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Urinary metabolomics as a potentially novel diagnostic and stratification tool for knee osteoarthritis

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Abstract

Metabolomics has been used as a tool in disease diagnosis and phenotype prediction. A urinary metabolomic study based on GC–MS in combination with multivariate statistics was used here to classify between knee osteoarthritis (OA) and healthy controls. OPLS-DA of the spectral data showed distinct metabolic profile variations between OA patients and healthy controls and between two OA phenotypes. Differential metabolites reveal up-regulated TCA cycle associated with OA and histamine metabolism disorders accompanied with knee effusion symptoms. This metabolomic method is potentially applicable as a novel strategy for OA diagnosis and patient stratification.

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Abbreviations

BMI:

Body mass index

COX-2:

Cyclooxygenase 2

CS:

Citrate synthase

GC–MS:

Gas chromatography–mass spectrometry

HAC:

Human articular chondrocytes

HDC:

Histidine decarboxylase

KL:

Kellgren–Lawrence

MCs:

Mast cells

MRI:

Magnetic resonance imaging

NMR:

Nuclear magnetic resonance

NSAIDs:

Nonsteroidal anti-inflammatory drugs

OA:

Osteoarthritis

OPLS-DA:

Orthogonal partial least squares projection to latent structure-discriminant analysis

PCA:

Principle component analysis

TCA:

Tricarboxylic acid

TIC:

Total ion current

VIP:

Variable importance in the projection

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Acknowledgements

This work was mainly supported by research grant from a National Basic Research Program of China (Program 973, Project Number 2007CB914700) and Research Grant No. 2006DFA02700 and partly supported by E-institutes of Shanghai Municipal Education Commission, Project Number E03008. The authors would especially like to thank all the study participants who made this research possible.

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Authors and Affiliations

  1. School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, People’s Republic of China

    Xin Li, Yunping Qiu, Tie Zhao, Tianlu Chen, Mingming Su & Wei Jia

  2. School of Acupuncture and Manipulation, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China

    Songbing Yang

  3. Department of Orthopaedics and Traumatology, Yueyang Hospital of Integrated Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, People’s Republic of China

    Lixi Chu

  4. E-Institute of Chinese Traditional Internal Medicine, Shanghai Municipal Education Commission, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China

    Aiping Lv & Ping Liu

  5. Department of Nutrition, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, 28081, USA

    Wei Jia

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  1. Xin Li
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  2. Songbing Yang
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Correspondence to Wei Jia.

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Li, X., Yang, S., Qiu, Y. et al. Urinary metabolomics as a potentially novel diagnostic and stratification tool for knee osteoarthritis. Metabolomics 6, 109–118 (2010). https://doi.org/10.1007/s11306-009-0184-0

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  • DOI: https://doi.org/10.1007/s11306-009-0184-0

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