Download biomedica product listOPG ELISA Kit (Human Osteoprotegerin) | BI-20403
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Method
Sandwich ELISA, HRP/TMB, 12×8-well detachable strips
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Sample type
Serum, plasma (EDTA, heparın, citrate)
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Sample volume
20 µl / well
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Assay time
4 h / 1 h / 30 min
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Sensitivity
0.07 pmol/l (= 1.4 pg/ml)
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Standard range
0 – 20 pmol/l (= 0 – 400 pg/ml)
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Conversion factor
1 pg/ml = 0.05 pmol/l (MW: 19.9 kDa)
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Specificity
Endogenous and recombinant human OPG.
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Precision
In-between-run (n=12): ≤ 5 % CV
Within-run (n=5): ≤ 3 % CV
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Cross-reactivity
The assay does not cross react with rat or mouse samples.
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Validation Data
See validation data tab for: precision, accuracy, dilution linearity, values for healthy donors, etc
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Use
Research use only
OPG ELISA Product Overview
The human Osteoprotegerin ELISA kit (OPG) is a 4.5 hour, 96-well sandwich ELISA for the quantitative determination of OPG in human serum and plasma. The Osteoprotegerin kit employs human serum-based standards to ensure the measurement of biologically reliable data.
OPG ELISA Assay Principle
The human OPG ELISA kit is a sandwich enzyme immunoassay for the determination of OPG in human serum and plasma samples.
The figure below explains the principle of the Osteoprotegerin sandwich ELISA:
Capture antibody: polyclonal goat anti-human OPG antibody
Detection antibody: monoclonal mouse anti-human OPG, biotin-labeled
Target antigen: human OPG
In a first step, assay buffer, standard/control/sample and detection antibody (biotinylated monoclonal mouse anti-human OPG) are pipetted into the wells of the microtiter strips, which are pre-coated with polyclonal goat anti-human OPG antibody. OPG present in the standard/control/sample binds to the pre-coated antibody in the well and forms a sandwich with the detection antibody. In the washing step all non-specific unbound material is removed. In a second step, the conjugate (streptavidin-HRP) is pipetted into the wells and reacts with the detection antibody. After another washing step, the substrate (TMB, tetramethylbenzidine) is pipetted into the wells. The enzyme-catalyzed color change of the substrate is directly proportional to the amount of OPG. This color change is detectable with a standard microtiter plate reader. A dose response curve of the absorbance (optical density, OD at 450 nm) vs. standard concentration is generated. The concentration of OPG in the sample is determined directly from the dose response curve.
OPG ELISA Typical Standard Curve
The figure below shows a typical standard curve for the ELISA for Osteoprotegerin. The immunoassay is calibrated against recombinant human OPG:
OPG ELISA ELISA Kit Components
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Contents |
Description |
Quantity |
|
PLATE |
Polyclonal goat anti-human OPG antibody pre-coated microtiter strips in strip holder, packed in aluminum bag with desiccant |
12 x 8 tests |
|
WASHBUF |
Wash buffer concentrate 20x, natural cap |
1 x 50 ml |
|
STD |
Standards 1-6, (0; 1.25; 2.5; 5; 10; 20 pmol/l), recombinant human OPG in human serum, white caps, ready to use |
6 x 300 µl |
|
CTRL |
Controls A+B, yellow cap, ready to use, exact concentration see labels |
2 x 300 µl |
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ASYBUF |
Assay buffer, red cap, ready to use |
1 x 25 ml |
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AB |
Monoclonal mouse anti-OPG antibody, biotin labeled, green cap, yellow dye, ready to use |
1 x 7 ml |
|
CONJ |
Conjugate (streptavidin-HRP), amber bottle, amber cap, ready to use |
1 x 22 ml |
|
SUB |
Substrate (TMB solution), amber bottle, blue cap, ready to use |
1 x 22 ml |
|
STOP |
Stop solution, white cap, ready to use |
1 x 7 ml |
Storage instructions: All reagents of the OPG ELISA kit are stable at 4°C (2-8°C) until the expiry date stated on the label of each reagent.
Sample Collection & Storage
Serum, EDTA plasma, heparın plasma and citrate plasma are suitable for use in this Osteoprotegerin Biomedica Assay. Do not change sample type during studies. We recommend duplicate measurements for all samples, standards and controls. The sample collection and storage conditions listed are intended as general guidelines.
Serum & Plasma
Collect venous blood samples in standardized serum separator tubes (SST) or standardized blood collection tubes using EDTA, heparın or citrate as an anticoagulant. For serum samples, allow samples to clot for 30 minutes at room temperature. Perform separation by centrifugation according to the tube manufacturer’s instructions for use. If this is not possible store the samples at 4°C (2-8°C) prior to centrifugation (up to one day). Assay the acquired samples immediately or aliquot and store at -25°C or lower. Lipemic or haemolyzed samples may give erroneous results. Samples can undergo at least four freeze-thaw cycles.
Reagent Preparation
Wash Buffer
|
1. |
Bring the WASHBUF concentrate to room temperature. Crystals in the buffer concentrate will dissolve at room temperature. |
|
2. |
Dilute the WASHBUF concentrate 1:20, e.g. 50 ml WASHBUF + 950 ml distilled or deionized water. Only use diluted WASHBUF when performing the assay. |
The diluted WASHBUF is stable up to one month at 4°C (2-8°C).
Sample Preparation
Bring samples to room temperature and mix samples gently to ensure the samples are homogenous. We recommend duplicate measurements for all samples.
Samples for which the OD value exceeds the highest point of the standard range can be diluted with STD1 or OPG negative human serum.
OPG ELISA Assay Protocol
Read the entire protocol before beginning the assay.
|
1. |
Bring samples and reagents to room temperature (18-24°C). |
|
2. |
Mark positions for STD/CTRL/SAMPLE (standard/control/sample) on the protocol sheet. |
|
3. |
Take microtiter strips out of the aluminum bag. Store unused strips with desiccant at 4°C in the aluminum bag. Strips are stable until expiry date stated on the label. |
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4. |
Pipette 150 µl ASYBUF (assay buffer, red cap) into each well. |
|
5. |
Add 20 µl STD/CTRL/SAMPLE (standard/control/sample) in duplicates into respective wells, swirl gently. |
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6. |
Add 50 µl AB (biotinylated anti-OPG antibody, green cap) into each well, swirl gently. |
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7. |
Cover the plate tightly and incubate for 4 hours at room temperature (18-24°C). |
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8. |
Aspirate and wash wells 5x with 300 µl diluted WASHBUF (wash buffer). After the final wash, remove remaining WASHBUF by strongly tapping the plate against a paper towel. |
|
9. |
Add 200 µl CONJ (conjugate, amber cap) into each well. |
|
10. |
Cover tightly and incubate for 1 hour at room temperature (18-24°C). |
|
11. |
Aspirate and wash wells 5x with 300 µl diluted WASHBUF (wash buffer). After the final wash, remove remaining WASHBUF by strongly tapping the plate against a paper towel. |
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12. |
Add 200 µl SUB (substrate, blue cap) into each well. |
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13. |
Incubate for 30 min at room temperature (18-24°C) in the dark. |
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14. |
Add 50 µl STOP (stop solution, white cap) into each well, swirl gently. |
|
15. |
Measure absorbance immediately at 450 nm with reference 630 nm, if available. |
Calculation of Results
Read the optical density (OD) of all wells on a plate reader using 450 nm wavelength (reference wavelength 630 nm). Construct a standard curve from the absorbance read-outs of the standards using commercially available software capable of generating a four-parameter logistic (4-PL) fit. Alternatively, plot the standards’ concentration on the x-axis against the mean absorbance for each standard on the y-axis and draw a best fit curve through the points on the graph. Curve fitting algorithms other than 4-PL have not been validated and will need to be evaluated by the user.
