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Ma S, Xie X, Deng Z, Wang W, Xiang D, Yao L, Kang L, Xu S, Wang H, Wang G, Yang J, Liu Z. A Machine Learning Analysis of Big Metabolomics Data for Classifying Depression: Model Development and Validation. Biol Psychiatry 2024; 96:44-56. [PMID: 38142718 DOI: 10.1016/j.biopsych.2023.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 12/06/2023] [Accepted: 12/13/2023] [Indexed: 12/26/2023]
Abstract
BACKGROUND Many metabolomics studies of depression have been performed, but these have been limited by their scale. A comprehensive in silico analysis of global metabolite levels in large populations could provide robust insights into the pathological mechanisms underlying depression and candidate clinical biomarkers. METHODS Depression-associated metabolomics was studied in 2 datasets from the UK Biobank database: participants with lifetime depression (N = 123,459) and participants with current depression (N = 94,921). The Whitehall II cohort (N = 4744) was used for external validation. CatBoost machine learning was used for modeling, and Shapley additive explanations were used to interpret the model. Fivefold cross-validation was used to validate model performance, training the model on 3 of the 5 sets with the remaining 2 sets for validation and testing, respectively. Diagnostic performance was assessed using the area under the receiver operating characteristic curve. RESULTS In the lifetime depression and current depression datasets and sex-specific analyses, 24 significantly associated metabolic biomarkers were identified, 12 of which overlapped in the 2 datasets. The addition of metabolic features slightly improved the performance of a diagnostic model using traditional (nonmetabolomics) risk factors alone (lifetime depression: area under the curve 0.655 vs. 0.658 with metabolomics; current depression: area under the curve 0.711 vs. 0.716 with metabolomics). CONCLUSIONS The machine learning model identified 24 metabolic biomarkers associated with depression. If validated, metabolic biomarkers may have future clinical applications as supplementary information to guide early and population-based depression detection.
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Affiliation(s)
- Simeng Ma
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xinhui Xie
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zipeng Deng
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Wei Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Dan Xiang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lihua Yao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lijun Kang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Shuxian Xu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jun Yang
- School of Information Engineering, Wuhan University of Technology, Wuhan, China.
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China; Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
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Mastitis: What It Is, Current Diagnostics, and the Potential of Metabolomics to Identify New Predictive Biomarkers. DAIRY 2022. [DOI: 10.3390/dairy3040050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
Periparturient diseases continue to be the greatest challenge to both farmers and dairy cows. They are associated with a decrease in productivity, lower profitability, and a negative impact on cows’ health as well as public health. This review article discusses the pathophysiology and diagnostic opportunities of mastitis, the most common disease of dairy cows. To better understand the disease, we dive deep into the causative agents, traditional paradigms, and the use of new technologies for diagnosis, treatment, and prevention of mastitis. This paper takes a systems biology approach by highlighting the relationship of mastitis with other diseases and introduces the use of omics sciences, specifically metabolomics and its analytical techniques. Concluding, this review is backed up by multiple studies that show how earlier identification of mastitis through predictive biomarkers can benefit the dairy industry and improve the overall animal health.
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Bioactive Compounds from Marine Sponges and Algae: Effects on Cancer Cell Metabolome and Chemical Structures. Int J Mol Sci 2022; 23:ijms231810680. [PMID: 36142592 PMCID: PMC9502410 DOI: 10.3390/ijms231810680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 09/04/2022] [Accepted: 09/08/2022] [Indexed: 11/17/2022] Open
Abstract
Metabolomics represent the set of small organic molecules generally called metabolites, which are located within cells, tissues or organisms. This new “omic” technology, together with other similar technologies (genomics, transcriptomics and proteomics) is becoming a widely used tool in cancer research, aiming at the understanding of global biology systems in their physiologic or altered conditions. Cancer is among the most alarming human diseases and it causes a considerable number of deaths each year. Cancer research is one of the most important fields in life sciences. In fact, several scientific advances have been made in recent years, aiming to illuminate the metabolism of cancer cells, which is different from that of healthy cells, as suggested by Otto Warburg in the 1950s. Studies on sponges and algae revealed that these organisms are the main sources of the marine bioactive compounds involved in drug discovery for cancer treatment and prevention. In this review, we analyzed these two promising groups of marine organisms to focus on new metabolomics approaches for the study of metabolic changes in cancer cell lines treated with chemical extracts from sponges and algae, and for the classification of the chemical structures of bioactive compounds that may potentially prove useful for specific biotechnological applications.
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4
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Singh A, Prakash V, Gupta N, Kumar A, Kant R, Kumar D. Serum Metabolic Disturbances in Lung Cancer Investigated through an Elaborative NMR-Based Serum Metabolomics Approach. ACS OMEGA 2022; 7:5510-5520. [PMID: 35187366 PMCID: PMC8851899 DOI: 10.1021/acsomega.1c06941] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 01/18/2022] [Indexed: 06/01/2023]
Abstract
Detection of metabolic disturbances in lung cancer (LC) has the potential to aid early diagnosis/prognosis and hence improve disease management strategies through reliable grading, staging, and determination of neoadjuvant status in LC. However, a majority of previous metabolomics studies compare the normalized spectral features which not only provide ambiguous information but further limit the clinical translation of this information. Various such issues can be resolved by performing the concentration profiling of various metabolites with respect to formate as an internal reference using commercial software Chenomx. Continuing our efforts in this direction, the serum metabolic profiles were measured on 39 LC patients and 42 normal controls (NCs, comparable in age/sex) using high-field 800 MHz NMR spectroscopy and compared using multivariate statistical analysis tools to identify metabolic disturbances and metabolites of diagnostic potential. Partial least-squares discriminant analysis (PLS-DA) model revealed a distinct separation between LC and NC groups and resulted in excellent discriminatory ability with the area under the receiver-operating characteristic (AUROC) = 0.97 [95% CI = 0.89-1.00]. The metabolic features contributing to the differentiation of LC from NC samples were identified first using variable importance in projection (VIP) score analysis and then checked for their statistical significance (with p-value < 0.05) and diagnostic potential using the ROC curve analysis. The analysis revealed relevant metabolic disturbances associated with LC. Among various circulatory metabolites, six metabolites, including histidine, glutamine, glycine, threonine, alanine, and valine, were found to be of apposite diagnostic potential for clinical implications. These metabolic alterations indicated altered glucose metabolism, aberrant fatty acid synthesis, and augmented utilization of various amino acids including active glutaminolysis in LC.
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Affiliation(s)
- Anjana Singh
- All
India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand 249201, India
- Pulmonary
& Critical Care Medicine, King George’s
Medical University, Lucknow, Uttar Pradesh 226003, India
| | - Ved Prakash
- Pulmonary
& Critical Care Medicine, King George’s
Medical University, Lucknow, Uttar Pradesh 226003, India
| | - Nikhil Gupta
- Centre
of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh 226014, India
- Department
of Chemistry, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India
| | - Ashish Kumar
- Department
of Chemistry, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India
| | - Ravi Kant
- All
India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand 249201, India
| | - Dinesh Kumar
- Centre
of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh 226014, India
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Chumachenko MS, Waseem TV, Fedorovich SV. Metabolomics and metabolites in ischemic stroke. Rev Neurosci 2021; 33:181-205. [PMID: 34213842 DOI: 10.1515/revneuro-2021-0048] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 06/09/2021] [Indexed: 12/27/2022]
Abstract
Stroke is a major reason for disability and the second highest cause of death in the world. When a patient is admitted to a hospital, it is necessary to identify the type of stroke, and the likelihood for development of a recurrent stroke, vascular dementia, and depression. These factors could be determined using different biomarkers. Metabolomics is a very promising strategy for identification of biomarkers. The advantage of metabolomics, in contrast to other analytical techniques, resides in providing low molecular weight metabolite profiles, rather than individual molecule profiles. Technically, this approach is based on mass spectrometry and nuclear magnetic resonance. Furthermore, variations in metabolite concentrations during brain ischemia could alter the principal neuronal functions. Different markers associated with ischemic stroke in the brain have been identified including those contributing to risk, acute onset, and severity of this pathology. In the brain, experimental studies using the ischemia/reperfusion model (IRI) have shown an impaired energy and amino acid metabolism and confirmed their principal roles. Literature data provide a good basis for identifying markers of ischemic stroke and hemorrhagic stroke and understanding metabolic mechanisms of these diseases. This opens an avenue for the successful use of identified markers along with metabolomics technologies to develop fast and reliable diagnostic tools for ischemic and hemorrhagic stroke.
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Affiliation(s)
- Maria S Chumachenko
- Department of Biochemistry, Faculty of Biology, Belarusian State University, Kurchatova St., 10, Minsk220030, Belarus
| | | | - Sergei V Fedorovich
- Department of Biochemistry, Faculty of Biology, Belarusian State University, Kurchatova St., 10, Minsk220030, Belarus
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Kumar U, Kumar A, Singh S, Arya P, Singh SK, Chaurasia RN, Singh A, Kumar D. An elaborative NMR based plasma metabolomics study revealed metabolic derangements in patients with mild cognitive impairment: a study on north Indian population. Metab Brain Dis 2021; 36:957-968. [PMID: 33651272 DOI: 10.1007/s11011-021-00700-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 02/17/2021] [Indexed: 12/18/2022]
Abstract
Mild cognitive impairment (MCI) is transition phase between cognitive decline and dementia. The current study aims to investigate altered metabolic pattern in plasma of MCI for potential biomarkers. MCI (N = 50) and healthy controls (HC, N = 50) age group 55-75 years were screened based on Mini Mental State Examination Test (MMSE) and diffusion tensor imaging (DTI imaging). The MMSE score of MCI was significantly lower (25.74 ± 1.83) compared to healthy control subjects (29 ± 1). The MCI patients exhibit significant changes in white matter integrity in the right frontal lobe, right temporal lobe, left frontal lobe, forcep major, fornix, corpus callosum. Further, the plasma samples of twenty seven MCI patients (N = 27) and twenty HC subjects (N = 20; having no significant differences in any demographics) were analyzed using 1H NMR based metabolomics approach. Consistent with many previous reports, the levels of several plasma metabolites were found to be elevated in MCI patients compared to healthy controls. Further univariate and multivariate ROC curve analyses provided three plasma metabolites as a diagnostic panel of biomarker for MCI; which are lysine, glycine, and glutamine. Overall, the results of this study will help to improve the diagnostic and prognostic strategies of MCI in addition to improving our understanding about disease pathogenesis. We believe that the over-nutritional metabolic phenotype of MCI needs to be targeted for developing future dietary interventions so that the progression of MCI can be limited. Metabolic derangements associated with Mild Cognitive Impairment.
