• atherosclerosis;
  • general population;
  • intima media thickness;
  • osteoprotegerin


  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure of Conflict of Interests
  8. References

Summary. Background: Previous studies have reported conflicting results on the relation between serum osteoprotegerin (OPG) concentration and carotid intima media thickness (CIMT). Patients/methods: The present study was conducted to investigate the relations between OPG, risk factors for cardiovascular diseases (CVD) and carotid intima media thickness (CIMT) in a large cross-sectional study including 6516 subjects aged 2585 years who participated in a population-based health survey. Results: CIMT increased significantly across tertiles of OPG after adjustment for traditional cardiovascular risk factors such as age, gender, smoking, total cholesterol, high-density lipoprotein (HDL) cholesterol, C-reactive protein (CRP), body mass index (BMI), systolic blood pressure, CVD and diabetes mellitus (P < 0.0001). There was a significant interaction between age and OPG (P = 0.026). The risk of being in the uppermost quartile of CIMT was reduced (OR 0.52, 95% CI 0.300.88) with each standard deviation (SD) higher level of OPG in subjects < 45 years (n = 444), whereas subjects ≥ 55 years of age (n = 4884) had an increased risk of being in the uppermost quartile of CIMT (OR 1.19, 95% CI 1.101.29) after adjustment for traditional CVD risk factors. Conclusions: Age has a differential impact on the association between OPG and CIMT in a general population. The present findings may suggest that increased serum OPG does not promote early atherosclerosis in younger subjects.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure of Conflict of Interests
  8. References

Osteoprotegerin (OPG) is a soluble member of the tumor necrosis factor (TNF) superfamily, expressed by arterial smooth muscle cells, endothelial cells and megakaryocytes [1–3]. It inhibits activation of specific proinflammatory and proapoptotic signaling pathways by neutralizing the effect of receptor activator of nuclear factor-kappa B ligand (RANKL) [1] and TNF-related apoptosis-inducing ligand (TRAIL) [1,4]. Pro-inflammatory cytokines are known to upregulate OPG in vascular smooth muscle cells and endothelial cells [5–7]. OPG stimulates expression of adhesion molecules in endothelial cells in the presence of TNF-α [8] and promotes leukocyte adhesion to endothelial cells in vivo [9]. However, OPG has also been reported to increase both vascular smooth muscle cell and endothelial cell survival [2,10,11], thus exhibiting a possible role in maintaining endothelial integrity. Endothelial dysfunction is considered a critical element in the pathogenesis of atherosclerosis [12] and is associated with increased levels of certain endothelial-derived molecules in plasma such as von Willebrand factor (VWF) [13,14]. OPG is stored and secreted from endothelial cells in complex with VWF in vitro, a complex also identified in human plasma [15].

Data from in vitro studies indicate that the OPG and RANKL could be important modulators in atherosclerosis [2,5–11,16]. Recent studies have shown a positive association between serum OPG and atherosclerotic disease [17–19], and serum OPG and RANKL levels have been reported to predict cardiovascular disease and mortality in prospective studies [20–22]. Contrary, OPG administration did not affect plaque progression in LDLr(−/−) and apoE(−/−) mice with intact endogenous OPG production [23,24], whereas apoE(−/−) mice deficient in OPG promoted plaque progression [25]. The apparent inconsistent findings in experimental and epidemiological studies nourish the discussion whether OPG is a mediator or a marker in the pathogenesis of atherosclerosis. The biological links between OPG and inflammation [5], and between atherosclerosis and inflammation [26], imply that particular caution should be applied to the causative role of the OPG-RANKL system in atherosclerosis.

Carotid intima media thickness (CIMT), measured precisely and non-invasively by B-mode ultrasonography, is a marker of early atherosclerosis [27] associated with cardiovascular risk factors such as age, smoking, hypertension, obesity, dyslipidemia, diabetes and metabolic syndrome [28–30] which has also been shown to predict cardiovascular events both in the myocardium and brain [31,32]. Previous studies have reported a positive association between serum OPG and CIMT in a small study on post-menopausal women [33], whereas no independent association was found in a larger population-based study [21]. The aim of the present large cross-sectional study was to investigate the relations between OPG, cardiovascular risk factors and CIMT in a general population.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure of Conflict of Interests
  8. References

Study participants

The participants were recruited from a population health study, the fourth survey of The Tromsø Study (1994/1995). All inhabitants older than 25 years living in Tromsø, Norway, were invited to participate and 27 158 (77%) attended the survey. All subjects aged 5574 years and 510% samples in the other 5-year age groups were offered an ultrasonographic examination of the right carotid artery, and this was performed in 6727 persons. Valid measurement of CIMT was available in 6677 subjects. Fifty-seven subjects were excluded because of lack of written consent to future medical research. OPG was measured in frozen serum samples in 6516 participants. The study was approved by the regional committee for research ethics, and all included participants gave written consent.