Obtain sample concentrations from the standard curve. If required, pmol/l can be converted into pg/ml by applying a conversion factor (1 pg/ml = 0.05 pmol/l; OPG MW: 19.9 kDa). Respective dilution factors have to be considered when calculating the final concentration of the sample.
The quality control (QC) protocol supplied with the kit shows the results of the final release QC for each kit at production date. Data for OD obtained by customers may differ due to various influences including the normal decrease of signal intensity throughout shelf life. However, this does not affect validity of results as long as an OD of 1.50 or more is obtained for the STD6 and the values of the CTRLs are within the targets (see labels).
OPG Protein
Osteoprotegerin (OPG) or osteoclast inhibitory factor (OCIF) is a glycoprotein of the tumor necrosis factor receptor superfamily encoded by the TNFRSF11B gene. OPG is synthesized as a monomer of 380 amino acids, assembled as a homodimer within the cell and then secreted mainly as a disulfide-linked homodimer into the extracellular compartment. OPG is produced by many different tissues and cell types including osteoblasts, breast tissue, vascular endothelial cells as well as B cells and dendritic cells in the immune system.
|
Molecular weight |
19.9 kDa |
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Cellular localization |
Extracellular |
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Post-translational modifications |
Glycosylation |
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Sequence similarities |
Member of the tumor necrosis factor receptor superfamily |
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Alternative names |
TNFRSF11B, OCIF, PDB5, TR1, tumor necrosis factor receptor superfamily member 11b, TNF receptor superfamily member 11b, osteoclastogenesis inhibitory factor |
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Entrez/NCBI ID |
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Genecards |
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OMIM |
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PDB |
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Protein Atlas |
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Uniprot ID |
OPG Function
OPG is a negative regulator of bone resorption by acting as decoy receptor for Receptor Activator of NF-κB Ligand (RANKL), thus neutralizing its function in osteoclastogenesis. It is also a decoy receptor for TRAIL and thereby inhibits apoptosis of mature osteoclasts. Hence, OPG is centrally involved in the regulation of bone resorbtion and formation. Since estrogen induces the expression of OPG in osteoblasts, post-menopausal decrease in estrogen levels can lead to the development of osteoporosis due to decreased OPG expression and enhanced RANKL-induced osteoclastogenesis. In contrast to estrogen, glucocorticoids induce the expression of RANKL and decrease the expressioin of OPG, which may lead to glucocorticoid-induced osteoporosis. Proinflammatory cytokines also increase the RANKL/OPG ratio and hence, induce bone loss in diseases like rheumatoid arthritis or periodontitis.
OPG has further been identified to promote tumor growth and survival by inducing tumor vascularization and inhibiting TRAIL-mediated tumor cell death. Dysregulation of the RANKL/OPG system is also common in metastatic bone disease, which is often observed in disseminated cancers of breast, prostate and lung. In multiple myeloma, reduced OPG levels and increased osteoclastogenesis cause the formation of osteolytic bone lesions.
Increased concentrations of OPG, especially in the context of diabetes and chronic kidney disease, are associated with vascular calcification and increased cardiovascular risk.
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Cardiovascular Diseases
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Vascular calcification
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Peripheral artery disease
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Heart failure
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Coronary artery disease
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Oncology
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Multiple myeloma
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Hairy cell leukemia
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Breast cancer
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Prostate Cancer
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Lung Cancer
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Bone metastasis
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Osteosarcoma
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Tumor-induced osteomalacia
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Literature
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Kenkre, J.S., Bassett, J., 2018. Ann. Clin. Biochem. 55, 308–327.
PMID:29368538 -
The Osteoprotegerin: multiple partners for multiple functions.
Baud’huin, M., Duplomb, L., Teletchea, S., Lamoureux, F., Ruiz-Velasco, C., Maillasson, M., Redini, F., Heymann, M.-F., Heymann, D., 2013. Cytokine Growth Factor Rev. 24, 401–409.
PMID:23827649 -
Bone Remodelling Markers in Rheumatoid Arthritis.
Fardellone, P., Séjourné, A., Paccou, J., Goëb, V., 2014. Mediators Inflamm 2014.
PMID:24839355 -
Glucocorticoid-induced osteoporosis.
Briot, K., Roux, C., 2015. RMD Open 1, e000014.
PMCID: PMC4613168
PMID:26509049 -
Inflammatory bone loss: pathogenesis and therapeutic intervention.
Redlich, K., Smolen, J.S., 2012. Nature Reviews Drug Discovery 11, 234–250.
PMID:22378270 -
The role of biomarkers in the management of bone-homing malignancies.
D’Oronzo, S., Brown, J., Coleman, R., 2017. J Bone Oncol 9, 1–9.
PMCID: PMC5602513
PMID:28948139 -
Rachner, T.D., Kasimir-Bauer, S., Göbel, A., Erdmann, K., Hoffmann, O., Browne, A.J., Wimberger, P., Rauner, M., Hofbauer, L.C., Kimmig, R., Bittner, A.-K., 2018. Clin. Cancer Res.
PMID:30425091 -
Aberrant regulation of RANKL/OPG in women at high risk of developing breast cancer.
Kiechl, S., Schramek, D., Widschwendter, M., Fourkala, E.-O., Zaikin, A., Jones, A., Jaeger, B., Rack, B., Janni, W., Scholz, C., Willeit, J., Weger, S., Mayr, A., Teschendorff, A., Rosenthal, A., Fraser, L., Philpott, S., Dubeau, L., Keshtgar, M., Roylance, R., Jacobs, I.J., Menon, U., Schett, G., Penninger, J.M., 2016. Oncotarget 8, 3811–3825.
PMCID: PMC5354797
PMID:28002811 -
Infante, M., Fabi, A., Cognetti, F., Gorini, S., Caprio, M., Fabbri, A., 2019. J. Exp. Clin. Cancer Res. 38, 12.
PMCID: PMC6325760
PMID:30621730 -
Serum osteoprotegerin and sex steroid levels in patients with prostate cancer.
Varsavsky, M., Reyes-Garcia, R., Avilés Perez, M.D., Gonzalez Ramírez, A.R., Mijan, J.L., Muñoz-Torres, M., 2012. J. Androl. 33, 594–600.
PMID:21903971 -
Role of the RANK/RANKL Pathway in Multiple Myeloma
Raje, N.S., Bhatta, S., Terpos, E., 2019. Clin. Cancer Res. 25, 12–20.
PMID:30093448 -
Rochette, L., Meloux, A., Rigal, E., Zeller, M., Cottin, Y., Vergely, C., 2018. Pharmacol. Ther. 182, 115–132.
PMID:28867452
PMID:29368538All Biomedica ELISAs are validated according to international FDA/ICH/EMEA guidelines. For more information about our validation guidelines, please refer to our quality page and published validation guidelines and literature.
- ICH Q2 (R1) Validation of Analytical Procedures: Text and Methodology
- EMEA/CHMP/EWP/192217/2009 Guideline on Validation of Bioanalytical Methods
- Bioanalytical Method Validation, Guidance for Industry, FDA, May 2018
Calibration
The OPG immunoassay is calibrated against recombinant human OPG protein (AA 22-194 of O00300 (Uniprot ID)).
OPG ELISA Detection Limit & Sensitivity
To determine the sensitivity of the OPG ELISA, experiments measuring the lower limit of detection (LOD) and the lower limit of quantification (LLOQ) were conducted.
