WO2007107003A1

WO2007107003A1 - Markers for the diagnosis, monitoring and prognosis of osteoporosis and for assessing the risk for osteoporosis and for osteoporotic fractures

Info

Publication number: WO2007107003A1
Application number: PCT/CA2007/000458
Authority: WO
Inventors: Sean Alexander Fitzgerald Peel
Original assignee: Osteopharm Inc.
Priority date: 2006-03-22
Filing date: 2007-03-22
Publication date: 2007-09-27
Also published as: WO2007107002A1

Abstract

Use of biomarkers in the diagnosis, monitoring and prognosis of osteoporosis and also assessing the risk for osteoporosis and for osteoporotic fractures. A marker can include a chemokine, or a combination of chemokines. Specific chemokines include CXCL1, CXCL4, CXCL6 and CXCL8. Another biomarker can be CGRP that is CGRPα or CGRPβ, or combinations thereof.

Description

MARKERS FOR THE DIAGNOSIS, MONITORING AND PROGNOSIS OF OSTEOPOROSIS AND FOR ASSESSING THE RISK FOR OSTEOPOROSIS AND FOR

OSTEOPOROTIC FRACTURES

FIELD OF THE INVENTION

This invention relates to the use of biomarkers in the diagnosis, monitoring and prognosis of osteoporosis and also assessing the risk for osteoporosis and for osteoporotic fractures.

BACKGROUND

Osteoporosis has been defined as "a systemic skeletal disease characterized by low bone mass and microarchitectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture" (Anonymous. Consensus Development Conference: diagnosis, prophylaxis, and treatment of osteoporosis. Am J Med. 1993;94:646-650). Osteoporosis has been further classified as primary (osteoporosis in the absence of known conditions that cause bone loss) and secondary osteoporosis (osteoporosis caused by another condition or use of a drug). Primary osteoporosis has also been subdivided into postmenopausal (also called type I) and senile (type II) osteoporosis. Broadly, osteoporosis relates to any condition which results in significant loss of bone mass and/or quality which results in a significant reduction in mechanical strength and increased risk of fracture.

Osteoporosis is a major health problem worldwide. It has been estimated that more than one third of adult women will experience a fracture due to osteoporosis. There were approximately 3 million osteoporotic fractures worldwide in 2005, and this is expected to increase dramatically as the world population continues to age.

Fractures due to osteoporosis are a principal cause of pain, disability and death. Osteoporotic hip and vertebral fractures result in 10-20% excess mortality within a year. The health cost of treating osteoporotic fractures in Europe is estimated to be €4.8 billion and over $12 billion in the US, and may reach US$240 billion by 2040. Consequently osteoporosis diagnosis and prevention is considered a priority of health care in many countries.

Osteoporotic bone loss is a gradual process that is asymptomatic until fractures occur. Even after osteoporotic fractures have occurred, fewer than one third of patients are appropriately diagnosed. This has led the US Preventative Services Task Force to recommend universal screening of all women over 65. This population numbers over 70 million in Europe and the United States and 270 million worldwide.

The World Health Organization has classified individuals as osteoporotic based on their bone mineral density (BMD) scores (WHO Study Group 1994). An individual's BMD, measured by densitometry and expressed in g/cm2, is compared with a "normal value." The normal value is the mean BMD of sex-matched young adults at their peak bone mass, sometimes referred to as the "young adult mean." When compared with the normal value, a patient's BMD can be expressed in terms of the number of standard deviations (SD) from the normal value. A convenient way to express this is a T-score. Based on this scoring system the WHO classifies individuals as being normal (T score >-1.0) osteopenic (-1.0>T score>-2.5) and osteoporotic (- 2.5> T score). WHO also classified individuals as having severe or established osteoporosis if their T score was less than -2.5 and they had at least one fragility fracture.

Although low BMD correlates with an increased risk for fracture, it is estimated that as high as 82% of osteoporotic fractures occur in women with a BMD score above that used to diagnose osteoporosis (T score <-2.5).

Another concern with the use of BMD is the minimum change in BMD that can be detected. Currently the DEXA scanner, which is considered the "gold standard" for measuring BMD, requires changes of between 3.1 to 6.2% in BMD to be able to detect the change. However, when DEXA units from different manufacturers are used to measure BMD of a single patient, results may differ by as much as 10 to 15%. Even manufacturer intersystem difference after primary calibration is approximately 2%. Thus when trying to determine whether individuals are losing BMD if different machines are used very large changes in BMD must have occurred before bone loss can be definitely identified. As many of the current osteoporosis therapies result in increases in BMD of 6 to 7% after eighteen months it is recognized that BMD can only be useful in determining whether therapy is efficacious after years of treatment have occurred.