Information on cardiovascular disease (CVD), diabetes mellitus, use of medication and smoking habits were obtained from a self-administrated questionnaire. CVD was defined as previous myocardial infarction and/or stroke. Height and weight were measured with light clothing without shoes; body mass index (BMI) was calculated as weight per height squared (kg m−2). Blood pressure was recorded in a sitting position after 2 min rest by the use of an automatic device (Dinamap Vital Signs Monitor; Critikon, Tampa, FL, USA). Three recordings were made at 2-min intervals, and the mean of the two last values was used in the present study.

Ultrasound examination

High-resolution B-mode and color Doppler/pulsed-wave Doppler ultrasonography of the right carotid artery was performed as described previously [34]. The examinations were performed by three experienced examiners, and with the use of an Acuson Xp10 128 ART ultrasound scanner equipped with a linear array 5–7 MHz transducer. The subjects were examined in the supine position with the head slightly tilted to the opposite side. In brief, intima media thickness (IMT) was measured in 10-mm segments in three locations: the near and far walls of the distal right common carotid artery and in the far wall of the bifurcation. Three frozen images from each location were stored on high-resolution videotapes. The images were analyzed offline with a computerized technique for automated ultrasound image analysis, and the maximum, minimum and average CIMT was calculated for each location. In the present study, the average of the mean CIMT for all three locations scanned is used. The reproducibility of the ultrasound examinations was acceptable [34].

Blood collection and measurements

Non-fasting blood samples were collected from an antecubital vein, serum prepared by centrifugation after 1 h respite at room temperature and further analyzed for serum lipids at the Department of Clinical Chemistry, University Hospital of North Norway. High-sensitivity C-reactive protein (hs-CRP) and OPG concentrations were analyzed in frozen serum aliquots stored at −70 °C. The concentration of total OPG was analyzed by an ELISA assay (R&D Systems, Abingdon, UK) with mouse anti-human OPG as capture antibody. Biotinylated goat anti-human OPG and streptavidin horseradish peroxydase were used for detection. The OPG assay was performed according to the manufacturer’s instructions. The intra- and interassay coefficients of variation (CV) in our laboratory were 6.5% and 9.3%, respectively. Between assays variations in OPG were adjusted for by use of an internal standard. The analysis for OPG was performed on coded samples without knowledge of status regarding atherosclerosis in the carotid artery by the person performing the assays. All samples were analyzed in duplicate and the mean value is used in this report. Lipids, HbA1c, fibrinogen, hs-CRP, creatinine and hematological variables were assessed as previously described [35].

Statistical analysis

Continuous variables are presented as mean [95% confidence interval (CI) or standard deviation (SD)], and categorical data as number or percentage. Spearman’s rank test was used to assess correlations. Logarithmic transformation was applied to variables with a skewed distribution. When transformation did not influence the statistical analysis, non-transformed data are presented. Differences between means were tested for significance using the Student’s t-test and ancova. Linear trends across quartiles of CIMT were tested by linear regression for continuous variables and by logistic regression for binary variables. Linear regression and binary logistic regression were used to assess the association between OPG and CIMT in models adjusted for age and gender and for age, gender, smoking, BMI, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, prevalent CVD, hs-CRP, diabetes mellitus and HbA1c. Addition of fibrinogen or fibrinogen in exchange for hs-CRP did not change the results significantly. Subjects with incomplete data for the assessed covariates were excluded from the multivariate models. Exclusion of these subjects also in crude and age and gender-adjusted models did not change the associations significantly. OPG was modeled both as a continuous variable and as a categorical variable (tertiles) in separate analyzes. Models assumptions were carefully checked and assessed by residual analysis. Tests of interactions between gender and OPG and between age and OPG were performed by including cross product terms between the variables. There were significant interactions between age and OPG, and in separate analyzes stratified by age group (< 45, 4554, and ≥ 55 years), we calculated the odds ratios (OR) for being in the highest quartile of CIMT by an increase in OPG. The statistical analyzes were performed using spss software for Windows, version 16.0 (SPSS, Inc., Chicago, IL, USA). Two-sided P-values< 0.05 were considered statistically significant.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure of Conflict of Interests
  8. References