The LOD, also called the detection limit, is the lowest point at which a signal can be distinguished above the background signal, i.e. the signal that is measured in the absence of OPG, with a confidence level of 99%. It is defined as the mean back calculated concentration of standard 1 (0 pmol/l of OPG, five independent measurements) plus three times the standard deviation of the measurements.
The LLOQ, or sensitivity of an assay, is the lowest concentration at which an analyte can be accurately quantified. The criteria for accurate quantification at the LLOQ are an analyte recovery between 75 and 125% and a coefficient of variation (CV) of less than 25%. To determine the LLOQ, standard 2, i.e. the lowest standards containing OPG, is diluted, measured two times and its concentration is back calculated. The lowest dilution, which meets both criteria, is reported as the LLOQ.
The following values were determined for the OPG ELISA:
|
LOD |
0.07 pmol/l |
|
LLOQ |
0.08 pmol/l |
OPG ELISA Precision
The precision of an ELISA is defined as its ability to measure the same concentration consistently within the same experiments carried out by one operator (within-run precision or repeatability) and across several experiments using the same samples but conducted by several operators at different locations using different ELISA lots (in-between-run precision or reproducibility).
Within-Run Precision
Within-run (intra-assay) precision was assessed by measuring two samples of known concentrations five times within one OPG ELISA kit lot by one operater.
|
ID |
n |
Mean OPG [pmol/l] |
SD [pmol/l] |
CV (%) |
|
Sample 1 |
5 |
3.2 |
0.05 |
2 |
|
Sample 2 |
5 |
10.1 |
0.34 |
3 |
In-Between Run Precision
In-between-run (inter-assay) precision was assessed by measuring two samples twelve times within two OPG ELISA kit lots by three different operaters.
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ID |
n |
Mean OPG [pmol/l] |
SD [pmol/l] |
CV (%) |
|
Sample 1 |
12 |
3.2 |
0.10 |
3 |
|
Sample 2 |
12 |
9.9 |
0.5 |
5 |
OPG ELISA Accuracy
The accuracy of an ELISA is defined as the precision with which it can recover samples of known concentrations.
The recovery of the OPG ELISA was measured by adding recombinant OPG to human samples containing a known concentration endogenous OPG. The %recovery of the spiked concentration was calculated as the percentage of measured compared over the expected value. All our ELISAs are expected to have %recovery rates within 15% of the nominal value of the sample.
This table shows the summary of the recovery experiments in the OPG ELISA in different sample matrices:
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|
% Recovery |
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|
+ 2 pmol/l |
+ 5 pmol/l |
+ 10 pmol/l |
|||||
|
Sample matrix |
n |
Mean |
Range |
Mean |
Range |
Mean |
Range |
|
Serum |
3 |
95 |
85-106 |
105 |
94-111 |
95 |
89-99 |
|
EDTA plasma |
3 |
100 |
99-102 |
93 |
83-113 |
108 |
93-119 |
|
Citrate plasma |
3 |
88 |
82-96 |
89 |
76-100 |
109 |
99-120 |
|
Heparın plasma |
3 |
91 |
67-118 |
82 |
70-95 |
94 |
84-110 |
Data showing recovery of recombinant OPG in human serum samples:
|
OPG [pmol/l] |
Recovery (%) |
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|
Sample matrix |
ID |
Reference |
+2 pmol/l |
+5 pmol/l |
+10 pmol/l |
+2 pmol/l |
+5 pmol/l |
+10 pmol/l |
|
Serum |
s1 |
3.8 |
5.5 |
8.1 |
13.3 |
106 |
94 |
99 |
|
Serum |
s2 |
2.6 |
4.5 |
8.2 |
12.3 |
95 |
110 |
97 |
|
Serum |
s3 |
3.5 |
5.2 |
9.0 |
12.4 |
85 |
111 |
89 |
|
Mean |
95 |
105 |
95 |
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Data showing recovery of recombinant OPG in human EDTA plasma samples:
|
OPG [pmol/l] |
Recovery (%) |
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|
Sample matrix |
ID |
Reference |
+2 pmol/l |
+5 pmol/l |
+10 pmol/l |
+2 pmol/l |
+5 pmol/l |
+10 pmol/l |
|
EDTA plasma |
e1 |
3.3 | 5.2 | 7.4 | 14.4 | 99 | 83 | 112 |
|
EDTA plasma |
e2 |
2.5 | 4.6 | 6.7 | 14.4 | 102 | 83 | 119 |
|
EDTA plasma |
e3 |
3.3 | 5.3 | 8.9 | 12.5 | 100 | 113 | 93 |
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Mean |
100 | 93 | 108 | |||||
Data showing recovery of recombinant OPG in human citrate plasma samples:
|
OPG [pmol/l] |
Recovery (%) |
|||||||
|
Sample matrix |
ID |
Reference |
+2 pmol/l |
+5 pmol/l |
+10 pmol/l |
+2 pmol/l |
+5 pmol/l |
+10 pmol/l |
|
Citrate plasma |
c1 |
2.7 | 4.4 | 7.7 | 12.6 | 85 | 100 | 99 |
|
Citrate plasma |
c2 |
2.1 | 4.0 | 5.9 | 12.9 | 96 | 76 | 108 |
|
Citrate plasma |
c3 |
2.8 | 4.4 | 7.3 | 14.8 | 82 | 90 | 120 |
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Mean |
88 | 89 | 109 | |||||
Data showing recovery of recombinant OPG in human heparın plasma samples:
|
OPG [pmol/l] |
Recovery (%) |
|||||||
|
Sample matrix |
ID |
Reference |
+2 pmol/l |
+5 pmol/l |
+10 pmol/l |
+2 pmol/l |
+5 pmol/l |
+10 pmol/l |
|
Heparın plasma |
h1 |
3.1 | 4.4 | 6.6 | 11.5 | 67 | 70 | 84 |
|
Heparın plasma |
h2 |
2.3 | 4.6 | 6.4 | 13.3 | 118 | 82 | 110 |
|
Heparın plasma |
h3 |
3.1 | 4.9 | 7.9 | 12.0 | 87 | 95 | 89 |
|
Mean |
91 | 82 | 94 | |||||
OPG ELISA Dilution Linearity & Paralellism
Tests of dilution linearity and parallelism ensure that samples containing recombinant or endogenous and OPG behave in a dose dependent manner and are not affected by matrix effects. Dilution linearity assesses the accuracy of measurements in diluted clinical samples spiked with known concentrations of recombinant analyte. By contrast, parallelism refers to dilution linearity in clinical samples and provides evidence that the endogenous analyte behaves in same way as the recombinant one. Dilution linearity and parallelism are assessed for each sample type and are considered acceptable if the results are within ±20% of the expected concentration.
Dilution Linearity
Dilution linearity was assessed by serially diluting human serum samples spiked with 6 pmol/l recombinant OPG with standard 1.
The table below shows the mean recovery and range of serially diluted recombinant OPG in serum samples:
|
|
|
% Recovery of recombinant OPG in diluted samples |
|
|
1+1 |
|||
|
Sample matrix |
n |
Mean |
Range |
|
Serum |
8 |
96 |
84-116 |
Data showing dilution linearity of 6 pmol/l recombinant OPG spiked into human serum samples containing endogenous OPG:
|
OPG [pmol/l] |
% Recovery |
||||
|
Sample matrix |
ID |
Unspiked |
Reference |
1+1 |
1+1 |
|
Serum |
s1 |
3.7 |
10.7 |
5.2 |
98 |
|
Serum |
s2 |
2.3 |
6.7 |
3.9 |
116 |
|
Serum |
s3 |
4.4 |
12.8 |
5.1 |
80 |
| Serum | s4 |
3.4 |
12.0 |
5.1 |
86 |
| Serum | s5 |
3.3 |
9.4 |
5.0 |
107 |
| Serum | s6 |
3.6 |
10.3 |
5.2 |
101 |
| Serum | s7 |
4.4 |
11.6 |
4.9 |
84 |
| Serum | s8 |
4.7 |
10.9 |
5.2 |
96 |
|
Mean |
96 | ||||
|
Min |
84 | ||||
|
Max |
116 | ||||
Parallelism
Parallelism was assessed by serially diluting human serum samples containing endogenous OPG with standard 1.
