A. naeslundii ATCC #49340
P. melaninogenica ATCC #25845
S. noxia ATCC #43541
T. denticola OMGS #3271
S. mutans ATCC #25175

Definition of METS

The presence of METS was defined by the revised National Cholesterol Education Program's Adult Treatment Panel III (23). Table 1 lists the five components of METS. The participants were considered to have METS if they had three or more of the components.

Covariates

Individual characteristics, including age, sex, race/ethnicity, education, smoking history, and medical records, were collected from a self-reported questionnaire. Subjects were categorized as smokers if they had smoked at least 100 cigarettes in their lifetime. We also recorded diabetes mellitus diagnosed by a doctor and measured BMI as the body weight in kilograms divided by the square of the body height in meters (kg/m2). Waist circumference was measured to the nearest 0.1 cm around the horizontal line at the high point of the iliac crest. We performed blood pressure measurements using a mercury sphygmomanometer. The fasting blood sugar level was quantified by a modified enzymatic reaction. The serum total cholesterol level and serum HDL cholesterol level were quantified by a Hitachi 737 analyzer (Boehringer-Mannheim Diagnostics, Indianapolis, IN). The data collection and laboratory procedures followed standardized guidelines and protocols.

Statistical analysis

We classified the subjects based on periodontitis severity. Socio-demographic characteristics, laboratory variables, and other co-variables were compared between subjects using the one-way ANOVA and chi-square test. We examined the association between periodontitis and the number of METS features by performing multivariate regression analysis. In addition, the relationship between the IgG antibody of the oral bacteria and the number of METS features was also assessed by multivariate regression analysis. Covariates including age, sex, race/ethnicity, BMI, education, smoking, periodontitis, and diabetes mellitus, were adjusted.

We performed a mediation analysis to assess which oral bacteria mediate the relationship between periodontitis (independent variable) and METS (outcome variable) (24). Bootstrapping with 1,000 replicates was performed to calculate the medication effects without making assumptions about the normality of the sample distribution (25). The direct and indirect (mediation) effects and 95% CIs were calculated using the bias-corrected bootstrap method. If the 95% bootstrap CIs did not include zero, the indirect effect of the independent variable on the outcome variable as mediated through the intermediary was considered significant. The proportion of the indirect effect was quantified by the following formula: ORdirect effect (ORindirect effect-1)*100/(ORdirect effect × ORindirect effect-1) (26). All statistical analyses and data management were executed using SPSS version 18 (SPSS Inc., Chicago, IL, USA).

Results

Characteristics of the study population

Table 3 presents the characteristics of the participants stratified by periodontitis severity. The average age of the subjects with no, mild, moderate and severe periodontitis was 57.74 ± 13.31, 59.24 ± 13.32, 61.42 ± 13.42, and 59.99 ± 10.60 years, respectively. The SBP of the participants with no, mild, moderate and severe periodontitis was 131.15 ± 21.91, 134.43 ± 22.94, 135.87 ± 22.43, and 141.40 ± 26.20 mmHg, respectively (p < 0.001). The waist circumference of the participants with no, mild, moderate and severe periodontitis was 96.20 ± 13.19, 97.0 ± 12.53, 97.99 ± 13.01, and 99.48 ± 13.96 cm, respectively (p < 0.001).

Table 3.

Characteristics of the study population.