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Affiliation(s)
- Umesh Kumar
- Centre of Biomedical Research (CBMR), SGPGIMS Campus, Raibareli Road, Lucknow, Uttar Pradesh, 226014, India
| | - Abhai Kumar
- Department of Neurology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, India.
| | - Smita Singh
- Department of Geriatric Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, India
| | - Payal Arya
- Centre of Biomedical Research (CBMR), SGPGIMS Campus, Raibareli Road, Lucknow, Uttar Pradesh, 226014, India
| | - Sandeep Kumar Singh
- Centre of Biomedical Research (CBMR), SGPGIMS Campus, Raibareli Road, Lucknow, Uttar Pradesh, 226014, India
- Indian Scientific Education and Technology Foundation, Lucknow, 226002, India
| | - Rameshwar Nath Chaurasia
- Department of Neurology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, India
| | - Anup Singh
- Department of Geriatric Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, India
| | - Dinesh Kumar
- Centre of Biomedical Research (CBMR), SGPGIMS Campus, Raibareli Road, Lucknow, Uttar Pradesh, 226014, India.
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Siddiqui MA, Pandey S, Azim A, Sinha N, Siddiqui MH. Metabolomics: An emerging potential approach to decipher critical illnesses. Biophys Chem 2020; 267:106462. [PMID: 32911125 PMCID: PMC9986419 DOI: 10.1016/j.bpc.2020.106462] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/18/2020] [Accepted: 08/23/2020] [Indexed: 12/15/2022]
Abstract
Critical illnesses contribute to the maximum morbidity and mortality of hospitalized patients. Acute respiratory distress syndrome (ARDS) and sepsis/septic shock are the two most common acute illnesses associated with intensive care unit (ICU) admission. Once triggered, both have an identical underlying mechanism, portrayed by inflammation and endothelial dysfunction. The diagnosis of ARDS is based on clinical findings, laboratory tests, and radiological imaging. Blood cultures remain the gold standard for the diagnosis of sepsis, with the limitation of time delay and low positive yield. A combination of biomarkers has been proposed to diagnose and prognosticate these acute disorders with strengths and limitations, but still, the gold standard has been elusive to clinicians. In this review article, we illustrate the potential of metabolomics to unravel biomarkers that can be clinically utilized as a rapid prognostic and diagnostic tool associated with specific patient populations (ARDS and sepsis/septic shock) based on the available scientific data.
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Affiliation(s)
- Mohd Adnan Siddiqui
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow 226014, India; Department of Bioengineering, Integral University, Lucknow 226026, India
| | - Swarnima Pandey
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow 226014, India; Department of Zoology, Banaras Hindu University, Banaras 221005, India
| | - Afzal Azim
- Sanjay Gandhi Postgraduate Institute of Medical Sciences, Raebareli Road, Lucknow 226014, India.
| | - Neeraj Sinha
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow 226014, India.
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8
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Metabolic Profile of Patients with Severe Endometriosis: a Prospective Experimental Study. Reprod Sci 2020; 28:728-735. [PMID: 33174185 PMCID: PMC7862197 DOI: 10.1007/s43032-020-00370-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 10/21/2020] [Indexed: 12/12/2022]
Abstract
Endometriosis is a common disease affecting women in reproductive age. There are several hypotheses on the pathogenesis of this disease. Often, its lesions and symptoms overlap with those of many other medical and surgical conditions, causing a delay in diagnosis. Metabolomics represents a useful diagnostic tool for the study of metabolic changes during a different physiological or pathological status. We used 1H-NMR to explore metabolic alteration in a cohort of patients with endometriosis in order to contribute to a better understanding of the pathophysiology of the disease and to suggest new useful biomarkers. Thirty-seven patients were recruited for the metabolomic analysis: 22 patients affected by symptomatic endometriosis and 15 not affected by it. Their serum samples were collected and analyzed with 1H-NMR. Multivariate statistical analysis was conducted, followed by univariate and pathway analyses. Partial Least Square Discriminant Analysis (PLS-DA) was performed to determine the presence of any differences between the non-endometriosis and endometriosis samples (R2X = 0.596, R2Y = 0.713, Q2 = 0.635, and p < 0.0001). β-hydroxybutyric acid and glutamine were significantly increased, whereas tryptophan was significantly decreased in the endometriosis patients. ROC curves were built to test the diagnostic power of the metabolites (β-hydroxybutyric acid: AUC = 0.85 CI = 0.71-0.99; glutamine: AUC = 0.83 CI = 0.68-0.98; tryptophan: AUC = 0.75 CI = 0.54-0.95; β-hydroxybutyric acid + glutamine + tryptophan AUC = 0.92 CI = 0.81-1). The metabolomic approach enabled the identification of several metabolic alterations occurring in women with endometriosis. These findings may provide new bases for a better understanding of the pathophysiological mechanisms of the disease and for the discovery of new biomarkers. Trial registration number NCT02337816.
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Cao Q, Liu H, Zhang G, Wang X, Manyande A, Du H. 1H-NMR based metabolomics reveals the nutrient differences of two kinds of freshwater fish soups before and after simulated gastrointestinal digestion. Food Funct 2020; 11:3095-3104. [PMID: 32195513 DOI: 10.1039/c9fo02661d] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Soups show diverse health functions, which could be linked to their original nutrient profiles and metabolites derived from digestion. NMR spectroscopy is a robust and rapid method that unveils or identifies the chemical composition of food or food-derived metabolites. In the current study, the 1H-NMR spectroscopy approach was applied to identify the differences in metabolic profiling of two kinds of home-cooked freshwater fish soups (crucian carp and snakehead fish) before and after in vitro gastrointestinal digestion. The nutritional profiles of these soups were studied using the 1H-NMR method for the first time. Two metabolomics methods, PCA (Principal Component Analysis) and OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis), were used to analyze the data. On the whole, levels of amino acid metabolites such as valine (Val), tyrosine, choline, taurine (Tau) and glycine were higher in the crucian carp soup, whereas higher levels of fatty acids and unsaturated fatty acids were found in the snakehead soup. Furthermore, the high content of seven metabolites valine, leucine, EPA C20:5 (PUFA eicosapentaenoic acid), acetic acid, taurine, GPCho (phosphatidylcholine) and creatine showed an upward trend after simulated gastrointestinal digestion. The results demonstrate that the 1H-NMR metabolic profile of different fish soups can shed some light on our understanding of food functional properties and dietary therapy. Furthermore, changes of metabolites in digested fish soups could reveal information about chemical compounds which play important roles in the body.
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Affiliation(s)
- Qiongju Cao
- Key Laboratory of Environment Correlative Dietology, Ministry of Education, College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, P.R. China. and National R & D Branch Center for Conventional Freshwater Fish Processing, Wuhan, 430070, Hubei, P.R. China
| | - Huili Liu
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Science, P.R. China
| | - Gaonan Zhang
- Key Laboratory of Environment Correlative Dietology, Ministry of Education, College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, P.R. China.
| | - Xiaohua Wang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Science, P.R. China and Hubei Provincial Institute for Food Supervision and Test, Wuhan, 430071, P.R. China
| | - Anne Manyande
- School of Human and Social Sciences, University of West London, London, UK
| | - Hongying Du
- Key Laboratory of Environment Correlative Dietology, Ministry of Education, College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, P.R. China. and National R & D Branch Center for Conventional Freshwater Fish Processing, Wuhan, 430070, Hubei, P.R. China
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10
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Korobkova EO, Kozhevnikova MV, Ilgisonis IS, Shakaryants GA, Appolonova SA, Kukharenko AV, Larcova EV, Maltseva AA, Khabarova NV, Belenkov YN. [Metabolomic profiling in patients with metabolic syndrome]. KARDIOLOGIIA 2020; 60:37-43. [PMID: 32375614 DOI: 10.18087/cardio.2020.3.n903] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 11/28/2019] [Indexed: 06/11/2023]
Abstract
OBJECTIVE To identify biomarkers, which are most specific for patients with metabolic syndrome (MS) using metabolomic profiling. MATERIALS AND METHODS Metabolomic profiling of patients with MS and comparison of their profile with the profile of volunteers was performed using high-performance liquid chromatography-mass-spectrometry. RESULTS The metabolomic profile of MS patients differed in several amino acids, including choline, cysteine, and serine and in the acylcarnitine group (р<0.05 for all comparisons). CONCLUSION The metabolites most specific for MS patients were identified. Increased concentrations of a combination of amino acids and carnitines can be considered as possible additional risk factors for cardiovascular diseases.
