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Torimoto K, Ueda T, Kasahara M, Hirayama A, Matsushita C, Matsumoto Y, Gotoh D, Nakai Y, Miyake M, Aoki K, Fujimoto K. Identification of diagnostic serum biomarkers for Hunner-type interstitial cystitis. Low Urin Tract Symptoms 2022; 14:334-340. [PMID: 35307976 DOI: 10.1111/luts.12439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/01/2022] [Accepted: 03/07/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVES Diagnosis of Hunner-type interstitial cystitis (HIC) relies on the ability to identify Hunner lesions endoscopically, which can lead to storage symptom misdiagnosis. Here, we examined serum biomarkers for HIC and verified their utility. METHODS Based on the previous definition of the Japanese guidelines, which did not distinguish HIC and non-HIC diseases, we searched for serum biomarkers in 25 patients with interstitial cystitis (IC) and 25 control participants using metabolomics during 2013-2014. In 2019, we conducted a validation study in HIC and control groups. Serum samples were analyzed using liquid chromatography-tandem mass spectrometry, and candidate biomarker concentrations were compared between the groups using Mann-Whitney test. RESULTS Metabolomics targeted 678 metabolites and revealed that the levels of 14 lysolipids, seven γ-glutamyl amino acids, and two monoacylglycerols were significantly different between the IC and control groups. The following metabolites were selected from each metabolite category as candidates: 1-linoleoylglycerophosphocholine (1-linoleloyl-GPC [18:2]), γ-glutamylisoleucine (γ-Glu-Ile), and 1-arachidonylglycerol (1-AG). The serum concentrations of 1-linoleoyl-GPC (18:2) in the HIC and control groups were 27 920 ± 6261 and 40 360 ± 1514 ng/mL (P = 0.0003), respectively. The serum concentrations of γ-Glu-Ile and 1-AG were not significantly different between the groups. When the cut-off value of 1-linoleoyl-GPC (18:2) was set at 28 400 ng/mL, the sensitivity and specificity were 68% and 84%, respectively. CONCLUSIONS Serum 1-linoleoyl-GPC (18:2) is a candidate diagnostic biomarker for HIC. Additional studies on whether this biomarker can distinguish HIC from other diseases with high urination frequency are required for its clinical use.
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Affiliation(s)
| | | | - Masato Kasahara
- Institute for Clinical and Translational Science, Nara Medical University, Kashihara, Japan
| | - Akihide Hirayama
- Department of Urology, Kindai University Nara Hospital, Ikoma, Japan
| | - Chie Matsushita
- Department of Urology, Saiseikai Chuwa Hospital, Sakurai, Japan
| | | | - Daisuke Gotoh
- Department of Urology, Nara Medical University, Kashihara, Japan
| | - Yasushi Nakai
- Department of Urology, Nara Medical University, Kashihara, Japan
| | - Makito Miyake
- Department of Urology, Nara Medical University, Kashihara, Japan
| | - Katsuya Aoki
- Department of Urology, Nara Medical University, Kashihara, Japan
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Sawicka-Smiarowska E, Bondarczuk K, Bauer W, Niemira M, Szalkowska A, Raczkowska J, Kwasniewski M, Tarasiuk E, Dubatowka M, Lapinska M, Szpakowicz M, Stachurska Z, Szpakowicz A, Sowa P, Raczkowski A, Kondraciuk M, Gierej M, Motyka J, Jamiolkowski J, Bondarczuk M, Chlabicz M, Bucko J, Kozuch M, Dobrzycki S, Bychowski J, Musial WJ, Godlewski A, Ciborowski M, Gyenesei A, Kretowski A, Kaminski KA. Gut Microbiome in Chronic Coronary Syndrome Patients. J Clin Med 2021; 10:jcm10215074. [PMID: 34768594 PMCID: PMC8584954 DOI: 10.3390/jcm10215074] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 02/07/2023] Open
Abstract
Despite knowledge of classical coronary artery disease (CAD) risk factors, the morbidity and mortality associated with this disease remain high. Therefore, new factors that may affect the development of CAD, such as the gut microbiome, are extensively investigated. This study aimed to evaluate gut microbiome composition in CAD patients in relation to the control group. We examined 169 CAD patients and 166 people in the control group, without CAD, matched in terms of age and sex to the study group. Both populations underwent a detailed health assessment. The microbiome analysis was based on the V3-V4 region of the 16S rRNA gene (NGS method). Among 4074 identified taxonomic units in the whole population, 1070 differed between study groups. The most common bacterial types were Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Furthermore, a higher Firmicutes/Bacteroidetes ratio in the CAD group compared with the control was demonstrated. Firmicutes/Bacteroidetes ratio, independent of age, sex, CAD status, LDL cholesterol concentration, and statins treatment, was related to altered phosphatidylcholine concentrations obtained in targeted metabolomics. Altered alpha-biodiversity (Kruskal-Wallis test, p = 0.001) and beta-biodiversity (Bray-Curtis metric, p < 0.001) in the CAD group were observed. Moreover, a predicted functional analysis revealed some taxonomic units, metabolic pathways, and proteins that might be characteristic of the CAD patients' microbiome, such as increased expressions of 6-phospho-β-glucosidase and protein-N(pi)-phosphohistidine-sugar phosphotransferase and decreased expressions of DNA topoisomerase, oxaloacetate decarboxylase, and 6-beta-glucosidase. In summary, CAD is associated with altered gut microbiome composition and function.