Variables Periodontitis
No Mild periodontitis Moderate periodontitis Severe periodontitis p
(n = 3,183) (n = 780) (n = 731) (n = 188)
Continuous variables, mean SD
Age (years) 57.74 (13.31) 59.24 (13.32) 61.42 (13.24) 59.99 (10.60) <0.001
BMI (kg/m2) 27.81 (5.4) 27.69 (5.12) 27.73 (5.55) 28.08 (6.16) 0.820
SBP (mmHg) 131.15 (21.91) 134.43 (22.94) 135.87 (22.43) 141.40 (26.20) <0.001
Waist circumference (cm) 96.20 (13.19) 97.0 (12.53) 97.99 (13.01) 99.48 (13.96) <0.001
Serum total bilirubin (mg/dL) 0.58 (0.30) 0.58 (0.28) 0.58 (0.29) 0.58 (0.30) 0.991
Serum triglycerides (mg/dL) 159.79 (126.57) 159.20 (119.54) 163.03 (111.73) 175.84 (190.45) 0.36
Serum HDL cholesterol (mg/dL) 51.34 (15.58) 50 (15.38) 50.29 (17.36) 50.31 (15.57) 0.099
Serum glucose (mmol/L) 5.75 (2.23) 5.90 (2.36) 6.13 (2.65) 6.58 (3.07) <0.001
Periodontal pathogen antibody level (EU)
P. gingivalis 2,742 (18640.52) 4086.09 (22905.18) 7756.03 (52266.4) 10373.06 (34165.88) <0.001
P. intermedia 770.36 (2698.05) 853.78 (1577.34) 960.08 (2401.22) 1125.09 (1656.58) 0.086
P. nigrescens 563.01 (2418.72) 498.03 (1183.87) 558.37 (1779.61) 534.7 (660.37) 0.895
T. forsythia 237.11 (437.26) 245.58 (339.16) 267.64 (560.01) 336.93 (553.92) 0.014
A. actinomycetemcomitans 3601.94 (28124.8) 3657.08 (20446.54) 4391.04 (24318.73) 3126.49 (8662.13) 0.883
F. nucleatum 324.06 (2600.9) 254.09 (705.86) 321.15 (973.68) 403.07 (1804.75) 0.807
S. oralis 180.76 (684.13) 192.26 (706.94) 181.65 (345.28) 239.70 (615.37) 0.659
M. micros 642.14 (3904.61) 633.41 (1901.66) 1956.02 (35928.43) 591.33 (1658.64) 0.151
C. rectus 258.52 (991.96) 330.69 (997.94) 401.36 (1071.95) 867.89 (2527.41) <0.001
E. corrodens 394.07 (895.91) 415.05 (678.87) 452.47 (954.35) 404.20 (581.21) 0.423
E. nodatum 6829.22 (22596.08) 4906.48 (14203.4) 4723.98 (15782.25) 4359.09 (10881.23) 0.009
S. intermedius 815.49 (6728.08) 634.29 (3513.21) 844.32 (2721.27) 831.55 (2562.74) 0.87
C. ochracea 334.47 (1437.68) 435.71 (4603.27) 284.95 (772.49) 335.01 (729.04) 0.584
V. parvula 87.50 (188.38) 88.12 (144.57) 98.22 (208.56) 109.96 (189.69) 0.233
A. naeslundii 2220.22 (7323.02) 2104.08 (15202.25) 1707.16 (5296.69) 2133.96 (5987.80) 0.568
P. melaninogenica 532.61 (1759.49) 600.12 (4380.72) 493.92 (1278.36) 508.57 (714.86) 0.832
S. noxia 717.69 (13713.52) 300.92 (4225.41) 285.48 (3262.44) 199.82 (930.48) 0.646
T. denticola 390.14 (1429.60) 350.30 (792.76) 411.75 (1104.01) 592.36 (1628.43) 0.149
S. mutans 220.29 (904.68) 249.03 (1337.98) 210.69 (354.37) 192.50 (261.18) 0.803
Categorical variables (%)
Male sex 43% 54.4% 60.5% 69.1% <0.001
Race-ethnicity <0.001
Non-hispanic white 55.5% 41.7% 43% 26.6%
Education
≥High school 63.4% 51.3% 46% 37.8% <0.001
Smokers 13.2% 15.4% 17.5% 17% 0.011
DM 8.7% 10.4% 12.6% 20.7% <0.001
Metabolic syndrome 44.3% 47.9% 49.7% 54.3% 0.003

SD, standard deviation; BMI, body mass index; SBP, systolic blood pressure; HDL, high density lipoprotein; DM, diabetes mellitus; EU, Elisa units. Bold values means statistical significance.

The serum glucose level of the participants with no, mild, moderate and severe periodontitis was 5.75 ± 2.23, 5.90 ± 2.36, 6.13 ± 2.65, and 6.58 ± 3.07 mmol/L, respectively (p < 0.001). The proportion of METS raised from 44.3% among subjects with no periodontitis to 47.9, 49.7, and 54.3% for participants with mild, moderate, and severe periodontitis, respectively (p = 0.003). The mean concentration of P. gingivalis IgG of the participants with no, mild, moderate, and severe periodontitis was 2,742 ± 18640.52, 4086.09 ± 22905.18, 7756.03 ± 52266.4, and 10373.06 ± 34165.88 EU, respectively (p < 0.001). The mean concentration of C. recuts IgG of the participants with no, mild, moderate and severe periodontitis was 258.52 ± 991.96, 330.69 ± 997.94, 401.36 ± 1071.95, and 867.89 ± 2527.41 EU, respectively (p < 0.001).