Further, since BMD is only a useful diagnostic tool once there has been significant bone loss, BMD is not a good indicator for initiating therapy to prevent the initial bone loss. Another concern with using BMD to diagnose osteoporosis is that the cost and availability of bone scanners limits their use. Consequently in the US less than 9% of women who meet the criteria for a BMD scans had received one in 2000.

Biomarker assays are cheaper and more convenient than BMD scans. Further, if appropriate markers are used they offer the possibility of identifying those who are at greater risk for osteoporotic bone loss prior to that loss occurring, providing the opportunity to initiate preventative measures, such as life style changes or therapeutic interventions, rather than having to restore lost bone later.

Current FDA approved bone biomarker assays are approved for use as aids in the diagnosis of osteoporosis and for monitoring the effectiveness of therapy. All of the approved biomarkers are based on the measurement of markers for bone turnover, and fall into two categories: markers of bone formation (e.g. osteocalcin, bone alkaline phosphatase, pro-collagen I N and C telopeptides), or markers of bone resorption (e.g. hydroxyproline, pyridinoline, deoxypridinoline, N-telopeptide, C-telopeptide, and tartrate resistant acid phosphatase). However their diagnostic accuracy is poor (typically one or both of sensitivity and/or specificity are <65%).

Chemokines are a superfamily of small, secreted proteins that function in leukocyte trafficking, recruitment, and recirculation. They also play a critical role in many pathophysiological processes such as allergic responses, infectious and autoimmune diseases, angiogenesis, inflammation, tumor growth, and hematopoietic development.

Chemokines are divided into four subfamilies based on conserved cysteine amino acid sequence motif. These are the CXC, CC, C and CX3C subfamilies, hi total, approximately 50 chemokines have been identified in humans.

The chemotactic activity of CXC family members depends largely on whether or not they possess the ELR amino acid motif; ELR-containing members are primarily chemotactic for neutrophils. Further, the ELR-CXC chemokines are pro-angiogenic, while the non-ELR CXC chemokines inhibit angiogenesis. CXCLl to 3 and 5 to 8 possess the ELR sequence while CXCL4 does not.

Tatakis has demonstrated that platelet factor 4 (CXCL4) inhibits the proliferation of osteoblast- like osteosarcoma cell lines (Tatakis DN., Human platelet factor 4 is a direct inhibitor of human osteoblast-like osteosarcoma cell growth. Biochem. Biophys. Res. Commun. 1992 Aug 31;187(l):287-93). Tarn has reported that a variant of CXCL7 stimulates the mineral apposition rate in rats. CXCL8 has been reported to stimulate osteoclast formation (Bendre MS, Montague DC, Peery T, Akel NS, Gaddy D, Suva LJ. Interleukin-8 stimulation of osteoclastogenesis and bone resorption is a mechanism for the increased osteolysis of metastatic bone disease. Bone. 2003 Jul;33(l):28-37) and activity and to increase parathyroid hormone secretion by parathyroid cells in vitro (Angeletti RH, D'Amico T, Ashok S, Russell J. The chemokine interleukin-8 regulates parathyroid secretion. J Bone Miner Res. 1998 Aug; 13(8): 1232-7).

A number of CXC chemokines are produced by osteoblasts including CXCLl, 3, 6 and 8.

Two studies have reported levels of CXCL8 in women with osteoporosis. In one study serum from 68 osteoporotic women and 30 age matched non-osteoporotic women were assayed for several cytokines including IL-8 (CXCL8) (Sahin G, Ozturk C, Bagis S, Cimen OB, Erdogan C. Correlation of serum cytokine levels with axial bone mineral density. Singapore Med J. 2002 Nov; 43(11):576). While they demonstrated that CXCL8 was elevated in the osteoporotic samples the difference between the mean of the controls and the mean value for osteoporotic patients was approximately 0.68 standard deviations. This led the authors to conclude that "Although, serum levels of IL-I and IL-8 were higher in osteoporotic patients than controls and the difference was statistically significant (p<0.01), their ranges were not high enough to confirm the hypothesis that osteoporotic patients have higher serum cytokine levels than normal subjects." These results led them to conclude that "we were unable to demonstrate abnormalities of cytokines affecting bone resorption in peripheral serum of women with post-menopausal osteoporosis."