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Affiliation(s)
- E O Korobkova
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - M V Kozhevnikova
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - I S Ilgisonis
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - G A Shakaryants
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - S A Appolonova
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - A V Kukharenko
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - E V Larcova
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - A A Maltseva
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - N V Khabarova
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
| | - Yu N Belenkov
- Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
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11
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Viswan A, Singh C, Kayastha AM, Azim A, Sinha N. An NMR based panorama of the heterogeneous biology of acute respiratory distress syndrome (ARDS) from the standpoint of metabolic biomarkers. NMR IN BIOMEDICINE 2020; 33:e4192. [PMID: 31733128 DOI: 10.1002/nbm.4192] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 08/16/2019] [Accepted: 09/05/2019] [Indexed: 06/10/2023]
Abstract
Acute respiratory distress syndrome (ARDS), manifested by intricate etiology and pathophysiology, demands careful clinical surveillance due to its high mortality and imminent life support measures. NMR based metabolomics provides an approach for ARDS which culminates from a wide spectrum of illness thereby confounding early manifestation and prognosis predictors. 1 H NMR with its manifold applications in critical disease settings can unravel the biomarker of ARDS thus holding potent implications by providing surrogate endpoints of clinical utility. NMR metabolomics which is the current apogee platform of omics trilogy is contributing towards the possible panacea of ARDS by subsequent validation of biomarker credential on larger datasets. In the present review, the physiological derangements that jeopardize the whole metabolic functioning in ARDS are exploited and the biomarkers involved in progression are addressed and substantiated. The following sections of the review also outline the clinical spectrum of ARDS from the standpoint of NMR based metabolomics which is an emerging element of systems biology. ARDS is the main premise of intensivists textbook, which has been thoroughly reviewed along with its incidence, progressive stages of severity, new proposed diagnostic definition, and the preventive measures and the current pitfalls of clinical management. The advent of new therapies, the need for biomarkers, the methodology and the contemporary promising approaches needed to improve survival and address heterogeneity have also been evaluated. The review has been stepwise illustrated with potent biometrics employed to selectively pool out differential metabolites as diagnostic markers and outcome predictors. The following sections have been drafted with an objective to better understand ARDS mechanisms with predictive and precise biomarkers detected so far on the basis of underlying physiological parameters having close proximity to diseased phenotype. The aim of this review is to stimulate interest in conducting more studies to help resolve the complex heterogeneity of ARDS with biomarkers of clinical utility and relevance.
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Affiliation(s)
- Akhila Viswan
- Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences (SGPGIMS) - Campus, Lucknow, Uttar Pradesh, India
- Faculty of Engineering and Technology, Dr. A. P. J Abdul Kalam Technical University, Lucknow, India
| | - Chandan Singh
- Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences (SGPGIMS) - Campus, Lucknow, Uttar Pradesh, India
- School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Arvind M Kayastha
- School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Afzal Azim
- Critical Care Medicine, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
| | - Neeraj Sinha
- Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences (SGPGIMS) - Campus, Lucknow, Uttar Pradesh, India
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12
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Gholizadeh N, Pundavela J, Nagarajan R, Dona A, Quadrelli S, Biswas T, Greer PB, Ramadan S. Nuclear magnetic resonance spectroscopy of human body fluids and in vivo magnetic resonance spectroscopy: Potential role in the diagnosis and management of prostate cancer. Urol Oncol 2020; 38:150-173. [PMID: 31937423 DOI: 10.1016/j.urolonc.2019.10.019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 09/22/2019] [Accepted: 10/31/2019] [Indexed: 01/17/2023]
Abstract
Prostate cancer is the most common solid organ cancer in men, and the second most common cause of male cancer-related mortality. It has few effective therapies, and is difficult to diagnose accurately. Prostate-specific antigen (PSA), which is currently the most effective diagnostic tool available, cannot reliably discriminate between different pathologies, and in fact only around 30% of patients found to have elevated levels of PSA are subsequently confirmed to actually have prostate cancer. As such, there is a desperate need for more reliable diagnostic tools that will allow the early detection of prostate cancer so that the appropriate interventions can be applied. Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopy (MRS) are 2 high throughput, noninvasive analytical procedures that have the potential to enable differentiation of prostate cancer from other pathologies using metabolomics, by focusing specifically on certain metabolites which are associated with the development of prostate cancer cells and its progression. The value that this type of approach has for the early detection, diagnosis, prognosis, and personalized treatment of prostate cancer is becoming increasingly apparent. Recent years have seen many promising developments in the fields of NMR spectroscopy and MRS, with improvements having been made to hardware as well as to techniques associated with the acquisition, processing, and analysis of related data. This review focuses firstly on proton NMR spectroscopy of blood serum, urine, and expressed prostatic secretions in vitro, and then on 1- and 2-dimensional proton MRS of the prostate in vivo. Major advances in these fields and methodological principles of data collection, acquisition, processing, and analysis are described along with some discussion of related challenges, before prospects that proton MRS has for future improvements to the clinical management of prostate cancer are considered.
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Affiliation(s)
- Neda Gholizadeh
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW, Australia
| | - Jay Pundavela
- Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Rajakumar Nagarajan
- Human Magnetic Resonance Center, Institute for Applied Life Sciences, University of Massachusetts Amherst, MA, USA
| | - Anthony Dona
- Kolling Institute of Medical Research, Royal North Shore Hospital, University of Sydney, St Leonards, NSW, Australia
| | - Scott Quadrelli
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW, Australia; Radiology Department, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - Tapan Biswas
- Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India
| | - Peter B Greer
- School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, NSW, Australia; Radiation Oncology, Calvary Mater Newcastle, Newcastle, NSW, Australia
| | - Saadallah Ramadan
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW, Australia; Imaging Centre, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.
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13
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Hu B, Cao Y, Zhu J, Xu W, Wu W. Analysis of metabolites in chardonnay dry white wine with various inactive yeasts by 1H NMR spectroscopy combined with pattern recognition analysis. AMB Express 2019; 9:140. [PMID: 31486932 PMCID: PMC6728109 DOI: 10.1186/s13568-019-0861-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 08/23/2019] [Indexed: 04/19/2023] Open
Abstract
The study aimed to investigate the effect of five inactive yeasts on the metabolites of Chardonnay dry white wines vinified in 2016 in Shacheng Manor Wine Co. Ltd., Hebei province, China. In this research, proton nuclear magnetic resonance (NMR) spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) were applied to identify and discriminate the different wine products. The results of principle component analysis (PCA) showed that there was significant difference between the metabolites of sample wines with different inactive yeasts, among them, the content of polyols, organic acids, amino acids and choline was notably influenced. The results of partial least squares discrimination analysis (PLS-DA) confirmed that the metabolites contributed to the discrimination of the wines were 2,3-butanediol, ethyl acetate, malic acid, valine, succinic acid, lactic acid, tartaric acid, glycerol, gallic acid, choline, proline, and alanine.
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14
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Murgia F, Iuculano A, Peddes C, Santoru ML, Tronci L, Deiana M, Atzori L, Monni G. Metabolic fingerprinting of chorionic villous samples in normal pregnancy and chromosomal disorders. Prenat Diagn 2019; 39:848-858. [PMID: 30995342 DOI: 10.1002/pd.5461] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 03/28/2019] [Accepted: 04/14/2019] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Placenta-related biological samples are used in biomedical research to investigate placental development. Metabolomics represents a promising approach for studying placental metabolism in an effort to explain physiological and pathological mechanisms. The aim of this study was to investigate metabolic changes in chorionic villi during the first trimester of pregnancy in euploid and aneuploid cases. METHODS Samples from 21 women (13 euploid and eight aneuploid) were analyzed with 1 H-nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and high-performance liquid chromatography (HPLC). Multivariate statistical analysis was performed, and differences in metabolites were used to identify the altered metabolic pathways. RESULTS A regression model to test the correlation between fetal crown-rump length (CRL) and metabolic profile of chorionic villi was performed in euploid pregnancies (R2 was 0.69 for the NMR analysis and 0.94 for the GC-MS analysis). Supervised analysis was used to compare chorionic villi of euploid and aneuploid fetuses (NMR: R2 X = 0.70, R2 Y = 0.65, Q2 = 0.30, R2 X = 0.62; GC-MS: R2 Y = 0.704, Q2 = 0.444). Polyol pathways, myo-inositol, and oxidative stress seem to have a fundamental role in euploid and aneuploid pregnancies. CONCLUSION Polyol pathways may have a crucial role in energy production in early pregnancy. Excessive activation in aneuploid pregnancies may lead to increased oxidative stress. Metabolomics represents a promising approach to investigate placental metabolic changes.
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Affiliation(s)
- Federica Murgia
- Department of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, Cagliari, Italy
| | - Ambra Iuculano
- Department of Prenatal and Preimplantation Genetic Diagnosis and Fetal Therapy, Ospedale Pediatrico Microcitemico A. Cao, Cagliari, Italy
| | - Cristina Peddes
- Department of Prenatal and Preimplantation Genetic Diagnosis and Fetal Therapy, Ospedale Pediatrico Microcitemico A. Cao, Cagliari, Italy
| | - Maria Laura Santoru
- Department of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, Cagliari, Italy
| | - Laura Tronci
- Department of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, Cagliari, Italy
| | - Monica Deiana
- Department of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, Cagliari, Italy
| | - Luigi Atzori
- Department of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, Cagliari, Italy
| | - Giovanni Monni
- Department of Prenatal and Preimplantation Genetic Diagnosis and Fetal Therapy, Ospedale Pediatrico Microcitemico A. Cao, Cagliari, Italy
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15
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Emwas AH, Roy R, McKay RT, Tenori L, Saccenti E, Gowda GAN, Raftery D, Alahmari F, Jaremko L, Jaremko M, Wishart DS. NMR Spectroscopy for Metabolomics Research. Metabolites 2019; 9:E123. [PMID: 31252628 PMCID: PMC6680826 DOI: 10.3390/metabo9070123] [Citation(s) in RCA: 504] [Impact Index Per Article: 100.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2019] [Revised: 06/14/2019] [Accepted: 06/18/2019] [Indexed: 12/14/2022] Open
Abstract
Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.
