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Keywords:

  • bone;
  • Crohn's disease;
  • inflammatory bowel disease;
  • osteoprotegerin;
  • population-based;
  • receptor for activated nuclear factor kappa-B;
  • ulcerative colitis

Abstract

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. References

Background: There is a potential interface between osteoporosis and the chronic inflammation of inflammatory bowel disease (IBD), and the osteoprotegerin (OPG)/receptor for activated nuclear factor-κB (RANK)/RANK ligand (RANKL) signaling pathway may be an important mediator, although data are limited.

Methods: We conducted a population-based case-control seroassay study to look for alterations in serum OPG and soluble RANKL (sRANKL). The study population included IBD patients who were 18 to 50 years old with Crohn's disease (CD; n = 287) or ulcerative colitis (UC; n = 166), age-matched healthy controls (n = 368), and nonaffected siblings of IBD patients (n = 146). Serum OPG and sRANKL were measured by enzyme-linked immunoassay. Sex-specific reference ranges were derived from the healthy controls.

Results: Analysis of variance (ANOVA) confirmed significant group differences in women for mean serum OPG (P = 0.018). CD women had higher values of OPG than UC women (P = 0.028) or healthy controls (P = 0.045), whereas the other groups were similar. OPG levels were above the reference range in 13/173 (8%) of CD women, exceeding the expected proportion (P = 0.032). In contrast, no differences in OPG were seen in men between controls, CD, or UC. Estrogen use in women (P = 0.000002) and corticosteroid use in men (P = 0.026) were associated with higher OPG levels. In multivariate analysis, CD diagnosis (P = 0.031) and estrogen use (P = 0.000002) were independently associated with higher OPG levels. No group differences were seen in mean serum sRANKL measurements.

Conclusions: An OPG:sRANKL imbalance with OPG exceeding sRANKL should inhibit osteoclastogenesis and promote bone formation. CD is associated with increased fracture risk, and possibly, the paradoxically higher OPG is a counterregulatory response to factors such as inflammatory cytokines, promoting high bone turnover. Alternatively, elevated OPG in CD may reflect T-cell activation.

Crohn's disease (CD) is associated with a slight but statistically significant increased risk of fracture compared with the general population.1–3 While the elderly have the highest risk of fracturing,1–4 the increased risk is evident across all age groups.1 Approximately 15% of patients with CD seen at specialty clinics have osteoporosis as measured by dual energy x-ray absorptiometry testing.5 Hence, reconciling the high rates of osteoporosis at specialty clinics and the lower than predicted rates of fractures suggests that there is a minority of patients with CD who are at substantial risk of fracturing. Two major risk factors have been considered to play a role in osteoporosis in CD: systemic inflammation and the use of corticosteroids.5 While corticosteroid use has been shown by some but not all studies to be associated with osteoporosis,5 only recently has the use of corticosteroids been shown to be associated with fracture risk in CD in a population-based study.6 However, those with the highest degree of systemic inflammation are also the ones most likely to use corticosteroids, and so teasing out distinct effects of each factor is difficult.

Our understanding of the pathophysiology of normal bone homeostasis and the pathogenesis of osteoporosis and its integration with the immune response has been greatly advanced by the discovery of a receptor-ligand pathway identified on osteoblast and osteoclast precursors. Osteoblasts express a surface ligand [receptor-activator of nuclear factor kappa B (NF-κB) ligand (RANKL)], which can bind to osteoclast precursors [the receptor activator of NF-κB (RANK)] or an osteoblast derived soluble decoy receptor-osteoprotegerin (OPG).7 The binding of RANK to RANKL induces a signaling and gene expression cascade that results in differentiation and maturation of osteoclasts that can ultimately lead to osteoporosis. OPG blocks this interaction, thereby inhibiting osteoclast formation and possibly interfering with osteoporosis. It has been shown that agents that can enhance RANKL production are associated with osteoporosis, whereas agents that enhance OPG reduce osteoporosis.8 Corticosteroids, for instance, enhance RANKL and inhibit OPG. Simplistically, one would anticipate that states associated with osteoporosis might be more likely to have lower OPG and higher RANKL.

