The human DKK1 ELISA kit is a 3.5 hour, 96-well sandwich ELISA for the quantitative determination of DKK-1 in human serum. The assay employs human serum-based standards to ensure the measurement of biologically reliable data.
DKK1 ELISA Assay Principle
The DKK-1 ELISA kit is a sandwich enzyme immunoassay for the quantitative determination of DKK1 in human serum samples.
The figure below explains the principle of the DKK1 ELISA assay:
In a first step, assay buffer, standard/control/sample and detection antibody (biotinylated polyclonal rabbit anti-human DKK-1) are pipetted into the wells of the microtiter strips, which are pre-coated with monoclonal mouse anti-human DKK-1 antibody. DKK-1 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 next 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 DKK-1 present in the sample. This color change is detectable with a standard microtiter plate reader. A dose response curve of the absorbance (optical density, OD at 450 nm) versus standard concentration is generated using the values obtained from the standard. The concentration of DKK-1 in the sample is determined directly from the dose response curve.
DKK1 ELISA Typical Standard Curve
The figure below shows a typical standard curve for the Dickkopf-1 ELISA. The immunoassay is calibrated against recombinant human DKK1.
DKK1 ELISA Kit Components
Contents
Description
Quantity
PLATE
Monoclonal mouse anti-human DKK-1 antibody pre-coated microtiter strips in strip holder packed in an aluminum bag with desiccant
12 x 8 tests
WASHBUF
Wash buffer concentrate 20x, natural cap
1 x 50 ml
STD
Standards 1-6, (0; 10; 20; 40; 80; 160 pmol/l), recombinant human DKK-1 in human serum, white caps, lyophilized
6 vials
CTRL
Control, yellow cap, lyophilized, exact concentration after reconstitution see label
1 vial
ASYBUF
Assay buffer, red cap, ready to use
1 x 10 ml
AB
Polyclonal rabbit anti-human DKK-1 – biotin labeled, green cap, ready to use
1 x 7 ml
CONJ
Conjugate (streptavidin-HRP), amber cap, ready to use
1 x 13 ml
SUB
Substrate (TMB solution), amber bottle, blue cap, ready to use
1 x 13 ml
STOP
Stop solution, white cap, ready to use
1 x 7 ml
Storage instructions: All reagents of the DKK-1 ELISA kit are stable at 4°C (2-8°C) until the expiry date stated on the label of each reagent.
Serum is suitable for use in this DKK-1 ELISA. 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
Collect venous blood samples in standardized serum separator tubes (SST). Allow samples to clot for 30 minutes at room temperature. Perform separation by centrifugation according to the tube manufacturer’s instructions for use. Assay the acquired samples immediately or aliquot and store at -25°C or lower. Lipemic or hemolyzed samples may give erroneous results. Samples can undergo up to three 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).
Standards & Controls for Serum Measurements
1.
Pipette 200 µl of distilled or deionized water into each standard (STD) and control (CTRL) vial. The exact concentration is printed on the label of each vial.
2.
Leave at room temperature (18-24°C) for 15 min. Swirl gently.
Reconstituted STDs and CTRLs are stable at -25°C or lower until expiry date stated on the label. Avoid more than one freeze-thaw cycle.
Sample Preparation
Bring samples to room temperature and mix gently to ensure the samples are homogenous. We recommend duplicate measurements for all samples.
Samples for which the OD value exceeds he highest point of the standard range can be diluted with STD1 (standard 1).
DKK1 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.
4.
Pipette 50 µl ASYBUF (assay buffer, red cap) into each well.
5.
Add 20 µl STD/CTRL/SAMPLE in duplicates into the respective wells, swirl gently.
6.
Add 50 µl AB (biotinylated anti-DKK-1 antibody, green cap) into each well, swirl gently.
7.
Cover the plate tightly and incubate for 2 hours at room temperature (18-24°C).
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 100 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. After the final wash, remove remaining WASHBUF by strongly tapping the plate against a paper towel.