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Affiliation(s)
- Abdul-Hamid Emwas
- Core Labs, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Raja Roy
- Centre of Biomedical Research, Formerly, Centre of Biomedical Magnetic Resonance, Sanjay Gandhi Post-Graduate Institute of Medical Sciences Campus, Uttar Pradesh 226014, India
| | - Ryan T McKay
- Department of Chemistry, University of Alberta, Edmonton, AB T6G 2W2, Canada
| | - Leonardo Tenori
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands
| | - G A Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, 850 Republican St., Seattle, WA 98109, USA
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, 850 Republican St., Seattle, WA 98109, USA
- Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue, Seattle, WA 98109, USA
| | - Fatimah Alahmari
- Department of NanoMedicine Research, Institute for Research and Medical Consultations (IRMC), Imam Abdulrahman bin Faisal University, Dammam 31441, Saudi Arabia
| | - Lukasz Jaremko
- Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Mariusz Jaremko
- Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - David S Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8, Canada
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16
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Park YH, Kong T, Roede JR, Jones DP, Lee K. A biplot correlation range for group-wise metabolite selection in mass spectrometry. BioData Min 2019; 12:4. [PMID: 30740145 PMCID: PMC6360680 DOI: 10.1186/s13040-019-0191-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Accepted: 01/10/2019] [Indexed: 02/08/2023] Open
Abstract
Background Analytic methods are available to acquire extensive metabolic information in a cost-effective manner for personalized medicine, yet disease risk and diagnosis mostly rely upon individual biomarkers based on statistical principles of false discovery rate and correlation. Due to functional redundancies and multiple layers of regulation in complex biologic systems, individual biomarkers, while useful, are inherently limited in disease characterization. Data reduction and discriminant analysis tools such as principal component analysis (PCA), partial least squares (PLS), or orthogonal PLS (O-PLS) provide approaches to separate the metabolic phenotypes, but do not offer a statistical basis for selection of group-wise metabolites as contributors to metabolic phenotypes. Methods We present a dimensionality-reduction based approach termed ‘biplot correlation range (BCR)’ that uses biplot correlation analysis with direct orthogonal signal correction and PLS to provide the group-wise selection of metabolic markers contributing to metabolic phenotypes. Results Using a simulated multiple-layer system that often arises in complex biologic systems, we show the feasibility and superiority of the proposed approach in comparison of existing approaches based on false discovery rate and correlation. To demonstrate the proposed method in a real-life dataset, we used LC-MS based metabolomics to determine spectrum of metabolites present in liver mitochondria from wild-type (WT) mice and thioredoxin-2 transgenic (TG) mice. We select discriminatory variables in terms of increased score in the direction of class identity using BCR. The results show that BCR provides means to identify metabolites contributing to class separation in a manner that a statistical method by false discovery rate or statistical total correlation spectroscopy can hardly find in complex data analysis for predictive health and personalized medicine. Electronic supplementary material The online version of this article (10.1186/s13040-019-0191-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Youngja H Park
- 1College of Pharmacy, Korea University, Sejong, 30019 South Korea
| | - Taewoon Kong
- 2Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA
| | - James R Roede
- 3Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Denver, CO 80045 USA
| | - Dean P Jones
- Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy and Critical Care Medicine, Atlanta, GA 30322 USA.,5Department of Medicine, Emory University, Atlanta, GA 30322 USA
| | - Kichun Lee
- 6Department of Industrial Engineering, Hanyang University, Seoul, 04763 South Korea
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17
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Arora N, Dubey D, Sharma M, Patel A, Guleria A, Pruthi PA, Kumar D, Pruthi V, Poluri KM. NMR-Based Metabolomic Approach To Elucidate the Differential Cellular Responses during Mitigation of Arsenic(III, V) in a Green Microalga. ACS OMEGA 2018; 3:11847-11856. [PMID: 30320279 PMCID: PMC6173561 DOI: 10.1021/acsomega.8b01692] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 09/11/2018] [Indexed: 05/24/2023]
Abstract
Nuclear magnetic resonance (NMR)-based metabolomic approach is a high-throughput fingerprinting technique that allows a rapid snapshot of metabolites without any prior knowledge of the organism. To demonstrate the applicability of NMR-based metabolomics in the field of microalgal-based bioremediation, novel freshwater microalga Scenedesmus sp. IITRIND2 that showed hypertolerance to As(III, V) was chosen for evaluating the metabolic perturbations during arsenic stress in both its oxidation states As(III) and As(V). Using NMR spectroscopy, we were able to identify and quantify an array of ∼45 metabolites, including amino acids, sugars, organic acids, phosphagens, osmolytes, nucleotides, etc. The NMR metabolomic experiments were complemented with various biophysical techniques to establish that the microalga tolerated the arsenic stress using a complex interplay of metabolites. The two different arsenic states distinctly influenced the microalgal cellular mechanisms due to their altered physicochemical properties. Eighteen differentially identified metabolites related to bioremediation of arsenic were then correlated to the major metabolic pathways to delineate the variable stress responses of microalga in the presence of As(III, V).
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Affiliation(s)
- Neha Arora
- Department
of Biotechnology and Centre for Transportation Systems, Indian
Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
| | - Durgesh Dubey
- Centre
of Biomedical Research, SGPGIMS, Lucknow 226014, Uttar Pradesh, India
| | - Meenakshi Sharma
- Department
of Biotechnology and Centre for Transportation Systems, Indian
Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
| | - Alok Patel
- Department
of Biotechnology and Centre for Transportation Systems, Indian
Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
| | - Anupam Guleria
- Centre
of Biomedical Research, SGPGIMS, Lucknow 226014, Uttar Pradesh, India
| | - Parul A. Pruthi
- Department
of Biotechnology and Centre for Transportation Systems, Indian
Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
| | - Dinesh Kumar
- Centre
of Biomedical Research, SGPGIMS, Lucknow 226014, Uttar Pradesh, India
| | - Vikas Pruthi
- Department
of Biotechnology and Centre for Transportation Systems, Indian
Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
| | - Krishna Mohan Poluri
- Department
of Biotechnology and Centre for Transportation Systems, Indian
Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
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18
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Abstract
Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by 1H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726–0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7–0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.
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19
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Gar C, Rottenkolber M, Prehn C, Adamski J, Seissler J, Lechner A. Serum and plasma amino acids as markers of prediabetes, insulin resistance, and incident diabetes. Crit Rev Clin Lab Sci 2017; 55:21-32. [PMID: 29239245 DOI: 10.1080/10408363.2017.1414143] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Presently, routine screening misses many cases of prediabetes and early type 2 diabetes (T2D). Therefore, better biomarkers are needed for a simple and early detection of abnormalities of glucose metabolism and prediction of future T2D. Possible candidates for this include plasma or serum amino acids because glucose and amino acid metabolism are closely connected. This review presents the available evidence of this connectivity and discusses its clinical implications. First, we examine the underlying physiological, pre-analytical, and analytical issues. Then, we summarize results of human studies that evaluate amino acid levels as markers for insulin resistance, prediabetes, and future incident T2D. Finally, we illustrate the interconnection of amino acid levels and metabolic syndrome with our own data from a deeply phenotyped human cohort. We also discuss how amino acids may contribute to the pathophysiology of T2D. We conclude that elevated branched-chain amino acids and reduced glycine are currently the most robust and consistent amino acid markers for prediabetes, insulin resistance, and future T2D. Yet, we are cautious regarding the clinical potential even of these parameters because their discriminatory power is insufficient and their levels depend not only on glycemia, but also on other components of the metabolic syndrome. The identification of more precise intermediates of amino acid metabolism or combinations with other biomarkers will, therefore, be necessary to obtain in order to develop laboratory tests that can improve T2D screening.
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Affiliation(s)
- C Gar
- a Diabetes Research Group , Medizinische Klinik und Poliklinik IV, Klinikum der Universität München , Munich , Germany.,b Clinical Cooperation Group Type 2 Diabetes , Helmholtz Zentrum München , Neuherberg , Germany.,c Deutsches Zentrum für Diabetesforschung (DZD) , Neuherberg , Germany
| | - M Rottenkolber
- a Diabetes Research Group , Medizinische Klinik und Poliklinik IV, Klinikum der Universität München , Munich , Germany.,b Clinical Cooperation Group Type 2 Diabetes , Helmholtz Zentrum München , Neuherberg , Germany.,c Deutsches Zentrum für Diabetesforschung (DZD) , Neuherberg , Germany
| | - C Prehn
- d Institute of Experimental Genetics, Genome Analysis Center , Helmholtz Zentrum München, German Research Center for Environmental Health , Neuherberg , Germany
| | - J Adamski
- c Deutsches Zentrum für Diabetesforschung (DZD) , Neuherberg , Germany.,d Institute of Experimental Genetics, Genome Analysis Center , Helmholtz Zentrum München, German Research Center for Environmental Health , Neuherberg , Germany.,e Lehrstuhl fu¨r Experimentelle Genetik , Technische Universität München , Freising , Germany
| | - J Seissler
- a Diabetes Research Group , Medizinische Klinik und Poliklinik IV, Klinikum der Universität München , Munich , Germany.,b Clinical Cooperation Group Type 2 Diabetes , Helmholtz Zentrum München , Neuherberg , Germany.,c Deutsches Zentrum für Diabetesforschung (DZD) , Neuherberg , Germany
| | - A Lechner
- a Diabetes Research Group , Medizinische Klinik und Poliklinik IV, Klinikum der Universität München , Munich , Germany.,b Clinical Cooperation Group Type 2 Diabetes , Helmholtz Zentrum München , Neuherberg , Germany.,c Deutsches Zentrum für Diabetesforschung (DZD) , Neuherberg , Germany
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20
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Moore RE, Kirwan J, Doherty MK, Whitfield PD. Biomarker Discovery in Animal Health and Disease: The Application of Post-Genomic Technologies. Biomark Insights 2017. [DOI: 10.1177/117727190700200040] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The causes of many important diseases in animals are complex and multifactorial, which present unique challenges. Biomarkers indicate the presence or extent of a biological process, which is directly linked to the clinical manifestations and outcome of a particular disease. Identifying biomarkers or biomarker profiles will be an important step towards disease characterization and management of disease in animals. The emergence of post-genomic technologies has led to the development of strategies aimed at identifying specific and sensitive biomarkers from the thousands of molecules present in a tissue or biological fluid. This review will summarize the current developments in biomarker discovery and will focus on the role of transcriptomics, proteomics and metabolomics in biomarker discovery for animal health and disease.
