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. 2021;17(4):509–516. doi: 10.4183/aeb.2021.509

Relationship between Osteopontin and Bone Mineral Density

A Vancea 1,*, O Serban 1, D Fodor 1
PMCID: PMC9206150  PMID: 35747863

Abstract

Recent studies suggest that osteopontin (OPN) could be used as an early marker for the diagnosis of bone disorders. Considering the contradictory opinions in the literature, the objective of this systematic review is to analyse the current information regarding the relationship between OPN and bone mineral density (BMD), which represents an important process in the development of osteoporosis. We performed a literature search of clinical trials using the PubMed database, published between 1999-2020, and identified 7 studies that were eligible for analysis. The eligibility criteria were based on studies that analysed the relationship between osteopontin and bone mineral density on human subjects. Conclusion: serum OPN levels might be used as a biomarker of the early diagnosis of osteoporosis in postmenopausal women, with or without osteoporotic vertebral fractures.

Keywords: osteopontin, bone mineral density, BMI, osteoporotic fracture

Introduction

Osteopontin (OPN) or secreted phosphoprotein-1 (SPP1) is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family of cell matrix proteins (1) and is found in bone, acute and chronic inflammatory cells, smooth cells, neurons, and foetal renal tissue (2). OPN has an important role in neuron-mediated and endocrine-regulated bone mass but is also involved in biological activities such as proliferation, migration and adhesion of different bone-related cells including bone marrow mesenchymal stem cells, hematopoietic stem cells, osteoclasts, and osteoblasts (1).

OPN has been shown to be a key regulator of many metabolic and inflammatory diseases, such as diabetes, cardiovascular diseases, and obesity. There are studies that showed the role of OPN in the pathogenesis of insulin resistance and type 2 diabetes, while other studies have demonstrated that this protein is a protective factor for the pancreatic islets, by emerging disclosed complex cytokine and hormonal crosstalk between bone cells, liver, and adipose tissue, influencing bone remodeling, energy metabolism, and glucose homeostasis (3). In terms of proinflammatory status, there are studies that analysed the role of OPN level in immune diseases, such as Graves’ disease, with evidence that the control of this protein may be important in the remission of the disease (4). Clinical studies showed that OPN is involved in bone strength and bone remodelling, being proved that serum OPN, as a biomarker for early diagnosis of osteoporosis (OP) in postmenopausal women, are positively related to the severity of osteoporosis (5-7) (Fig. 1).

Figure 1.

Figure 1

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Osteopontin-mediated bone remodeling process. Resorption of bone is carried out mainly by osteoclasts derived from the common precursor of macrophages and osteoclasts. Osteoclast-mediated resorption of bone takes place in resorptive pits where the osteoclasts are attached through a specific α4β3 integrin to components of the bone matrix such as osteopontin. Also, macrophage colony-stimulating factor (M-CSF) plays an important role during several steps in the pathway and ultimately leads to fusion of osteoclast progenitor cells to form multinucleated, active osteoclasts. RANK ligand (RANKL), a member of the tumor necrosis factor (TNF) family, is expressed on the surface of osteoblast progenitors and stromal fibroblasts and binds to the RANK receptor on osteoclast progenitors, stimulating osteoclast differentiation and activation. Alternatively, a soluble decoy receptor, osteoprotegerin, can bind RANK ligand and inhibit osteoclast differentiation. There are numerous factors and cytokines (including interleukins 1, 6, and 11; TNF; and interferon γ) modulate osteoclast differentiation and function.

The bone is a specialized form of metabolically active, mineralized connective tissue (8), a dynamic organ that remodels itself throughout life by a process called bone remodelling, which involves the removal of old bone and the formation of new one. This activity varies in different types of bone (cancellous bone having a higher turnover rate than cortical bone) and all mechanisms seem to prevent progression of the bone micro architectural damage (9). For maintaining bone health, the remodelling process must remain balanced (10).

In the bone marrow, OPN is estimated to comprise about 2% of non-collagenous proteins in bone tissue and is mainly secreted by osteoblasts (11, 12). The OPN activity in relation to bone health is influenced by hormonal status through its effect on bone metabolism. The expression of OPN by osteoclast and osteoblasts progenitors in murine bone marrow increased after ovariectomy (13); OPN-deficient mice are resistant to bone loss after ovariectomy (14). Reza et al. (15) demonstrated that the level of osteopontin and of other bone turnover markers (BTMs) (osteocalcin, carboxy-terminal collagen crosslinks and bone alkaline phosphatase) are elevated in postmenopausal women due to the high bone turnover with accelerated bone loss. This idea was supported also in other studies (16-20) by showing that BTMs measurement can improve the exploration of bone turnover. But, due to the preanalytical variability and absence of guidelines, there are studies which showed that bone turnover markers have poor diagnostic value in assessing the osteoporotic status (21, 22).