The other study examined the effect of alendronate or calcitonin treatment on cytokine levels, including IL-8 (CXCL8), in two groups of 60 osteoporotic women and compared them to 50 healthy postmenopausal controls (Gur A, Denli A, Cevik R, Nas K, Karakoc M, Sarac AJ. The effects of alendronate and calcitonin on cytokines in postmenopausal osteoporosis: a 6-month randomized and controlled study. Yonsei Med J. 2003 Feb;44(l):99-109). The authors reported that the two osteoporotic groups had significantly elevated CXCL8 levels. Similar to the first study the osteoporotic means were 0.58 and 0.77 standard deviations higher than the control mean and lay within the normal range reported for the test used. The authors demonstrated that calcitonin treatment but not alendronate significantly reduced CXCL8 levels to those of normal controls. The authors concluded that IL-8 "must be studied in more detail to identify the role of these cytokines in the pathogenesis of osteoporosis"

A need thus exists for a robust and reproducible biomarkers assay for osteoporosis which possesses improved accuracy compared to current biomarkers, and desirably with the sensitivity and specificity required for diagnosis of the disease and ability to evaluate the risk of osteoporotic fracture.

SUMMARY OF THE INVENTION

According to this invention an assay is provided based on the surprising and unexpected finding that specific CXC chemokines are useful biomarkers for the diagnosis of osteoporosis.

One objective of this invention is to provide improved biomarker assays, which can be used to diagnose a predisposition to osteoporosis, the presence of the disease and also to monitor the progression of the disease.

According to one aspect of this invention a method of diagnosing osteoporosis is provided which comprises the following steps: a) taking a biological sample from an individual; b) measuring the level of at least one CXC chemokine; and c) diagnosing osteoporosis, the risk of osteoporosis, risk of osteoporotic fracture, or monitoring the progression of the disease by comparing the measured level(s) of the CXC chemokine to known level(s) associated with osteoporosis or the risk of osteoporosis or osteoporotic fracture, or the levels taken from the individual at different times..

In one embodiment a method is provided for determining whether an individual has or is at risk of having osteoporosis and/or at risk of having osteoporotic fractures, comprising the steps of (a) taking a sample, preferably whole blood, plasma or serum from a patient, (b) measuring the levels of at least one CXC chemokine in the sample, and (c) diagnosing osteoporosis or the risk of osteoporosis or risk of osteoporotic fracture by comparing the measured level(s) to known level(s) associated with osteoporosis or the risk of osteoporosis or osteoporotic fracture. The sample may of course be processed, as appropriate, prior to step (b), so the measuring step can thus be of the chemokine in a specimen comprising whole blood, plasma or serum, or in a fluid, or a specimen comprising a fraction of whole blood, fraction of plasma, or fraction of serum.

In another embodiment a method is provided for determining whether an individual has or is at risk of having osteoporosis and/or at risk of having osteoporotic fractures, comprising the steps of (a) taking a sample, preferably whole blood, plasma or serum from an individual, (b) measuring levels of at least one CXC chemokine from the sample, and (c) diagnosing osteoporosis or the risk of osteoporosis or risk of osteoporotic fracture by comparing the measured level(s) to known level(s) associated with osteoporosis or the risk of osteoporosis or osteoporotic fracture.

In another embodiment a method is provided for determining whether an individual has or is at risk of having osteoporosis and/or at risk of having osteoporotic fractures, comprising the steps of (a) taking a sample, preferably whole blood, plasma or serum from an individual, (b) measuring the levels of at least three CXC chemokines in the sample, and (c) diagnosing osteoporosis or the risk of osteoporosis or risk of osteoporotic fracture by comparing the correlation of the measured level(s) to the known correlation of level(s) associated with osteoporosis or the risk of osteoporosis or osteoporotic fracture.

In another embodiment a method is provided for determining whether an individual has or is at risk of having osteoporosis and/or at risk of having osteoporotic fractures comprising the steps of (a) taking a sample, preferably whole blood, plasma or serum from an individual, (b) measuring the levels of at least one CXC chemokine and at least one other non CXC chemokine in the sample, and (c) diagnosing osteoporosis or the risk of osteoporosis or risk of osteoporotic fracture by comparing the measured level(s) to the known level(s) associated with osteoporosis or the risk of osteoporosis or osteoporotic fracture.