There were 50.5% (3288) women in the cohort. In the total population, mean CIMT was 863 ± 190 μm (mean ± 1SD) with significantly lower CIMT in women (830 ± 173 μm) than in men (896 ± 200 μm, P < 0.0001). Characteristics of participants across age- and gender-adjusted quartiles of CIMT are shown in Table 1. There were significant linear associations between CIMT and age, male gender, OPG, BMI, current smoking, blood pressure, total cholesterol, HDL cholesterol (inverse), triglycerides, HbA1c, hs-CRP, creatinine, fibrinogen, and prevalent CVD and diabetes mellitus (Table 1). Strong positive correlations were found between age and OPG (rs = 0.61, P < 0.0001) and CIMT and OPG (rs = 0.36, = < 0.0001) (Fig. 1).

Table 1.   Distribution of cardiovascular risk factors across quartiles of carotid intima-media thickness (CIMT) adjusted for age and gender (n = 6516). Continuous variables are reported as mean with 95% confidence intervals (CIs) and categorical values as percentage. The Tromsø Study
 CIMT by quartiles
1, n = 16292, n = 16343, n = 16194, n = 1634P (trend)
  1. HDL, high-density lipoprotein; OPG, osteoprotegerin. *Adjusted for gender, adjusted for age, CVD, cardiovascular disease defined as prior myocardial infarction or stroke.

CIMT (range, μm)3587297308348359649652092 
Age (years)*51.9 (51.552.4)60.7 (60.361.1)64.0 (63.664.4)66.9 (66.467.3)< 0.0001
Gender (% men)30.747.055.966.9< 0.0001
OPG (ng mL−1)3.29 (3.243.35)3.21 (3.163.25)3.33 (3.283.38)3.56 (3.513.61)< 0.0001
Current smoker (%)28.430.332.234.30.001
Body mass index (kg m−2)24.9 (24.725.2)26.0 (25.826.2)26.3 (26.126.5)26.8 (26.627.0)< 0.0001
Systolic blood pressure (mm Hg)138 (137139)143 (142144)146 (145147)152 (151153)< 0.0001
Diastolic blood pressure (mm Hg)81 (8082)83 (8384)84 (8385)85 (8485)< 0.0001
Total cholesterol (mmol L−1)6.49 (6.426.55)6.78 (6.726.83)6.78 (6.726.83)6.86 (6.806.93)< 0.0001
HDL cholesterol (mmol L−1)1.58 (1.561.60)1.55 (1.531.57)1.51 (1.491.53)1.46 (1.441.48)< 0.0001
Triglycerides (mmol L−1)1.46 (1.411.51)1.63 (1.591.68)1.67 (1.631.72)1.76 (1.711.80)< 0.0001
HbA1c (%)5.40 (5.375.44)5.44 (5.405.47)5.48 (5.455.52)5.57 (5.535.61)< 0.0001
Fibrinogen (g L−1)3.32 (3.273.36)3.32 (3.283.36)3.38 (3.343.42)3.52 (3.473.56)< 0.0001
C-reactive protein (mg L−1)2.47 (2.112.82)2.45 (2.142.76)2.70 (2.383.02)3.06 (2.723.39)0.012
Creatinine (μmol L−1)78.8 (77.979.7)78.2 (77.479.0)78.1 (77.378.9)80.1 (79.381.0)0.040
Carotid plaques (%)19.838.452.377.7< 0.0001
Diabetes mellitus or HbA1c> 6.1 (%)< 0.0001
Diabetes mellitus (selfreported) (%)< 0.0001
Cardiovascular disease (%)< 0.0001

Figure 1.  Scatter plots between age and osteoprotegerin (OPG) [panel A; rs = 0.61, P < 0.0001 (n = 6516)], and between OPG and carotid intima media thickness (CIMT) in subjects < 45 years [panel B; rs = −0.11, P = 0.010 (n = 509)], in subjects ≥ 45 years and < 55 years [panel C; rs = 0.13, P = 0.001 (n = 652)] and in subjects ≥ 55 years [panel D; rs = 0.24, P < 0.0001 (n = 5355)].