The table below shows the mean recovery and range of serially diluted endogenous OPG in human serum samples:
|
% Recovery of endogenous OPG in diluted samples |
|||||||
|
1+1 |
1+3 |
1+7 |
|||||
|
Sample matrix |
n |
Mean |
Range |
Mean |
Range |
Mean |
Range |
|
Serum |
3 |
98 |
92-102 |
90 |
86-94 |
87 |
79-86 |
Data showing dilution linearity of endogenous OPG in human serum samples:
|
OPG [pmol/l] |
% Recovery |
|||||||
|
Sample matrix |
ID |
Reference |
1+1 |
1+3 |
1+7 |
1+ |
1+3 |
1+7 |
|
Serum |
s1 |
8.2 |
4.1 |
1.9 |
0.9 |
99 |
94 |
86 |
|
Serum |
s2 |
3.6 |
1.9 |
0.8 |
0.4 |
102 |
92 |
95 |
|
Serum |
s3 |
6.7 |
3.1 |
1.4 |
0.7 |
92 |
86 |
79 |
|
|
|
|
|
|
Mean |
98 |
90 |
87 |
OPG ELISA Specificity
The OPG ELISA recognizes human endogenous and recombinant OPG. It detects monomeric and dimeric OPG as well as OPG-RANKL complexes. The assay does not cross-react with rat or mouse samples.
Sample Stability
The stability of endogenous OPG was tested by comparing OPG measurements in samples that had undergone four freeze-thaw (F/T) cycles.
For freeze-thaw experiments, samples were collected according to the supplier’s instruction using blood collection devices and stored at -80°C. Reference samples were freeze-thawed once. The mean recovery of sample concentration after four freeze-thaw cycles is 101%.
|
OPG [pmol/l] |
||||||
|
Sample matrix |
ID |
Reference |
2x |
3x |
4x |
% Recovery after 4x F/T |
|
Serum |
s1 |
2.8 |
2.8 |
3.7 |
2.5 |
86 |
|
Serum |
s2 |
3.1 |
3.8 |
4.1 |
3.7 |
119 |
|
Serum |
s3 |
5.0 |
5.4 |
5.3 |
5.1 |
103 |
|
Serum |
s4 |
2.6 |
3.0 |
2.6 |
2.5 |
94 |
|
|
|
|
|
|
Mean |
101 |
Samples can undergo at least four freeze-thaw cycles.
Sample Values
OPG Values in Apparently Healthy Individuals
To provide expected values for circulating OPG, a panel of samples from apparently healthy donors was tested.
A summary of the results is shown below:
|
OPG [pmol/l] |
||
|
Sample matrix |
n |
Mean |
|
Serum |
60 |
2.7 |
|
EDTA plasma |
6 |
2.2 |
|
Citrate plasma |
5 |
2.3 |
|
Heparın plasma |
7 |
2.3 |
It is recommended to establish the normal range for each laboratory.
Matrix Comparison
To assess whether all tested matrices behave the same way in the OPG ELISA, concentrations of OPG were measured in serum, EDTA, citrate and heparın plasma samples prepared from four apparently healthy donors. Each individual donated blood in all tested sample matrices.
A summary table of OPG levels in various sample matrices is shown below:
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|
|
OPG [pmol/l] |
|
|||
|
Sample ID |
Serum |
EDTA plasma |
Citrate plasma |
Heparın plasma |
% CV |
|
#1 |
2.8 |
3.4 |
2.4 |
2.9 |
14 |
|
#2 |
2.8 |
2.8 |
2.6 |
2.3 |
9 |
|
#3 |
2.1 |
3.1 |
2.3 |
2.6 |
17 |
|
#4 |
0.9 |
1.0 |
0.8 |
0.8 |
11 |
| Mean |
13 |
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- Evolution of Circulating Bone-Related Biomarkers After Kidney Transplantation. Juliana Carvalho Magalhães. 2021, Dissertation: https://hdl.handle.net/10216/134330
- Association of bone biomarkers with advanced atherosclerotic disease in people with overweight/obesity. Del Toro R, Cavallari I, Tramontana F, Park K, Strollo R, Valente L, De Pascalis M, Grigioni F, Pozzilli P, Buzzetti R, Napoli N, Maddaloni E. Endocrine. 2021 Aug;73(2):339-346. doi: 10.1007/s12020-021-02736-8. Epub 2021 May 4. PMID: 33948786.
- Tocilizumab decreases T cells but not macrophages in the synovium of patients with rheumatoid arthritis while it increases the levels of serum interleukin-6 and RANKL. Chatzidionysiou K, Circiumaru A, Rethi B, Joshua V, Engstrom M, Hensvold A, Af Klint E, Catrina A RMD Open. 2021 Jun;7(2):e001662. doi: 10.1136/rmdopen-2021-001662. PMID: 34112702.
- Osteoprotegerin is an independent risk factor predicting death in stable renal transplant recipients. Zeng S, Hasan AA, Chu C, Xiong Y, Hocher JG, Elitok S, Krämer BK, Hocher B. Clin Nephrol. 2021 May 27. doi: 10.5414/CN110470. Epub ahead of print. PMID: 34042584.
- Atherosclerosis and Bone Loss in Humans-Results From Deceased Donors and From Patients Submitted to Carotid Endarterectomy. Carmona-Fernandes D, Barreira SC, Leonardo N, Casimiro RI, Castro AM, Santos PO, Fernandes AN, Cortes-Figueiredo F, Gonçalves CA, Cruz R, Fernandes ML, Ivo M, Pedro LM, Canhão H, Fonseca JE, Santos MJ.Front Med (Lausanne). 2021 May 20;8:672496. doi: 10.3389/fmed.2021.672496. PMID: 34095177.
- Associations of Circulating Osteoglycin With Bone Parameters and Metabolic Markers in Patients With Diabetes. Starup-Linde JK, Viggers R, Langdahl B, Gregersen S, Lykkeboe S, Handberg A, Vestergaard P.Front Endocrinol (Lausanne). 2021 Mar 15;12:649718. doi: 10.3389/fendo.2021.649718. PMID: 33790870; PMCID: PMC8006932.
- Carfilzomib Improves Bone Metabolism in Patients with Advanced Relapsed/Refractory Multiple Myeloma: Results of the CarMMa Study. Terpos E, Ntanasis-Stathopoulos I, Katodritou E, Kyrtsonis MC, Douka V, Spanoudakis E, Papatheodorou A, Eleutherakis-Papaiakovou E, Kanellias N, Gavriatopoulou M, Makras P, Kastritis E, Dimopoulos MA. Cancers (Basel). 2021 Mar 12;13(6):1257. doi: 10.3390/cancers13061257. PMID: 33809268.
- Effects of Er:YAG laser irradiation of different titanium surfaces on osteoblast response. Wehner C, Laky M, Shokoohi-Tabrizi HA, Behm C, Moritz A, Rausch-Fan X, Andrukhov O. J Mater Sci Mater Med. 2021 Mar 6;32(3):22. doi: 10.1007/s10856-021-06493-y. PMID: 33675441.
