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Article: Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis
Title | Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis |
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Authors | |
Keywords | Burkholderia pseudomallei Melioidosis Biomarkers Metabolomics Plasma |
Issue Date | 2016 |
Publisher | Molecular Diversity Preservation International. The Journal's web site is located at http://www.mdpi.org/ijms |
Citation | International Journal of Molecular Sciences, 2016, v. 17 n. 3, p. 307 How to Cite? |
Abstract | © 2016 by the authors; licensee MDPI, Basel, Switzerland.To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis. |
Persistent Identifier | http://hdl.handle.net/10722/229685 |
ISSN | 2023 Impact Factor: 4.9 2023 SCImago Journal Rankings: 1.179 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Lau, SKP | - |
dc.contributor.author | Lee, KC | - |
dc.contributor.author | Lo, CS | - |
dc.contributor.author | Ding, SY | - |
dc.contributor.author | Chow, WN | - |
dc.contributor.author | Ke, Y | - |
dc.contributor.author | Curreem, SOT | - |
dc.contributor.author | To, KKW | - |
dc.contributor.author | Ho, TY | - |
dc.contributor.author | Sridhar, S | - |
dc.contributor.author | Wong, SC | - |
dc.contributor.author | Chan, JFW | - |
dc.contributor.author | Hung, FNI | - |
dc.contributor.author | Sze, KH | - |
dc.contributor.author | Lam, CW | - |
dc.contributor.author | Yuen, KY | - |
dc.contributor.author | Woo, PCY | - |
dc.date.accessioned | 2016-08-23T14:12:39Z | - |
dc.date.available | 2016-08-23T14:12:39Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | International Journal of Molecular Sciences, 2016, v. 17 n. 3, p. 307 | - |
dc.identifier.issn | 1422-0067 | - |
dc.identifier.uri | http://hdl.handle.net/10722/229685 | - |
dc.description.abstract | © 2016 by the authors; licensee MDPI, Basel, Switzerland.To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis. | - |
dc.language | eng | - |
dc.publisher | Molecular Diversity Preservation International. The Journal's web site is located at http://www.mdpi.org/ijms | - |
dc.relation.ispartof | International Journal of Molecular Sciences | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Burkholderia pseudomallei | - |
dc.subject | Melioidosis | - |
dc.subject | Biomarkers | - |
dc.subject | Metabolomics | - |
dc.subject | Plasma | - |
dc.title | Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis | - |
dc.type | Article | - |
dc.identifier.email | Lau, SKP: skplau@hkucc.hku.hk | - |
dc.identifier.email | Ding, SY: sydin1@hku.hk | - |
dc.identifier.email | To, KKW: kelvinto@hkucc.hku.hk | - |
dc.identifier.email | Ho, TY: tipyinho@HKUCC-COM.hku.hk | - |
dc.identifier.email | Sridhar, S: sid8998@hku.hk | - |
dc.identifier.email | Chan, JFW: jfwchan@hku.hk | - |
dc.identifier.email | Hung, FNI: ivanhung@hkucc.hku.hk | - |
dc.identifier.email | Sze, KH: khsze@hku.hk | - |
dc.identifier.email | Lam, CW: ching-wanlam@pathology.hku.hk | - |
dc.identifier.email | Yuen, KY: kyyuen@hkucc.hku.hk | - |
dc.identifier.email | Woo, PCY: pcywoo@hkucc.hku.hk | - |
dc.identifier.authority | Lau, SKP=rp00486 | - |
dc.identifier.authority | To, KKW=rp01384 | - |
dc.identifier.authority | Chan, JFW=rp01736 | - |
dc.identifier.authority | Hung, FNI=rp00508 | - |
dc.identifier.authority | Sze, KH=rp00785 | - |
dc.identifier.authority | Lam, CW=rp00260 | - |
dc.identifier.authority | Yuen, KY=rp00366 | - |
dc.identifier.authority | Woo, PCY=rp00430 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.3390/ijms17030307 | - |
dc.identifier.pmid | 26927094 | - |
dc.identifier.pmcid | PMC4813170 | - |
dc.identifier.scopus | eid_2-s2.0-84959422680 | - |
dc.identifier.hkuros | 262239 | - |
dc.identifier.volume | 17 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 307 | - |
dc.identifier.epage | 307 | - |
dc.identifier.isi | WOS:000373712800122 | - |
dc.publisher.place | Switzerland | - |
dc.identifier.issnl | 1422-0067 | - |