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Serum OPG was a significant predictor for CIMT in crude analysis and after adjustment for cardiovascular risk factors, both when treated as a continuous variable and categorized in tertiles (Table 2). A significant interaction between age and OPG appeared in this model (P = 0.026), whereas no significant interaction was demonstrated between gender and OPG (P = 0.41). Age-stratified analysis between CIMT and serum OPG in young (< 45 years), middle-aged (4554 years) and older (≥ 55 years) participants are shown in Table 3 and Fig. 2. In subjects younger than 45 years (n = 509), each SD higher level of OPG was associated with a lower risk of being in the highest quartile of CIMT both in crude analyzes (OR 0.49, 95% CI 0.320.77) and after adjustment for cardiovascular risk factors, CVD and diabetes (OR 0.52, 95% CI 0.300.88). In contrast, an independent positive association was found between OPG and CIMT in participants ≥ 55 years (n = 5355). The risk estimates across age-strata were similar in men and women (data not shown).

Table 2.   Carotid intima media thickness (CIMT) by osteoprotegerin (OPG) tertiles and estimated change in CIMT (μm) with each SD higher level of OPG*. The Tromsø Study
 Unadjusted n = 6516Age and gender adjusted n = 6516Model 1 n = 6417Model 2 n = 5915
  1. *Values are means (95% CI) or regression coefficients (95% CI) from linear regression models. Model 1; Adjusted for age, gender, smoking, total cholesterol, HDL cholesterol, hs-CRP, BMI, systolic blood pressure. Model 2; As model 1 + CVD and diabetes mellitus or HbA1c > 6.1%. SD OPG = 1.15 ng mL−1.

OPG by tertiles
 1791 (783799)847 (839854)850 (843857)851 (844859)
 2863 (855870)856 (849862)857 (850863)858 (851865)
 3935 (928943)886 (879894)882 (875889)882 (875890)
 P (trend)< 0.0001< 0.0001< 0.0001< 0.0001
OPG (SD)59 (5563)19 (1524)17 (1221)18 (1323)
P-value< 0.0001< 0.0001< 0.0001< 0.0001
Table 3.   Odds ratios (95% CI) for being in the top quartile of carotid intima media thickness (CIMT) by OPG tertiles and with each SD higher level of OPG. The Tromsø Study
Age group < 45 yearsUnadjusted n = 509Age and gender adjusted n = 509Model 1 n = 502Model 2 n = 444
  1. Model 1; Adjusted for age, gender, smoking, total cholesterol, HDL cholesterol, hs-CRP, BMI, systolic blood pressure. Model 2; As model 1 + CVD and diabetes mellitus or HbA1c > 6.1%. SD OPG*; 1.26 ng mL−1, 1SD OPG; 0.77 ng mL−1, 1SD OPG; 1.10 mL−1.

 20.49 (0.300.79)0.40 (0.230.67)0.40 (0.230.70)0.36 (0.200.64)
 30.41 (0.250.67)0.43 (0.250.75)0.42 (0.240.75)0.37 (0.200.68)
 P (trend)0.00030.0020.0020.001
OPG (SD)*0.49 (0.320.77)0.56 (0.340.92)0.55 (0.330.91)0.52 (0.300.88)
P value0.0020.0220.0200.016
4554 yearsn = 652n = 652n = 642n = 587
 21.23 (0.781.93)1.06 (0.661.69)1.14 (0.701.85)1.32 (0.802.19)
 31.64 (1.062.53)1.32 (0.842.09)1.35 (0.832.19)1.51 (0.912.52)
 P (trend)0.0270.220.230.11
OPG (SD)1.18 (0.9981.39)1.10 (0.931.32)1.11 (0.921.35)1.23 (0.991.52)
P value0.0520.260.280.057
≥ 55 yearsn = 5355n = 5355n = 5273n = 4884
 21.67 (1.411.97)1.36 (1.141.62)1.33 (1.111.59)1.38 (1.141.66)
 32.64 (2.253.10)1.63 (1.361.96)1.52 (1.261.85)1.53 (1.251.87)
 P (trend)<0.0001<0.0001<0.0001<0.0001
OPG (SD)1.51 (1.421.61)1.25 (1.161.34)1.21 (1.121.30)1.19 (1.101.29)
P value<0.0001<0.0001<0.0001<0.0001