12.
Add 100 µl SUB (substrate, blue cap) into each well.
13.
Incubate for 30 min at room temperature (18-24°C) in the dark.
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 = 0.039 pmol/l (MW: 25.8 kDa)). Respective dilution factors have to be considered when calculating the final concentration of the sample.
The quality control protocol supplied with the kit shows the results of the final release QC for each kit. ODs obtained by customers may differ due to various influences including a normal decrease of signal intensity throughout shelf life. However, this does not affect validity of results as long as an OD of 1.5 or higher is obtained for STD 6 and the value of the CTRL is within the target range (see label).
Background & Therapeutic Areas
DKK-1 Protein
DKK-1 is a 25.8 kDa secreted protein functioning as antagonist of the canonical Wnt signaling pathway. It is a member of the dickkopf-related protein family characterized by two cysteine-rich domains separated by a linker region. Binding of DKK-1 to the LRP5/6 co-receptor inhibits the interaction with Wnt and by forming a ternary complex with transmembrane Kremen-1 or -2, promotes the internalization of LRP5/6.
Molecular weight
25.8 kDa
Cellular localization
Extracellular
Post-translational modifications
Glycosylation
Sequence similarities
Member of the dickkopf-related protein family
Alternative names
Dickkopf-1, DKK1, dickkopf WNT signaling pathway inhibitor, dickkopf (Xenopus laevis) homolog 1, dickkopf homolog 1 (Xenopus laevis), dickkopf related protein-1, dickkopf-related protein 1, SKdickkopf-1 like
The Wnt signaling pathway is involved in embryonic development, tissue differentiation and homeostasis as well as carcinogenesis. As soluble inhibitor of Wnt signaling, DKK-1 influences cell fate, proliferation, migration, polarity and gene expression.
Wnt signaling is particularly important in bone homeostasis as it induces the differentiation of osteoblasts while inhibiting osteoclastogenesis. DKK-1 is expressed in mature osteoblast and osteocytes and regulates the differentiation of osteoblasts. Thus, DKK-1 is centrally involved in the regulation of bone remodeling and its dysregulation is associated with bone pathologies.
Moreover, DKK-1 has emerged as a biomarker of cancer progression and prognosis as well as potential therapeutic target in various types of malignancies. In a range of different types of cancers, DKK-1 is further associated with formation of bone metastasis and osteolytic bone lesions.
Bone Disease
Osteoporosis
Rheumatoid arthritis
Ankylosing spondylitis
Axial spondyloarthritis
Osteoarthritis
Cancer-induced bone disease
Psoriatic arthritis
Primary hyperparathyroidism
Osteonecrosis
Osteopathy in type 1 diabetes
Osteogenesis imperfecta
Cancer
Breast cancer
Prostate cancer
Multiple myeloma
Cervical cancer
Hepatocellular carcinoma
Non-small cell lung cancer
Papillary thyroid cancer
Lung cancer
Bone metastasis
Cutaneous malignant melanoma
Monoclonal gammopathy of undetermined significance (MGUS)
All 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 bioanalytical method validation
Bioanalytical Method Validation, Guidance for Industry, FDA, May 2018
Calibration
The DKK-1 immunoassay is calibrated against recombinant DKK-1 protein (Uniprot ID O94907 ).
DKK1 ELISA Detection Limit & Sensitivity
To determine the sensitivity of the DKK-1 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 DKK-1, with a confidence level of 99%. It is defined as the mean back calculated concentration of standard 1 (0 pmol/l of DKK-1, 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 DKK-1, is diluted, measured and its concentration back calculated. The lowest dilution, which meets both criteria, is reported as the LLOQ.
The following values were determined for the DKK-1 ELISA:
LOD
1.7 pmol/l
LLOQ
1.25 pmol/l
DKK1 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 precision (intra-assay precision) was assessed by measuring two samples of known concentration five times within one DKK-1 ELISA lot by one operator.