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Affiliation(s)
- Rowan E. Moore
- Proteomics and Functional Genomics Research Group, Faculty of Veterinary Science, University of Liverpool, Liverpool, United Kingdom
| | - Jennifer Kirwan
- Proteomics and Functional Genomics Research Group, Faculty of Veterinary Science, University of Liverpool, Liverpool, United Kingdom
| | - Mary K. Doherty
- Proteomics and Functional Genomics Research Group, Faculty of Veterinary Science, University of Liverpool, Liverpool, United Kingdom
| | - Phillip D. Whitfield
- Proteomics and Functional Genomics Research Group, Faculty of Veterinary Science, University of Liverpool, Liverpool, United Kingdom
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21
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Wu C, Chen CH, Chen HC, Liang HJ, Chen ST, Lin WY, Wu KY, Chiang SY, Lin CY. Nuclear magnetic resonance- and mass spectrometry-based metabolomics to study maleic acid toxicity from repeated dose exposure in rats. J Appl Toxicol 2017; 37:1493-1506. [PMID: 28691739 DOI: 10.1002/jat.3500] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 05/16/2017] [Accepted: 05/21/2017] [Indexed: 01/11/2023]
Abstract
Maleic acid (MA), a chemical intermediate used in many consumer and industrial products, was intentionally adulterated in a variety of starch-based foods and instigated food safety incidents in Asia. We aim to elucidate possible mechanisms of MA toxicity after repeated exposure by (1) determining the changes of metabolic profile using 1 H nuclear magnetic resonance spectroscopy and multivariate analysis, and (2) investigating the occurrence of oxidative stress using liquid chromatography tandem mass spectrometry by using Sprague-Dawley rat urine samples. Adult male rats were subjected to a 28 day subchronic study (0, 6, 20 and 60 mg kg-1 ) via oral gavage. Urine was collected twice a day on days 0, 7, 14, 21 and 28; organs underwent histopathological examination. Changes in body weight and relative kidney weights in medium- and high-dose groups were significantly different compared to controls. Morphological alterations were evident in the kidneys and liver. Metabolomic results demonstrated that MA exposure increases the urinary concentrations of 8-hydroxy-2'-deoxyguanosine, 8-nitroguanine and 8-iso-prostaglandin F2α ; levels of acetoacetate, hippurate, alanine and acetate demonstrated time- and dose-dependent variations in the treatment groups. Findings suggest that MA consumption escalates oxidative damage, membrane lipid destruction and disrupt energy metabolism. These aforementioned changes in biomarkers and endogenous metabolites elucidate and assist in characterizing the possible mechanisms by which MA induces nephro- and hepatotoxicity.
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Affiliation(s)
- Charlene Wu
- Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, No. 17, ShiuJou Rd., Taipei, 10055, Taiwan
| | - Chi-Hung Chen
- Institute of Environmental Health, College of Public Health, National Taiwan University, No. 17, ShiuJou Rd., Taipei, 10055, Taiwan
| | - Hsin-Chang Chen
- Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, No. 17, ShiuJou Rd., Taipei, 10055, Taiwan
| | - Hao-Jan Liang
- Institute of Environmental Health, College of Public Health, National Taiwan University, No. 17, ShiuJou Rd., Taipei, 10055, Taiwan
| | - Shu-Ting Chen
- National Environmental Health Research Center, National Health Research Institutes, No. 35, Keyan Rd., Zhunan, Miaoli County, 35053, Taiwan
| | - Wan-Yu Lin
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, No. 17, ShiuJou Rd., Taipei, 10055, Taiwan
| | - Kuen-Yuh Wu
- Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, No. 17, ShiuJou Rd., Taipei, 10055, Taiwan
| | - Su-Yin Chiang
- School of Chinese Medicine, China Medical University, Taichung, 404, Taiwan
| | - Ching-Yu Lin
- Institute of Environmental Health, College of Public Health, National Taiwan University, No. 17, ShiuJou Rd., Taipei, 10055, Taiwan
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22
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Investigation of discriminant metabolites in tamoxifen-resistant and choline kinase-alpha-downregulated breast cancer cells using 1H-nuclear magnetic resonance spectroscopy. PLoS One 2017. [PMID: 28644842 PMCID: PMC5482454 DOI: 10.1371/journal.pone.0179773] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Metabolites linked to changes in choline kinase-α (CK-α) expression and drug resistance, which contribute to survival and autophagy mechanisms, are attractive targets for breast cancer therapies. We previously reported that autophagy played a causative role in driving tamoxifen (TAM) resistance of breast cancer cells (BCCs) and was also promoted by CK-α knockdown, resulting in the survival of TAM-resistant BCCs. There is no comparative study yet about the metabolites resulting from BCCs with TAM-resistance and CK-α knockdown. Therefore, the aim of this study was to explore the discriminant metabolic biomarkers responsible for TAM resistance as well as CK-α expression, which might be linked with autophagy through a protective role. A total of 33 intracellular metabolites, including a range of amino acids, energy metabolism-related molecules and others from cell extracts of the parental cells (MCF-7), TAM-resistant cells (MCF-7/TAM) and CK-α knockdown cells (MCF-7/shCK-α, MCF-7/TAM/shCK-α) were analyzed by proton nuclear magnetic resonance spectroscopy (1H-NMRS). Principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) revealed the existence of differences in the intracellular metabolites to separate the 4 groups: MCF-7 cells, MCF-7/TAM cells, MCF-7-shCK-α cells, and MCF-7/TAM/shCK-α cells. The metabolites with VIP>1 contributed most to the differentiation of the cell groups, and they included fumarate, UA (unknown A), lactate, myo-inositol, glycine, phosphocholine, UE (unknown E), glutamine, formate, and AXP (AMP/ADP/ATP). Our results suggest that these altered metabolites would be promising metabolic biomarkers for a targeted therapeutic strategy in BCCs that exhibit TAM-resistance and aberrant CK-α expression, which triggers a survival and drug resistance mechanism.
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Capati A, Ijare OB, Bezabeh T. Diagnostic Applications of Nuclear Magnetic Resonance-Based Urinary Metabolomics. MAGNETIC RESONANCE INSIGHTS 2017; 10:1178623X17694346. [PMID: 28579794 PMCID: PMC5428226 DOI: 10.1177/1178623x17694346] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2016] [Accepted: 01/25/2017] [Indexed: 12/23/2022]
Abstract
Metabolomics is a rapidly growing field with potential applications in various disciplines. In particular, metabolomics has received special attention in the discovery of biomarkers and diagnostics. This is largely due to the fact that metabolomics provides critical information related to the downstream products of many cellular and metabolic processes which could provide a snapshot of the health/disease status of a particular tissue or organ. Many of these cellular products eventually find their way to urine; hence, analysis of urine via metabolomics has the potential to yield useful diagnostic and prognostic information. Although there are a number of analytical platforms that can be used for this purpose, this review article will focus on nuclear magnetic resonance-based metabolomics. Furthermore, although there have been many studies addressing different diseases and metabolic disorders, the focus of this review article will be in the following specific applications: urinary tract infection, kidney transplant rejection, diabetes, some types of cancer, and inborn errors of metabolism. A number of methodological considerations that need to be taken into account for the development of a clinically useful optimal test are discussed briefly.
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Affiliation(s)
- Ana Capati
- College of Natural and Applied Sciences, University of Guam, Mangilao, GU, USA
| | - Omkar B Ijare
- Department of Chemistry, The University of Winnipeg, Winnipeg, MB, Canada
| | - Tedros Bezabeh
- College of Natural and Applied Sciences, University of Guam, Mangilao, GU, USA.,Department of Chemistry, The University of Winnipeg, Winnipeg, MB, Canada
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Kruk J, Doskocz M, Jodłowska E, Zacharzewska A, Łakomiec J, Czaja K, Kujawski J. NMR Techniques in Metabolomic Studies: A Quick Overview on Examples of Utilization. APPLIED MAGNETIC RESONANCE 2017; 48:1-21. [PMID: 28111499 PMCID: PMC5222922 DOI: 10.1007/s00723-016-0846-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2016] [Revised: 10/10/2016] [Indexed: 05/08/2023]
Abstract
Metabolomics is a rapidly developing branch of science that concentrates on identifying biologically active molecules with potential biomarker properties. To define the best biomarkers for diseases, metabolomics uses both models (in vitro, animals) and human, as well as, various techniques such as mass spectroscopy, gas chromatography, liquid chromatography, infrared and UV-VIS spectroscopy and nuclear magnetic resonance. The last one takes advantage of the magnetic properties of certain nuclei, such as 1H, 13C, 31P, 19F, especially their ability to absorb and emit energy, what is crucial for analyzing samples. Among many spectroscopic NMR techniques not only one-dimensional (1D) techniques are known, but for many years two-dimensional (2D, for example, COSY, DOSY, JRES, HETCORE, HMQS), three-dimensional (3D, DART-MS, HRMAS, HSQC, HMBC) and solid-state NMR have been used. In this paper, authors taking apart fundamental division of nuclear magnetic resonance techniques intend to shown their wide application in metabolomic studies, especially in identifying biomarkers.
