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Original Article

A dual-label time-resolved fluorescence immunoassay for screening of osteoporosis based on simultaneous detection of C-terminal telopeptide (β-CTX) and aminoterminal propeptide (P1NP) of type I procollagen

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Pages 80-85 | Received 19 Jul 2018, Accepted 02 Dec 2018, Published online: 12 Jan 2019
 

Abstract

Osteoporosis is a disease where increased bone weakness increases the risk of a broken bone. Until a broken bone occurs, there are typically no symptoms. Osteoporosis affects more than 75 million people in the United States, Europe and Japan. The diagnosis of osteoporosis is primarily determined by measuring bone mineral density using dual-energy X-ray absorptiometry, but for men under 50 years of age, premenopausal women should not be made on the basis of densitometric criteria alone. Bone biomarkers are a useful tool in detecting osteoporotic. A two-step dual-label time-resolved fluorescence immunoassay (TRFIA) was developed for the simultaneous detection of serum C-terminal telopeptide (β-CTX) and amino-terminal propeptide (P1NP) of Type I procollagen in a single run. The performance of this assay was first evaluated using clinical serum samples, and then compared with commercialized kits. The sensitivity of this assay for β-CTX was 1 ng/L (dynamic range, 0–1000 ng/L), and the sensitivity for P1NP detection was 1 μg/L (dynamic range, 1–1000 μg/L). High correlation coefficients (R) were obtained between the present dual-label TRFIA and commercially available kits (R = 0.99 for β-CTX and P1NP). The present dual-label TRFIA has high sensitivity, specificity and accuracy in clinical sample analysis. It is a good alternative to the single-label diagnostic methods.

Acknowledgements

The authors would like to thank the funding support from the project. We are especially thankful to two anonymous reviewers for their constructive comments which undoubtedly improved this manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was supported by the Guangdong Province Science and Technology Plan Projects [20150119].

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