ID
n
Mean DKK-1 [pmol/l]
SD [pmol/l]
CV [%]
Sample 1
5
19.9
0.5
3
Sample 2
5
80.1
2.7
3
In-Between-Run Precision
In-between-run precision (inter-assay precision) was assessed by measuring two samples nine times within two DKK-1 ELISA kit lots by two different operators.
ID
n
Mean DKK-1 [pmol/l]
SD [pmol/l]
CV [%]
Sample 1
9
19.7
0.6
3
Sample 2
9
80.4
2.1
3
DKK1 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 DKK-1 ELISA was measured by adding recombinant DKK-1 to human samples containing a known concentration endogenous DKK-1. 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 DKK-1 ELISA in serum matrix:
% Recovery
Sample matrix
n
+40 pmol/l DKK-1
+80 pmol/l DKK-1
Mean
Range
Mean
Range
Serum
7
93%
86-103%
96%
87-106%
+ Individual measurements
Recovery of spiked samples was tested by adding two concentrations of human recombinant DKK-1 (40 pmol/l + 80 pmol/l) to human serum.
Data showing spike/recovery of human serum samples:
DKK-1 [pmol/l]
% Recovery
Sample ID
Reference
+40 pmol/l
+80 pmol/l
+40 pmol/l
+80 pmol/l
#s1
6
43
88
96%
103%
#s2
10
38
79
86%
87%
#s3
12
43
82
92%
94%
#s4
29
50
90
93%
92%
#s5
41
57
98
93%
92%
#s6
50
61
104
92%
95%
#s7
61
70
122
103%
106%
Mean [%]
93
96
DKK1 ELISA Dilution Linearity & Parallelism
Tests of dilution linearity and parallelism ensure that both endogenous and recombinant samples containing DKK-1 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 acceptable if the results are within ±20% of the expected concentration.
Dilution linearity was assessed by serially diluting samples spiked with recombinant DKK-1 with STD1 (standard 1).
The table below shows the mean recovery and range of serially diluted recombinant DKK-1:
% Recovery of recombinant DKK-1 in diluted samples
Sample
matrix
n
1+1
1+3
1+7
Mean
Range
Mean
Range
Mean
Range
Serum
3
106
91-116
102
93-109
102
100-105
+ Individual measurements
Data showing dilution linearity of recombinant DKK-1 in human serum samples:
DKK-1 [pmol/l]
% Recovery
Sample matrix
ID
Reference
1+1
1+3
1+7
1+1
1+3
1+7
Serum
s1
80
36.2
16.8
8.6
91
93
102
Serum
s2
94.2
54.5
29.8
15.0
116
109
100
Serum
s3
135
75
37.1
19.5
111
99
105
Mean
106
102
102
Min
91
93
100
Max
116
109
105
Parallelism was assessed by serially diluting samples containing endogenous DKK-1 with with STD1 (standard 1).
The table below show the mean recovery and range of serially diluted endogenous DKK-1:
% Recovery of endogenous DKK-1 in diluted samples
Sample
matrix
n
1+1
1+3
1+7
Mean
Range
Mean
Range
Mean
Range
Serum
4
109
108-112
104
99-107
100
90-114
+ Individual measurements
Data showing dilution linearity of endogenous DKK-1 in human serum samples:
DKK-1 [pmol/l]
% Recovery
Sample matrix
ID
Reference
1+1
1+3
1+7
1+1
1+3
1+7
Serum
s1
51.8
28.5
14.8
8.4
110
103
114
Serum
s2
30.2
16.3
8.7
3.9
108
107
90
Serum
s3
47.6
26.5
14.0
6.6
112
106
95
Serum
s4
42.8
23.1
11.4
5.7
108
99
100
Mean
109
104
100
Min
108
99
90
Max
110
107
114
DKK1 ELISA Specificity
The specificity of an ELISA is defined as its ability to exclusively recognize the analyte of interest.
The specificity of the ELISA was established through competition experiments, which measure the ability of the antibodies to exclusively bind DKK-1.