RANKL is also a regulator of T cell-dendritic cell interaction in the immune system and is a crucial factor in early lymphocyte development and lymph node organogenesis.9 The central importance of this system is seen in that RANKL gene-deficient mice, which are unable to support osteoclast differentiation, display severe osteopetrosis (even in the presence of bone resorbing factors such as vitamin D3, dexamethasone, and prostaglandin E), show no evidence of bone remodeling, and simultaneously lack all lymph nodes.9 Activated T cells can directly trigger osteoclastogenesis through RANKL, leading to bone loss, an effect that is blocked by OPG.9–11 Hence, this system may be critical in linking systemic or mucosal inflammation with altered bone metabolism and, ultimately, osteoporosis.

We aimed to develop a serum assay to measure each of OPG and soluble RANKL (sRANKL) and to test it in a population-based case control sample of CD, ulcerative colitis (UC), and healthy controls to determine if there were differences between the groups, stratified by sex.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. References

Study Design

A population-based case control study was undertaken. Cases were drawn from the University of Manitoba Inflammatory Bowel Disease Research Registry, which has been described previously.12 Briefly, this registry of persons with inflammatory bowel disease (IBD) is based on recruiting subjects through the administrative database of Manitoba Health, which provides comprehensive health care to all provincial residents. Individuals with at least 3 physician contacts (or at least 1 if resident for <2 yr) were sent a basic questionnaire and letter soliciting their permission to be listed in the Registry and possibly to be contacted for future research studies. Approximately 60% of persons responded with questionnaires and consent to be listed in the Research Registry.12 There were no significant socio-demographic or geographical differences between responders and nonresponders. At the beginning of this study, there were 2890 subjects in the Research Registry. Persons in this Research Registry who agreed to participate in future studies furnished a mailing address and a telephone number to facilitate contact. We accessed the Registry to enroll subjects <50 years of age and mailed them information sheets and questionnaires for the present case control study. Serum OPG is known to be higher in older individuals, and limiting the study to subjects <50 years of age reduced the effect of age. In addition, studies were conducted of this case control sample exploring early life events and serological assays of past infections.13 The diagnoses of CD and UC were verified by chart review for clinical data including, but not limited to, endoscopic, histologic, and radiologic findings. All subjects completed questionnaires and underwent venipuncture. The questionnaire included a detailed assessment of current and past medication use. The protocol was approved by the Human Research Ethics Board of the University of Manitoba.

Control Selection

A population-based set of controls was selected from the Manitoba Health population registry. The Manitoba Health registry contains demographic information on all persons registered with the Manitoba Health public health insurance system. The registry is regularly updated with vital registrations and information from medical and hospital transactions and closely matches population estimates derived from Statistics Canada.14 A random sample of registered persons was selected with restriction to ages 18 to 50 years, stratified by sex and 5-year age groups to approximate the age and sex distribution of the combined IBD case group in the Research Registry. Manitoba Health generated a mailing list of eligible controls and sent an information package prepared by the investigators explaining the study and requesting participation. The investigators did not know the identity of the controls unless they received a mailed response. For a second control group, we asked patients with IBD to refer us to ≥1 siblings without IBD. Siblings were not available for all cases; therefore, inferences from direct comparisons between average results of IBD patients and sibling controls is limited.

Laboratory Methods

Fasting blood samples were drawn, and serum was immediately frozen and stored at −70°C until analysis without any intervening thawing-warming cycles. Serum OPG and sRANKL were measured with sandwich enzyme-linked immunoassays (ELISAs) developed in our laboratory, and these are described below. All assays were performed by a single experienced technician who was unaware of any characteristics of the study subjects.