The invention also contemplates a method of analyzing the biological sample for the presence of at least one CGRP and also other bone markers that are indicators of osteoporosis and an aid in the diagnosis of the disease. A preferred other bone marker is one or more calcitonin gene related peptides (CGRP). The calcitonin gene related peptides (CGRP) are 37 amino acid peptides which are expressed in the central and peripheral nervous systems and act as neurotransmitters. There are two CGRPs: CGRP alpha (CGRPa) and CGRP beta (CGRPb). CGRPa is a product of the CT/CGRP gene. Alternate splicing of the primary RNA product of this gene can produce calcitonin or CGRPa. CGRPb is derived from a second gene, thought to exist due to gene duplication of the CT/CGRP gene. Human CGRPa and b differ by 3 amino acids. The preferred CGRP for use in this invention is CGRP/3.

The use of such CGRPs in the diagnosis, monitoring and prognosis of osteoporosis is described and claimed in our co-pending application No. the contents which is incorporated herein in its entirety. Other bone markers which may be used in combination with the CGRP either alone or in combination with one or more chemokines include for example, the bone turnover markers selected from the group of osteocalcin, alkaline phosphatase,bone sialoprotein,pro-collagen 1-N- telopeptide, pro-collagen 1-C-telopeptide, tartrate resistant acid phosphatase (TRAP), TRAP5b, deoxpyridiline ,pyridinoline, Cathespin K and combinations thereof.

DETAILED DESCRIPTION OF INVENTION

The present invention provides methods and means for the diagnosis and prognosis of osteoporosis and for assessing the risk for osteoporosis and for osteoporotic fractures in individuals.

The present invention is particularly useful for physicians or others who do not have ready or have no access to bone mineral density testing, by providing a simple method for screening patients to determine their risk for osteoporosis and/or osteoporotic fractures.

The present invention provides simple methods to determine the risk for osteoporosis and/or osteoporotic fractures prior to significant bone loss.

According to the present invention osteoporosis relates to all forms of osteoporosis.

Diagnosis according to the present invention includes determination, confirmation, sub- classification and prediction of osteoporosis. Prognosis according to the present invention relates to the monitoring of osteoporosis. Monitoring relates to keeping track of an already diagnosed osteoporosis or complication, e.g. to analyze the progression of the disease or condition, or influence of treatment on progression of the disease or condition.

Risk stratification according to the present invention relates to the use of clinical risk factors to allow a physician to classify an individual into various categories of risk for developing osteoporosis or osteoporotic fractures e.g. low, moderate or high.

The term "individual" according to the present invention relates to a healthy individual, an apparently healthy individual or an individual with osteoporosis.

The present invention allows diagnosing whether an individual is at risk of having osteoporosis or of having an osteoporotic fracture.

The invention takes advantage of certain biomarkers. Usually a biomarker is a protein, peptide, vitamin, lipid or other biochemical entity and may also include minerals or nucleic acids, which is elevated, decreased or altered in the presence or absence of a condition, disease or complication. The level of a suitable biomarker can indicate the presence, absence or relative risk of the condition, disease or complication and thus allow for assessment of disease risk, diagnosis, or prognosis.

The preferred CGRP is CGRP/3. The preferred CXC chemokines are CXCLl, CXCL4, CXCL6, and CXCL8.

The term "fragments" in the present invention relates to individual components derived from the intact molecule. These may be proteolytic degradation products.

The term "variants" in the present invention relates to molecules which are substantially similar to the said biomarkers. In particular a variant may be an isoform or an allele which shows amino acid exchanges compared to the amino acid sequence of the most prevalent isoforms in the human population. The method may also comprise the step of taking a sample, e.g. a body fluid or tissue sample from the patient. The body fluid can be but is not restricted to whole blood, plasma, serum, urine or saliva. Preferably the sample is blood, plasma or serum.

A person skilled in the art will be familiar with different methods of measuring the level of a biomarker in a sample. The term "level" relates to the amount or concentration of the analyte to be measured.

The term "measuring" according to the present invention relates to determining the amount or concentration of the biomarker preferably semi-quantitatively or quantitatively. Measuring can be done directly or indirectly. Direct measurement methods include the use of high performance liquid chromatography (HPLC), near or mid infra-red spectroscopy or mass spectroscopy. Indirect measurement includes measuring cellular responses, bound ligands, labels, or enzymatic reaction products. Measurement can be done according to any method known in the art.