Competition of Signal
Competition experiments were carried out by pre-incubating human samples with an excess of coating antibody. The concentration measured in this mixture was then compared to a reference value, which was obtained from the same sample but without the pre-incubation step. The mean competition was 98%, demonstrating that this assay is specific for DKK-1.
DKK-1 [pmol/l]
% Competition
Sample matrix
ID
Reference
Reference + capture AB
Serum
s1
40
0
100
Serum
s2
42
5
89
Serum
s3
85
0
100
Serum
s4
255
22
92
Serum
s5
16
0
100
Serum
s6
44
0
100
Serum
s7
142
3
98
Serum
s8
86
2
97
Serum
s9
106
3
97
Serum
s10
17
0
100
Serum
s11
46
0
100
Serum
s12
26
0
100
Serum
s13
56
1
98
Serum
s14
51
3
95
Mean
98
Cross-Reactivity
The cross-reactivity of the DKK-1 ELISA was tested with recombinant DKK-2, which is 42% identical to DKK-1. The DKK-1 ELISA does not cross-react with DKK-2. No cross-reactivity or interference with recombinant human DKK-4, Kremen-1, Kremen-2 or LRP-6 is observed.
Sample Stability
The stability of endogenous DKK-1 was tested by comparing measurements in samples that had undergone six freeze-thaw cycles.
For freeze-thaw experiments, samples were collected according to the supplier’s instruction using blood collection devices and stored at -80°C. The mean recovery of sample concentration after an additional three freeze-thaw (F/T) cycles is 93%.
DKK-1 [pmol/l]
% Recovery
Sample matrix
ID
Reference
3x F/T cycles
6x F/T cycles
3x F/T cycles
6x F/T cycles
Serum
s1
43
40
40
93
92
Serum
s2
70
63
62
90
89
Serum
s3
46
46
43
94
93
Serum
s4
21
21
19
96
88
Serum
s5
30
30
31
100
103
Serum
s6
41
39
38
95
91
Serum
s7
29
26
27
89
92
Serum
s8
46
43
40
92
87
Serum
s9
152
139
131
91
86
Serum
s10
106
99
93
94
88
Mean
93
91
All samples should undergo a maximum of three freeze-thaw cycles.
Sample Values
DKK-1 Values in Apparently Healthy Individuals
To provide expected values for circulating DKK-1, a panel of samples from apparently healthy donors was tested.
A summary of the results is shown below:
DKK-1 [pmol/l]
Sample Matrix
n
Mean
Median
Minimum
Maximum
Serum
51
35
34
5
70
We recommended establishing the normal range for each laboratory.
DKK-1 Values in an Osteoporosis Panel
In addition to samples from apparently healthy donors, a panel of samples from osteoporosis patients was tested.
A summary of the results is shown below:
DKK-1 [pmol/l]
Sample Matrix
n
Mean
Median
Minimum
Maximum
Serum
48
69
60
25
150
A comparison of apparently healthy individuals and patients with osteoporosis shows that DKK-1 is increased in osteoporosis patients:
Automation
The assay was programmed on the ETI-Max3000. Standards and samples were tested and show a CV of <7% in the low to high calibration range. The coefficient of determination is >0.998 for a logit-log transformation.
An assay protocol for the ETI-max3000 is available on request.
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.
Dissecting the mechanisms of bone loss in Gorham-Stout disease. Rossi M., Buonuomo P.S., Battafarano G., Conforti A., Mariani E., Algeri M., Pelle S., D'Agostini M., Macchiaiolo M., De Vito R., Gonfiantini M.V., Jenkner A., Rana I., Bartuli A., Del Fattore A., 2020. Bone 130:115068. PMID: 31525474.