- Effects of competitive physical activity on serum irisin levels and bone turnover markers. Gaudio A, Rapisarda R, Xourafa A, Zanoli L, Manfrè V, Catalano A, Signorelli SS, Castellino P. J Endocrinol Invest. 2021 Mar 6. doi: 10.1007/s40618-021-01529-0. PMID: 33675533.
- Myostatin and markers of bone metabolism in dermatomyositis. Kerschan-Schindl K, Gruther W, Föger-Samwald U, Bangert C, Kudlacek S, Pietschmann P. BMC Musculoskelet Disord. 2021 Feb 5;22(1):150. doi: 10.1186/s12891-021-04030-0. PMID: 33546660; PMCID: PMC7866468
- Obesity potentially protects against systemic bone loss in patients with rheumatoid arthritis treated with tumour necrosis factor inhibitors. Lee SY, Jung KH, Park SG, Kwon SR, Park W, Lim MJ. Clin Exp Rheumatol. 2021 Jan-Feb;39(1):125-131. Epub 2020 Apr 9. PMID: 32301429.
- Relation of the Serum Levels of DKK-1 and Osteoprotegerin with Bone Mass in Tightly Controlled Rheumatoid Arthritis. Gómez-Vaquero C, Martín I, Zacarías A, Alía P, Loza E, Carmona L, Narváez J. Curr Rheumatol Rev. 2021;17(1):101-108. PMID: 33349216.
- Systemic Bone Density at Disease Onset Is Associated With Joint Erosion Progression in Early Naive to Treatment Rheumatoid Arthritis: A Prospective 12-Month Follow-Up Open-Label Study. Bruno D., Fedele A.L., Tolusso B., Barini A., Petricca L., Di Mario C., Barini A., Mirone L., Ferraccioli G., Alivernini S., Gremese E., 2021. Front Med (Lausanne); 8:613889.
- Association between serum osteoprotegerin level and mortality in kidney transplant recipients. Gupta V., Ekundayo O., Nemeth Z.K., Yang Y., Covic A., Mathe Z., Kovesdy C.P., Molnar M.Z., Mucsi I., Transpl Int. 2021. Feb 19. doi: 10.1111/tri.13847. PMID: 33606319.
- Obesity potentially protects against systemic bone loss in patients with rheumatoid arthritis treated with tumour necrosis factor inhibitors. Lee S.Y., Jung K.H., Park S.G., Kwon S.R., Park W., Lim M.J., 2021. Clin Exp Rheumatol 39(1):125-131. PMID: 32301429.
- Association of Receptor Activator of Nuclear Factor-κB Ligand (RANKL) and Osteoprotegerin with Secondary Hypogonadism in Egyptian Females with Beta-Thalassemia Major. Rashad N.M., El-Helaly A.M., Radwan A.M., Ibrahim N.F., 2021. The Egyptian Journal of Hospital Medicine 29; 82(2):369-378.
- Effects of marathon race on selected myokines and sclerostin in middle-aged male amateur runners. Śliwicka E., Cisoń .T, Pilaczyńska-Szcześniak Ł., Ziemba A., Straburzyńska-Lupa A., Sci Rep. 2021. 11(1):2813.
- High Cardiovascular Risk in Older Men with Poor Bone Microarchitecture-The Prospective STRAMBO Study. Szulc P., Foesser D., Chapurlat R., 2021. J Bone Miner Res Feb 2. doi: 10.1002/jbmr.4261. PMID: 33528838.
- Vascular calcification relationship to vascular biomarkers and bone metabolism in advanced chronic kidney disease. Salam S., Gallagher O., Gossiel F., Paggiosi M., Eastell R., Khwaja A., Bone. 2021. Feb;143:115699. doi: 10.1016/j.bone.2020.115699. PMID: 33091638.
- Effects of a whey protein pre-meal on bone turnover in participants with and without type 2 diabetes-A post hoc analysis of a randomised, controlled, crossover trial. Bjørnshave A., Lykkeboe S., Hartmann B., Holst J.J., Hermansen K., Starup-Linde J., 2020. Diabet Med 1:e14471. PMID: 33259643.
- Osteoprotegerin, interleukin and hepatocyte growth factor for prediction of diabetes and hypertension in the third trimester of pregnancy. Huang S.J., Wang H.W., Wu H.F., Wei Q.Y., Luo S., Xu L., Guan H.Q., 2020. World J Clin Cases 26;8(22):5529-5534. PMID: 33344543.
- Osteoprotegerin levels in children with subclinical hypothyroidism. Giannakopoulos A., Katsantoni E., Kritikou D., Chrysis D., 2020. Acta Paediatr 109(12):2770-2774. doi: 10.1111/apa.15291. PMID: 32259306.
- Chronic obstructive pulmonary disease severity in middle-aged and older men with osteoporosis associates with decreased bone formation. Tsukamoto M., Mori T., Nakamura E., Okada Y., Fukuda H., Yamanaka Y., Sabanai K., Wang K.Y., Hanagiri T., Kuboi S., Yatera K., Sakai A., 2020. Osteoporos Sarcopenia 6(4):179-184. PMID: 33426306.
- Clinical and Instrumental Evaluation of the Effectiveness of Surgical Treatment of Chronic Generalized Periodontitis Using RANK-RANKL-OPG Biomarkers. Gaybullaev, Elbek A.; Rizaev, Jasur A.; Abdullaev, Bekhzod Sh. 2020. Indian J Forensic Med & Toxicol 14 (4): 7454-7456.
- Bone remodeling features in elderly and senile patients with the proximal femur fractures after hip replacement. Khvysyuk O.M., Babalian V.O., Pavlov S.B., Pavlova G.B., 2020. Wiad Lek 73(2):259-265. PMID: 32248156.
- The relationship between bone regulatory markers and bone turnover in renal osteodystrophy. Salam S., Gallagher O., Gossiel F., Arif Khwaja A., Eastell R., 2020. Nephrology Dialysis Transplantation 35, Issue Supplement_3, gfaa142.P0885.
- Significance of acPWV for Survival of Hemodialysis Patients. Petrovic M., Baralic M., Brkovic V., Arsenovic A., Stojanov V., Lalic N., Stanisavljevic D., Jankovic A., Radivojevic N., Pejanovic S., Maric I., Lezaic V., 2020. Medicina 28;56(9):435. PMID: 32872092.
- Metabolic bone markers can be related to preserved insulin secretion in children with newly diagnosed type 1 diabetes. Szymańska M., Michałus I., Kaszkowiak M., Wyka K., Chlebna-Sokół D., Fendler W., Jakubowska-Pietkiewicz E., Młynarski W., Szadkowska A., Zmysłowska A., 2020. Pediatr Endocrinol Diabetes Metab 26(1):10-16. PMID: 32418417.
- Is the personalized approach the key to improve clinical diagnosis of peri-implant conditions? The role of bone markers. Rakic M., Monje A., Radovanovic S., Petkovic-Curcin A., Vojvodic D., Tatic Z., 2020. J Periodontol 91(7):859-869. PMID: 31773730.
- The effect of 4 months exercise training on systemic biomarkers of cartilage and bone turnover in hip osteoarthritis patients. Ellegaard M., Bieler T., Beyer N., Kjaer M., Jorgensen NR.n 2020. Translational Sports Medicine 3(1):16-25.
- Effects of a whey protein pre-meal on bone turnover in participants with and without type 2 diabetes-A post hoc analysis of a randomised, controlled, crossover trial. Bjørnshave A., Lykkeboe S., Hartmann B., Holst J.J., Hermansen K., Starup-Linde J., 2020. Diabet Med 1:e14471. PMID: 33259643.
- Osteoprotegerin, interleukin and hepatocyte growth factor for prediction of diabetes and hypertension in the third trimester of pregnancy. Huang S.J., Wang H.W., Wu H.F., Wei Q.Y., Luo S., Xu L., Guan H.Q., 2020. World J Clin Cases 26;8(22):5529-5534. PMID: 33344543.