The OPG assay used a mouse antihuman OPG (CedarLane, Hornby, Ontario, Canada) diluted to 2 μg/mL in phosphate-buffered saline (PBS), and this solution was used to coat the microplates. Both free and bound OPG are measured with this assay. The plates were immediately sealed using Linbro plate sealers (ICN Biomedical, Aurora, Ohio) and left to stand at room temperature over night. The plates were aspirated and washed 4 times in 0.05% Tween-20 in PBS. A blocking buffer was added to each well and incubated for 1 hour at room temperature. After washing, 100 μL of serum sample was added to each well in duplicate and incubated at room temperature for 2 hours. The plates were washed, and 100 μL/well of 50 ng/mL biotinylated goat antihuman OPG (CedarLane) detection antibody diluted in a diluent of 1.0% bovine serum albumin in PBS was added and incubated at room temperature for 2 hours. After washing, a streptavidin-horseradish peroxidase conjugate (CedarLane) diluted in diluent was added and incubated for 20 minutes at room temperature. The plates were washed, a 1:1 mixture of substrate solution was added and incubated out of light for 20 minutes, and 50 μL of 2N H2SO4 stop solution was added to each well. The sides of the plate were gently tapping to ensure thorough mixing. The plates were read using an ELISA plate reader with the wavelength set at 450 nm.

An OPG standard was used (CedarLane) that contained 1 vial of 60 ng/mL of recombinant human OPG when reconstituted with 0.5 mL of reagent diluent. The OPG standard was run from a concentration of 8 ng/mL serially diluted down to 0.1562 ng/mL. The standard used detects all circulating forms of OPG. The detection antibody was a goat immunoglobin G biotin conjugate. A standard normal curve was generated and used to relate optical density to concentration.

The hsRANKL ELISA kit (CedarLane) contains the key components required for quantitative measurements (32-2000 pg/mL) of natural and/or recombinant hsRANKL. A monoclonal capture antibody anti-hsRANKL (CedarLane) was diluted to 1 μg/mL in PBS and used to coat the microplates. The plates were immediately sealed using Linbro plate sealers (ICN Biomedical) and left to stand at room temperature over night. The plates were aspirated and washed as per the OPG protocol. Then 300 μL of 1% bovine serum albumin in PBS blocking buffer (Sigma Scientific, Oakville, Ontario, Canada) was added to each well and incubated for 1 hour at room temperature. The plates were washed, and 100 μL of serum sample was added to each well in duplicate and incubated at room temperature for 2 hours. The plates were washed, and 100 μL/well of 0.5 μg/mL biotinylated antigen-affinity purified goat hsRANKL (CedarLane) detection antibody diluted in a diluent (0.05% Tween-20, 0.1% bovine serum albumin in PBS) was added and incubated at room temperature for 2 hours. The plates were washed, and 100 μL of a 1:2000 avidin peroxidase conjugate (Sigma Scientific) diluted in diluent was added and incubated for 30 minutes at room temperature. The plates were washed, and 100 μL 2 azino-bis (3-ethylthiazoline-6 sulfonate) liquid substrate solution (Sigma Scientific) was added and incubated out of light for 20 minutes and read immediately after using an ELISA plate reader at 405 nm.

An sRANKL standard was used (CedarLane) that contained 1 vial of 1.0 μg/mL of recombinant hsRANKL when reconstituted with 1.0 mL of sterile water. The RANKL standard was run from a concentration of 8 ng/mL serially diluted down to 0.1562 ng/mL. The standard used detects all circulating forms of RANKL. The detection antibody was a goat immunoglobulin G biotin conjugate. A standard normal curve was generated and used to relate optical density to concentration.

Statistics

Statistical analysis was performed with a commercial software package (Statistica Version 6.1; StatSoft, Tulsa, Okla.). OPG and sRANKL showed a skewed (non-normal) distribution.