Figure 2.  Carotid intima media thickness (CIMT) across tertiles of serum OPG in subjects < 45 years [----, P for linear trend = 0.006, (n = 444)], in subjects ≥ 45 years and < 55 years [······, P for linear trend = 0.068 (n = 587)] and in subjects ≥ 55 years [- - - -, P for linear trend = 0.040 (n = 4884)]. Values are means with 95% confidence interval (CI). Adjusted for age, gender, smoking, total cholesterol, high-density lipoprotein (HDL) cholesterol, High-sensitivity C-reactive protein (hs-CRP), body mass index (BMI), systolic blood pressure, cardiovascular diseases (CVD) and diabetes mellitus or HbA1c> 6.1%.

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  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure of Conflict of Interests
  8. References

In the present population-based cross-sectional study, we found that age had a differential impact on the association between OPG and CIMT. In agreement with a previous finding [36], the scatter plot between OPG and age in our study indicated an apparent change in the relation with age (Fig. 1), and statistical analyses revealed a significant interaction between age and serum OPG. Subsequent age-stratified analyses revealed that subjects younger than 45 years had a reduced risk of being in the uppermost quartile of CIMT with increasing serum OPG in crude and adjusted models irrespective of whether OPG was treated as a continuous or a categorized variable. In contrast, subjects 55 years or older showed a significant positive association between OPG and CIMT which persisted even after adjustment for cardiovascular risk factors. None of the other risk factors or markers of atherosclerosis assessed in the present study demonstrated the observed switch across age strata from a negative association to a positive association with CIMT.

Our finding that high serum OPG was associated with a reduced risk of being in the upper quartile of CIMT in young subjects (< 45 years) apparently contradicts previous findings of elevated OPG in the presence of CAD and increase in OPG with the severity of the disease [17,18]. However, interventional studies in animal models have shown that OPG is an inhibitor rather than mediator of atherosclerosis [23,25,37], and prospective cohort studies in humans have shown that OPG was not associated with novel plaque formation [21,35] and had a weak [21], if any [35], impact on plaque growth. Although no firm conclusions can be drawn from a cross-sectional study where unrecognized confounders could not be ruled out, it is tempting to suggest that the inverse relation between OPG and CIMT in young age represent a counter regulatory mechanism in order to keep excessive activation of inflammation pathways and other injurious stimuli under control in atherogenesis. Our unexpected finding provides further evidence to the concept that OPG do not promote early atherosclerosis or even inhibit development of atherosclerosis.

In contrast, OPG increased significantly with CIMT in older subjects. Proinflammatory cytokines such as interleukin-1β and TNF-α is known to induce OPG expression in human vascular smooth muscle cells [5–7]. Thus, it is likely to assume that the positive relation between OPG and CIMT in older age is mediated by increased atherosclerotic burden, a chronic inflammatory condition [26] known to increase with age [35], most probably overwhelming the counter regulatory mechanism(s) at early stages of atherosclerosis.

However, the age-dependent switch in the relation between serum OPG and CIMT also attracts attention to the possible influence of sex hormones and menopausal status. Unfortunately, we do not have accurate information of the menopausal status or serum levels of sex hormones in our cohort. However, it is unlikely that the menopausal status and serum levels of sex hormones are unrecognized confounders, as the risk estimates are similar in men and women across all age-strata, assuming that women below 45 years are pre-menopausal and above 55 years are post-menopausal.

The main strengths of the present study are the population-based design, the high attendance rate and the large number of participants with a wide age span. The study also has limitations that merit considerations. The cross-sectional design does not allow firm conclusions about causal relationships between variables of interest. Despite a high attendance rate, it is likely that severely ill and disabled individuals were underrepresented. However, we found similar associations between OPG and cardiovascular risk factors such as age, blood pressure, serum lipids and HbA1c as reported in previous population-based studies [19,21]. Our serum samples were kept frozen for 12 years at −70 °C without any freezing-thawing cycles before measurement of OPG. Others have reported long-term stability when stored at −70 °C [21,38].

In conclusion, the present study showed a differential impact of age on the association between OPG and CIMT in a general population. Our findings suggest that increased serum OPG may inhibit progression of early atherosclerosis in younger subjects.

Disclosure of Conflict of Interests

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure of Conflict of Interests
  8. References

C.A.R.T. was supported by an independent grant from Pfizer AS.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure of Conflict of Interests
  8. References
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