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Affiliation(s)
- Emilia Sawicka-Smiarowska
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
- Department of Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.T.); (A.S.); (W.J.M.)
| | - Kinga Bondarczuk
- Centre for Bioinformatics and Data Analysis, Medical University of Bialystok, 15-269 Bialystok, Poland; (K.B.); (M.K.); (M.B.)
| | - Witold Bauer
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Magdalena Niemira
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Anna Szalkowska
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Justyna Raczkowska
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Miroslaw Kwasniewski
- Centre for Bioinformatics and Data Analysis, Medical University of Bialystok, 15-269 Bialystok, Poland; (K.B.); (M.K.); (M.B.)
| | - Ewa Tarasiuk
- Department of Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.T.); (A.S.); (W.J.M.)
| | - Marlena Dubatowka
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Magda Lapinska
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Malgorzata Szpakowicz
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Zofia Stachurska
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Anna Szpakowicz
- Department of Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.T.); (A.S.); (W.J.M.)
| | - Pawel Sowa
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Andrzej Raczkowski
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Marcin Kondraciuk
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Magdalena Gierej
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Joanna Motyka
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Jacek Jamiolkowski
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Mateusz Bondarczuk
- Centre for Bioinformatics and Data Analysis, Medical University of Bialystok, 15-269 Bialystok, Poland; (K.B.); (M.K.); (M.B.)
| | - Malgorzata Chlabicz
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
- Department of Invasive Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (M.K.); (S.D.)
| | - Jolanta Bucko
- Department of Cardiology, Bialystok Regional Hospital, 15-950 Bialystok, Poland; (J.B.); (J.B.)
| | - Marcin Kozuch
- Department of Invasive Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (M.K.); (S.D.)
| | - Slawomir Dobrzycki
- Department of Invasive Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (M.K.); (S.D.)
| | - Jerzy Bychowski
- Department of Cardiology, Bialystok Regional Hospital, 15-950 Bialystok, Poland; (J.B.); (J.B.)
| | - Wlodzimierz Jerzy Musial
- Department of Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.T.); (A.S.); (W.J.M.)
| | - Adrian Godlewski
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Attila Gyenesei
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Adam Kretowski
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Karol Adam Kaminski
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
- Correspondence: ; Tel.: +48-85-8318-656
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Chacko S, Mamas MA, El-Omar M, Simon D, Haseeb S, Fath-Ordoubadi F, Clarke B, Neyses L, Dunn WB. Perturbations in cardiac metabolism in a human model of acute myocardial ischaemia. Metabolomics 2021; 17:76. [PMID: 34424431 PMCID: PMC8382649 DOI: 10.1007/s11306-021-01827-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Accepted: 07/29/2021] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Acute myocardial ischaemia and the transition from reversible to irreversible myocardial injury are associated with abnormal metabolic patterns. Advances in metabolomics have extended our capabilities to define these metabolic perturbations on a metabolome-wide scale. OBJECTIVES This study was designed to identify cardiac metabolic changes in serum during the first 5 min following early myocardial ischaemia in humans, applying an untargeted metabolomics approach. METHODS Peripheral venous samples were collected from 46 patients in a discovery study (DS) and a validation study (VS) (25 for DS, 21 for VS). Coronary sinus venous samples were collected from 7 patients (4 for DS, 3 for VS). Acute myocardial ischaemia was induced by transient coronary occlusion during percutaneous coronary intervention (PCI). Plasma samples were collected at baseline (prior to PCI) and at 1 and 5 min post-coronary occlusion. Samples were analyzed by Ultra Performance Liquid Chromatography-Mass Spectrometry in an untargeted metabolomics approach. RESULTS The study observed changes in the circulating levels of metabolites at 1 and 5 min following transient coronary ischaemia. Both DS and VS identified 54 and 55 metabolites as significant (P < 0.05) when compared to baseline levels, respectively. Fatty acid beta-oxidation and anaerobic respiration, lysoglycerophospholipids, arachidonic acid, docosahexaenoic acid, tryptophan metabolism and sphingosine-1-phosphate were identified as mechanistically important. CONCLUSION Using an untargeted metabolomics approach, the study identified important cardiac metabolic changes in peripheral and coronary sinus plasma, in a human model of controlled acute myocardial ischaemia. Distinct classes of metabolites were shown to be involved in the rapid cardiac response to ischemia and provide insights into diagnostic and interventional targets.
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Affiliation(s)
- Sanoj Chacko
- Division of Cardiology, Queen's University, Kingston, ON, Canada.
- Institute of Cardiovascular Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
- Keele Cardiovascular Research Group, Keele University, Stoke-on-Trent, UK.
- Manchester Heart Centre, Manchester Royal Infirmary, Central Manchester University Hospitals NHS Trust, Manchester, UK.