Associations of serum IgG antibodies of oral pathogens and the number of metabolic syndrome features

Table 4 illustrates the relationship between oral pathogens and the number of metabolic syndrome features using a multivariable model. P. nigrescens IgG was correlated with the presence of METS (β = 192.91, p = 0.006). E. corrodens IgG was correlated with the presence of METS (β = 69.66, p = 0.014). E. nodatum IgG was correlated with the presence of METS (β = 1565.63, p = 0.018). P. intermedia IgG was correlated with the presence of METS and ≥4 features of METS (β = 277.76, p = 0.001; β = 633.45, p = 0.019, respectively). T. forsythia IgG was correlated with the presence of METS and ≥4 features of METS (β = 37.22, p = 0.011; β = 109.71, p = 0.025, respectively). V. parvula IgG was correlated with the presence of METS and ≥4 features of METS (β = 18.66, p = 0.002; β = 47.23, p = 0.02, respectively).

Table 4.1.

Regression coefficients of the number of metabolic syndrome features for periodontal pathogens.

Variables Presence of metabolic syndrome Number of metabolic syndrome features
1 2 3 ≥4
β (95% CI) p β (95% CI) p β (95% CI) p β (95% CI) p β (95% CI) p
P. gingivalis Unadjusted 2166.63 (597.53, 3735.73) 0.007 360.52 (−5370.2, 6091.25) 0.902 1741.91 (−3873.49, 7357.32) 0.543 2667.13 (−2963.48, 8297.76) 0.353 4601.16 (−1179.36, 10381.69) 0.119
Adjusted 1434.94 (−350.71, 3220.61) 0.115 380.99 (−5347.15, 6109.14) 0.896 1309.94 (−4329.62, 6949.51) 0.649 1944.08 (−3791.56, 7679.73) 0.506 3626.46 (−2342.68, 9595.62) 0.234
P. intermedia Unadjusted 257.26 (117.54, 396.97) <0.001 166.17 (−344.15, 676.5) 0.523 190.61 (−309.44, 690.67) 0.455 369.96 (−131.45, 871.37) 0.148 545.46 (30.69, 1060.22) 0.038
Adjusted 277.76 (118.76, 436.76) 0.001 209.64 (−300.33, 719.62) 0.42 236.38 (−265.71, 738.48) 0.356 443.58 (−67.07, 954.23) 0.089 633.45 (102.01, 1164.89) 0.019
P. nigrescens Unadjusted 184.18 (63.79, 304.56) 0.003 91.08 (−348.77, 530.93) 0.685 103.37 (−327.63, 534.37) 0.638 278.83 (−153.33, 711.01) 0.206 279.89 (−163.78, 723.57) 0.216
Adjusted 192.91 (55.65, 330.18) 0.006 115.55 (−324.87, 555.98) 0.607 124.12 (−309.49, 557.73) 0.575 307.36 (−133.63, 748.37) 0.172 319.9 (−139.05, 778.86) 0.172
T. forsythia Unadjusted 51.26 (26.12, 76.41) <0.001 50.94 (−40.9, 142.78) 0.277 66.12 (−23.86, 156.12) 0.15 100.37 (10.13, 190.61) 0.029 126.09 (33.45, 218.73) 0.008
Adjusted 37.22 (8.58, 65.86) 0.011 54.02 (−37.85, 145.9) 0.249 61.72 (−28.72, 152.18) 0.181 88.81 (−3.17, 180.81) 0.058 109.71 (13.97, 205.45) 0.025
A. actinomycete-mcomitans (mix) Unadjusted 1018.36 (−452.32, 2489.05) 0.175 1846.84 (−3525.54, 7219.22) 0.5 413.42 (−4850.84, 5677.7) 0.878 1711.63 (−3566.9, 6990.17) 0.525 2322.43 (−3096.63, 7741.51) 0.401
Adjusted 1484.24 (−192.51, 3161.01) 0.083 1948.71 (−3430.38, 7327.81) 0.478 673.04 (−4622.87, 5968.95) 0.803 2286.83 (−3099.3, 7672.96) 0.405 3015.49 (−2589.92, 8620.91) 0.292
F. nucleatum Unadjusted 98.17 (−25.4, 221.74) 0.119 126.07 (−325.21, 577.35) 0.584 64.02 (−378.18, 506.22) 0.777 109.93 (−333.47, 553.33) 0.627 313.87 (−141.33, 769.08) 0.177
Adjusted 125.94 (−14.99, 266.87) 0.08 150.58 (−301.37, 602.55) 0.514 109.41 (−335.55, 554.38) 0.63 179.24 (−273.3, 631.79) 0.437 397.93 (−73.04, 868.9) 0.098