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Affiliation(s)
- Joanna Kruk
- Department of Organic Chemistry, Faculty of Pharmacy, Poznan University of Medical Sciences, Grunwaldzka 6 Str., 60-780 Poznan, Poland
| | - Marek Doskocz
- RootInnovation Sp. z o.o., Jana Matejki 11 Str., 50-333 Wrocław, Poland
| | - Elżbieta Jodłowska
- Department of Organic Chemistry, Faculty of Pharmacy, Poznan University of Medical Sciences, Grunwaldzka 6 Str., 60-780 Poznan, Poland
| | - Anna Zacharzewska
- Department of Organic Chemistry, Faculty of Pharmacy, Poznan University of Medical Sciences, Grunwaldzka 6 Str., 60-780 Poznan, Poland
| | - Joanna Łakomiec
- Department of Organic Chemistry, Faculty of Pharmacy, Poznan University of Medical Sciences, Grunwaldzka 6 Str., 60-780 Poznan, Poland
| | - Kornelia Czaja
- Department of Organic Chemistry, Faculty of Pharmacy, Poznan University of Medical Sciences, Grunwaldzka 6 Str., 60-780 Poznan, Poland
| | - Jacek Kujawski
- Department of Organic Chemistry, Faculty of Pharmacy, Poznan University of Medical Sciences, Grunwaldzka 6 Str., 60-780 Poznan, Poland
- Foundation for Development of Science and Business on Medical and Exact Sciences Area, Legnicka 65 Str., 54-206 Wrocław, Poland
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Hrydziuszko O, Perera MTPR, Laing R, Kirwan J, Silva MA, Richards DA, Murphy N, Mirza DF, Viant MR. Mass Spectrometry Based Metabolomics Comparison of Liver Grafts from Donors after Circulatory Death (DCD) and Donors after Brain Death (DBD) Used in Human Orthotopic Liver Transplantation. PLoS One 2016; 11:e0165884. [PMID: 27835640 PMCID: PMC5105997 DOI: 10.1371/journal.pone.0165884] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2015] [Accepted: 10/19/2016] [Indexed: 12/14/2022] Open
Abstract
Use of marginal liver grafts, especially those from donors after circulatory death (DCD), has been considered as a solution to organ shortage. Inferior outcomes have been attributed to donor warm ischaemic damage in these DCD organs. Here we sought to profile the metabolic mechanisms underpinning donor warm ischaemia. Non-targeted Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry metabolomics was applied to biopsies of liver grafts from donors after brain death (DBD; n = 27) and DCD (n = 10), both during static cold storage (T1) as well as post-reperfusion (T2). Furthermore 6 biopsies from DBD donors prior to the organ donation (T0) were also profiled. Considering DBD and DCD together, significant metabolic differences were discovered between T1 and T2 (688 peaks) that were primarily related to amino acid metabolism, meanwhile T0 biopsies grouped together with T2, denoting the distinctively different metabolic activity of the perfused state. Major metabolic differences were discovered between DCD and DBD during cold-phase (T1) primarily related to glucose, tryptophan and kynurenine metabolism, and in the post-reperfusion phase (T2) related to amino acid and glutathione metabolism. We propose tryptophan/kynurenine and S-adenosylmethionine as possible biomarkers for the previously established higher graft failure of DCD livers, and conclude that the associated pathways should be targeted in more exhaustive and quantitative investigations.
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Affiliation(s)
- Olga Hrydziuszko
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - M. Thamara P. R. Perera
- The Liver Unit, Queen Elizabeth Hospital Birmingham, Edgbaston, Birmingham, B15 2TH, United Kingdom
| | - Richard Laing
- The Liver Unit, Queen Elizabeth Hospital Birmingham, Edgbaston, Birmingham, B15 2TH, United Kingdom
| | - Jennifer Kirwan
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Michael A. Silva
- The Liver Unit, Queen Elizabeth Hospital Birmingham, Edgbaston, Birmingham, B15 2TH, United Kingdom
| | - Douglas A. Richards
- The Department of Pharmacology, School of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Nick Murphy
- Department of Critical Care and Anaesthesia, Queen Elizabeth Hospital Birmingham, Edgbaston, Birmingham, B15 2TH, United Kingdom
| | - Darius F. Mirza
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Mark R. Viant
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
- * E-mail:
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Guo W, Jiang C, Yang L, Li T, Liu X, Jin M, Qu K, Chen H, Jin X, Liu H, Zhu H, Wang Y. Quantitative Metabolomic Profiling of Plasma, Urine, and Liver Extracts by 1H NMR Spectroscopy Characterizes Different Stages of Atherosclerosis in Hamsters. J Proteome Res 2016; 15:3500-3510. [PMID: 27570155 DOI: 10.1021/acs.jproteome.6b00179] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Atherosclerosis (AS) is a progressive disease that contributes to cardiovascular disease and shows a complex etiology, including genetic and environmental factors. To understand systemic metabolic changes and to identify potential biomarkers correlated with the occurrence and perpetuation of diet-induced AS, we applied 1H NMR-based metabolomics to detect the time-related metabolic profiles of plasma, urine, and liver extracts from male hamsters fed a high fat and high cholesterol (HFHC) diet. Conventional biochemical assays and histopathological examinations as well as protein expression analyses were performed to provide complementary information. We found that diet treatment caused obvious aortic lesions, lipid accumulation, and inflammatory infiltration in hamsters. Downregulation of proteins related to cholesterol metabolism, including hepatic SREBP2, LDL-R, CYP7A1, SR-BI, HMGCR, LCAT, and SOAT1 was detected, which elucidated the perturbation of cholesterol homeostasis during the HFHC diet challenge. Using "targeted analysis", we quantified 40 plasma, 80 urine, and 60 liver hydrophilic extract metabolites. Multivariate analyses of the identified metabolites elucidated sophisticated metabolic disturbances in multiple matrices, including energy homeostasis, intestinal microbiota functions, inflammation, and oxidative stress coupled with the metabolisms of cholesterol, fatty acids, saccharides, choline, amino acids, and nucleotides. For the first time, our results demonstrate a time-dependent metabolic progression of multiple biological matrices in hamsters from physiological status to early AS and further to late-stage AS, demonstrating that 1H NMR-based metabolomics is a reliable tool for early diagnosis and monitoring of the process of AS.
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Affiliation(s)
- Wei Guo
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Chunying Jiang
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Liu Yang
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Tianqi Li
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Xia Liu
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Mengxia Jin
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Kai Qu
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Huili Chen
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Xiangju Jin
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Hongyue Liu
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Haibo Zhu
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
| | - Yinghong Wang
- State Key Laboratory for Bioactive Substances and Functions of Natural Medicines and ‡Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , No.1 Xiannongtan Street, Beijing 100050, P. R. China
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Kurczy ME, Forsberg EM, Thorgersen MP, Poole FL, Benton HP, Ivanisevic J, Tran ML, Wall JD, Elias DA, Adams MWW, Siuzdak G. Global Isotope Metabolomics Reveals Adaptive Strategies for Nitrogen Assimilation. ACS Chem Biol 2016; 11:1677-85. [PMID: 27045776 DOI: 10.1021/acschembio.6b00082] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Nitrogen cycling is a microbial metabolic process essential for global ecological/agricultural balance. To investigate the link between the well-established ammonium and the alternative nitrate assimilation metabolic pathways, global isotope metabolomics was employed to examine three nitrate reducing bacteria using (15)NO3 as a nitrogen source. In contrast to a control (Pseudomonas stutzeri RCH2), the results show that two of the isolates from Oak Ridge, Tennessee (Pseudomonas N2A2 and N2E2) utilize nitrate and ammonia for assimilation concurrently with differential labeling observed across multiple classes of metabolites including amino acids and nucleotides. The data reveal that the N2A2 and N2E2 strains conserve nitrogen-containing metabolites, indicating that the nitrate assimilation pathway is a conservation mechanism for the assimilation of nitrogen. Co-utilization of nitrate and ammonia is likely an adaption to manage higher levels of nitrite since the denitrification pathways utilized by the N2A2 and N2E2 strains from the Oak Ridge site are predisposed to the accumulation of the toxic nitrite. The use of global isotope metabolomics allowed for this adaptive strategy to be investigated, which would otherwise not have been possible to decipher.
