Urinary metabolomic profiling to identify potential biomarkers for the diagnosis of behcet’s disease by gas chromatography/time-of-flight- mass spectrometry

Joong Kyong Ahn; Jungyeon Kim; Jiwon Hwang; Juhwan Song; Kyoung Heon Kim; Hoon Suk Cha

doi:10.3390/ijms18112309

Urinary metabolomic profiling to identify potential biomarkers for the diagnosis of behcet’s disease by gas chromatography/time-of-flight- mass spectrometry

Joong Kyong Ahn, Jungyeon Kim, Jiwon Hwang, Juhwan Song, Kyoung Heon Kim, Hoon Suk Cha

Department of Biotechnology

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23 Citations (Scopus)

Abstract

Diagnosing Behcet’s disease (BD) is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flighta-mass spectrometry (GC/TOF-MS). Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC) were assessed using GC/TOF-MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF-MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA) model were R²X of 0.231, R²Y of 0.804, and Q2 of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, L-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974). OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%). We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF-MS.

Original language	English
Article number	2309
Journal	International journal of molecular sciences
Volume	18
Issue number	11
DOIs	https://doi.org/10.3390/ijms18112309
Publication status	Published - 2017 Nov 2

Bibliographical note

Funding Information:
Acknowledgments: This work was supported by the Advanced Biomass R & D Center of Korea (2011-0031353), the National Research Foundation of Korea funded by the Ministry of Education (NRF-2013R1A1A2059103), and a grant of the Korea Health Technology R & D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare (HI14C2285), which are funded by the Korean government. Experiments were performed using the facilities of the Institute of Biomedical Science and Food Safety at the Korea University Food Safety Hall. The study sponsors did not have a role in the study design, collection, analysis and interpretation of data; in the writing of the manuscript; nor in the decision to submit the manuscript for publication.

Publisher Copyright:
© 2017 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

Behcet’s disease
Biomarker
Diagnosis
Gas chromatography-mass spectrometry
Metabolomics
Urine

ASJC Scopus subject areas

Catalysis
Molecular Biology
Spectroscopy
Computer Science Applications
Physical and Theoretical Chemistry
Organic Chemistry
Inorganic Chemistry

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@article{32f22200646d40e1a914234c8fc4cdc5,

title = "Urinary metabolomic profiling to identify potential biomarkers for the diagnosis of behcet{\textquoteright}s disease by gas chromatography/time-of-flight- mass spectrometry",

abstract = "Diagnosing Behcet{\textquoteright}s disease (BD) is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flighta-mass spectrometry (GC/TOF-MS). Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC) were assessed using GC/TOF-MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF-MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA) model were R2X of 0.231, R2Y of 0.804, and Q2 of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, L-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974). OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%). We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF-MS.",

keywords = "Behcet{\textquoteright}s disease, Biomarker, Diagnosis, Gas chromatography-mass spectrometry, Metabolomics, Urine",

author = "Ahn, {Joong Kyong} and Jungyeon Kim and Jiwon Hwang and Juhwan Song and Kim, {Kyoung Heon} and Cha, {Hoon Suk}",

note = "Funding Information: Acknowledgments: This work was supported by the Advanced Biomass R & D Center of Korea (2011-0031353), the National Research Foundation of Korea funded by the Ministry of Education (NRF-2013R1A1A2059103), and a grant of the Korea Health Technology R & D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare (HI14C2285), which are funded by the Korean government. Experiments were performed using the facilities of the Institute of Biomedical Science and Food Safety at the Korea University Food Safety Hall. The study sponsors did not have a role in the study design, collection, analysis and interpretation of data; in the writing of the manuscript; nor in the decision to submit the manuscript for publication. Publisher Copyright: {\textcopyright} 2017 by the authors. Licensee MDPI, Basel, Switzerland.",

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AU - Song, Juhwan

AU - Kim, Kyoung Heon

AU - Cha, Hoon Suk

N1 - Funding Information: Acknowledgments: This work was supported by the Advanced Biomass R & D Center of Korea (2011-0031353), the National Research Foundation of Korea funded by the Ministry of Education (NRF-2013R1A1A2059103), and a grant of the Korea Health Technology R & D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare (HI14C2285), which are funded by the Korean government. Experiments were performed using the facilities of the Institute of Biomedical Science and Food Safety at the Korea University Food Safety Hall. The study sponsors did not have a role in the study design, collection, analysis and interpretation of data; in the writing of the manuscript; nor in the decision to submit the manuscript for publication. Publisher Copyright: © 2017 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2017/11/2

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N2 - Diagnosing Behcet’s disease (BD) is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flighta-mass spectrometry (GC/TOF-MS). Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC) were assessed using GC/TOF-MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF-MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA) model were R2X of 0.231, R2Y of 0.804, and Q2 of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, L-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974). OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%). We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF-MS.

AB - Diagnosing Behcet’s disease (BD) is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flighta-mass spectrometry (GC/TOF-MS). Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC) were assessed using GC/TOF-MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF-MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA) model were R2X of 0.231, R2Y of 0.804, and Q2 of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, L-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974). OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%). We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF-MS.

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Urinary metabolomic profiling to identify potential biomarkers for the diagnosis of behcet’s disease by gas chromatography/time-of-flight- mass spectrometry

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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