- Kingston Health Sciences Centre, Queen's University, 76 Stuart St, Kingston, ON, Canada.
| | - Mamas A Mamas
- Institute of Cardiovascular Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
- Keele Cardiovascular Research Group, Keele University, Stoke-on-Trent, UK
| | - Magdi El-Omar
- Institute of Cardiovascular Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
- Manchester Heart Centre, Manchester Royal Infirmary, Central Manchester University Hospitals NHS Trust, Manchester, UK
| | - David Simon
- Department of Chemistry, Queen's University, Kingston, ON, Canada
| | - Sohaib Haseeb
- Division of Cardiology, Queen's University, Kingston, ON, Canada
| | - Farzin Fath-Ordoubadi
- Institute of Cardiovascular Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
- Manchester Heart Centre, Manchester Royal Infirmary, Central Manchester University Hospitals NHS Trust, Manchester, UK
| | - Bernard Clarke
- Institute of Cardiovascular Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
- School of Chemistry and Manchester Centre for Integrative Systems Biology, Manchester Institute of Biotechnology, The University of Manchester, Manchester, UK
| | - Ludwig Neyses
- Institute of Cardiovascular Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
- University of Luxembourg, 4365, Esch-sur-Alzette, Luxembourg
| | - Warwick B Dunn
- School of Chemistry and Manchester Centre for Integrative Systems Biology, Manchester Institute of Biotechnology, The University of Manchester, Manchester, UK
- School of Biosciences and Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK
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Zhong W, Deng Q, Deng X, Zhong Z, Hou J. Plasma Metabolomics of Acute Coronary Syndrome Patients Based on Untargeted Liquid Chromatography-Mass Spectrometry. Front Cardiovasc Med 2021; 8:616081. [PMID: 34095243 PMCID: PMC8172787 DOI: 10.3389/fcvm.2021.616081] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Accepted: 03/18/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Acute coronary syndrome (ACS) is the main cause of death and morbidity worldwide. The present study aims to investigate the altered metabolites in plasma from patients with ACS and sought to identify metabolic biomarkers for ACS. Methods: The plasma metabolomics profiles of 284 ACS patients and 130 controls were carried out based on an untargeted liquid chromatography coupled with tandem mass spectrometry (LC-MS) approach. Multivariate statistical methods, pathway enrichment analysis, and univariate receiver operating characteristic (ROC) curve analysis were performed. Results: A total of 328 and 194 features were determined in positive and negative electrospray ionization mode in the LC-MS analysis, respectively. Twenty-eight metabolites were found to be differentially expressed, in ACS patients relative to controls (p < 0.05). Pathway analysis revealed that these metabolites are mainly involved in synthesis and degradation of ketone bodies, phenylalanine metabolism, and arginine and proline metabolism. Furthermore, a diagnostic model was constructed based on the metabolites identified and the areas under the curve (AUC) for 5-oxo-D-proline, creatinine, phosphatidylethanolamine lyso 16:0, and LPC (20:4) range from 0.764 to 0.844. The higher AUC value of 0.905 was obtained for the combined detection of phosphatidylethanolamine lyso 16:0 and LPC (20:4). Conclusions: Differential metabolic profiles may be useful for the effective diagnosis of ACS and may provide additional insight into the molecular mechanisms underlying ACS.
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Affiliation(s)
- Wei Zhong
- Center for Cardiovascular Diseases, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China.,Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China
| | - Qiaoting Deng
- Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China.,Research Experimental Center, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China
| | - Xunwei Deng
- Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China.,Research Experimental Center, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China
| | - Zhixiong Zhong
- Center for Cardiovascular Diseases, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China.,Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China
| | - Jingyuan Hou
- Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China.,Research Experimental Center, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China
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Surendran A, Aliani M, Ravandi A. Metabolomic characterization of myocardial ischemia-reperfusion injury in ST-segment elevation myocardial infarction patients undergoing percutaneous coronary intervention. Sci Rep 2019; 9:11742. [PMID: 31409856 PMCID: PMC6692400 DOI: 10.1038/s41598-019-48227-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 07/16/2019] [Indexed: 02/07/2023] Open
Abstract
AIM The aim of the study was to discover the metabolomic changes in plasma that occur during human Ischemia-Reperfusion (I/R) injury and to evaluate the diagnostic utility of plasma metabolomic biomarkers for determination of myocardial injury. Deciphering the details of plasma metabolome in ST-segment elevation myocardial infarction (STEMI) patients before and after primary percutaneous coronary interventions (PPCI) would allow for better understanding of the mechanisms involved during acute myocardial ischemia and reperfusion in humans. We performed a detailed non-targeted metabolomic analysis of plasma from 27 STEMI patients who had undergone PPCI in the first 48 hrs employing a LC-MS approach. Plasma metabolome at ischemic condition was compared to multiple time points after PPCI which allowed us to focus on changes in the reperfusion phase. Classification of the differential metabolites based on chemical taxonomy identified a major role for lipids and lipid-derived molecules. Biochemical pathway analysis identified valine, leucine and isoleucine biosynthesis, vitamin B6 metabolism and glutathione metabolism as the most significant metabolic pathways representing early response to I/R injury. We also identified phenyl alanine, tyrosine, linoleic acid and glycerophospholipid metabolism as the most significant pathways representing late response to I/R injury. A panel of three metabolites pentadecanoic acid, linoleoyl carnitine and 1-linoleoylglycerophosphocholine was discovered to have diagnostic value in determining the extent of I/R injury based on cardiac biomarkers. Using a non-targeted LC-MS approach, we have successfully generated the most comprehensive data to date on significant changes in the plasma metabolome in STEMI patients who had undergone PPCI in the first 48 hrs showing that lipid metabolites represent the largest cohort of molecules undergoing significant change.
