To address whether periodontal disease indexes are associated with urinary albumin-to-creatinine ratio (UACR) in conditions of high and low systemic inflammation as reflected by levels of high-sensitivity C-reactive protein (hs-CRP) in untreated hypertensive patients, we studied 242 hypertensive patients 51 ± 9 years old (24-hour systolic/diastolic blood pressure [BP] 132 ± 10/83 ± 8 mm Hg) with varying severity of periodontal disease evaluated by 3 periodontal disease indexes (PDIs) (i.e., mean clinical loss of attachment, maximum probe depth, and gingival bleeding index). Patients underwent BP measurements, echocardiography, and periodontal examination, and from fasting blood samples we assessed metabolic profile and hs-CRP. From 2 nonconsecutive overnight spot urine samples we evaluated UACR. With respect to median hs-CRP and UACR levels (1.67 mg/L and 10 mg/g, respectively), the total population was divided into patients with low-UACR/low–hs-CRP (n = 65), low-UACR/high–hs-CRP (n = 63), high-UACR/low–hs-CRP (n = 51), and high-UACR/high–hs-CRP (n = 63). PDIs differed among the 4 groups, and those with high UACR had significantly higher 24-hour systolic BP compared to those with low UACR. UACR was determined by all periodontal disease indexes, hs-CRP, and the interaction of each periodontal disease index with hs-CRP. In addition, mean clinical loss of attachment was the strongest determinant of the high-UACR/high–hs-CRP pattern among all studied periodontal disease indexes. In conclusion, in untreated middle-aged hypertensive patients, periodontal disease indexes and hs-CRP have a synergistic effect on UACR levels independently of the underlying hemodynamic load.
Periodontal disease is a common localized, chronic inflammatory disease affecting 30% to 50% of adults and mostly has a silent subclinical course until symptoms develop. Although long-term periodontal disease represents a smoldering spark for systemic inflammation and immune system activation, such conditions are not captured by standard laboratory examinations or interpreted as nonspecific indicators of a persistent, low-grade, acute-phase inflammatory response. Most studies thus far have shown an independent association of long-term periodontal disease across the broad cardiorenal continuum (i.e., endothelial dysfunction, arterial stiffening, cardiovascular events, and chronic kidney disease). It has been also suggested that periodontal disease resembles an accelerator of atherosclerotic processes and consequently may contribute to the pathophysiology of essential hypertension. Urinary albumin excretion, a marker of generalized vascular dysfunction and kidney damage, is strongly associated with different surrogates of systemic inflammation, prothrombotic states, indexes of other target organ damage in hypertensive patients, and greatly increased cardiovascular risk. We hypothesized that deteriorated periodontal tissue would exert its detrimental effects on the kidney beyond the extent of systemic inflammation in the setting of uncomplicated essential hypertension.
Methods
A cross-sectional design was chosen to assess levels of urinary albumin-to-creatinine ratio (UACR) and high-sensitivity C-reactive protein (hs-CRP) in hypertensive patients with varying severity of periodontal disease. A careful medical history was obtained and all participants underwent clinical, echocardiographic, and periodontal examinations. Apart from strictly scheduled clinic blood pressure (BP) evaluation and ambulatory BP monitoring, we performed routine biochemical profile assessment complemented by oral glucose tolerance testing and serum hs-CRP and UACR measurements. The study protocol complied with the Declaration of Helsinki, was approved by our institutional ethics committee, Hippokration Hospital, Athens, Greece, all participants gave written informed consent, and data were evaluated anonymously.
The final study population consisted of 242 of 545 consecutive white, hypertensive patients who were never treated with antihypertensive drugs, were ≥30 to <65 years old, and were referred or self-referred to our outpatient hypertensive clinic for high BP. Diagnosis of sustained hypertension was made in 387 patients presenting clinically with systolic and diastolic BP ≥140 and ≥90 mm Hg that was subsequently confirmed by 24-hour systolic and diastolic BP ≥130 and ≥80 mm Hg. We excluded 63 and 51 patients labeled as masked and white-coat hypertensives, respectively, and 44 patients with normal levels for clinical and ambulatory BP measurements.