Bold values means statistical significance.

Table 4.3.

Regression coefficients of the number of metabolic syndrome features for periodontal pathogens.

Variables Presence of metabolic syndrome Number of metabolic syndrome features
1 2 3 ≥4
β (95% CI) p β (95% CI) p β (95% CI) p β (95% CI) p β (95% CI) p
C. ochracea Unadjusted 18.67 (−106.02, 143.37) 0.769 99.88 (−355.57, 555.33) 0.667 139.13 (−307.15, 585.42) 0.541 77.14 (−370.34, 524.64) 0.735 251.04 (−208.36, 710.45) 0.284
Adjusted 3.87 (−138.39, 146.13) 0.957 90.42 (−365.9, 546.75) 0.698 128.43 (−320.84, 577.7) 0.575 67.4 (−389.52, 524.33) 0.772 237.56 (−237.96, 713.09) 0.327
V. parvula Unadjusted 18.04 (7.62, 28.46) 0.001 11.15 (−26.9, 49.21) 0.566 21.33 (−15.95, 58.62) 0.262 31.52 (−5.87, 68.91) 0.099 41.19 (2.8, 79.58) 0.035
Adjusted 18.66 (6.79, 30.53) 0.002 13.16 (−24.91, 51.23) 0.498 24.28 (−13.19, 61.77) 0.204 35.66 (−2.46, 73.78) 0.067 47.23 (7.55, 86.9) 0.02
A. naeslundii Unadjusted −237.21 (−735.02, 260.59) 0.35 −577.16 (−2395.52,1241.19) 0.534 −958.5 (−2740.27, 823.26) 0.292 −893.83 (−2680.42, 892.76) 0.327 −1260.15 (−3094.31, 574) 0.178
Adjusted 90.93 (−475.71, 657.57) 0.753 −484.32 (−2302.29, 1333.64) 0.601 −668.57 (−2458.42, 1121.28) 0.464 −424.97 (−2245.31, 1395.37) 0.647 −698.82 (−2593.28, 1195.63) 0.47
P. melaninogenica Unadjusted 104.37 (−26.6 235.34) 0.118 111.86 (−366.52, 590.25) 0.647 127.16 (−341.6, 595.92) 0.595 157.79 (−312.24, 627.82) 0.51 337.6 (−144.94, 820.14) 0.17
Adjusted 113.64 (−35.78, 263.06) 0.136 126.15 (−353.09, 605.4) 0.606 149.19 (−322.65, 621.03) 0.535 194.96 (−284.92, 674.84) 0.426 387.61 (−111.8, 887.02) 0.128
S. noxia Unadjusted −453.49 (−1092.44, 185.46) 0.164 1173.24 (−1160.71, 3507.2) 0.324 489.57 (−1797.41, 2776.57) 0.675 192.92 (−2100.27, 2486.11) 0.869 386.24 (−1967.99, 2740.49) 0.748
Adjusted −332.15 (−1051.02, 406.72) 0.386 1213.04 (−1125.13, 3551.22) 0.309 618.14 (−1683.87, 2920.17) 0.599 384.45 (−1956.78, 2725.69) 0.748 600.53 (−1836.02, 3037.08) 0.629
T. denticola Unadjusted 3.93 (−70.3, 78.18) 0.917 241.06 (−30.02, 512.15) 0.081 120.87 (−144.75, 386.51) 0.372 165.99 (−100.35, 432.34) 0.222 157.62 (−115.82, 431.06) 0.259
Adjusted 12.55 (−71.85, 96.96) 0.771 267.17 (−3.47, 537.83) 0.053 147.42 (−119.04, 413.88) 0.278 194.71 (−76.28, 465.72) 0.159 178.85 (−103.18, 460.89) 0.214
S. mutans Unadjusted 45.99 (−5.94, 97.92) 0.083 29.84 (−159.87, 219.55) 0.758 79.56 (−106.33, 265.46) 0.401 98.51 (−87.88, 284.91) 0.3 116.27 (−75.08, 307.63) 0.234
Adjusted 26.36 (−32.86, 85.58) 0.383 33.79 (−156.19, 223.78) 0.727 78.8 (−108.24, 265.86) 0.409 87.57 (−102.66, 277.81) 0.367 96.03 (−101.95, 294.01) 0.342