- The Effect of Treatment and Bone Metabolic Factors on Fracture Incidence in Patients with Thalassemia-Induced Osteoporosis: An Observational Study. Tsartsalis A.N., Lambrou G.I., Vlachou E., Samartzi A., Chrousos G.P., Kanaka-Gantenbein K., Kattamis A., 15(4): 381 – 388.
- Effects of 1-year anti-TNF-α therapies on bone mineral density and bone biomarkers in rheumatoid arthritis and ankylosing spondylitis. Gulyás, K., Horváth, Á., Végh, E., Pusztai, A., Szentpétery, Á., Pethö, Z., Váncsa, A., Bodnár, N., Csomor, P., Hamar, A., Bodoki, L., Bhattoa, H.P., Juhász, B., Nagy, Z., Hodosi, K., Karosi, T., FitzGerald, O., Szücs, G., Szekanecz, Z., Szamosi, S., Szántó, S., 2020. Clin Rheumatol 39, 167–175.
- RANKL and OPG and their influence on breast volume changes during pregnancy in healthy women. Wunderle, M., Ruebner, M., Häberle, L., Schwenke, E., Hack, C.C., Bayer, C.M., Koch, M.C., Schwitulla, J., Schulz-Wendtland, R., Kozieradzki, I., Lux, M.P., Beckmann, M.W., Jud, S.M., Penninger, J.M., Schneider, M.O., Fasching, P.A., 2020. Scientific Reports 10, 1–8.
- Juvenile Paget’s disease with compound heterozygous mutations in TNFRSF11B presenting with recurrent clavicular fractures and a mild skeletal phenotype.
Naot, D., Wilson, L.C., Allgrove, J., Adviento, E., Piec, I., Musson, D.S., Cundy, T., Calder, A.D., 2020. Bone 130, 115098.
- Evaluating RANKL and OPG levels in patients with Duchenne muscular dystrophy. Ali, S.A., Kang, H., Olney, R., Ramos-Platt, L., Ryabets-Lienhard, A., Cheung, C., Georgia, S., Pitukcheewanont, P., 2019. Osteoporos Int 30, 2283–2288.
- Clinical Inference of Serum and Bone Sclerostin Levels in Patients with End-Stage Kidney Disease. De Maré, A., Verhulst, A., Cavalier, E., Delanaye, P., Behets, G.J., Meijers, B., Kuypers, D., D’Haese, P.C., Evenepoel, P., 2019. Journal of Clinical Medicine 8, 2027.
- Poor Vitamin K Status Is Associated With Low Bone Mineral Density and Increased Fracture Risk in End-Stage Renal Disease. Evenepoel, P., Claes, K., Meijers, B., Laurent, M., Bammens, B., Naesens, M., Sprangers, B., Pottel, H., Cavalier, E., Kuypers, D., 2019a. Journal of Bone and Mineral Research 34, 262–269.
- Bone mineral density, bone turnover markers, and incident fractures in de novo kidney transplant recipients. Evenepoel, P., Claes, K., Meijers, B., Laurent, M.R., Bammens, B., Naesens, M., Sprangers, B., Pottel, H., Cavalier, E., Kuypers, D., 2019b. Kidney Int. 95, 1461–1470. PMID: 30922664
- Effects of 1-year anti-TNF-α therapies on bone mineral density and bone biomarkers in rheumatoid arthritis and ankylosing spondylitis. Gulyás, K., Horváth, Á., Végh, E., Pusztai, A., Szentpétery, Á., Pethö, Z., Váncsa, A., Bodnár, N., Csomor, P., Hamar, A., Bodoki, L., Bhattoa, H.P., Juhász, B., Nagy, Z., Hodosi, K., Karosi, T., FitzGerald, O., Szücs, G., Szekanecz, Z., Szamosi, S., Szántó, S., 2019. Clin Rheumatol.
- Effectiveness of anti-osteoporotic treatment after successful parathyroidectomy for primary hyperparathyroidism: a randomized, double-blind, placebo-controlled trial. Niederle, M.B., Foeger-Samwald, U., Riss, P., Selberherr, A., Scheuba, C., Pietschmann, P., Niederle, B., Kerschan-Schindl, K., 2019. Langenbecks Arch Surg 404, 681–691.
- Is the personalized approach the key to improve clinical diagnosis of peri-implant conditions? the role of bone markers. Rakic, M., Monje, A., Radovanovic, S., Petkovic‐Curcin, A., Vojvodic, D., Tatic, Z., 2019. Journal of Periodontology.
- Serum levels of Wnt-signalling parameters poorly reflect bone mass and metabolism in healthy boys and men. Thiberiu, B., Charlotte, V., Hans-Georg, Z., Stefan, G., Sara, V., Jean-Marc, K., Bruno, L., 2019. Presented at the Belgian Endocrine Society 2019, BioScientifica.
- Bone Metabolism Markers in Thalassemia Major-Induced Osteoporosis: Results from a Cross-Sectional Observational Study [WWW Document]. Tsartsalis, A.N., Lambrou, G.I., Tsartsalis, D.N., Papassotiriou, I., Vlachou, E., Terpos, E., Chrousos, G.P., Kanaka-Gantenbein, C., Kattamis, A., 2019.
- Effects of Biliopancreatic Diversion on Bone Turnover Markers and Association with Hormonal Factors in Patients with Severe Obesity. Turcotte, A.-F., Grenier-Larouche, T., Ung, R.-V., Simonyan, D., Carreau, A.-M., Carpentier, A.C., Mac-Way, F., Michou, L., Tchernof, A., Biertho, L., Lebel, S., Marceau, S., Gagnon, C., 2019. OBES SURG 29, 990–998.
- Quantifying RANKL and OPG levels in healthy children: A large cross-sectional analysis.
Ali, S.A., Kang, H., Olney, R., Ramos-Platt, L., Ryabets-Lienhard, A., Georgia, S., Pitukcheewanont, P., 2019. Bone 127, 215–219.
PMID:31212033 - A distinct bone phenotype in ADPKD patients with end-stage renal disease.
Evenepoel, P., Claes, K., Cavalier, E., Meijers, B., Stenvinkel, P., Behets, G., Jankowska, M., D’Haese, P., Bammens, B., 2019a. Kidney Int. 95, 412–419.
PMID:30665572 - Bone mineral density, bone turnover markers, and incident fractures in de novo kidney transplant recipients.
Evenepoel, P., Claes, K., Meijers, B., Laurent, M.R., Bammens, B., Naesens, M., Sprangers, B., Pottel, H., Cavalier, E., Kuypers, D., 2019b. Kidney Int. 95, 1461-1470.
PMID:30922664 - Absence of an osteopetrosis phenotype in IKBKG (NEMO) mutation-positive women: A case-control study.
Frost, M., Tencerova, M., Andreasen, C.M., Andersen, T.L., Ejersted, C., Svaneby, D., Qui, W., Kassem, M., Zarei, A., McAlister, W.H., Veis, D.J., Whyte, M.P., Frederiksen, A.L., 2019. Bone 121, 243-354.
PMID:30659980 - Biomarkers of bone healing induced by a regenerative approach based on expanded bone marrow–derived mesenchymal stromal cells.
Granchi, D., Ciapetti, G., Gómez-barrena, E., Rojewski, M., Rosset, P., Layrolle, P., Spazzoli, B., Donati, D.M., Baldini, N., 2019. Cytotherapy.
- Dietary Protein and Changes in Biomarkers of Inflammation and Oxidative Stress in the Framingham Heart Study Offspring Cohort.
