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

Xin Li; Songbing Yang; Yunping Qiu; Tie Zhao; Tianlu Chen; Mingming Su; Lixi Chu; Aiping Lv; Ping Liu; Wei Jia

doi:10.1007/s11306-009-0184-0

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

Xin Li, Songbing Yang, Yunping Qiu, Tie Zhao, Tianlu Chen, Mingming Su, Lixi Chu, Aiping Lv, Ping Liu, Wei Jia

Research output: Contribution to journal › Article › peer-review

37 Scopus citations

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.

Original language	English (US)
Pages (from-to)	109-118
Number of pages	10
Journal	Metabolomics
Volume	6
Issue number	1
DOIs	https://doi.org/10.1007/s11306-009-0184-0
State	Published - Mar 2010
Externally published	Yes

Keywords

Biomarker
Histamine
Metabolomics
Osteoarthritis
Phenotype
Stratification

ASJC Scopus subject areas

Endocrinology, Diabetes and Metabolism
Biochemistry
Clinical Biochemistry

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s11306-009-0184-0

Cite this

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title = "Urinary metabolomics as a potentially novel diagnostic and stratification tool for knee osteoarthritis",

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.",

keywords = "Biomarker, Histamine, Metabolomics, Osteoarthritis, Phenotype, Stratification",

author = "Xin Li and Songbing Yang and Yunping Qiu and Tie Zhao and Tianlu Chen and Mingming Su and Lixi Chu and Aiping Lv and Ping Liu and Wei Jia",

note = "Funding Information: 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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doi = "10.1007/s11306-009-0184-0",

language = "English (US)",

volume = "6",

pages = "109--118",

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T1 - Urinary metabolomics as a potentially novel diagnostic and stratification tool for knee osteoarthritis

AU - Li, Xin

AU - Yang, Songbing

AU - Qiu, Yunping

AU - Zhao, Tie

AU - Chen, Tianlu

AU - Su, Mingming

AU - Chu, Lixi

AU - Lv, Aiping

AU - Liu, Ping

AU - Jia, Wei

N1 - Funding Information: 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.

PY - 2010/3

Y1 - 2010/3

N2 - 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.

AB - 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.

KW - Biomarker

KW - Histamine

KW - Metabolomics

KW - Osteoarthritis

KW - Phenotype

KW - Stratification

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JO - Metabolomics

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

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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