Adjusted variables = age, gender, race-ethnicity, education, body mass index, smoking, diabetes mellitus and periodontitis. β, coefficient; CI, confidence interval; p, p-value. Bold values means statistical significance.

Mediation of serum IgG antibodies of oral pathogens for the association between periodontitis and METS

Table 5 presents the significant indirect effect of periodontitis on METS as only mediated through P. intermedia IgG (β = 0.003; 95% CI: 0.0007, 0.01). The proportion mediated through P. intermedia IgG was 11.2%. The indirect effects mediated through the other five oral bacterial antibodies were not significant, as their 95% CIs included zero.

Table 4.2.

Regression coefficients of the number of metabolic syndrome features for periodontal pathogens.

Variables Presence of metabolic syndrome Number of metabolic syndrome features
1 2 3 ≥4
β (95% CI) p β (95% CI) p β (95% CI) p β (95% CI) p β (95% CI) p
S. oralis Unadjusted 31.69 (−4.89, 68.28) 0.09 52.05 (−81.61, 185.73) 0.445 30.48 (−100.49, 161.47) 0.648 62.27 (−69.06, 193.61) 0.353 80.5 (−54.33, 215.33) 0.242
Adjusted 19.27 (−22.42, 60.97) 0.365 54.34 (−79.43, 188.12) 0.426 28.67 (−103.03, 160.38) 0.67 51.6 (−82.34, 185.56) 0.45 61.28 (−78.11, 200.69) 0.389
M. micros Unadjusted −477.13 (−1286.42, 332.15) 0.248 288.83 (−2667.91, 3245.58) 0.848 743.76 (−2153.49, 3641.01) 0.615 70.09 (−2835,01, 2975.19) 0.962 86.64 (−2895.8, 3069.09) 0.955
Adjusted −297.97 (−1220.1, 624.15) 0.526 444.02 (−2514.43, 3402.47) 0.769 1021.56 (−1891.14, 3934.26) 0.492 490.11 (−2472.21, 3452.44) 0.746 623.75 (−2459.17, 3706.68) 0.692
C. rectus Unadjusted 72.98 (10.45, 135.52) 0.022 49.29 (−179.1, 277.69) 0.672 100.68 (−123.12, 324.48) 0.378 127.09 (−97.31, 351.5) 0.267 196.25 (−34.13, 426.63) 0.095
Adjusted 24.93 (−46.05, 95.92) 0.491 64.12 (−163.62, 291.86) 0.581 85.57 (−138.64, 309.79) 0.454 85.74 (−142.29, 313.78) 0.461 140.46 (−96.86, 377.78) 0.246
E. corrodens Unadjusted 62.15 (13.48, 110.82) 0.012 2.46 (−175.33, 180.25) 0.978 20 (−154.21, 194.21) 0.822 55.26 (−119.42, 229.95) 0.535 111.6 (−67.73, 290.94) 0.223
Adjusted 69.66 (14.34, 124.98) 0.014 9.22 (−168.21, 186.66) 0.919 20.93 (−153.76, 195.62) 0.814 66.12 (−111.54, 243.79) 0.466 135.44 (−49.45, 320.35) 0.151
E. nodatum Unadjusted 563.52 (−578.26, 1705.31) 0.333 768.75 (−3402.97, 4940.47) 0.718 829.62 (−3258.14, 4917.4) 0.691 1467.42 (−2631.42, 5566.28) 0.483 1105.22 (−3102.75, 5313.19) 0.607
Adjusted 1565.63 (271.59, 2859.67) 0.018 1207.84 (−2943.68, 5359.37) 0.568 1958.61 (−2128.71, 6045.93) 0.348 3282.65 (−874.3, 7439.61) 0.122 3187.19 (−1139, 7513.39) 0.149
S. intermedius Unadjusted 283.35 (−41.27, 607.99) 0.087 −126.23 (−1311.53, 1050.07) 0.835 10.5 (−1150.94, 1171.95) 0.986 13.67 (−1150.92, 1178.26) 0.982 668.71 (−526.89, 1864.31) 0.273
Adjusted 302.26 (−67.88, 672.41) 0.109 −51.63 (−1238.43, 1135.16) 0.932 119.64 (−1048.8, 1288.08) 0.841 169.23 (−1019.11, 1357.58) 0.78 845.57 (−391.15, 2082.29) 0.18