Hruby, A., Jacques, P.F., 2019. Curr Dev Nutr 3.
PMID:31037277; PMCID: PMC6483052 - Possible link between FSH and RANKL release from adipocytes in men with impaired gonadal function including Klinefelter syndrome.
Juel Mortensen, L., Lorenzen, M., Jørgensen, N., Andersson, A.-M., Nielsen, J.E., Petersen, L.I., Lanske, B., Juul, A., Hansen, J.B., Blomberg Jensen, M., 2019. Bone 123, 103–114.
- Imbalance of osteoprotegerin/receptor activator of nuclear factor-κB ligand and oxidative stress in patients with obstructive sleep apnea-hypopnea syndrome.
Ma, X.-R., Wang, Y., Sun, Y.-C., 2019. Chinese Medical Journal 132, 25.
- A pilot study showing acute inhibitory effect of GLP-1 on the bone resorption marker CTX in humans.
Nissen, A., Marstrand, S., Skov‐Jeppesen, K., Bremholm, L., Hornum, M., Andersen, U.B., Holst, J.J., Rosenkilde, M.M., Hartmann, B., 2019. JBMR Plus.
- Osteoprotegerin and RANKL serum concentrations in neonates of mothers with early-onset pre-eclampsia: comparison with neonates of normotensive mothers.
Oikonomou, N., Papadopoulou, C., Fouzas, S., Kritikou, D., Chrysis, D., Sinopidis, X., Dimitriou, G., Karatza, A.A., 2019. Early Human Development 135, 1–5.
- Gingival Crevicular Fluid Levels of RANKL and OPG After Placement of Collagen Membrane With Sımvastatin in the Treatment of Intrabony Defects in Chronic Periodontitis.
Suthanthiran, T., Annamalai, S., Chellapandi, S., Puthenveetil, S., Dhasthaheer, S., Narasimhan, S., 2019. J Pharm Bioallied Sci 11, S301–S304.
PMID:31198358; PMCID: PMC6555350 - Effect of induction therapy with lеnalidomide, doxorubicın and dеxamethasone on bone remodeling and angiogenesis in newly diagnosed multiple myeloma.
Terpos, E., Katodritou, E., Symeonidis, A., Zagouri, F., Gerofotis, A., Christopoulou, G., Gavriatopoulou, M., Christoulas, D., Ntanasis-Stathopoulos, I., Kourakli, A., Konstantinidou, P., Kastritis, E., Dimopoulos, M.A., 2019. Int. J. Cancer 145, 559-568.
PMID:30650184 - The role of sclerostin/dickkopf-1 and receptor activator of nuclear factor kB ligand/osteoprotegerin signalling pathways in the development of osteoporosis in patients with haemophilia A and B: A cross-sectional study.
Anagnostis, P., Vakalopoulou, S., Christoulas, D., Paschou, S.A., Papatheodorou, A., Garipidou, V., Kokkoris, P., Terpos, E., 2018. Haemophilia 24, 316–322.
- LRP5 gene polymorphisms and radiographic joint damage in rheumatoid arthritis patients.
Bernardes, M., Durães, C., Oliveira, A., Martins, M.J., Lucas, R., Costa, L., Pereira, J.G., Ramos, I., Machado, J.C., Simões-Ventura, F., 2018. Osteoporosis International.
- GH prevents adipogenic differentiation of mesenchymal stromal stem cells derived from human trabecular bone via canonical Wnt signaling.
Bolamperti, S., Signo, M., Spinello, A., Moro, G., Fraschini, G., Guidobono, F., Rubinacci, A., Villa, I., 2018. Bone 112, 136–144.
PMID:29694926 - Study of bone metabolism and angiogenesis in patients undergoing high-dose chemotherapy/autologous hematopoietic stem cell transplantation.
Boutsikas, G., Terpos, E., Papatheodorou, A., Tsirkinidis, P., Tsirigotis, P., Meletiou, A., Lalou, E., Telonis, V., Zannou, A., Kanellopoulos, A., Galani, Z., Stefanou, A., Tsaftaridis, P., Viniou, N.-A., Panayiotidis, P., Kyrtsonis, M.-C., Meletis, J., Vassilakopoulos, T.P., Angelopoulou, M.K., 2018. European Journal of Haematology 100, 131–139.
- Monocytes from male patients with ankylosing spondylitis display decreased osteoclastogenesis and decreased RANKL/OPG ratio.
Caparbo, V.F., Saad, C.G.S., Moraes, J.C., de Brum-Fernandes, A.J., Pereira, R.M.R., 2018. Osteoporos Int.
PMID:30006885 - Circulating Soluble Receptor Activator of Nuclear Factor Kappa B Ligand and C-C Motif Ligand 3 Correlate With Survival in Patients With Waldenström Macroglobulinemia.
Eleutherakis-Papaiakovou, E., Kastritis, E., Gavriatopoulou, M., Christoulas, D., Roussou, M., Ntanasis-Stathopoulos, I., Kanellias, N., Papatheodorou, A., Dimopoulos, M.A., Terpos, E., 2018. Clin Lymphoma Myeloma Leuk 18, 431–437.
PMID:29685422 - Poor Vitamin K Status Is Associated With Low Bone Mineral Density and Increased Fracture Risk in End-Stage Renal Disease.
Evenepoel, P., Claes, K., Meijers, B., Laurent, M., Bammens, B., Naesens, M., Sprangers, B., Pottel, H., Cavalier, E., Kuypers, D., 2018. J. Bone Miner. Res.
PMID:30427544 - RANKL/RANK/OPG Axis Is Deregulated in the Cerebrospinal Fluid of Multiple Sclerosis Patients at Clinical Onset.
Glasnović, A., Stojić, M., Dežmalj, L., Tudorić-Đeno, I., Romić, D., Jeleč, V., Vrca, A., Vuletić, V., Grčević, D., 2018. Neuroimmunomodulation 25, 23–33.
PMID:29920500 - Clinical predictive biomarkers for normoalbuminuric diabetic kidney disease.
Gohda, T., Nishizaki, Y., Murakoshi, M., Nojiri, S., Yanagisawa, N., Shibata, T., Yamashita, M., Tanaka, K., Yamashita, Y., Suzuki, Y., Kamei, N., 2018. Diabetes Res. Clin. Pract. 141, 62–68.
PMID:29729375 - Cardiovascular autonomic neuropathy and bone metabolism in Type 1 diabetes.
Hansen, C.S., Theilade, S., Lajer, M., Hansen, T.W., Rossing, P., 2018. Diabet. Med.
PMID:29999549 - Increased frequency of temporal acoustic window failure in rheumatoid arthritis: a manifestation of altered bone metabolism?
Kardos, Z., Oláh, C., Sepsi, M., Sas, A., Kostyál, L., Bóta, T., Bhattoa, H.P., Hodosi, K., Kerekes, G., Tamási, L., Bereczki, D., Szekanecz, Z., 2018. Clin. Rheumatol. 37, 1183–1188.
PMID:29383454 - Comparison of bone turnover markers in peripheral blood and bone marrow aspirate.
Ornstrup, M.J., Kjær, T.N., Harsløf, T., Jørgensen, N.R., Pedersen, S.B., Langdahl, B.L., 2018. Bone 116, 315–320.
PMID:30176391 - Associations of osteoprotegerin with coronary artery calcification among women with systemic lupus erythematosus and healthy controls.
Poornima, I.G., Shields, K., Kuller, L.H., Manzi, S.M., Ramsey-Goldman, R., Richardson, C., Rhew, E., Dunlop, D.D., Song, J., Edmundowicz, D., Kondos, G.T., Carr, J.J., Langman, C.B., Price, H., Chung, A.H., Santelices, L.B., Mackey, R.H., 2018. Lupus 961203317751060. PMCID: PMC6026582
PMID:29310535 - Prognostic value of RANKL/OPG serum levels and disseminated tumor cells in non-metastatic breast cancer.