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Affiliation(s)
- Arun Surendran
- Cardiovascular Lipidomics Laboratory, St. Boniface Hospital, Albrechtsen Research Centre, University of Manitoba, Winnipeg, Canada
- Department of Physiology and Pathophysiology, Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Michel Aliani
- Department of Human Nutritional Sciences, University of Manitoba, Winnipeg, Canada.
- Department of Physiology and Pathophysiology, Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada.
| | - Amir Ravandi
- Cardiovascular Lipidomics Laboratory, St. Boniface Hospital, Albrechtsen Research Centre, University of Manitoba, Winnipeg, Canada.
- Department of Physiology and Pathophysiology, Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada.
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Sun L, Li H, Lin X. Linking of metabolomic biomarkers with cardiometabolic health in Chinese population. J Diabetes 2019; 11:280-291. [PMID: 30239137 DOI: 10.1111/1753-0407.12858] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 09/13/2018] [Accepted: 09/14/2018] [Indexed: 12/13/2022] Open
Abstract
Due to rapid nutrition transitions, the prevalence of cardiometabolic diseases, such as metabolic syndrome, type 2 diabetes, and cardiovascular diseases, has been increasing at an alarming rate in the Chinese population. Moreover, Asians, including Chinese, have been hypothesized to have a higher susceptibility to cardiometabolic diseases than Caucasians. Early prediction and prevention are key to controlling this epidemic trend; to this end, the identification of novel biomarkers is critical to reflect environmental exposure, as well as to reveal endogenous metabolic and pathophysiologic mechanisms. The emerging "omics" technologies, especially metabolomics, offer a unique opportunity to provide novel signatures or fingerprints to understand the effects of genetic and non-genetic factors on cardiometabolic health. During the past two decades, metabolomic approaches have been increasingly used in various epidemiological studies, primarily in Western populations. Although the field is still in its early stages, some studies have tried to identify novel compounds or confirm their metabolites and associations with cardiometabolic diseases in Chinese populations, including amino acids, fatty acids, acylcarnitines and other metabolites. Despite major efforts to discover novel biomarkers for disease prediction or intervention, the limits in current study design, analytical platforms, and data processing approaches are challenges in metabolomic research worldwide. Therefore, future research with more advanced technologies, rigorous study designs, standardized detection and analytic approaches, and integrated data from multiomics approaches are essential to evaluate the feasibility of using metabolomics in clinical settings. Finally, the functional roles and underlying biological mechanisms of metabolomic biomarkers should be elucidated by future mechanistic research.
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Affiliation(s)
- Liang Sun
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Huaixing Li
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xu Lin
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
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Lam SM, Wang Y, Li B, Du J, Shui G. Metabolomics through the lens of precision cardiovascular medicine. J Genet Genomics 2017; 44:127-138. [PMID: 28325553 DOI: 10.1016/j.jgg.2017.02.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2017] [Revised: 02/21/2017] [Accepted: 02/27/2017] [Indexed: 12/14/2022]
Abstract
Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular, metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed: 1) the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2) the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed.
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Affiliation(s)
- Sin Man Lam
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yuan Wang
- Beijing Anzhen Hospital, Capital Medical University, The Key Laboratory of Remodeling-Related Cardiovascular Diseases, Ministry of Education, Beijing Collaborative Innovation Center for Cardiovascular Disorders, Beijing Institute of Heart, Lung & Blood Vessel Disease, Beijing 100029, China
| | - Bowen Li
- Lipidall Technologies Company Limited, Changzhou 213000, China
| | - Jie Du
- Beijing Anzhen Hospital, Capital Medical University, The Key Laboratory of Remodeling-Related Cardiovascular Diseases, Ministry of Education, Beijing Collaborative Innovation Center for Cardiovascular Disorders, Beijing Institute of Heart, Lung & Blood Vessel Disease, Beijing 100029, China
| | - Guanghou Shui
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
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8
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Stratmann B, Richter K, Wang R, Yu Z, Xu T, Prehn C, Adamski J, Illig T, Tschoepe D, Wang-Sattler R. Metabolomic Signature of Coronary Artery Disease in Type 2 Diabetes Mellitus. Int J Endocrinol 2017; 2017:7938216. [PMID: 28348587 PMCID: PMC5350534 DOI: 10.1155/2017/7938216] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Revised: 12/01/2016] [Accepted: 12/20/2016] [Indexed: 01/08/2023] Open
Abstract
Coronary artery disease (CAD) is a common complication of type 2 diabetes mellitus (T2D). This case-control study was done to identify metabolites with different concentrations between T2D patients with and without CAD and to characterise implicated metabolic mechanisms relating to CAD. Fasting serum samples of 57 T2D subjects, 26 with (cases) and 31 without CAD (controls), were targeted for metabolite profiling of 163 metabolites. To assess the association between metabolite levels and CAD, partial least squares (PLS) analysis and multivariate logistic regression analysis with adjustment for CAD risk factors and medications were performed. We observed a separation of cases and controls with two classes of metabolites being significantly associated with CAD, including phosphatidylcholines, and serine. Four metabolites being independent from the common CAD risk factors displaying best separation between cases and controls were further selected. Addition of the metabolite concentrations to risk factor analysis raised the area under the receiver-operating-characteristic curve from 0.72 to 0.88 (p = 0.020), providing improved sensitivity and specificity for CAD classification. Serum phospholipid and serine levels independently discriminate T2D patients with and without CAD. Oxidative stress and reduced antioxidative capacity lead to lower metabolite concentrations probably due to changes in membrane composition and accelerated phospholipid degradation.