After log transformation, both measures approximated a normal distribution. The log-transformed values were used in the statistical analyses, but for simplicity, the numeric results are shown as the exponentiated (i.e., nontransformed) values. Sex-specific upper limits of normal for OPG and RANKL were derived from the healthy controls based on the upper 95% confidence interval (i.e., 1.96 SD above the mean). The functional sensitivity of the assay did not permit a reliable lower limit. P < 0.05 was considered to represent a statistically significant difference. Comparisons between subject groups were performed using 1-way analysis of variance (ANOVA) with Tukey's test for post hoc comparisons of group means. Two-way ANOVA was used to assess the independent effects of diagnosis and other subject characteristics and to compute means adjusted for the effect of diagnosis. A Pearson χ2 test was used for categorical variables. Linear correlation between continuous measures was assessed with the Pearson product-moment correlation statistic.

Results

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. References

The group demographics and characteristics are summarized in Table 1. They were well matched for age, ethnicity, and current smoking. As expected, corticosteroid use was largely confined to the CD and UC subgroups. There was slight excess estrogen hormone use (predominantly in the form of oral contraceptives) by CD women, and slightly more current smoking by CD and UC women, but this was not statistically significant.

Table 1. Subject Demographics and Characteristics
   HealthySibling
 CDUCControlsControls
Women    
N1738326991
Age ± SD (yr)38 ± 738 ± 740 ± 539 ± 9
White ethnicity (%)97929688
Current sμoking (%)27261821
Corticosteroid    
user (%)191701
Estrogen horμone    
user (%)18131415
Men    
N114809955
Age ± SD (yr)35 ± 838 ± 840 ± 739 ± 8
White ethnicity (%)95949392
Current sμoking (%)25212322
Corticosteroid    
user (%)231002

Healthy women had significantly higher mean OPG values than healthy men (0.90 versus 0.80 pg/mL, respectively; P = 0.043). Therefore, women and men were analyzed separately. For consistency, sRANKL analyses were also performed according to sex, although no significant sex difference was detected (healthy women, 0.45 pg/mL; healthy men, 0.48 pg/mL; P > 0.2). OPG did not show any significant correlation with age in healthy control men or women (P > 0.2). There was a weak negative correlation between sRANKL and older age in women (r = −0.13, P = 0.035) but not in men (P > 0.2). When the analysis was extended to all men, no significant correlations with age were seen (P > 0.2). OPG and sRANKL were positively correlated in healthy women (r = 0.15, P = 0.012) but not in healthy men (P > 0.2). When the analysis was extended to all women, no significant correlation between OPG and sRANKL was seen (P > 0.2).

ANOVA confirmed significant group differences in women for mean serum OPG (P = 0.018; Table 2). Post hoc analysis showed that CD women had higher values of OPG than UC women (P = 0.028) or healthy control women (P = 0.045), whereas the healthy controls, sibling controls, and UC women were similar. The upper limit of normal for OPG was 1.87 pg/mL in women and 1.58 pg/mL in men, and the upper limit of normal for sRANKL was 1.65 pg/mL in women and 2.22 pg/mL in men. OPG levels were above the reference range in 13 of 173 (8%) CD women, and this exceeded the expected proportion of 2.5% (P = 0.032). In contrast, no differences were seen in serum OPG in men between healthy controls, sibling controls, CD, or UC. No group differences were seen in mean sRANKL measurements for women or men.

Table 2. Mean Serum OPG and sRANKL Levels
 CDUCHealthy ControlsSibling Controls
  • *

    *ANOVA P= 0.018.

Women    
OPG, μean (95% CI), pg/μL*1.02 (0.95-1.11)0.84 (0.76-0.94)0.90 (0.84-0.95)0.95 (0.85-1.06)
sRANKL, μean (95% CI), pg/μL0.41 (0.38-0.45)0.42 (0.38-0.48)0.45 (0.42-0.48)0.48 (0.42-0.54)
Men    
OPG, μean (95% CI), pg/μL0.83 (0.75-0.91)0.81 (0.73-0.91)0.80 (0.72-0.88)0.87 (0.76-0.99)
sRANKL, μean (95% CI), pg/μL0.45 (0.4-0.51)0.49 (0.42-0.57)0.48 (0.42-0.55)0.56 (0.47-0.68)