The aim of this systematic review is to analyse the current data regarding the relationship between osteopontin, bone mineral density and body mass index (BMI) and to summarize their results.

Methods

Search strategy

A systematic literature research of the PubMed database, filtered to the period 1999-2020, was performed to identify the studies addressing to the role of osteopontin in bone health. The search used the terms “osteopontin”, “bone mineral density”, “BMD”, “BMI”, “OPN”, and “bone sialoprotein 1” in multiple combinations of formulas using the operators “AND” and “OR” to avoid most of the irrelevant papers and to ensure the widest search spectrum.

Study selection

The inclusion criteria were human studies with a female population of interest, all studies that analysed the relationship between OPN and BMD using the same methods (ELISA- enzyme-linked immunosorbent assay and DXA), studies that measured BMD at the interest areas (hip and/or lumbar) and studies that included the BMI values. Also all studies included in the analysis were cross-sectional studies.

The exclusion criteria were animal studies, other methods for measuring OPN and BMD, BMD determined in areas other than those of interest and review articles. The flow chart of the literature research is detailed in Figure 2.

Figure 2.

Figure 2

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Flow chart of the literature research.

Data extraction

After collecting all qualified studies, we extracted the following content: the surname of the first author, year of publication, number of postmenopausal women included in each study analysis, age of patients included in the studies, the values of OPN, BMD, T-score and BMI, but also the correlation between OPN and BMD. We also extracted the conclusion from each study and the information needed to calculate the Newcastle Ottawa Scale (NOS).

Risk of bias assessment

We used the Newcastle Ottawa Scale (NOS) adapted by Herzog et al. (23) for cross-sectional studies to evaluate the risk of bias of individual included studies. It assesses the risk of bias on three main domains: selection, comparability and outcome. The question that assessed non-respondents was not applicable in our analysis. Each study could score a maximum of 9 points. NOS was independently applied by two reviewers (VA and SO) and the results were discussed and a consensus was reached in case of disagreement. The studies scoring 0-4 points were considered unsatisfactory, 5-6 points satisfactory, 7-8 points good and 9 points very good. We used Review Manager (RevMan) [Computer program]. Version 5.4.1 (The Cochrane Collaboration, 2020) for the risk of bias graph and summary.

Results

Seven studies regarding the relationship between osteopontin and bone mineral density, all cross-sectional studies, fulfilled the inclusion criteria and were further analysed (Table 1).

Table 1.