A preferred method of measurement is an immunoassay. The term "immunoassay" in the present invention relates to a test that uses the binding of antibodies to antigens to identify and measure certain substances. Immunoassay refers to all immunological methods of measuring an analyte including radioimmunoassay (RIA), enzyme immunoassays (EIA) e.g. enzyme linked immunosorbant assay (ELISA), western blot and immunoprecipitation.

In a preferred embodiment of the invention the method for measuring the biomarker of interest comprises the steps of (a) contacting the analyte with a specific binding ligand (b) (optionally) removing non-bound analyte, and (c) measuring the amount of the bound ligand.

Preferably the binding ligand in (a) should be specific for the analyte to be measured. "Specific" in the present invention means that the ligand does not "cross-react" with another substance present in the sample to be investigated. The term "cross-react" in the current invention means the degree in which the other (interfering) substances are shown to generate positive test results. Preferably other structurally similar substances should have a percent cross reactivity of <35%, more preferably <20%, and most preferably <10%.

The invention further relates to a method of producing immunoassays as defined above. Methods of producing such immunoassays are generally known. In another preferred embodiment a multiplexed assay will be used where multiple markers will be assayed simultaneously. The term "multiplexed" refers to the measurement of more than one analyte, or more than one fragment or variant of the same analyte simultaneously in a single small volume of the sample.

Such an assay can be performed using an array. Said array will be capable of quantitating at least two biomarkers. According to the present invention the term "array" refers to a solid-phase or gel-like carrier upon which at least 2 binding ligands are attached or bound in one-, two-, or three dimensions. Such arrays (including protein chips, antibody arrays and the like) are generally known to a person skilled in the art and are typically generated on glass slides, or membranes such as those based on nitrocellulose or nylon.

In another preferred embodiment the multiplexed assay will utilize a microsphere-based flow cytometric assay (Carson, R.T.; Vignali, D.A., "Simultaneous quantitation of 15 cytokines using a multiplexed flow cytometric assay" J. Immunol. Methods 1999; 41). In such an assay the carrier, e.g. a microbead or microsphere, is present in suspension. Each different binding ligand is attached to a different microbead type.

The invention further relates to a method of producing multiplexed assays as defined above. Methods of producing such multiplexed assays are generally known.

The person skilled in the art is able to determine the known levels of markers which are associated with the presence or risk of suffering from osteoporosis or osteoporosis related fractures. Such levels can be determined by well known methods as described in Examples 1, 2, 3, and 4. For example the measured levels in a population of patients with osteoporosis can be compared to a population of patients without osteoporosis. A reference level can be determined above or below which a diagnosis is made or risk stratification is made. Evaluating the levels in further patients, e.g., in cohort studies, can help refine the reference levels and distinguish between different grades of severity and status of disease progression.

The reference levels given in the examples may serve only as a first guideline to diagnose the risk of an individual. The person skilled in the art will be able to determine other reference levels. The value of the reference level may also depend on the desired sensitivity and specificity of the diagnosis. This level can be determined empirically or through the use of statistical methods. A preferred method is by using the Receiver Operating Characteristic (ROC) curve analysis to optimize the diagnostic accuracy.

EXAMPLES

Example 1

CXC Chemokine biomarkers

Serum levels of CXC chemokines were determined in young normal, post menopausal and osteoporotic samples as follows:

Serum Samples

118 individual human serum samples were obtained from Bioreclamation (East Meadow, NY). We also obtained a single pooled set of samples to use as a normalization standard. All samples were from donors who were fasted overnight. The samples were stored at -8O⁰C until use. The specifications for each group were:

Young Normal (YNML)

Thirty healthy Caucasian females taking no medications aged 30-45.

Postmenopausal (PMP)

Fifty healthy Caucasian females aged 55+ who were postmenopausal (minimum 1 year since menses) and were not on hormone therapy.

Osteoporotic (OSP)

Thirty Caucasian females, diagnosed osteoporotic based on a BMD T-score at any site of <2.5. A further 8 Caucasian women who had been diagnosed osteoporotic but had BMD scores >-2.5 were also analyzed. Pooled. Samples pooled from 10 healthy Caucasian female donors aged 20 to 35.

Commercial assays were used for determining serum levels of CXCLl (Gro alpha, RnD Systems Catalog No. DY275), CXCL5 (Ena78, RnD Systems Catalog No. DY254), CXCL6 (GCP-2, RnD Systems Catalog No. DY333), CXCL7 (NAP-2, RnD Systems Catalog No. DY393), and CXCL8 (IL-8, RnD Systems Catalog No. DY208). All assays were performed according to the manufacturer's published procedures. Since no ELISA kit was commercially available for CXCL4, an ELISA was developed using the antibodies MAB 795, BAF 795, 795 -P4 purchased from RnD Systems, and was used for determining serum levels of CXCL4 in the samples.