Dissecting the mechanisms of bone loss in Gorham-Stout disease. Rossi, M., Buonuomo, P.S., Battafarano, G., Conforti, A., Mariani, E., Algeri, M., Pelle, S., D’Agostini, M., Macchiaiolo, M., De Vito, R., Gonfiantini, M.V., Jenkner, A., Rana, I., Bartuli, A., Del Fattore, A., 2020. Bone 130, 115068.
Sex steroids as determinants of Wnt-Signalling markers in men. Banica, T., Verroken, C., Zmierczak, H.-G., Goemaere, S., Defreyne, J., T, G., Kaufman, J.-M., Lapauw, B., 2019. Presented at the 21st European Congress of Endocrinology, BioScientifica.
Rheumatoid arthritis in remission. Kerschan-Schindl, K., Ebenbichler, G., Föeger-Samwald, U., Leiss, H., Gesslbauer, C., Herceg, M., Stummvoll, G., Marculescu, R., Crevenna, R., Pietschmann, P., 2019a. Wien Klin Wochenschr 131, 1–7.
Fassio, A., Adami, G., Benini, C., Vantaggiato, E., Saag, K.G., Giollo, A., Lippolis, I., Viapiana, O., Idolazzi, L., Orsolini, G., Rossini, M., Gatti, D., 2019. Bone 123, 191–195. PMID:30910600
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. PMID:30650184
Bojanić, K., Bilić Ćurčić, I., Kuna, L., Kizivat, T., Smolic, R., Raguž Lučić, N., Kralik, K., Šerić, V., Ivanac, G., Tucak-Zorić, S., Včev, A., Smolić, M., 2018. J Clin Med 7. PMID:30227689; PMCID: PMC6162798
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.
Idolazzi, L., El Ghoch, M., Dalle Grave, R., Bazzani, P.V., Calugi, S., Fassio, S., Caimmi, C., Viapiana, O., Bertoldo, F., Braga, V., Rossini, M., Gatti, D., 2018. Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity 23, 255–261.
Mabille, C., Ruyssen-Witrand, A., Degboe, Y., Gennero, I., Loiseau, H.A., Roussel, M., Hebraud, B., Nigon, D., Attal, M., Laroche, M., 2018. Bone 113, 114–117.
Mantovani, A., Sani, E., Fassio, A., Colecchia, A., Viapiana, O., Gatti, D., Idolazzi, L., Rossini, M., Salvagno, G., Lippi, G., Zoppini, G., Byrne, C.D., Bonora, E., Targher, G., 2018. Diabetes Metab. PMID:30315891
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
Tsirkinidis, P., Terpos, E., Boutsikas, G., Papatheodorou, A., Anargyrou, K., Lalou, E., Dimitrakopoulou, A., Kalpadakis, C., Konstantopoulos, K., Siakantaris, M., Panayiotidis, P., Pangalis, G., Kyrtsonis, M.-C., Vassilakopoulos, T., Angelopoulou, M.K., 2018. Journal of Bone and Mineral Metabolism 36, 399–409.
Bernardes, M., Vieira, T.S., Martins, M.J., Lucas, R., Costa, L., Pereira, J.G., Ventura, F., Martins, E., 2017. BioMed Research International 2017, 1–9.
Catalano, A., Pintaudi, B., Morabito, N., Giunta, L., Loddo, S., Corrado, F., D’Anna, R., Lasco, A., Di Benedetto, A., 2017. Diabetes & Metabolism 43, 375–377.
Göbel, A., Kuhlmann, J.D., Link, T., Wimberger, P., Browne, A.J., Rauner, M., Hofbauer, L.C., Rachner, T.D., 2017. Breast Cancer Research and Treatment 164, 737–743.
Muschitz, G.K., Schwabegger, E., Fochtmann, A., Baierl, A., Kocijan, R., Haschka, J., Gruther, W., Schanda, J.E., Resch, H., Rath, T., Pietschmann, P., Muschitz, C., 2017. Journal of Bone and Mineral Research 32, 2381–2393.
Perpétuo, I.P., Caetano-Lopes, J., Vieira-Sousa, E., Campanilho-Marques, R., Ponte, C., Canhão, H., Ainola, M., Fonseca, J.E., 2017. Frontiers in Medicine 4.