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Affiliation(s)
- Bernd Stratmann
- Herz- und Diabeteszentrum NRW, Ruhr-Universitaet Bochum, Diabeteszentrum, 32545 Bad Oeynhausen, Germany
- *Bernd Stratmann:
| | - Katrin Richter
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Ruichao Wang
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Zhonghao Yu
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Tao Xu
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Cornelia Prehn
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Experimental Genetics, Life and Food Science Center Weihenstephan, Technische Universität München, 85354 Freising, Germany
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Diethelm Tschoepe
- Herz- und Diabeteszentrum NRW, Ruhr-Universitaet Bochum, Diabeteszentrum, 32545 Bad Oeynhausen, Germany
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
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9
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Ali SE, Farag MA, Holvoet P, Hanafi RS, Gad MZ. A Comparative Metabolomics Approach Reveals Early Biomarkers for Metabolic Response to Acute Myocardial Infarction. Sci Rep 2016; 6:36359. [PMID: 27821850 PMCID: PMC5099572 DOI: 10.1038/srep36359] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Accepted: 10/13/2016] [Indexed: 12/22/2022] Open
Abstract
Discovery of novel biomarkers is critical for early diagnosis of acute coronary syndrome (ACS). Serum metabolite profiling of ST-elevation myocardial infarction (STEMI), unstable angina (UA) and healthy controls was performed using gas chromatography mass spectrometry (GC/MS), solid-phase microextraction coupled to gas chromatography mass spectrometry (SPME-GC/MS) and nuclear magnetic resonance (1H-NMR). Multivariate data analysis revealed a metabolic signature that could robustly discriminate STEMI patients from both healthy controls and UA patients. This panel of biomarkers consisted of 19 metabolites identified in the serum of STEMI patients. One of the most intriguing biomarkers among these metabolites is hydrogen sulfide (H2S), an endogenous gasotransmitter with profound effect on the heart. Serum H2S absolute levels were further investigated using a quantitative double-antibody sandwich enzyme-linked immunosorbent assay (ELISA). This highly sensitive immunoassay confirmed the elevation of serum H2S in STEMI patients. H2S level discriminated between UA and STEMI groups, providing an initial insight into serum-free H2S bioavailability during ACS. In conclusion, the current study provides a detailed map illustrating the most predominant altered metabolic pathways and the biochemical linkages among the biomarker metabolites identified in STEMI patients. Metabolomics analysis may yield novel predictive biomarkers that will potentially allow for an earlier medical intervention.
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Affiliation(s)
- Sara E Ali
- Department of Pharmaceutical Biology, Faculty of Pharmacy &Biotechnology, The German University in Cairo, Egypt
| | - Mohamed A Farag
- Department of Pharmacognosy, Faculty of Pharmacy, Cairo University, Cairo, 11562, Egypt
| | - Paul Holvoet
- Department of Cardiovascular Sciences, Atherosclerosis and Metabolism Unit, KatholiekeUniversiteit Leuven, Belgium
| | - Rasha S Hanafi
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy &Biotechnology, The German University in Cairo, Egypt
| | - Mohamed Z Gad
- Department of Biochemistry, Faculty of Pharmacy &Biotechnology, The German University in Cairo, Egypt
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10
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Tuñón J, Barbas C, Blanco-Colio L, Burillo E, Lorenzo Ó, Martín-Ventura JL, Más S, Rupérez FJ, Egido J. Proteomics and metabolomics in biomarker discovery for cardiovascular diseases: progress and potential. Expert Rev Proteomics 2016; 13:857-71. [PMID: 27459711 DOI: 10.1080/14789450.2016.1217775] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
INTRODUCTION The process of discovering novel biomarkers and potential therapeutic targets may be shortened using proteomic and metabolomic approaches. AREAS COVERED Several complementary strategies, each one presenting different advantages and limitations, may be used with these novel approaches. In vitro studies show how cells involved in cardiovascular disease react, although the phenotype of cultured cells differs to that occurring in vivo. Tissue analysis either in human specimens or animal models may show the proteins that are expressed in the pathological process, although the presence of structural proteins may be confounding. To identify circulating biomarkers, analyzing the secretome of cultured atherosclerotic tissue, analysis of blood cells and/or plasma may be more straightforward. However, in the latter approach, high-abundant proteins may mask small molecules that could be potential biomarkers. The study of sub-proteomes such as high-density lipoproteins may be useful to circumvent this limitation. Regarding metabolomics, most studies have been performed in small populations, and we need to perform studies in large populations in order to discover robust biomarkers. Expert commentary: It is necessary to involve the clinicians in these areas to improve the design of clinical studies, including larger populations, in order to obtain consistent novel biomarkers.