Bold values means statistical significance.

Table 5.

Mediation of serum IgG antibodies of oral bacteria for the association between periodontitis and metabolic syndrome.

Pathway P. intermedia P. nigrescens
β 95% CI OR 95% CI p β 95% CI OR 95% CI p
X → M 0.059 0.033, 0.086 <0.001 0.005 −0.021, 0.031 0.719
M|X → Y 0.05 0.021, 0.007 0.001 0.065 0.036, 0.093 <0.001
X|M → Y (direct effect) 0.032 0.003, 0.06 1.032 0.96, 1.09 0.02 0.034 0.006, 0.06 – – 0.016
X → M → Z (indirect effect) 0.003 0.0007, 0.01 1.003 0.99, 1.008 0.004 0.0006 −0.002, 0.0001 – – 0.92
Percent of mediation effect 11.2% No mediation
Pathway T. forsythia E. corrodens
β 95% CI OR 95% CI p β 95% CI OR 95% CI p
X → M 0.036 0.01, 0.065 0.011 0.022 −0.002, 0.048 0.086
M|X → Y 0.038 0.009, 0.064 0.006 0.041 0.014, 0.068 0.004
X|M → Y (direct effect) 0.033 0.004, 0.06 – – 0.016 0.033 0.006, 0.06 – – 0.01
X → M → Z (indirect effect) 0.001 −0.00003, 0.0001 – – 0.06 0.0009 −0.0006, 0.0001 – – 0.254
Percent of mediation effect No mediation No mediation
Pathway E. nodatum V. parvula
β 95% CI OR 95% CI p β 95% CI OR 95% CI p
X → M −0.038 −0.062, −0.015 0.002 0.014 −0.012, 0.04 0.271
M|X → Y 0.021 −0.006, 0.047 0.13 0.026 −0.001, 0.055 0.062
X|M → Y (direct effect) 0.035 0.009, 0.06 – – 0.01 0.034 0.007, 0.06 – – 0.01
X → M → Z (indirect effect) −0.001 −0.002, 0.0001 – – 0.2 0.0005 −0.0005, 0.0001 – – 0.374
Percent of mediation effect No mediation No mediation

b, coefficient; CI, confidence interval; p, p-value; OR, Odds ratio; X, independent variable (Periodontitis); M, mediator (Periodontal bacteria); Y, outcome variable (metabolic syndrome). X → M, effect of X on M; M| X → Y, effect of M on Y controlling for X; X| M → Y, effect of X on Y controlling for M (direct effect); X → M → Y, effect of X on Y mediated by M (indirect effect).

Discussion

This study draws attention to the association between serum IgG antibodies of oral pathogens and the number of METS features. We observed that the antibodies of two periodontal bacterial (P. gingivalis and C. recuts) increased with the severity of periodontitis in a univariate analysis (Table 3). Participants with more severe periodontitis had a higher proportion of METS compared to those without periodontitis. We demonstrated a positive relationship between the antibodies of P. nigrescens, E. corrodens, E. nodatum, and the presence of METS. The antibodies of P. intermedia, T. forsythia, and V. parvula were positively correlated with the presence of METS and ≥4 features of METS. We observed an indirect effect between periodontitis and METS through P. intermedia IgG in the mediation analysis.