Study characteristics and outcomes for osteopontin and bone mineral density

Study N(G) Age (years) OPN values * (ng/mL) BMD (g/cm2) T-score BMI (kg/m2) Correlation OPN-BMD Conclusion NOS
Chang, 2010 [24] 219 (F) MG: 68.4±12.3 Non-MG: 33.1±10.8 MG: 15.4±6.2 Non-MG: 7.8±1.8 MG: Lumbar:0.9±0.2 Hip: 0.8±0.1 Non-MG: Lumbar:1.2±0.1 Hip: 0.9±0.1 MG: -2.2±1.6 Non-MG: -0.1±0.8 MG: 24.5±4.1 Non-MG: 22.2±4.7 MG: Lumbar: r=-0.278 (p=0.002) Hip: r=-0.405 (p < 0.0001) OP group: ↑ levels of OPN 9
Lumbar: -1.57±1.60
Hip: -0.92±1.35
Fodor, 2013 [25] 214 (F) MG: 65.31±9.49 13.17±12.63 VFs: 15.69±13.26 noVFs: 12.63±12.46 Lumbar: 1.00±0.20 Hip: 0.89±0.18 FN:0.83±0.15 FN: -1.45±1.14 VFs, Lumbar: -2.18±1.69 FN: -2.17±0.82 noVFs, Lumbar: 28.64±5.99 MG: Lumbar: r=-0.19 (p=0.004) Hip: not available FN: r=-0.17 (p=0.01) OP group: ↑ levels of OPN 9
-1.43±1.56
FN: -1.29±1.14
Cho, 2013 [26] 441 (F) MG: 61.4±7.8 Non-MG: 51.4±1.9 MG: 43.6±25.9 Non-MG: 26.3±18.6 MG, Lumbar: 0.958±0.140 Hip: 0.867±0.116 FN: 0.786±0.099 Non-MG, Lumbar: 1.17±0.13 Hip:1.01±0.12 FN: 0.918±0.092 MG: 24±3.2 Non-MG: 23.2±3.3 MG: Lumbar: r=-0.113 (p=0.023) Hip: no correlation Non-MG: Lumbar: no correlation Hip: no correlation OP group: ↑ levels of OPN 9
Mohammed, 2015 [27] 85 (F) MG-VFs: 58.44±3.74 MG+VFs: 59.70±4.54 CG: 61.78±5.25 noVFs: 15.496±0.596 VFs: 21.065±2.439 CG: 32.504±2.352 noVFs, Lumbar: 1.10±0.11 VFs, Lumbar: 0.73±0.05 CG: 0.63±0.08 noVFs, Lumbar: -0.77±0.08 VFs, Lumbar: -3.03±0.42 CG: -4.21±0.89 noVFs: 29.64±4.49 VFs: 28.65±4.93 CG: 26.51±3.97 MG+VFs: not available MG-VFs: not available OP group ± VFs: ↑ levels of OPN 6
Al-Nejjar, 2015 [28] 88 (F) OP: 62.63±9.52 CG: 53.72±7.09 OP group (n=44): 16.41±6.33 CG (n=44): 7.13±5.88 OP, Lumbar: 0.73±0.06 Hip: 0.5±0.1 CG, Lumbar: 1.13±0.08 Hip: 0.97±0.09 OP, Lumbar: -3.16±0.53 Hip: -3.24±0.5 CG, Lumbar: 0.18±0.65 Hip: 0.39±0.73 OP: 31.84±4.47 CG: 30.81±3.54 MG: Lumbar: not available Hip: not available OP group: ↑ levels of OPN 5
OPE group OPE, Lumbar: 1.06±0.11 OPE, Lumbar: -1.14±1.2 OPE: Lumbar: r=-0.04 (p=0.66)
Wei, 2015 [29] 362 (F) OPE: 61.33±6.99 OP: 70.94±9.54 CG: 55.16±6.73 (n=158):10.2±2.68 OP group (n=129): 17.71±5.41 CG (n=75): FN: 0.85±0.08 OP, Lumbar: 0.78±0.12 FN: 0.62±0.08 CG, Lumbar: 1.34±0.19 FN: -1.01±0.94 OP, Lumbar: -3.08±0.54 FN: -2.07±0.74 CG, Lumbar: 0.81±1.00 OPE: 23.39±3.56 OP: 21.97±2.91 CG: 28.58±4.93 FN: r=-0.07 (p=0.35) OP: Lumbar: r=-0.54 (p=0.00) FN: r=-0.42 (p=0.00) CG: Lumbar: r=-0.07 (p=0.56) OP group: ↑ levels of OPN 9
7.68±3.19 FN: 1.10±0.15 FN:0.34±0.96 FN: r=-0.18 (p=0.12)
Reza, 2016 [30] 120 (F) MG: 54.32±4.57 Non-MG: 33.83±5.56 MG: 16.34±1.51 Non-MG: 11.19±1.52 MG, Lumbar: 0.91±0.81 Hip: 0.77±0.22 Non-MG, Lumbar: 1.22±1.14 Hip: 0.92±0.13 MG: -1.57±1.60 Non-MG: 0.16±0.78 MG: 28.65±5.23 Non-MG: 27.16±5.12 MG: Lumbar: r=-0.71 (p<0.0001) Hip: r=-0.52 (p<0.0001) Non-MG: Lumbar: no correlation Hip: no correlation OP group: ↑ levels of OPN 6
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The results are expressed as mean ± standard deviation. G; gender; N: number of patients; F: female; M: male; MG: Menopausal group; non-MG: Non-Menopausal group; VFs: Osteoporotic vertebral fractures; noVFs: No osteoporotic vertebral fractures; FN: femoral neck; CG: Control group; OP group: Osteoporosis group; OPE group: Osteopenia group; BFG: Bone fracture group, NOS- Newcastle Ottawa Scale. * all p < 0.05, all mean are significantly different between groups.

Risk of bias of the included studies

The quality of all the included studies was at least satisfactory scoring a NOS between 5 and 9: 3 studies had a satisfactory quality (26, 28, 30) and 4 studies had a very good quality (24-26, 30).

The risk of bias was low in 3 studies (24, 27, 28), and high in 4 studies (24-26, 29). Overall, most studies had a high risk of bias in the two comparability domains, selection of controls, ascertainment of exposure and assessment of outcome. Also, there was a moderate risk of bias in the domains relating to sample size and statistical test. The risk of bias of the included studies is summarised in Figure 3.