Yu, B., Kiechl, S., Qi, D., Wang, X., Song, Y., Weger, S., Mayr, A., Le Bras, A., Karamariti, E., Zhang, Z., Barco Barrantes, I. del, Niehrs, C., Schett, G., Hu, Y., Wang, W., Willeit, J., Qu, A., Xu, Q., 2017. Circulation 136, 1022–1036.
Morabito, N., Catalano, A., Gaudio, A., Morini, E., Bruno, L.M., Basile, G., Tsiantouli, E., Bellone, F., Agostino, R.M., Piraino, B., La Rosa, M.A., Salpietro, C., Lasco, A., 2016. Journal of Bone and Mineral Metabolism 34, 540–546.
Muschitz, C., Kocijan, R., Haschka, J., Zendeli, A., Pirker, T., Geiger, C., Müller, A., Tschinder, B., Kocijan, A., Marterer, C., Nia, A., Muschitz, G.K., Resch, H., Pietschmann, P., 2016. Journal of Bone and Mineral Research 31, 672–682.
Polyzos, S.A., Anastasilakis, A.D., Kountouras, J., Makras, P., Papatheodorou, A., Kokkoris, P., Sakellariou, G.T., Terpos, E., 2016. Journal of Bone and Mineral Metabolism 34, 447–456.
Valassi, E., Crespo, I., Malouf, J., Vilades, D., Leta, R., Llauger, J., Urgell, E., Aulinas, A., Marín, A.M., Biagetti, B., Webb, S.M., 2016. Endocrine 53, 860–864.
Gatti, D., El Ghoch, M., Viapiana, O., Ruocco, A., Chignola, E., Rossini, M., Giollo, A., Idolazzi, L., Adami, S., Dalle Grave, R., 2015. Bone 78, 212–215.
Gifre, L., Vidal, J., Carrasco, J.L., Filella, X., Ruiz-Gaspà, S., Muxi, A., Portell, E., Monegal, A., Guañabens, N., Peris, P., 2015. Journal of Bone and Mineral Research 30, 1014–1021.
Kerschan-Schindl, K., Thalmann, M.M., Weiss, E., Tsironi, M., Föger-Samwald, U., Meinhart, J., Skenderi, K., Pietschmann, P., 2015. PLOS ONE 10, e0132478.
Malluche, H.H., Blomquist, G., Monier-Faugere, M.-C., Cantor, T.L., Davenport, D.L., 2015. Journal of the American Society of Nephrology 26, 2534–2544.
Muschitz, C., Kocijan, R., Pahr, D., Patsch, J.M., Amrein, K., Misof, B.M., Kaider, A., Resch, H., Pietschmann, P., 2015. Calcified Tissue International 96, 477–489.
Garcia-Martín, A., Reyes-Garcia, R., García-Fontana, B., Morales-Santana, S., Coto-Montes, A., Muñoz-Garach, M., Rozas-Moreno, P., Muñoz-Torres, M., 2014. PLoS ONE 9, e111703.
Kyvernitakis, I., Rachner, T.D., Urbschat, A., Hars, O., Hofbauer, L.C., Hadji, P., 2014. Journal of Cancer Research and Clinical Oncology 140, 1671–1680.
Rachner, T.D., Göbel, A., Thiele, S., Rauner, M., Benad-Mehner, P., Hadji, P., Bauer, T., Muders, M.H., Baretton, G.B., Jakob, F., Ebert, R., Bornhäuser, M., Schem, C., Hofbauer, L.C., 2014. Breast Cancer Research 16.