Data Analyses

As several samples had analytes below the limit of detection, these were given a nominal value of zero in the appropriate test. This resulted in much of the data sets not being normally distributed.

To minimize the effect of age a subset of 40 donors from the postmenopausal (n=20) and osteoporotic groups (n=20) were selected that were aged between 59 and 70.

All data was analyzed using the Sigma Stat 3.2 (Systat Software Inc., Richmond CA). Normally distributed data was analyzed by 1 way ANOVA followed by Holm-Sidak post hoc analysis to identify significantly different factors. ANOVA on Ranks was used for non-normally distributed data with the Dunn's post hoc test. A P value of 0.05 was considered significant in these analyses.

Four measures of diagnostic accuracy were determined. These were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).

These are defined as:

Sensitivity Proportion of people with disease who have a positive test result

Specificity Proportion of people without disease who have a negative test result

PPV Proportion of people with a positive test who have the target disorder NPV Proportion of people with a negative test who are free of the target disorder

Sensitivity, specificity, PPV and NPV are calculated by the following formulae:

Sensitivity = a/a+c, Specificity =d/b+d, PPV = a/a+b, and NPV = d/c+d;

where a is the number of true positives and c is the number of false negatives among the osteoporotic samples, and b is the number of false positives and d is the number of true negatives among the non-osteoporotic samples.

Results

CXCLl, 4, 6 and 8 were significantly elevated in osteoporotic compared to postmenopausal and young normal samples where as CXCL5 and 7 did not vary between the groups (Table 5; PO.0.5).

CXC ligand levels in age matched post menopausal and osteoporotic samples

Comparison of the age range matched subsets of postmenopausal and osteoporotic samples demonstrated CXCLl, 4, 6, 7 and 8 were significantly elevated in osteoporotic samples (Table 6; PO.05).

Table 5 Summary of Results for the Chemokines

Young Normal Postmenopausal Osteoporotic

CXCLl pg/ml 42.76 ± 49.05 54.16 ± 33.98 102.4 ± 60.54 a,b

CXCL4 pg/ml 784.2 ± 747.5 1748 ± 3008 5808 ± 8398 a,b

CXCL5 pg/ml 729.0 ± 973.4 1998 ± 3143 a 855.5 ± 479.2

CXCL6 pg/ml 99.12 ± 100.2 177.6 ± 199.2 247.2 ± 271.1 a,b

CXCL7 pg/ml 3503 ± 6116 5025 ± 4292 6242 ± 2415

CXCL8 pg/ml 591.2 ± 1184 537.6 ± 1034 4129 ± 3619 a,b

Results are displayed as mean ± SD

a significantly different from young normal (P<0.05)

b significantly different from postmenopausal (P<0.05)

Table 6 Summary of Results for the Chemokines (age matched)

Postmenopausal Osteoporotic

CXCLl 48.4 ± 37.2 92.0 ± 55.5 b

CXCL4 990 ± 1060 6194 ± 9100 b

CXCL5 1605 ± 2479 911 ± 536

CXCL6 106 ± 123 180 ± 66 b

CXCL7 3581 ± 3725 5954 ± 2644 b

CXCL8 506 ± 1395 4644 ± 4214 b

Results are displayed as mean ± SD

b significantly different from postmenopausal (P<0.05)

Diagnostic accuracy of CXC 1, 4, 6, and 8 in differentiating between osteoporotic and non- osteoporotic samples

The diagnostic accuracy of a single analyte assay using CXCLl, 4, 6 or 8 for the diagnosis of osteoporosis was determined as described in example 1. The results are shown in Tables 7 to 10.

Table 7 Accuracy of CXCLl diagnostic for osteoporosis

Estimate 95% CI

Sensitivity

65.8% [ 49.9 to 78.8 ]

Specificity

82.3% [ 72.4 to 89.1 ]

Positive Predictive Value

64.1% [ 48.4 to 77.3 ]

Negative Predictive Value

83.3% [ 73.5 to 90.0 ]

Samples were diagnosed as osteoporotic if they had CXCLl levels of 67.5 pg/ml or greater.