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Affiliation(s)
- José Tuñón
- a Department of Cardiology , Fundación Jiménez Díaz , Madrid , Spain.,b Vascular Pathology Laboratory , Fundación Jiménez Díaz , Madrid , Spain.,c Department of Medicine, Autónoma University , Madrid , Spain
| | - Coral Barbas
- d CEMBIO, Centre for Metabolomics and Bioanalysis, Facultad de Farmacia , Universidad San Pablo CEU , Madrid , Spain
| | - Luis Blanco-Colio
- b Vascular Pathology Laboratory , Fundación Jiménez Díaz , Madrid , Spain
| | - Elena Burillo
- b Vascular Pathology Laboratory , Fundación Jiménez Díaz , Madrid , Spain
| | - Óscar Lorenzo
- b Vascular Pathology Laboratory , Fundación Jiménez Díaz , Madrid , Spain.,c Department of Medicine, Autónoma University , Madrid , Spain
| | - José Luis Martín-Ventura
- b Vascular Pathology Laboratory , Fundación Jiménez Díaz , Madrid , Spain.,c Department of Medicine, Autónoma University , Madrid , Spain
| | - Sebastián Más
- b Vascular Pathology Laboratory , Fundación Jiménez Díaz , Madrid , Spain.,c Department of Medicine, Autónoma University , Madrid , Spain
| | - Francisco Javier Rupérez
- d CEMBIO, Centre for Metabolomics and Bioanalysis, Facultad de Farmacia , Universidad San Pablo CEU , Madrid , Spain
| | - Jesús Egido
- b Vascular Pathology Laboratory , Fundación Jiménez Díaz , Madrid , Spain.,c Department of Medicine, Autónoma University , Madrid , Spain.,e Department of Nephrology , Fundación Jiménez Díaz , Madrid , Spain.,f CIBERDEM , Madrid , Spain
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11
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Deidda M, Piras C, Bassareo PP, Cadeddu Dessalvi C, Mercuro G. Metabolomics, a promising approach to translational research in cardiology. ACTA ACUST UNITED AC 2015. [DOI: 10.1016/j.ijcme.2015.10.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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12
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Armitage EG, Rupérez FJ, Barbas C. Metabolomics of diet-related diseases using mass spectrometry. Trends Analyt Chem 2013. [DOI: 10.1016/j.trac.2013.08.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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13
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Heather LC, Wang X, West JA, Griffin JL. A practical guide to metabolomic profiling as a discovery tool for human heart disease. J Mol Cell Cardiol 2013; 55:2-11. [PMID: 23231771 DOI: 10.1016/j.yjmcc.2012.12.001] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2012] [Revised: 11/30/2012] [Accepted: 12/01/2012] [Indexed: 12/12/2022]
Abstract
Metabolomics has refreshed interest in metabolism across biology and medicine, particularly in the areas of functional genomics and biomarker discovery. In this review we will discuss the experimental techniques and challenges involved in metabolomic profiling and how these technologies have been applied to cardiovascular disease. Open profiling and targeted approaches to metabolomics are compared, focusing on high resolution NMR spectroscopy and mass spectrometry, as well as discussing how to analyse the large amounts of data generated using multivariate statistics. Finally, the current literature on metabolomic profiling in human cardiovascular disease is reviewed to illustrate the diversity of approaches, and discuss some of the key metabolites and pathways found to be perturbed in plasma, urine and tissue from patients with these diseases. This includes studies of coronary artery disease, myocardial infarction, and ischemic heart disease. These studies demonstrate the potential of the technology for biomarker discovery and elucidating metabolic mechanisms associated with given pathologies, but also in some cases provide a warning of the pitfalls of poor study design. This article is part of a Special Issue entitled "Focus on Cardiac Metabolism".