Rachner, T.D., Thiele, S., Göbel, A., Browne, A., Fuessel, S., Erdmann, K., Wirth, M.P., Fröhner, M., Todenhöfer, T., Muders, M.H., Kieslinger, M., Rauner, M., Hofbauer, L.C., 2014. BMC Cancer 14
Terpos, Evangelos, Christoulas, D., Kastritis, E., Katodritou, E., Papatheodorou, A., Pouli, A., Kyrtsonis, M.-C., Michalis, E., Papanikolaou, X., Gkotzamanidou, M., Koulieris, E., Gavriatopoulou, M., Zervas, K., Dimopoulos, M.A., on behalf of the Greek Myeloma Study Group, 2014. American Journal of Hematology 89, 34–40
Terpos, E, Christoulas, D., Kastritis, E., Roussou, M., Migkou, M., Eleutherakis-Papaiakovou, E., Gavriatopoulou, M., Gkotzamanidou, M., Kanellias, N., Manios, E., Papadimitriou, C., Dimopoulos, M.A., 2014. Leukemia 28, 928–934
de Rooy, D.P.C., Yeremenko, N.G., Wilson, A.G., Knevel, R., Lindqvist, E., Saxne, T., Krabben, A., Leijsma, M.K., Daha, N.A., Tsonaka, S., Zhernakova, A., Houwing-Duistermaat, J.J., Huizinga, T.W.J., Toes, R.E.M., Baeten, D.L.P., Brouwer, E., van der Helm-van Mil, A.H.M., 2013. Annals of the Rheumatic Diseases 72, 769–775.
Gatti, D., Viapiana, O., Fracassi, E., Idolazzi, L., Dartizio, C., Povino, M.R., Adami, S., Rossini, M., 2012. Journal of Bone and Mineral Research 27, 2259–2263
Gaudio, A., Privitera, F., Battaglia, K., Torrisi, V., Sidoti, M.H., Pulvirenti, I., Canzonieri, E., Tringali, G., Fiore, C.E., 2012. The Journal of Clinical Endocrinology & Metabolism 97, 3744–3750
Voskaridou, E., Christoulas, D., Plata, E., Bratengeier, C., Anastasilakis, A.D., Komninaka, V., Kaliontzi, D., Gkotzamanidou, M., Polyzos, S.A., Dimopoulou, M., Terpos, E., 2012. Horm. Metab. Res. 44, 909–913.
Cejka, D., Herberth, J., Branscum, A.J., Fardo, D.W., Monier-Faugere, M.-C., Diarra, D., Haas, M., Malluche, H.H., 2011. Clinical Journal of the American Society of Nephrology 6, 877–882.
Frost, M., Andersen, T., Gossiel, F., Hansen, S., Bollerslev, J., van Hul, W., Eastell, R., Kassem, M., Brixen, K., 2011. Journal of Bone and Mineral Research 26, 1721–1728
Terpos, E., Christoulas, D., Gkotzamanidou, M., Bratengeier, C., Gavriatopoulou, M., Migkou, M., Papatheodorou, A., Kastritis, E., Woloszczuk, W., Dimopoulos, M.A., 2010. Blood 116, 2963–2963
Polyzos, S.A., Anastasilakis, A.D., Efstathiadou, Z., Kita, M., Litsas, I., Avramidis, A., Arsos, G., Moralidis, E., Gerou, S., Pavlidou, V., Papatheodorou, A., Terpos, E., 2009. Hormone and Metabolic Research 41, 846–850.
Terpos, E., Christoulas, D., Katodritou, E., Bratengeier, C., Lindner, B., Harmelin, S., Hawa, G., Boutsikas, G., Migkou, M., Gavriatopoulou, M., 2009. Blood 114:425;
Voskaridou, E., Christoulas, D., Xirakia, C., Varvagiannis, K., Boutsikas, G., Bilalis, A., Kastritis, E., Papatheodorou, A., Terpos, E., 2009. Haematologica, 94(5):725-8.
Roato, I., D’Amelio, P., Gorassini, E., Grimaldi, A., Bonello, L., Fiori, C., Delsedime, L., Tizzani, A., De Libero, A., Isaia, G., Ferracini, R., 2008. PLoS ONE 3, e3627.