Table 8 Accuracy of CXCL4 diagnostic for osteoporosis

Estimate 95% CI

Sensitivity

92.1% [ 79.2 to 97.3 ]

Specificity

63.8% [ 52.8 to 73.4 ]

Positive Predictive Value

54.7% [ 42.6 to 66.3 ]

Negative Predictive Value

94.4% [ 84.9 to 98.1 ]

Samples were diagnosed as osteoporotic if they had CXCL4 levels of 1200pg/ml or greater.

Table 9 Accuracy of CXCL6 diagnostic for osteoporosis

Estimate 95% CI

Sensitivity

81.6 [ 66.6 to 90.8 ]

Specificity

75.0 [ 64.5 to 83.2 ]

Positive Predictive Value

60.8 [ 47.1 to 73.0 ]

Negative Predictive Value

89.6 [ 80 to 94.8 ]

Samples were diagnosed as osteoporotic if they had CXCL6 levels of 160 pg/ml or greater.

Table 10 Accuracy of CXCL8 diagnostic for osteoporosis

Estimate 95% CI

Sensitivity 86.8% [72.7 to 94.2]

Specificity 86.0% [73.8 to 93.0]

Positive Predictive Value 82.5% [68.1 to 91.3]

Negative Predictive Value 89.6% [77.8 to 95.5]

Samples were diagnosed as osteoporotic if they had CXCL8 levels of 1000 pg/ml or greater.

Example 2

Correlation of CXC ligands with each other

Serum levels of CXCLl, CXCL4, CXCL5, CXCL6, CXCL7, and CXCL8 were determined according to Example 2.

Correlations were determined based on Spearman's rank correlation. For the correlation tests a P<0.01 was considered significant. (The lower P for correlation significance was chosen to minimize the risk of identifying correlations where none were present which might occur due to the large number of correlations tested)

A significant strong positive correlation was noted between all the CXC chemokines measured, when considering all the samples from the non-osteoporotic groups (Table 11). However, within the osteoporotic samples there was no positive correlation observed between the chemokines with the exception of CXCL4, 5 and 7 (Table 12). Table 11 Correlation of Chemokines in non-osteoporotic samples (YNML + PM)

Table 12 Correlation of Chemokines (osteoporotic samples only)

CXCL4 CXCL5 CXCL6 CXCL7 CXCL8

CXCLl r -0.348 -0.494 0.294 -0.385 0.278

P 0.0303 0.0015 0.0695 0.0158 0.0908

n 39 39 39 39 38

CXCL4 r 0.374 -0.0269 0.477 -0.075

P 0.0192 0.87 0.00228 0.653

n 39 39 39 38

CXCL5 r 0.0907 0.545 -0.358

P 0.581 O.0001 0.0274

n 39 39 38

CXCL6 r * 0.0408 -0.177

P 0.803 0.286

I^s! n 39 38

CXCL7 r 0.0864

P 0.603

n ^% 38 Although some positive correlations were observed in the osteoporosis group, even in these samples the correlation co-efficients observed in the young normal and postmenopausal samples were much higher (r > 0.80) than in the osteoporosis samples (r<0.55).

Example 3

Multi-analyte Diagnostic Test combining CGRP, CXC chemokines and bone markers

Serum samples used were the young normal, post menopausal and osteoporotic samples that were described in Example 1. Serum levels of osteocalcin and CGRPb were determined and serum levels of CXCL4, CXCL5, CXCL6, CXCL7, and CXCL8 were determined according to Example 1. Commercial assays were used for determining serum levels of IGF-I (RnD Systems DGlOO) IGFBP-3 (RnD Systems DGB300), BMP-2 (RnD Systems DBP200), BMP-4 (RnD Systems DY314), BMP-7 (RnD Systems DY354).

As an example we estimated the diagnostic accuracy of a multiplex assay combining osteocalcin, CGRPb, CXCL4 to 8, IGF-I and IGFBP-3 and BMP-2 and performing discriminant analysis using the StatistiXL software. This resulted in an increase in all measures of diagnostic accuracy. The results are shown in Table 13.

Table 13 Accuracy of a multiplex diagnostic for osteoporosis

Estimate 95% CI

Sensitivity 92.0% [75.0-97.8]

Specificity 90.9% [72.2-97.5]

Positive Predictive Value 92.0% [75.0-97.8]

Negative Predictive Value 90.9% [72.2-97.5]

Claims

1. A method of diagnosing and/or monitoring osteoporosis in an individual which comprises the following steps; a) taking a biological sample from the individual; b) measuring the level of at least one chemokine in said sample; and c) comparing the level(s) in said sample with the level of said chemokine in a control biological sample.

