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Bioanalytical Method Development and Validation for the Estimation of Hydroxyproline in Urine Samples of Osteoarthritic Patients Using LC–MS/MS Technique

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Abstract

Osteoarthritis (OA) is a prevalent disorder among the elderly, which is characterized by the degradation of articular cartilage, leading to joint erosion and pain. The release of hydroxyproline, a major component of collagen, into body fluids is a marker of cartilage degradation. Still, an increasing number of people are studying bioanalytical methods and validation for the estimation of hydroxyproline. Yet, there are still no consistent conclusions about OA patients. Blood contains a massive number of metabolites that can potentially become biomarkers, but the metabolome coverage of current analytical techniques remains insufficient. Clear knowledge related to this important issue would definitely facilitate a better understanding and validation of the hydroxyproline. Therefore, this study aims to develop and validate a reliable LC–MS/MS method for estimating hydroxyproline levels in urine samples of osteoarthritic patients. The method demonstrated high sensitivity, selectivity, and precision, with a linear range of 10 ng–320 ng ml−1 and a correlation coefficient (r2) of 0.9993. Sample preparation involved hydrolyzing urine samples and optimizing chromatographic conditions for effective separation. The method validation followed ICH M10 guidelines, ensuring accuracy, precision, and stability. The results indicated that hydroxyproline is a significant biomarker for assessing cartilage degradation severity, thus aiding in the effective management of OA. The developed LC–MS/MS method provides a tool for diagnosing and monitoring OA, thus providing sensitivity to disease progression and treatment efficacy. This method's high-throughput capability is essential for large-scale clinical studies, enhancing the understanding of OA and improving patient outcomes.

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All data generated or analysed during this study are included in the manuscript.

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Not applicable.

Abbreviations

LC–MS/MS:

Liquid chromatography–mass spectroscopy/mass spectroscopy

ACN:

Acetonitrile

CN:

Cyano

RSD:

Relative standard deviation

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All author is contributed to the design and methodology of this study, the assessment of the outcomes and the writing of the manuscript.

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Correspondence to Anil Kumar Tallam.

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Tallam, A.K., Reddy, K.T.K., Panigrahy, U.P. et al. Bioanalytical Method Development and Validation for the Estimation of Hydroxyproline in Urine Samples of Osteoarthritic Patients Using LC–MS/MS Technique. SN COMPUT. SCI. 5, 884 (2024). https://doi.org/10.1007/s42979-024-03237-x

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