From the middle-aged population of hypertensive patients (n = 387) we further excluded those with diabetes mellitus (i.e., treatment with antidiabetic drugs or fasting glucose level >125 mg/dl, n = 26; impaired glucose metabolism, i.e., fasting glucose level >110 mg/dl associated with abnormal oral glucose test, n = 35); those with strong clinical/laboratory evidence of familial dyslipidemia (n = 8); and those with a history of any cardiovascular disease (n = 18), secondary hypertension including sleep apnea (n = 4), and any other clinically concurrent medical condition (thyroidal, psychiatric, neuromuscular, kidney, hepatic, or gastrointestinal disease, n = 7). Patients with a history or clinical/laboratory evidence of recent infection and inflammation or who underwent any medical treatment (including lipid-lowering, nonsteroidal anti-inflammatory, and hormone replacement therapies) 1 month before entry in the study were also excluded (n = 18). We excluded those who underwent any medical or surgical periodontal treatment over the previous 12 months (n = 13) and edentulous patients (n = 6), and 10 patients, although eligible to participate, refused to give informed consent.
BP measurement was made at 3 separate visits with a mean elapsing time of 1 week according to guidelines. Over workweek (Monday through Friday) and just after completion of clinical BP measurements at the third visit, ambulatory BP was recorded using the automatic Spacelabs unit 90207 (Spacelabs, Redmond, Washington) with a procedure previously described in detail. Subjects with nighttime BP decrease ≥10% were defined as dippers and those with <10% as nondippers.
Echocardiographic study was performed by an experienced operator who was blind to the clinical status of an examined patient using a Vivid 3 PRO ultrasound imager (General Electric Medical Systems, Milwaukee, Wisconsin) with a 2.5- to 5-MHz transducer according to guidelines of the American Society of Echocardiography. Left ventricular mass was measured using the formula of Devereux indexed for the power of its growth relation to height (i.e., height 2.7 ).
Apart from dental history, a full examination of intraoral tissues was performed by the same experienced dentist blinded to the clinical status of examinees. Periodontal examination included gingival and periodontal probing tests. In brief, all teeth surfaces were probed for periodontal disease assessment with University of Michigan probes (PGF/W, Hu-Friedy, Inc., Chicago, Illinois). Probing depth and clinical attachment level were recorded for all teeth at each of 6 locations (i.e., buccal, lingual, mesiobuccal, mesiolingual, distolingual, and distobuccal). Thereafter, the following parameters of periodontal disease were measured: mean clinical loss of attachment (MCLA; i.e., mean distance among examined sites, between the cementoenamel junction to the base of the pocket or crevice), maximum probe depth (MPD; i.e., maximum measured distance between the free gingival bleeding margins to the base of the pocket or crevice), and gingival bleeding index (GBI; i.e., ratio between number of periodontal bleeding sites by probing to total examined periodontal sites). In the first 20 examined patients, a second measurement of periodontal parameters was performed 2 weeks later to test intraobserver variability; accordingly, mean relative errors of 2.7%, 2.5%, and 1.1% for MCLA, MPD, and GBI, respectively, were registered.
Venous blood samples were obtained from each participant in the morning (from 7:00 to 8:00 a.m. ) after an overnight fast for determination of plasma glucose, serum creatinine, and lipid profile. Plasma was snap-frozen in liquid nitrogen and stored at −70°C until analyzed. Plasma levels of hs-CRP were assessed using a validated high-sensitivity assay (Cardiophase High Sensitivity CRP Assay; Dade Behring, Marburg, Germany) with intra-assay and interassay coefficients of variation of 3.4% and 2.1%, respectively, and a minimal detectable concentration of 0.175 mg/L. UACR was assessed using a disposable cartridge device encapsulating an immunoturbidimetric assay for albumin and a colorimetric assay for creatinine and a programmable photometer with an incubation chamber (DCA 2000; Bayer PLC, Inc., Newbury, United Kingdom) with a coefficient of variation of 2.8% as the average of 2 nonconsecutive overnight spot urine samples with a mean elapsing time of 10 days.