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Affiliation(s)
- Michael E. Kurczy
- Scripps
Center for Metabolomics, The Scripps Research Institute, 10550 North
Torrey Pines Road, La Jolla, California 92037, United States
| | - Erica M. Forsberg
- Scripps
Center for Metabolomics, The Scripps Research Institute, 10550 North
Torrey Pines Road, La Jolla, California 92037, United States
| | - Michael P. Thorgersen
- Department
of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia 30602, United States
| | - Farris L. Poole
- Department
of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia 30602, United States
| | - H. Paul Benton
- Scripps
Center for Metabolomics, The Scripps Research Institute, 10550 North
Torrey Pines Road, La Jolla, California 92037, United States
| | - Julijana Ivanisevic
- Metabolomics
Platform, Faculty of Biology and Medicine, University of Lausanne, Rue du Bugnon 19, 1011 Lausanne, Switzerland
| | - Minerva L. Tran
- Scripps
Center for Metabolomics, The Scripps Research Institute, 10550 North
Torrey Pines Road, La Jolla, California 92037, United States
| | - Judy D. Wall
- Department
of Biochemistry, University of Missouri, Columbia, Missouri 65211, United States
| | - Dwayne A. Elias
- Biosciences
Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Michael W. W. Adams
- Department
of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia 30602, United States
| | - Gary Siuzdak
- Scripps
Center for Metabolomics, The Scripps Research Institute, 10550 North
Torrey Pines Road, La Jolla, California 92037, United States
- Departments
of Chemistry, Molecular, and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
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Rawat A, Dubey D, Guleria A, Kumar U, Keshari AK, Chaturvedi S, Prakash A, Saha S, Kumar D. 1H NMR-based serum metabolomics reveals erythromycin-induced liver toxicity in albino Wistar rats. J Pharm Bioallied Sci 2016; 8:327-334. [PMID: 28216958 PMCID: PMC5314833 DOI: 10.4103/0975-7406.199339] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Introduction: Erythromycin (ERY) is known to induce hepatic toxicity which mimics other liver diseases. Thus, ERY is often used to produce experimental models of drug-induced liver-toxicity. The serum metabolic profiles can be used to evaluate the liver-toxicity and to further improve the understanding of underlying mechanism. Objective: To establish the serum metabolic patterns of Erythromycin induced hepatotoxicity in albino wistar rats using 1H NMR based serum metabolomics. Experimental: Fourteen male rats were randomly divided into two groups (n = 7 in each group): control and ERY treated. After 28 days of intervention, the metabolic profiles of sera obtained from ERY and control groups were analyzed using high-resolution 1D 1H CPMG and diffusion-edited nuclear magnetic resonance (NMR) spectra. The histopathological and SEM examinations were employed to evaluate the liver toxicity in ERY treated group. Results: The serum metabolic profiles of control and ERY treated rats were compared using multivariate statistical analysis and the metabolic patterns specific to ERY-induced liver toxicity were established. The toxic response of ERY was characterized with: (a) increased serum levels of Glucose, glutamine, dimethylamine, malonate, choline, phosphocholine and phospholipids and (b) decreased levels of isoleucine, leucine, valine, alanine, glutamate, citrate, glycerol, lactate, threonine, circulating lipoproteins, N-acetyl glycoproteins, and poly-unsaturated lipids. These metabolic alterations were found to be associated with (a) decreased TCA cycle activity and enhanced fatty acid oxidation, (b) dysfunction of lipid and amino acid metabolism and (c) oxidative stress. Conclusion and Recommendations: Erythromycin is often used to produce experimental models of liver toxicity; therefore, the established NMR-based metabolic patterns will form the basis for future studies aiming to evaluate the efficacy of anti-hepatotoxic agents or the hepatotoxicity of new drug-formulations.
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Affiliation(s)
- Atul Rawat
- Department of Biotechnology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India; Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences Campus, Lucknow, Uttar Pradesh, India
| | - Durgesh Dubey
- Department of Biotechnology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India; Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences Campus, Lucknow, Uttar Pradesh, India
| | - Anupam Guleria
- Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences Campus, Lucknow, Uttar Pradesh, India
| | - Umesh Kumar
- Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences Campus, Lucknow, Uttar Pradesh, India
| | - Amit K Keshari
- Department of Pharmaceutical Sciences, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India
| | - Swati Chaturvedi
- Department of Pharmaceutical Sciences, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India
| | - Anand Prakash
- Department of Biotechnology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India
| | - Sudipta Saha
- Department of Pharmaceutical Sciences, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India
| | - Dinesh Kumar
- Centre of Biomedical Research, Sanjay Gandhi Post Graduate Institute of Medical Sciences Campus, Lucknow, Uttar Pradesh, India
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Gralka E, Luchinat C, Tenori L, Ernst B, Thurnheer M, Schultes B. Metabolomic fingerprint of severe obesity is dynamically affected by bariatric surgery in a procedure-dependent manner. Am J Clin Nutr 2015; 102:1313-22. [PMID: 26581381 DOI: 10.3945/ajcn.115.110536] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 09/16/2015] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Obesity is associated with multiple diseases. Bariatric surgery is the most effective therapy for severe obesity that can reduce body weight and obesity-associated morbidity. The metabolic alterations associated with obesity and respective changes after bariatric surgery are incompletely understood. OBJECTIVE We comprehensively assessed metabolic alterations associated with severe obesity and distinct bariatric procedures. DESIGN In our longitudinal observational study, we applied a (1)H-nuclear magnetic resonance-based global, untargeted metabolomics strategy on human serum samples that were collected before and repeatedly ≤1 y after distinct bariatric procedures [i.e., a sleeve gastrectomy, proximal Roux-en Y gastric bypass (RYGB), and distal RYGB]. For comparison, we also analyzed serum samples from normal-weight and less-obese subjects who were matched for 1-y postoperative body mass index (BMI) values of the surgical groups. RESULTS We identified a metabolomic fingerprint in obese subjects that was clearly discriminated from that of normal-weight subjects. Furthermore, we showed that bariatric surgery (sleeve gastrectomy and proximal and distal RYGB) dynamically affected this fingerprint in a procedure-dependent manner, thereby establishing new fingerprints that could be discriminated from those of BMI-matched and normal-weight control subjects. Metabolites that largely contributed to the metabolomic fingerprints of severe obesity were aromatic and branched-chain amino acids (elevated), metabolites related to energy metabolism (pyruvate and citrate; elevated), and metabolites suggested to be derived from gut microbiota (formate, methanol, and isopropanol; all elevated). CONCLUSION Our data indicate that bariatric surgery, irrespective of the specific kind of procedure used, reverses most of the metabolic alterations associated with obesity and suggest profound changes in gut microbiome-host interactions after the surgery. This trial was registered at clinicaltrials.gov as NCT02480322.
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Affiliation(s)
- Ewa Gralka
- FiorGen Foundation, Sesto Fiorentino, Italy; Magnetic Resonance Center and
| | - Claudio Luchinat
- Magnetic Resonance Center and Chemistry Department, University of Florence, Sesto Fiorentino, Italy; and
| | | | - Barbara Ernst
- eSwiss Medical & Surgical Center, Interdisciplinary Obesity Center, St. Gallen, Switzerland
| | - Martin Thurnheer
- eSwiss Medical & Surgical Center, Interdisciplinary Obesity Center, St. Gallen, Switzerland
| | - Bernd Schultes
- eSwiss Medical & Surgical Center, Interdisciplinary Obesity Center, St. Gallen, Switzerland
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30
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Koundal S, Gandhi S, Kaur T, Mazumder A, Khushu S. “Omics” of High Altitude Biology: A Urinary Metabolomics Biomarker Study of Rats Under Hypobaric Hypoxia. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2015; 19:757-65. [DOI: 10.1089/omi.2015.0155] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Sunil Koundal
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), Timarpur, Delhi, India
- Department of Biophysics, Panjab University, Chandigarh, India
| | - Sonia Gandhi
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), Timarpur, Delhi, India
| | - Tanzeer Kaur
- Department of Biophysics, Panjab University, Chandigarh, India
| | - Avik Mazumder
- Vertox Laboratory, Defence Research and Development Establishment, Gwalior, India
| | - Subash Khushu
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), Timarpur, Delhi, India
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Perera MTPR, Higdon R, Richards DA, Silva MA, Murphy N, Kolker E, Mirza DF. Biomarker differences between cadaveric grafts used in human orthotopic liver transplantation as identified by coulometric electrochemical array detection (CEAD) metabolomics. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2015; 18:767-77. [PMID: 25353146 DOI: 10.1089/omi.2014.0094] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Metabolomics in systems biology research unravels intracellular metabolic changes by high throughput methods, but such studies focusing on liver transplantation (LT) are limited. Microdialysate samples of liver grafts from donors after circulatory death (DCD; n=13) and brain death (DBD; n=27) during cold storage and post-reperfusion phase were analyzed through coulometric electrochemical array detection (CEAD) for identification of key metabolomics changes. Metabolite peak differences between the graft types at cold phase, post-reperfusion trends, and in failed allografts, were identified against reference chromatograms. In the cold phase, xanthine, uric acid, and kynurenine were overexpressed in DCD by 3-fold, and 3-nitrotyrosine (3-NT) and 4-hydroxy-3-methoxymandelic acid (HMMA) in DBD by 2-fold (p<0.05). In both grafts, homovanillic acid and methionine increased by 20%-30% with each 100 min increase in cold ischemia time (p<0.05). Uric acid expression was significantly different in DCD post-reperfusion. Failed allografts had overexpression of reduced glutathione and kynurenine (cold phase) and xanthine (post-reperfusion) (p<0.05). This differential expression of metabolites between graft types is a novel finding, meanwhile identification of overexpression of kynurenine in DCD grafts and in failed allografts is unique. Further studies should examine kynurenine as a potential biomarker predicting graft function, its causation, and actions on subsequent clinical outcomes.
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Affiliation(s)
- M Thamara P R Perera
- 1 The Liver Unit, Queen Elizabeth Hospital Birmingham , Edgbaston, Birmingham, United Kingdom
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32
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Theophilou G, Paraskevaidi M, Lima KMG, Kyrgiou M, Martin-Hirsch PL, Martin FL. Extracting biomarkers of commitment to cancer development: potential role of vibrational spectroscopy in systems biology. Expert Rev Mol Diagn 2015; 15:693-713. [DOI: 10.1586/14737159.2015.1028372] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Tenori L, Oakman C, Morris PG, Gralka E, Turner N, Cappadona S, Fornier M, Hudis C, Norton L, Luchinat C, Di Leo A. Serum metabolomic profiles evaluated after surgery may identify patients with oestrogen receptor negative early breast cancer at increased risk of disease recurrence. Results from a retrospective study. Mol Oncol 2014; 9:128-39. [PMID: 25151299 DOI: 10.1016/j.molonc.2014.07.012] [Citation(s) in RCA: 73] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2014] [Revised: 07/14/2014] [Accepted: 07/15/2014] [Indexed: 11/15/2022] Open
Abstract
PURPOSE Metabolomics is a global study of metabolites in biological samples. In this study we explored whether serum metabolomic spectra could distinguish between early and metastatic breast cancer patients and predict disease relapse. METHODS Serum samples were analysed from women with metastatic (n = 95) and predominantly oestrogen receptor (ER) negative early stage (n = 80) breast cancer using high resolution nuclear magnetic resonance spectroscopy. Multivariate statistics and a Random Forest classifier were used to create a prognostic model for disease relapse in early patients. RESULTS In the early breast cancer training set (n = 40), metabolomics correctly distinguished between early and metastatic disease in 83.7% of cases. A prognostic risk model predicted relapse with 90% sensitivity (95% CI 74.9-94.8%), 67% specificity (95% CI 63.0-73.4%) and 73% predictive accuracy (95% CI 70.6-74.8%). These results were reproduced in an independent early breast cancer set (n = 40), with 82% sensitivity, 72% specificity and 75% predictive accuracy. Disease relapse was associated with significantly lower levels of histidine (p = 0.0003) and higher levels of glucose (p = 0.01), and lipids (p = 0.0003), compared with patients with no relapse. CONCLUSIONS The performance of a serum metabolomic prognostic model for disease relapse in individuals with ER-negative early stage breast cancer is promising. A confirmation study is ongoing to better define the potential of metabolomics as a host and tumour-derived prognostic tool.