Figure 3.

Figure 3

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Risk of bias graph and summary.

Patient characteristics

A total number of 1.529 women (pre and postmenopausal mean age 58.11 ± 6.7 years) were included in the seven analysed studies. Six studies from all seven had control groups: three studies (24, 26, 30) compared the results obtained from postmenopausal group with a premenopausal group, while other three studies (27, 28, 29) compared the results within the group of menopausal patients, in terms of bone mineral density (osteoporosis, osteopenia and healthy postmenopausal women, with or without vertebral fractures).Studies were conducted in Taiwan (24), Romania (25), Korea (26), Baghdad (27, 28), China (29) and Pakistan (30). All studies investigated the same characteristics: gender, age, menopause age, osteopontin values, BMD (lumbar and hip bone mineral density), T-score and BMI (body mass index expressed as kg/m2).

Four studies investigated only the relationship between OPN and BMD (N=789 participants), whilst the other three added the presence of osteoporotic fractures (N=820 participants). The methods for measuring the OPN serum level was the enzyme-linked immunosorbent assay (ELISA) in all 7 studies. Considering this, but also the fact that normal values differed depending on the patient’s menopausal status, the cutoff value for OPN might not be established. BMD was analysed in all studies through dual-energy X-ray absorptiometry (DXA). As a secondary outcome of this study, we analysed the relationships between osteopontin and vertebral fractures and between osteopontin and bone turnover markers, in both premenopausal and postmenopausal women.

Risk of bias of the included studies

The quality of all the included studies was at least satisfactory scoring a NOS between 5 and 9: 3 studies had a satisfactory quality (26, 28, 30) and 4 studies had a very good quality (24-26, 30).

The risk of bias was low in 3 studies (24, 27, 28), and high in 4 studies (24-26, 29). Overall, most studies had a high risk of bias in the two comparability domains, selection of controls, ascertainment of exposure and assessment of outcome. Also, there was a moderate risk of bias in the domains relating to sample size and statistical test. The risk of bias of the included studies is summarised in Figure 3.

Relationship between serum OPN levels and BMI

Most studies found no correlations between OPN levels and BMI (24, 26-28). Negative correlations were established in 3 studies (25, 29, 30), but not for the control group in one study (29).

Relationship between serum OPN levels and BMD at the lumbar spine

Five studies found negative correlations between serum OPN levels and BMD at the lumbar spine in postmenopausal women (24-26, 29-30).

Relationship between serum OPN levels and BMD at the hip

Four studies showed negative correlation between serum OPN levels and BMD at the hip in the menopausal group (24, 28-30). No relationship was demonstrated between OPN and hip BMD in postmenopausal women in 2 studies (25, 26).

Relationship between serum OPN levels and osteoporotic fractures

There was one study that found significantly higher levels of serum OPN in postmenopausal group with osteoporotic bone fractures (25).

Taking into account serum OPN levels regarding fragility fractures there were two studies that found higher levels of serum OPN in postmenopausal groups with fractures (26, 27), while one study (26) demonstrated that OPN levels were not different between postmenopausal group with or without fractures.

Relationship between serum OPN levels and other BTMs

Two studies found a positive correlation between OPN and CTX (carboxy-terminal collagen crosslinks) (24, 25). Regarding the relationship between the bone formation marker bone alkaline phosphatase and OPN, one study found a positive correlation (25), whilst another one (24) showed a weak positive correlation. Serum OPN levels were significantly and positively correlated with serum osteocalcin (OCN) levels in patients with OP in two studies (25, 27). Also, no correlations were found between serum OPN levels and serum OC levels in control subjects (27).

Serum OPN levels in premenopausal and postmenopausal groups

Four studies showed higher levels of OPN in postmenopausal groups, compared to premenopausal groups (24, 26, 28, 30). Also, the mean for OPN in postmenopausal group was 18.82 ± 9.75 ng/mL, as for OPN and premenopausal groups was 12.02 ± 8.14 ng/mL.

Discussion

In this systematic review that included seven studies and 1.529 participants, we have found evidence of the correlation between high serum OPN levels and low BMD (particularly at the lumbar spine) in osteoporotic postmenopausal women (24-29). Moreover, higher OPN levels were associated with osteoporotic fractures in postmenopausal women (25). Our analysis supports the idea that serum OPN levels might be used for the early and improved detection of fracture risk, especially in postmenopausal women, with or without osteoporotic vertebral fractures. We believe that this hypothesis can improve the diagnostic method for early osteoporosis, being a faster and more accessible method. Also, we think that higher levels of serum OPN levels in postmenopausal women suggest low bone mineral density, thereafter the need to perform DXA can be considered.