Univariate analysis was undertaken to assess whether OPG was affected by factors other than diagnosis. Smoking and ethnicity did not affect levels of OPG (Table 3). Estrogen hormone use in women (P = 0.000002) and corticosteroid use in men (P = 0.026) were each associated with higher OPG levels. Two-way ANOVA was undertaken to test the significant univariate factors after adjusting for diagnosis. There was no evidence of a significant interaction between estrogen hormone use and diagnosis in women or corticosteroid use and diagnosis in men (interaction P > 0.2). In multivariate analysis, a diagnosis of CD (P = 0.031) and estrogen hormone use (P = 0.000002) were independently associated with higher OPG levels in women. Corticosteroid use in men remained statistically significant (P = 0.021) after adjusting for diagnosis. No significant factors affecting sRANKL were identified.

Table 3. Effect of Subject Characteristics (Other Than Diagnosis) on Serum OPG
 Unadjusted OPG, Mean (95% CI), pg/μLAdjusted for Diagnosis OPG, Mean (95% CI), pg/μL
 Factor PresentFactor AbsentFactor PresentFactor Absent
  • *

    *P = 0.000002, factor present versus factor absent.

  • † P < 0.05, factor present versus factor absent.

Woμen    
Current sμoking0.99 (0.90-1.08)0.91 (0.87-0.96)0.98 (0.89-1.07)0.91 (0.86-0.96)
Corticosteroid user1.00(0.86-1.17)0.92 (0.88-0.96)0.97(0.83-1.13)0.92 (0.87-0.96)
Estrogen horμone user (%)1.19(1.05-135)*0.89 (0.85-0.93)1.18 (1.05-1.31)*0.89 (0.85-0.93)
Men    
Current sμoking0.85 (0.76-0.96)0.82 (0.77-0.87)0.86 (0.76-0.96)0.82 (0.77-0.88)
Corticosteroid user0.99 (0.85-1.16)0.80 (0.76-0.85)1.02(0.84-l.23)t0.81 (0.76-0.86)

Discussion

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. References

There is precedence in the literature for assessing serum OPG and sRANKL levels in health and disease.15–21 In a healthy adult population, serum OPG has been reported to increase with age, with a sharp increase in women after age 60 and in men after age 70, but little effect of age in younger subjects <40 years old.16,17 By only evaluating subjects between 18 and 50 years of age, the effect of age on serum OPG and sRANKL was minimized. Similar to our findings, slightly higher OPG levels in women than men have been reported previously.18

Primary biliary cirrhosis and chronic hepatitis C, 2 diseases known to be associated with increased fracture rates,22 are associated with increased serum levels of OPG.19 Serum OPG was not associated with bone mineral density in a study of liver disease, and the authors suggested that the high serum OPG was related to active inflammation.19 Others found a direct correlation between serum OPG and erythrocyte sedimentation rate and the Larsen score (a disease activity score) in patients with rheumatoid arthritis, supporting the notion that serum OPG may be driven by systemic inflammation.20 Our observation of increased OPG in women with CD parallels these findings. This may at first seem counterintuitive because OPG interferes with osteoclast differentiation, conferring skeletal benefit, whereas these conditions are associated with bone loss. OPG may therefore be a protective host response that partially offsets the adverse skeletal effect created by the inflammatory state. This interpretation is supported by the lack of correlation between serum OPG and bone mineral density in the previously cited study of liver disease.19 Others have found a lack of correlation between serum OPG with bone mineral density.16,19,23,24

After cardiac transplantation, serum OPG progressively decreases.25 This is also a time when bone mineral density decreases rapidly, in part, related to the antirejection regimens that may include corticosteroids and cyclosporine. The fall in OPG may have a permissive effect contributing to acute bone resorption. This seems to contrast with chronic inflammatory states, such as CD, where serum OPG levels do not decrease (and may actually increase) and bone loss declines much more slowly.