SPSS 15.0 (SPSS, Inc., Chicago, Illinois) was used for all statistical analyses. All descriptive continuous variables are presented as mean ± SD if their distribution was normal (Shapiro-Wilk test), whereas non-normally distributed variables are presented as median and range. Because of their skewed distribution, hs-CRP and UACR values were logarithmically (log 10 ) transformed before testing. Categorical variables are described as absolute and relative frequencies (percentages). Distributions of hs-CRP and UACR were split by medians, and high and low values were defined accordingly for each marker. Significant differences between study subgroups were determined using Student’s t test after checking for equality of variances using the Levene test and analysis of variance. To adjust for inflation type I error due to the large amount of multiple comparisons, we used the Bonferroni correction. Univariate linear regression analysis was used to examine significant correlates of logarithmically (log 10 ) transformed UACR. Furthermore, to test the possibility of a synergistic effect of systemic inflammation with periodontal disease on levels of UACR, we constructed linear stepwise multivariable models; before being entered into the models, log 10 hs-CRP and each periodontal disease index were centered and a new term was created that was the interaction between the centered variables. Thereafter, we performed multinomial logistic regression analyses to test whether periodontal indexes were determinants of the combined molecular patterns produced by high and low hs-CRP and UACR, using as reference the low–hs-CRP/low-UACR pattern after adjustment for significant confounders. Periodontal disease determinants were also standardized for their SD (z scores) to compare the magnitude of their associations with the conjoint dichotomized patterns.
Results
The total study population consisted of 242 hypertensive patients 51 ± 9 years old (135 men, 56%; 84 active smokers, 35%; body mass index 28 ± 4 kg/m 2 ; waist circumference 93 ± 12 cm) who presented mean clinic systolic/diastolic BP and heart rate of 150 ± 16/97 ± 9 mm Hg and 77 ± 7 beats/min, respectively, and 24-hour systolic/diastolic blood pressure and heart rate of 132 ± 10/83 ± 8 mm Hg and 76 ± 8 beats/min, respectively.
Based on median UACR (10 mg/g, range 3 to 45) and hs-CRP (1.67 mg/L, range 0.21 to 8.9) the total population was divided into 4 groups. Accordingly, groups with high UACR demonstrated significantly higher levels of 24-hour systolic BP and prevalence of nondipping profile compared to those with low UACR, whereas all remaining hemodynamic, echocardiographic, and metabolic parameters did not differ significantly among the 4 groups ( Table 1 ).
| Characteristic | Low-UACR/Low–hs-CRP | Low-UACR/High–hs-CRP | High-UACR/Low–hs-CRP | High-UACR/High–hs-CRP | Overall p Value |
|---|---|---|---|---|---|
| (n = 65) | (n = 63) | (n = 51) | (n = 63) | ||
| Age (years) | 52 ± 9 | 50 ± 9 | 50 ± 10 | 50 ± 8 | 0.366 |
| Men | 41 (63%) | 35 (56%) | 22 (43%) | 37 (60%) | 0.157 |
| Smokers | 21 (33%) | 21 (35%) | 18 (35%) | 24 (40%) | 0.761 |