Rachner, T.D., Kasimir-Bauer, S., Göbel, A., Erdmann, K., Hoffmann, O., Browne, A.J., Wimberger, P., Rauner, M., Hofbauer, L.C., Kimmig, R., Bittner, A.-K., 2018. Clin. Cancer Res.
PMID:30425091 - Rheumatoid Arthritis Magnetic Resonance Imaging Score Predicts Therapy Response: Results of the German ArthroMark Cohort.
Sewerin, P., Le, L., Vordenbäumen, S., Schleich, C., Sengewein, R., Brinks, R., Pongratz, G., Bleck, E., Lesch, J., Mansmann, U., Schneider, M., Ostendorf, B., 2018. The Journal of Rheumatology 45, 753–759.
- Consolidation therapy with the combination of bortеzomib and lеnalidomide (VR) without dеxamethasone in multiple myeloma patients after transplant: Effects on survival and bone outcomes in the absence of bisphosphonates.
Terpos, E., Kastritis, E., Ntanasis-Stathopoulos, I., Christoulas, D., Papatheodorou, A., Eleutherakis-Papaiakovou, E., Kanellias, N., Fotiou, D., Ziogas, D.C., Migkou, M., Roussou, M., Trougkakos, I.P., Gavriatopoulou, M., Dimopoulos, M.A., 2018. Am. J. Hematol.
PMID:30592079 - Effects of Biliopancreatic Diversion on Bone Turnover Markers and Association with Hormonal Factors in Patients with Severe Obesity.
Turcotte, A.-F., Grenier-Larouche, T., Ung, R.-V., Simonyan, D., Carreau, A.-M., Carpentier, A.C., Mac-Way, F., Michou, L., Tchernof, A., Biertho, L., Lebel, S., Marceau, S., Gagnon, C., 2018. Obes Surg.
PMID:30478790 - Cardiovascular disease and bone loss—new research in identifying common disease pathophysiologies and predictors.
West, S.L., O’Donnell, E., 2018. AME Medical Journal 3
- Gene variants of osteoprotegerin, estrogen-, calcitonin- and vitamin D-receptor genes and serum markers of bone metabolism in patients with Gaucher disease type 1.
Zimmermann, A., Popp, R.A., Rossmann, H., Bucerzan, S., Nascu, I., Leucuta, D., Weber, M.M., Grigorescu-Sido, P., 2018. Therapeutics and Clinical Risk Management Volume 14, 2069–2080.
- Serum serotonin levels and bone in rheumatoid arthritis patients.
Bernardes, M., Vieira, T., Lucas, R., Pereira, J., Costa, L., Simões-Ventura, F., Martins, M.J., 2017a. Rheumatology International 37, 1891–1898.
- Myocardial Perfusion in Rheumatoid Arthritis Patients: Associations with Traditional Risk Factors and Novel Biomarkers.
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- Calcification Propensity of Serum is Independent of Excretory Renal Function.
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PMID:27592446 - Daily Intake of Milk Enriched with n-3 Fatty Acids, Oleic Acid, and Calcium Improves Metabolic and Bone Biomarkers in Postmenopausal Women.
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PMID:28002811 - Subclinical arteriosclerosis and osteoprotegerin levels in a population with systemic lupus erythematous in the south of Europe.
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PMID:27311721 - Differences in biochemical bone markers by diabetes type and the impact of glucose.
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PMID:26884284 - Role of Osteoprotegerin and Receptor Activator of Nuclear Factor-κB Ligand in Bone Loss Related to Advanced Chronic Obstructive Pulmonary Disease.
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PMID:27411457 - Chronic skin inflammation leads to bone loss by IL-17-mediated inhibition of Wnt signaling in osteoblasts.
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PMID:25609157 - The effect of tocılizumab on bone mineral density, serum levels of Dickkopf-1 and bone remodeling markers in patients with rheumatoid arthritis.
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PMID:26163998 - Osteoprotegerin is a significant prognostic factor for overall survival in patients with primary systemic amyloidosis independent of the Mayo staging.
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PMID:26311162 - Effects of Antitumor Necrosis Factor Therapy on Osteoprotegerin, Neopterin, and sRANKL Concentrations in Patients with Rheumatoid Arthritis.
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PMID:24566391 - Role of osteoprotegerin in vascular disorders of the end-stage renal disease patients.
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PMID:25585925 - Switching from tеnofovır to abacavır in HIV-1-infected patients with low bone mineral density: changes in bone turnover markers and circulating sclerostin levels.
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PMID:25769303 - Serum osteoprotegerin is associated with pulse pressure in kidney transplant recipients.
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PMID:26459001 - Association of osteoprotegerin and bone loss after adjuvant chemotherapy in early-stage breast cancer.
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PMID:25217276 - Osteoprotegerin concentrations in patients with suspected reversible myocardial ischemia: observations from the Akershus Cardiac Examination (ACE) 1 Study.
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PMID:25748834 - Serum fetuin-A levels and abdominal aortic calcification in healthy men — The STRAMBO study.
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PMID:26094529 - Serum sclerostin in high-activity adult patients with juvenile idiopathic arthritis.
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PMID:24276456 - The combination of lеnalidomide and dеxamethasone reduces bone resorption in responding patients with relapsed/refractory multiple myeloma but has no effect on bone formation: Final results on 205 patients of the Greek myeloma study group.
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PMID:24001743 - High dickkopf-1 levels in sera and leukocytes from children with 21-hydroxylase deficiency on chronic glucocorticoid treatment.
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PMID:23275387 - Activation of the receptor activator of the nuclear factor-κB ligand pathway during coronary bypass surgery: comparison between on- and off-pump coronary artery bypass surgery procedures.
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PMID:23671202 - OPG and sRANKL serum levels and incident hip fracture in postmenopausal Caucasian women in the Women’s Health Initiative Observational Study.
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PMID:23735608 - An independent positive relationship between the serum total osteocalcin level and fat-free mass in healthy premenopausal women.
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PMID:23553865 - Synovial membrane immunohistology in early-untreated rheumatoid arthritis reveals high expression of catabolic bone markers that is modulated by mеthotrexate.
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PMID:23322328 - Bone metabolism compensates for the delayed growth in small for gestational age neonates.
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PMID:23538775 - Sclerostin and its association with physical activity, age, gender, body composition, and bone mineral content in healthy adults.
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PMID:21994959 - Physical training increases osteoprotegerin in postmenopausal women.
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PMID:21823052 - Diets higher in dairy foods and dietary protein support bone health during diet- and exercise-induced weight loss in overweight and obese premenopausal women.
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PMID:22791764 - Serum Osteoprotegerin, RANKL, and Dkk-1 Levels in Adults with Langerhans Cell Histiocytosis.
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PMID:22753650 - Plasma pyridoxal-5-phosphate is inversely associated with systemic markers of inflammation in a population of U.S. adults.
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PMID:22623384 - Serum Level of the Phosphaturic Factor FGF23 Is Associated with Abdominal Aortic Calcification in Men: The STRAMBO Study.
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We have been using the Biomedica ELISA kits for measurements of OPG and soluble RANKL in several contexts and are very pleased with how well they perform both in terms of specificity and reproducibility. For the RANKL kit the measurements are validated by no measurable free soluble RANKL when analyzing culture media where a RANKL inhibitor has been added. Furthermore, we have measured the proteins in a range of human body fluids as well as in tissue and cell culture media and the kits work both when larger and smaller concentrations are measured and when samples are diluted.