Short-term corticosteroids given for active CD lead to transient reductions in OPG at 2 weeks, but by 12 weeks after therapy initiation when all subjects were free of corticosteroids, OPG levels returned to baseline.26 In another study, no correlation was evident between corticosteroids and serum OPG.27 In our study, corticosteroid use affected OPG levels in men only. The elevated serum levels among corticosteroid users might be considered surprising unless corticosteroid effects on serum levels differ from their effects on cellular levels (where these agents typically reduce OPG), or alternatively, the corticosteroid users may have had diminished bone mass, and the increased serum level might be seen as a response to diminished bone mass. The basis for the sex-specific effects of corticosteroids (in men) and CD (in women) is unclear and requires further study. In women, estrogen hormone use strongly affected OPG levels. Others have reported that OPG levels were significantly higher in healthy young women on oral contraceptives than in nonusers.28 In postmenopausal women, there is a significant but weak positive correlation between serum OPG and serum estradiol levels.24 OPG is increased in anorectic women and may be a compensatory response to the bone loss seen in this population.29 Nutritional factors could also be contributing to the higher OPG levels seen in women with CD in our study.

OPG can be produced by a variety of tissues and cell types other than skeletal osteoblasts. For example, OPG is also expressed by endothelial cells30 and the media of arteries in wild-type mice,31 suggesting a possible role in vascular biology. Collin-Osdoby et al32 showed that inflammatory cytokine activation of human microvascular endothelial cells caused a dramatic up-regulation of OPG and even more sustained RANKL expression. OPG can prolong endothelial cell survival by inhibiting apoptosis.33 Serum OPG is increased in patients with advanced coronary artery disease compared with subjects with normal coronary arteries.34 If CD is a vasculitis,35 elevations seen in serum OPG may reflect vascular release of OPG in response to inflammation rather than necessarily being released as a response to bone resorption.

OPG:sRANKL imbalance with OPG exceeding sRANKL should inhibit osteoclastogenesis and promote bone formation. CD is associated with increased fracture risk, and it is possible that the paradoxically higher OPG is a counterregulatory response to other factors (such as inflammatory cytokines) promoting high bone turnover. Unfortunately, we do not have direct evidence (from either bone biopsy or biochemical markers of bone turnover) that bone resorption is indeed increased. Compelling evidence for the importance of OPG in maintaining bone health during an intestinal inflammatory state comes from an animal model, which simultaneously suggested a role for OPG in intestinal inflammation.36 This study used the interleukin-2 (IL-2)-deficient mouse model of colitis, which is known to develop both osteopenia and colitis. Study animals had elevated levels of bone marrow mononuclear cell expression of sRANKL and OPG mRNA, as well as circulating sRANKL and OPG, compared with control littermates. Osteopenia was not evident in IL-2-deficient mice cross-bred to be T-cell deficient, and osteopenia could be induced in T-cell-deficient mice by adoptive transfer of T cells from IL-2-deficient mice. These data suggest that activated T cells are critical for mediating the osteopenia. Importantly, exogenous OPG administration reversed both the osteopenia and the colitis. The colitis was found to be abrogated by a specific reduction in colonic dendritic cells, whereas circulating inflammatory cytokines were unaffected by exogenous OPG. These data, therefore, show directly the importance of OPG in osteopenia and colitis in IL-2-deficient mice and the importance of activated T cells in mediating these conditions. This suggests that increased OPG in CD may be generated as much by intestinal inflammation as in response to osteopenia. Furthermore, this study provides direct experimental evidence for the human finding of elevated OPG levels in a setting of concurrent intestinal inflammation and osteopenia. More recently, Vidal et al37 showed, in humans, that OPG is constitutively produced by intestinal epithelial cells, is up-regulated by tumor necrosis factor-α, and may be important in mucosal immunoregulation and bone physiology. Exogenously administered OPG may even warrant clinical study as a novel therapeutic approach in CD.

In summary, we have found that female patients with CD have elevated levels of serum OPG. Whether this is a response to osteopenia, intestinal inflammation, nutritional factors, or a combination is unclear. Further study of the role of this protein in the immunopathogenesis of CD and bone disease that accompanies some patients with CD is necessary.

References

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. References
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