2. A me of claim 1 wherein the control biological sample is from an individual known not to be afflicted by osteoporosis or from the same individual at different times.

3. A method of claim 1 or claim 2, which comprises the following steps: a) contacting the biological sample with an antibody specific for at least one CXC chemokine, said antibody being labeled with a detectable substance; b) measuring the detectable substance to quantitate each CXC chemokine in the sample; and c) comparing the quantitated CXC chemokine levels to levels for a control sample.

4. A method of claim 3 which further comprises: in step a), further contacting the sample with a second antibody specific for the CXC chemokine which is immobilized; following step a) separating the first antibody from the second antibody to provide a first antibody phase and second antibody phase; and in step b), measuring the detectable substrate in either the first or second antibody phase, thereby quantitating the level of CXC chemokine in the biological sample.

5. A method of claim 4, wherein in step a) the first and second antibodies are contacted simultaneously or sequentially with the biological sample.

6. A method of diagnosing an individual's osteoporosis risk or assessing the risk of osteoporotic fracture comprising the steps of examining the concentration profile in a biological sample of the individual of at least one CXC chemokine and correlating the profile with osteoporosis diagnosis.

7. A method of claim 6, wherein the examining step includes exposing the sample to an antibody of each of the at least one CXC chemokine to determine the level of the CXC chemokine in the sample and the correlating step includes comparing the level of the CXC chemokine in the sample with the level of the CXC chemokine in a control population.

8. A method of claim 7 wherein the control population is comprised of individuals each diagnosed as not having osteoporosis, and optionally, wherein the control population is matched to the age of the individual.

9. A method of claim 7 wherein the control population is comprised of individuals each diagnosed as having osteoporosis, and optionally, wherein the control population is matched to the age of the individual.

10. A method of diagnosing osteoporosis, or assessing the risk of osteoporotic fracture in a postmenopausal female individual comprising the steps of examining the concentration profile in a biological sample of the patient of a CXC chemokine and correlating the profile with osteoporosis diagnosis.

11. A method of claim 10, wherein the correlating step includes comparing the level of the CXC chemokine in the sample with the level of CXC chemokine in a control population of non- osteoporotic postmenopausal females in which a positive diagnosis is indicated by a non- elevated level of CXC chemokine in the individual relative to the control population.

12. A method of claim 10 or 11, wherein the correlating step includes comparing the level of the CXC chemokine in the sample with the level of CXC chemokine in a positive control population of osteoporotic postmenopausal females in which a negative diagnosis is indicated by an elevated level of CXC chemokine in the patient relative to the positive control population.

13. A method of any one of the preceding claims wherein the chemokine is selected from the group consisting of CXCLl, CXCL4, CXCL6 and CXCL8.

14. A method as claimed in any one of the preceding claims in which the biological sample , is a whole blood sample, a plasma sample, or a serum sample.

15. A method according to any one of the preceding claims which further comprises measuring the level of at least one CGRP.

16. A method according to any one of the preceding claims wherein the CGRP is CGRPβ.

17. A method of any one of the preceding claims, further comprising correlating the level of a bone turnover marker(s) selected from the group of osteocalcin, alkaline phosphatase, bone sialoprotein, pro-collagen I N-telopeptide, pro-collagen I C-telopeptide, tartrate resistant acid phosphatase (TRAP), TRAP 5b, deoxypryidiniline, pyridinoline, Cathepsin K, and combinations thereof in said sample with the level of the marker(s) in a control population.

18. A method according to any one of the preceding claims, wherein the individual is female, optionally a postmenopausal female.

19. A kit for differentiating between an osteoporotic and a non-osteoporotic condition in an individual comprising: a) a device for obtaining a sample of a biological fluid from the individual; and b) a test for determining the level of a chemokine in said sample relative to the level in a control population.

20. A device for differentiating between an osteoporotic and a non-osteoporotic condition in an individual comprising: a) a capture antibody bound to a support, said capture antibody being specific for a CXC chemokine and b) a reporter antibody, said reporter antibody being specific for said CXC chemokine and having an indicator attached thereto such that the level of the chemokine in said sample relative to the level in a control population can be determined.

21. A method of claim 19, or 20 wherein the fluid comprises a blood sample of the individual, or a whole blood sample, a plasma sample, or a serum sample.