OPN is mainly localized in the mineralized tissue, as cement lines and lamellae, being more prominent in trabecular than in cortical bone (37, 38). It has been shown that in ovariectomized (OVX) OPN +/+ mice the bone mass is relatively quickly lost, and the mice BDM is decreased, while OPN -/- mice showed higher bone volume and BMD. Moreover, a reduction in the number and area of resorption pits was observed when treating OVX mice with anti-OPN antibody in a dose-dependent manner (phenomenon probably related to osteoclasts apoptosis) (39). These findings agreed with the conclusion data from this systematic review that higher levels of serum OPN might be used for early diagnosis of osteoporosis in postmenopausal women, if any cuttoff values could be established.

Regarding the relationship between OPN and BMI, it has been suggested that OPN influences the adipogenic process in the bone marrow of obese women, contributing to the development of OP (40). In postmenopausal osteoporotic women an imbalance has been demonstrated between differentiation capacity (adipogenesis or osteogenesis) of the mesenchymal stem cell (MSCs) resident in bone marrow. The adipocytic versus osteoblastic differentiation is prevailing in this group compared to healthy women and, due to the decrease in the synthesis and deposition of type I collagen of the extracellular matrix, the mineralization process is diminished (40). Considerable amount of fat in the bone marrow of osteoporotic women compared to healthy young women was demonstrated (41-45). There is evidence that increased weight or BMI translate into higher BMD, but the parallel increase in adiposity alters bone-regulating hormones that can diminish bone quality (46). Lower body fat mass was observed to be an independent risk factor for higher bone loss at the lumbar spine in women (45). Some reports have shown that excessive visceral fat, fat mass and central adiposity have negative effects on bone health, being associated with low BMD (47-50). Supporting this hypothesis, one study showed that trunk fat was negatively correlated with BMD, playing an important role in skeletal metabolism in terms of low BMD, bone markers, and systemic factors influencing bone tissue (51). In our analysis, there were three studies (25, 29, 30) that found a negative correlation between OPN and BMI, suggesting that OPN may represent a multifaceted regulator between fat and bone remodelling, but further studies are necessary to define the precise relationship between OPN, OP and obesity.

BTMs can be used as surrogates for monitoring osteoblastic and osteoclastic activity (52). OCN is produced by osteoblasts during bone formation and is accumulated in the reversal lines in the fully mineralized matrix. Increased levels of OCN were observed during the transition from osteoid to mature mineralized matrix, while low concentrations were showed during the first mineral formation, indicating that OCN is closely associated with progression of the mineralization process (53, 54). Bone alkaline phosphatase (BAP) is the most used marker of bone formation, being actively excreted by osteoblasts. In OP BAP can be moderately increased due to the generalized increased bone turnover (55). During bone resorption, osteoclasts secrete a mixture of acid and neutral proteases that degrade the collagen fibrils intro molecular fragments including C-terminal telopeptide (CTx). As bone ages, the alpha form of aspartic acid present in CTx converts to the beta form, which is found in the bloodstream during bone resorption and is a specific marker for the degradation of mature type I collagen. High serum levels of beta-CTx have been reported in patients with increased bone resorption (56) and positive correlations between OPN and CTX (23, 24), OPN and BAP (25), and OPN and OC in patients with OP has been demonstrated (25, 27).

The results of this systematic review must be considered within their limitations. First, we only included studies published in English, which may cause potential biases regarding the exclusion of qualified studies based on language criteria. Second, we excluded studies that had the same interest but did not observe our inclusion criteria. Third, the normal values of the analysed parameters were different in terms of patients’ menopausal status which prevented us to establish the cut-off value for OPN. Also, we encountered difficulties regarding BMD analysis as not all studies expressed results as T-score and BMD. Moreover, the studies included in the analysis were not homogeneous: three studies, from all seven, used also control groups, therefore OPN was measured not only in postmenopausal women but, also in control groups. Also, not all the seven studies included in this analysis investigated the presence of vertebral fractures or measured BMD at both sites (lumbar spine and hip). BMD measurements of the lumbar spine in postmenopausal group were not performed in all seven studies.

In conclusion, serum OPN levels might be used for the early and improved detection of fracture risk, especially in postmenopausal women, with or without osteoporotic vertebral fractures. Nevertheless, further clinical research with larger sample size is necessary in order to obtain a more comprehensive statistical analysis.

Conflict of interest

The authors declare that they have no conflict of interest.

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