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Affiliation(s)
- Lisa C Heather
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3PT, UK
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14
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Ou ZJ, Li L, Liao XL, Wang YM, Hu XX, Zhang QL, Wang ZP, Yu H, Zhang X, Hu P, Xu YQ, Liang QL, Ou JS, Luo G. Apolipoprotein A-I mimetic peptide inhibits atherosclerosis by altering plasma metabolites in hypercholesterolemia. Am J Physiol Endocrinol Metab 2012; 303:E683-94. [PMID: 22535745 DOI: 10.1152/ajpendo.00136.2012] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
An apolipoprotein A-I mimetic peptide, D-4F, has been shown to improve vasodilation and inhibit atherosclerosis in hypercholesterolemic low-density lipoprotein receptor-null (LDLr(-/-)) mice. To study the metabolic variations of D-4F ininhibiting atherosclerosis, metabonomics, a novel system biological strategy to investigate the pathogenesis, was developed. Female LDLr(-/-) mice were fed a Western diet and injected with or without D-4F intraperitoneally. Atherosclerotic lesion formation was measured, whereas plasma metabolic profiling was obtained on the basis of ultra-high-performance liquid chromatography in tandem with time-of-flight mass spectrometry operating in both positive and negative ion modes. Data were processed by multivariate statistical analysis to graphically demonstrate metabolic changes. The partial least-squares discriminate analysis model was validated with cross-validation and permutation tests to ensure the model's reliability. D-4F significantly inhibited the formation of atherosclerosis in a time-dependent manner. The metabolic profiling was altered dramatically in hypercholesterolemic LDLr(-/-) mice, and a significant metabolic profiling change in response to D-4F treatment was observed in both positive and negative ion modes. Thirty-six significantly changed metabolites were identified as potential biomarkers. A series of phospholipid metabolites, including lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE), phosphatidylcholine (PC), phatidylethanolamine (PE), sphingomyelin (SM), and diacylglycerol (DG), particularly the long-chain LysoPC, was elevated dramatically in hypercholesterolemic LDLr(-/-) mice but reduced by D-4F in a time-dependent manner. Quantitative analysis of LysoPC, LysoPE, PC, and DG using HPLC was chosen to validate the variation of these potential biomarkers, and the results were consistent with the metabonomics findings. Our findings demonstrated that D-4F may inhibit atherosclerosis by regulating phospholipid metabolites specifically by decreasing plasma long-chain LysoPC.
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MESH Headings
- Animals
- Aorta/drug effects
- Aorta/pathology
- Apolipoprotein A-I/administration & dosage
- Apolipoprotein A-I/therapeutic use
- Atherosclerosis/etiology
- Atherosclerosis/prevention & control
- Biomarkers/blood
- Biomarkers/chemistry
- Chromatography, High Pressure Liquid
- Diet, Atherogenic/adverse effects
- Female
- Hypercholesterolemia/blood
- Hypercholesterolemia/drug therapy
- Hypercholesterolemia/pathology
- Hypercholesterolemia/physiopathology
- Hypolipidemic Agents/administration & dosage
- Hypolipidemic Agents/therapeutic use
- Injections, Intraperitoneal
- Lipids/blood
- Lipids/chemistry
- Lysophosphatidylcholines/blood
- Lysophosphatidylcholines/chemistry
- Mice
- Mice, Inbred C57BL
- Mice, Knockout
- Plaque, Atherosclerotic/etiology
- Plaque, Atherosclerotic/prevention & control
- Receptors, LDL/genetics
- Receptors, LDL/metabolism
- Spectrometry, Mass, Electrospray Ionization
- Vasodilator Agents/administration & dosage
- Vasodilator Agents/therapeutic use
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Affiliation(s)
- Zhi-Jun Ou
- Division of Hypertension and Vascular Diseases, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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15
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Bodi V, Sanchis J, Morales JM, Marrachelli VG, Nunez J, Forteza MJ, Chaustre F, Gomez C, Mainar L, Minana G, Rumiz E, Husser O, Noguera I, Diaz A, Moratal D, Carratala A, Bosch X, Llacer A, Chorro FJ, Viña JR, Monleon D. Metabolomic profile of human myocardial ischemia by nuclear magnetic resonance spectroscopy of peripheral blood serum: a translational study based on transient coronary occlusion models. J Am Coll Cardiol 2012; 59:1629-41. [PMID: 22538333 DOI: 10.1016/j.jacc.2011.09.083] [Citation(s) in RCA: 73] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2011] [Accepted: 09/25/2011] [Indexed: 12/20/2022]
Abstract
OBJECTIVES The aim of this study was to investigate the metabolomic profile of acute myocardial ischemia (MIS) using nuclear magnetic resonance spectroscopy of peripheral blood serum of swine and patients undergoing angioplasty balloon-induced transient coronary occlusion. BACKGROUND Biochemical detection of MIS is a major challenge. The validation of novel biosignatures is of utmost importance. METHODS High-resolution nuclear magnetic resonance spectroscopy was used to profile 32 blood serum metabolites obtained (before and after controlled ischemia) from swine (n = 9) and patients (n = 20) undergoing transitory MIS in the setting of planned coronary angioplasty. Additionally, blood serum of control patients (n = 10) was sequentially profiled. Preliminary clinical validation of the developed metabolomic biosignature was undertaken in patients with spontaneous acute chest pain (n = 30). RESULTS Striking differences were detected in the blood profiles of swine and patients immediately after MIS. MIS induced early increases (10 min) of circulating glucose, lactate, glutamine, glycine, glycerol, phenylalanine, tyrosine, and phosphoethanolamine; decreases in choline-containing compounds and triacylglycerols; and a change in the pattern of total, esterified, and nonesterified fatty acids. Creatine increased 2 h after ischemia. Using multivariate analyses, a biosignature was developed that accurately detected patients with MIS both in the setting of angioplasty-related MIS (area under the curve 0.94) and in patients with acute chest pain (negative predictive value 95%). CONCLUSIONS This study reports, to the authors' knowledge, the first metabolic biosignature of acute MIS developed under highly controlled coronary flow restriction. Metabolic profiling of blood plasma appears to be a promising approach for the early detection of MIS in patients.