Previous literature revealed that periodontal bacteria was associated with the component of METS. A Japanese cross-sectional study reported that an elevated level of antibodies against P. gingivalis was observed in METS (27). Periodontal bacterial antibody (P. gingivalis and P. intermedia) titers were correlated with elevated blood glucose levels (28). The Oral Infections and Vascular Disease Epidemiology Study noted that compared with the lowest subgingival periodontal bacterial burden, subjects with the highest subgingival periodontal bacterial burden had a three times greater chance of having hypertension (29). An observational study from Columbia demonstrated antibodies of periodontopathic bacteria were associated with a reduced level of HDL cholesterol (30). In addition, serologic markers of periodontal pathogens are correlated with an elevated odd of stroke (31), type 2 diabetes mellitus (32), and coronary heart disease (33).

Studies have suggested that periodontal bacteria may induce an immune response and inflammatory processes (34). The serum IgG antibodies against P. gingivalis, P. intermedia, and E. corrodens are linked to oxidative stress (35). The local infections caused by periodontal bacteria were associated with systemic inflammatory markers including C-reactive protein (CRP), IL-6, and TNF-α (36, 37). Several plausible mechanisms have been proposed. Lipopolysaccharide, a constituent of the outer membrane of periodontopathogenic bacteria such as P. intermedia, T. forsythia, and V. parvula has been indicated to stimulate the production of various proinflammatory mediators (38–40). In an experimental study by Sun et al. (41), lipopolysaccharides elicited the release of inflammatory cytokines through toll-like receptors 2 and 4. Furthermore, complement system activation and neuropeptide modulation are linked to inflammation (42). Complement receptor 3 (CR3) activation by periodontal bacterial fimbriae and C5a accumulation may result in increased inflammation (43). Substance P, a neuropeptide, is involved in periodontal inflammation process (44). Collectively, these results suggest that periodontal bacterial infection could cause immune dysregulation (45) and result in systemic inflammation (1). Systemic inflammation plays an essential role in the pathogenesis of METS (46). Oxidative stress was also recognized as a potential pathophysiological link to the association between METS and periodontitis (47). Although the mechanism underlying the relationship between periodontal bacteria and METS remains unclear, the abovementioned investigations indicate that periodontal infection and subsequent inflammation might increase the risk of METS.

In this study, we discovered a mediation effect of P. intermedia on the association between periodontitis and METS. Our analyses imply that periodontal bacteria antibodies play a modest role in the mediation analysis. Prior reports have indicated the mediation effect of systemic inflammation regarding periodontitis. Demmer et al. (48) reported that inflammatory markers act as a mediator in the association between periodontal infection and insulin resistance. A cross-sectional study from Thailand revealed CRP (5.2%) and white blood count (19.1%) are mediators of the relationship between periodontitis and impaired fasting glucose (49). The significant indirect effect of periodontal infection on hypertension mediated through CRP was determined via two national databases (50).

There are several limitations in the present investigation. The cross-sectional analysis restricts the causal relationship between oral bacteria and METS. Our data were retrieved from a single database, and the study population was mainly Caucasian. Thus, the generalization of our results is limited. Lastly, because of the nature of observational studies, our results will inevitably be influenced by residual confounding factors due to unmeasured covariates.

Conclusion

Our study extended the examinations of the commonly reported relationship between P. gingivalis and P. intermedia to 19 oral bacterial antibodies. The serum IgG antibodies of oral pathogens were correlated with the presence and the number of METS features. We also conducted a mediation analysis, which revealed that P. intermedia acts as a mediator in the correlation between periodontitis and METS. An experimental model and prospective study are warranted to investigate the mechanisms underlying the observed correlations and to explore the potential median effect of oral bacteria.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Ethics statement

The studies involving human participants were reviewed and approved by the National Center for Health Statistics Research Ethics Review Board. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

Z-YY: conceptualization, investigation, visualization, and writing—original draft preparation. W-HF: methodology, formal analysis, and supervision. C-CK: investigation and writing—original draft preparation. W-LC: conceptualization, data curation, methodology, formal analysis, supervision, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Glossary

Abbreviations

METS

metabolic syndrome

BMI

body mass index

CRP

c-reactive protein

IL-6

interleukin-6

TNF-α

tumor necrosis factor-α

IgG

immunoglobulin G

CR3

complement receptor 3

EU

elisa units

NCHS

National Center for Health Statistics

NHANES III

the third National Health and Nutrition Examination Survey

HDL

high density lipoprotein

SBP

systolic blood pressure.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.


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