| Body mass index (kg/m 2 ) | 27.6 ± 4.5 | 28.8 ± 4.5 | 27.2 ± 2.8 | 28.5 ± 4 | 0.123 |
| Waist circumference (cm) | 92 ± 12 | 95 ± 13 | 92 ± 11 | 95 ± 11 | 0.310 |
| Systolic blood pressure (mm Hg) | 148 ± 17 | 149 ± 13 | 150 ± 17 | 152 ± 16 | 0.578 |
| Diastolic blood pressure (mm Hg) | 94 ± 9 | 98 ± 9 | 96 ± 7 | 98 ± 9 | 0.038 |
| 24-hour systolic blood pressure (mm Hg) | 129 ± 8 | 131 ± 10 | 134 ± 10 ⁎,† | 135 ± 11 ⁎,† | 0.003 |
| 24-hour diastolic blood pressure (mm Hg) | 82 ± 7 | 83 ± 9 | 83 ± 8 | 84 ± 9 | 0.402 |
| 24-hour heart rate (beats/min) | 74 ± 7 | 76 ± 10 | 76 ± 8 | 76 ± 8 | 0.372 |
| Nondippers | 13 (19%) † | 8 (13%) | 12 (23%) ⁎,† | 18 (28%) ⁎,† | 0.004 |
| Plasma glucose (mg/dl) | 96 ± 12 | 98 ± 12 | 98 ± 17 | 98 ± 11 | 0.880 |
| 2-hour plasma glucose, oral glucose tolerance testing (mg/dl) | 103 ± 15 | 109 ± 17 | 110 ± 16 | 107 ± 14 | 0.652 |
| Total cholesterol (mg/dl) | 221 ± 38 | 221 ± 42 | 211 ± 46 | 221 ± 60 | 0.567 |
| Triglycerides (mg/dl) | 114 ± 50 | 114 ± 47 | 116 ± 48 | 124 ± 49 | 0.609 |
| Low-density lipoprotein cholesterol (mg/dl) | 143 ± 28 | 149 ± 27 | 143 ± 25 | 154 ± 41 | 0.114 |
| High-density lipoprotein cholesterol (mg/dl) | 53 ± 15 | 52 ± 13 | 50 ± 10 | 47 ± 11 | 0.027 |
| Serum creatinine (mg/dl) | 0.93 ± 0.17 | 0.89 ± 0.16 | 0.88 ± 0.16 | 0.89 ± 0.15 | 0.379 |
| Estimated glomerular filtration rate (ml/min) | 113 ± 28 | 110 ± 28 | 108 ± 23 | 103 ± 25 | 0.030 |
| Left ventricular mass/height 2.7 (g/m) | 45.3 ± 11 | 45.2 ± 10 | 42.7 ± 11 | 45.6 ± 13 | 0.532 |
| Log 10 urinary albumin-to-creatinine ratio (mg/g) | 0.74 ± 0.28 | 0.74 ± 0.28 | 1.32 ± 0.27 | 0.21 ± 0.21 | <0.001 |
| Log 10 high-sensitivity C-reactive protein (mg/L) | −0.11 ± 0.24 | 0.44 ± 0.22 | −0.11 ± 0.27 | 0.41 ± 0.25 | <0.001 |
| Mean clinical loss of attachment (mm) | 3.51 ± 0.69 | 3.61 ± 0.53 | 4.36 ± 0.52 ⁎,† | 4.68 ± 0.48 ⁎,†,‡ | <0.001 |
| Maximum probe depth (mm) | 6.2 ± 1.66 | 8.1 ± 1.8 ⁎ | 8.3 ± 1.2 ⁎,† | 9.3 ± 1.9 ⁎,†,‡ | <0.001 |
| Gingival bleeding index | 0.35 ± 0.18 | 0.47 ± 0.23 ⁎ | 0.54 ± 0.25 ⁎,† | 0.60 ± 0.23 ⁎,†,‡ | <0.001 |
⁎,†,‡ p <0.008, significant differences of each molecular pattern from the first, second, and third numerical columns, respectively.
Measurements of periodontal disease were significantly different among the 4 groups, with higher levels in those with high UACR compared to those with low UACR independently of hs-CRP levels. In addition, presence of high hs-CRP was associated with a further significant deterioration of periodontal disease indexes in the high-UACR groups ( Table 1 ).
After adjustment for significant correlates of log 10 UACR presented in Table 2 , we constructed multivariate models to test, first, whether each periodontal index remained a determinant of log 10 UACR and, second, whether systemic inflammation by log 10 hs-CRP had a synergistic effect on the latter association ( Table 3 ). Interestingly, all periodontal indexes were associated with urinary albumin excretion, whereas centered log 10 hs-CRP, 24-hour systolic BP, waist circumference, older age, and the interaction of centered log 10 hs-CRP with any centered periodontal index had a significant impact on the dependent variable.