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Affiliation(s)
- Vicente Bodi
- Cardiology Department, Hospital Clinico Universitario-INCLIVA, Universidad de Valencia, Valencia, Spain.
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16
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Abstract
The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment.
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Affiliation(s)
- Stephen M Rappaport
- Center for Exposure Biology, School of Public Health, University of California, Berkeley, CA 94720-7356, USA.
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17
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Mercuro G, Bassareo PP, Deidda M, Cadeddu C, Barberini L, Atzori L. Metabolomics: a new era in cardiology? J Cardiovasc Med (Hagerstown) 2012; 12:800-5. [PMID: 21934525 DOI: 10.2459/jcm.0b013e32834a658f] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end-products of cellular processes. Metabolomics is the systematic study of small-molecule metabolite profiles that specific cellular processes leave behind. RNA messenger gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell. Metabolic profiling, in turn, amplifies changes both in the proteome and the genome, and represents a more accurate approximation to the phenotype of an organism in health and disease. In this article, we have provided a description of metabolomics, in the presence of other, more familiar 'omics' disciplines, such as genomics and proteomics. In addition, we have reviewed the current rationale for metabolomics in cardiology, its basic methodology and the data actually available in human studies in this discipline. The discussed topics highlight the importance of being able to use the metabolomics information in order to understand disease mechanisms from a systems biology perspective as a noninvasive approach to diagnose, grade and treat cardiovascular diseases.
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Affiliation(s)
- Giuseppe Mercuro
- Department of Cardiovascular and Neurological Sciences, University of Cagliari, Monserrato, Italy.
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18
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Tan G, Lou Z, Liao W, Dong X, Zhu Z, Li W, Chai Y. Hydrophilic interaction and reversed-phase ultraperformance liquid chromatographyTOF-MS for serum metabonomic analysis of myocardial infarction in rats and its applications. ACTA ACUST UNITED AC 2012; 8:548-56. [DOI: 10.1039/c1mb05324h] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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19
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Integration of metabolomics in heart disease and diabetes research: current achievements and future outlook. Bioanalysis 2011; 3:2205-22. [DOI: 10.4155/bio.11.223] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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20
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Metabolomics of oxidative stress in recent studies of endogenous and exogenously administered intermediate metabolites. Int J Mol Sci 2011; 12:6469-501. [PMID: 22072900 PMCID: PMC3210991 DOI: 10.3390/ijms12106469] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2011] [Revised: 09/13/2011] [Accepted: 09/21/2011] [Indexed: 11/19/2022] Open
Abstract
Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS) that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case) greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites—pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate—whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately developing “omics”-based, diagnostic tests to help influence therapies.
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21
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Zhu P, Bowden P, Zhang D, Marshall JG. Mass spectrometry of peptides and proteins from human blood. MASS SPECTROMETRY REVIEWS 2011; 30:685-732. [PMID: 24737629 DOI: 10.1002/mas.20291] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2008] [Revised: 12/09/2009] [Accepted: 01/19/2010] [Indexed: 06/03/2023]
Abstract
It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.
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Affiliation(s)
- Peihong Zhu
- Department of Chemistry and Biology, Ryerson University, 350 Victoria Street, Toronto, Ontario, Canada M5B 2K3
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22
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Roux A, Lison D, Junot C, Heilier JF. Applications of liquid chromatography coupled to mass spectrometry-based metabolomics in clinical chemistry and toxicology: A review. Clin Biochem 2011; 44:119-35. [DOI: 10.1016/j.clinbiochem.2010.08.016] [Citation(s) in RCA: 168] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2010] [Revised: 08/09/2010] [Accepted: 08/10/2010] [Indexed: 01/01/2023]
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23
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Metabolomics: moving to the clinic. J Neuroimmune Pharmacol 2009; 5:4-17. [PMID: 19399626 DOI: 10.1007/s11481-009-9156-4] [Citation(s) in RCA: 111] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2009] [Accepted: 04/06/2009] [Indexed: 12/12/2022]
Abstract
Assessment of a biological system by means of global and non-targeted metabolite profiling--metabolomics or metabonomics--provides the investigator with molecular information that is close to the phenotype in question in the sense that metabolites are an ultimate product of gene, mRNA, and protein activity. Over the last few years, there has been a rapidly growing number of metabolomics applications aimed at finding biomarkers which could assist diagnosis, provide therapy guidance, and evaluate response to therapy for particular diseases. Also, within the fields of drug discovery, drug toxicology, and personalized pharmacology, metabolomics is emerging as a powerful tool. This review seeks to update the reader on analytical strategies, biomarker findings, and implications of metabolomics for the clinic. Particular attention is paid to recent biomarkers found related to neurological, cardiovascular, and cancer diseases. Moreover, the impact of metabolomics in the drug discovery and development process is examined.
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