| Linear Regression Results in Total Population | B ± SE | Beta | 95% CI for B | p Value |
|---|---|---|---|---|
| Age (years) | 0.003 ± 0.001 | 0.145 | 0.002–0.005 | 0.002 |
| Men | −0.083 ± 0.047 | 0.19 | −0.135 to −0.019 | 0.021 |
| Waist circumference (cm) | 0.005 ± 0.002 | 0.231 | 0.002–0.014 | <0.001 |
| Body mass index (kg/m 2 ) | 0.010 ± 0.006 | 0.132 | 0.003–0.018 | 0.035 |
| Active smoking | 0.041 ± 0.049 | 0.053 | −0.056 to 0.137 | 0.408 |
| Left ventricular mass/height 2.7 (g/m) | 0.004 ± 0.002 | 0.125 | 0.001–0.007 | 0.032 |
| 24-hour systolic blood pressure (mm Hg) | 0.006 ± 0.002 | 0.191 | 0.002–0.011 | 0.003 |
| 24-hour diastolic blood pressure (mm Hg) | 0.003 ± 0.003 | 0.079 | −0.002 to 0.009 | 0.223 |
| 24-hour heart rate (beats/min) | 0.005 ± 0.003 | 0.074 | −0.002 to 0.009 | 0.132 |
| Nondippers | 0.088 ± 0.047 | 0.123 | 0.036–0.150 | 0.010 |
| Plasma glucose (mg/dl) | 0.005 ± 0.002 | 0.133 | 0.002–0.009 | 0.012 |
| Low-density lipoprotein cholesterol (mg/dl) | 0.005 ± 0.003 | 0.134 | 0.001–0.011 | 0.012 |
| Estimated glomerular filtration rate (ml/min) | −0.004 ± 0.001 | −0.234 | −0.006 to −0.002 | <0.001 |
| Mean clinical loss of attachment (mm) | 0.078 ± 0.021 | 0.212 | 0.033–0.114 | <0.001 |
| Maximum probe depth (mm) | 0.024 ± 0.008 | 0.222 | 0.011–0.049 | <0.001 |
| Gingival bleeding index | 0.010 ± 0.003 | 0.275 | 0.004–0.016 | <0.001 |
| Forward Linear Multivariable Regression Models (A, B, C) in Total Population | B ± SE | Beta | 95% CI for B | p Value |
|---|---|---|---|---|
| Model A: R 2 adjusted = 53.2% | ||||
| Mean clinical loss of attachment (mm) | 0.104 ± 0.025 | 0.24 | 0.053–0.294 | <0.001 |
| Log 10 high-sensitivity C-reactive protein (mg/L) | 0.071 ± 0.012 | 0.31 | 0.038–0.182 | <0.001 |
| Mean clinical loss of attachment × log 10 high-sensitivity C-reactive protein | 0.456 ± 0.154 | 0.19 | 0.076–1.778 | 0.005 |
| 24-hour systolic blood pressure (mm Hg) | 0.011 ± 0.003 | 0.27 | 0.006–0.019 | <0.001 |
| Age (years) | 0.008 ± 0.004 | 0.17 | 0.003–0.016 | 0.002 |
| 0.010 ± 0.004 | 0.16 | 0.003–0.018 | 0.002 | |
| Model B: R 2 adjusted = 47.2% | ||||
| Maximum probe depth (mm) | 0.031 ± 0.011 | 0.25 | 0.014–0.095 | <0.001 |
| Log 10 high-sensitivity C-reactive protein (mg/L) | 0.055 ± 0.029 | 0.33 | 0.010–0.111 | <0.001 |
| Maximum probe depth × log 10 high-sensitivity C-reactive protein | 0.678 ± 0.212 | 0.16 | 0.123–1.879 | 0.006 |
| 24-hour systolic blood pressure (mm Hg) | 0.009 ± 0.005 | 0.16 | 0.002–0.017 | 0.043 |
| Age (years) | 0.007 ± 0.003 | 0.20 | 0.002–0.013 | <0.001 |
| Waist circumference (cm) | 0.011 ± 0.006 | 0.14 | 0.003–0.020 | 0.042 |
| Model C: R 2 adjusted = 51.1% | ||||
| Gingival bleeding index | 0.009 ± 0.003 | 0.24 | 0.004–0.019 | <0.001 |
| Log 10 high-sensitivity C-reactive protein (mg/L) | 0.027 ± 0.012 | 0.16 | 0.006–0.052 | 0.030 |
| Gingival bleeding index × log 10 high-sensitivity C-reactive protein | 0.554 ± 0.154 | 0.22 | 0.112–1.397 | <0.001 |
| 24-hour systolic blood pressure (mm Hg) | 0.010 ± 0.004 | 0.18 | 0.004–0.017 | 0.002 |
| Age (years) | 0.008 ± 0.003 | 0.19 | 0.002–0.015 | 0.002 |
| Waist circumference (cm) | 0.014 ± 0.006 | 0.22 | 0.005–0.023 | <0.001 |
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