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Affiliation(s)
- Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy; FiorGen Foundation, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy.
| | - Catherine Oakman
- 'Sandro Pitigliani' Medical Oncology Department, Hospital of Prato, Via Suor Niccolina 20, Istituto Toscano Tumori, 59100 Prato, Italy.
| | - Patrick G Morris
- Breast Cancer Medicine Service, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
| | - Ewa Gralka
- Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy; FiorGen Foundation, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy.
| | - Natalie Turner
- 'Sandro Pitigliani' Medical Oncology Department, Hospital of Prato, Via Suor Niccolina 20, Istituto Toscano Tumori, 59100 Prato, Italy.
| | - Silvia Cappadona
- 'Sandro Pitigliani' Medical Oncology Department, Hospital of Prato, Via Suor Niccolina 20, Istituto Toscano Tumori, 59100 Prato, Italy.
| | - Monica Fornier
- Breast Cancer Medicine Service, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
| | - Cliff Hudis
- Breast Cancer Medicine Service, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
| | - Larry Norton
- Breast Cancer Medicine Service, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy; Department of Chemistry, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy.
| | - Angelo Di Leo
- 'Sandro Pitigliani' Medical Oncology Department, Hospital of Prato, Via Suor Niccolina 20, Istituto Toscano Tumori, 59100 Prato, Italy.
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Sitole L, Steffens F, Krüger TPJ, Meyer D. Mid-ATR-FTIR spectroscopic profiling of HIV/AIDS sera for novel systems diagnostics in global health. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2014; 18:513-23. [PMID: 24937213 DOI: 10.1089/omi.2013.0157] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Global health, whether in developed or developing countries, is in need of robust systems diagnostics for major diseases, such as HIV/AIDS, impacting the world populations. Fourier transform Infrared (FTIR) spectroscopy of serum is a quick and reagent-free methodology with which to analyze metabolic alterations such as those caused by disease or treatment. In this study, Attenuated Total Reflectance Fourier-Transform (ATR-FTIR) Spectroscopy was investigated as a means of distinguishing HIV-infected treatment-experienced (HIV(pos) ART(pos), n=39) and HIV-infected-treatment-naïve (HIV(pos) ART(neg), n=16) subjects from uninfected control subjects (n=30). Multivariate pattern recognition techniques, including partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), successfully distinguished sample classes, while univariate approaches identified significant differences (p<0.05) after Benjamini-Hochberg corrections. OPLS-DA discriminated between all groups with sensitivity, specificity, and accuracy of >90%. Compared to uninfected controls, HIV(pos) ART(pos) and HIV(pos) ART(neg) subjects displayed significant differences in spectral regions linked to lipids/fatty acids (3010 cm(-1)), carbohydrates (1299 cm(-1); 1498 cm(-1)), glucose (1035 cm(-1)), and proteins (1600 cm(-1); 1652 cm(-1)). These are all molecules shown by conventional biochemical analysis to be affected by HIV/ART interference. The biofluid metabolomics approach applied here successfully differentiated global metabolic profiles of HIV-infected patients and uninfected controls and detected potential biomarkers for development into indicators of host response to treatment and/or disease progression. Our findings therefore contribute to ongoing efforts for capacity-building in global health for robust omics science and systems diagnostics towards major diseases impacting population health.
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Affiliation(s)
- Lungile Sitole
- 1 Department of Biochemistry, University of Pretoria , Pretoria, South Africa
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Yadav AP, Chaturvedi S, Mishra KP, Pal S, Ganju L, Singh SB. Evidence for altered metabolic pathways during environmental stress: (1)H-NMR spectroscopy based metabolomics and clinical studies on subjects of sea-voyage and Antarctic-stay. Physiol Behav 2014; 135:81-90. [PMID: 24910139 DOI: 10.1016/j.physbeh.2014.05.045] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2013] [Revised: 04/25/2014] [Accepted: 05/30/2014] [Indexed: 12/27/2022]
Abstract
The Antarctic context is an analogue of space travel, with close similarity in ambience of extreme climate, isolation, constrained living spaces, disrupted sleep cycles, and environmental stress. The present study examined the impact of the harsh habitat of Antarctica on human physiology and its metabolic pathways, by analyzing human serum samples, using (1)H-NMR spectroscopy for identification of metabolites; and quantifying other physiological and clinical parameters for correlation between expression data and metabolite data. Sera from seven adult males (of median age 36years) who participated in this study, from the 28th Indian Expeditionary group to the Antarctica station Maitri, were collected in chronological sequence. These included: i) baseline control; ii) during ship journey; iii) at Antarctica, in the months of March, May, August and November; to enable study of temporal evolution of monitored physiological states. 29 metabolites in serum were identified from the 400MHz (1)H-NMR spectra. Out of these, 19 metabolites showed significant variations in levels, during the ship journey and the stay at Maitri, compared to the base-line levels. Further biochemical analysis also supported these results, indicating that the ship journey, and the long-term Antarctic exposure, affected kidney and liver functioning. Our metabolite data highlights for the first time the effect of environmental stress on the patho-physiology of the human system. Multivariate analysis tools were employed for this metabonomics study, using (1)H-NMR spectroscopy.
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Affiliation(s)
- Anand Prakash Yadav
- Immunomodulation Laboratory, Defence Institute of Physiology & Allied Sciences, Lucknow Road, Timarpur, Delhi 110054, India
| | - Shubhra Chaturvedi
- Cyclotron & Radiopharmaceutical Sciences Division, Institute of Nuclear Medicine & Allied Sciences, Lucknow Road, Timarpur, Delhi 110054, India
| | - Kamla Prasad Mishra
- Immunomodulation Laboratory, Defence Institute of Physiology & Allied Sciences, Lucknow Road, Timarpur, Delhi 110054, India
| | - Sunil Pal
- Cyclotron & Radiopharmaceutical Sciences Division, Institute of Nuclear Medicine & Allied Sciences, Lucknow Road, Timarpur, Delhi 110054, India
| | - Lilly Ganju
- Immunomodulation Laboratory, Defence Institute of Physiology & Allied Sciences, Lucknow Road, Timarpur, Delhi 110054, India.
| | - Shashi Bala Singh
- Immunomodulation Laboratory, Defence Institute of Physiology & Allied Sciences, Lucknow Road, Timarpur, Delhi 110054, India
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Abstract
![]()
The
pharmaceutical industry has significantly contributed to improving
human health. Drugs have been attributed to both increasing life expectancy
and decreasing health care costs. Unfortunately, there has been a
recent decline in the creativity and productivity of the pharmaceutical
industry. This is a complex issue with many contributing factors resulting
from the numerous mergers, increase in out-sourcing, and the heavy
dependency on high-throughput screening (HTS). While a simple solution
to such a complex problem is unrealistic and highly unlikely, the
inclusion of metabolomics as a routine component of the drug discovery
process may provide some solutions to these problems. Specifically,
as the binding affinity of a chemical lead is evolved during the iterative
structure-based drug design process, metabolomics can provide feedback
on the selectivity and the in vivo mechanism of action. Similarly,
metabolomics can be used to evaluate and validate HTS leads. In effect,
metabolomics can be used to eliminate compounds with potential efficacy
and side effect problems while prioritizing well-behaved leads with
druglike characteristics.
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Affiliation(s)
- Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln , 722 Hamilton Hall, Lincoln, Nebraska 68588-0304, United States
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Bowers J, Hughes E, Skill N, Maluccio M, Raftery D. Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS. J Chromatogr B Analyt Technol Biomed Life Sci 2014; 966:154-62. [PMID: 24666728 DOI: 10.1016/j.jchromb.2014.02.043] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2013] [Revised: 02/17/2014] [Accepted: 02/22/2014] [Indexed: 02/06/2023]
Abstract
Hepatocellular carcinoma (HCC) accounts for most cases of liver cancer worldwide; contraction of hepatitis C (HCV) is considered a major risk factor for liver cancer even when individuals have not developed formal cirrhosis. Global, untargeted metabolic profiling methods were applied to serum samples from patients with either HCV alone or HCC (with underlying HCV). The main objective of the study was to identify metabolite based biomarkers associated with cancer risk, with the long term goal of ultimately improving early detection and prognosis. Serum global metabolite profiles from patients with HCC (n=37) and HCV (n=21) were obtained using high performance liquid chromatography-mass spectrometry (HPLC-MS) methods. The selection of statistically significant metabolites for partial least-squares discriminant analysis (PLS-DA) model creation based on biological and statistical significance was contrasted to that of a traditional approach utilizing p-values alone. A PLS-DA model created using the former approach resulted in a model with 92% sensitivity, 95% specificity, and an AUROC of 0.93. A series of PLS-DA models iteratively utilizing three to seven metabolites that were altered significantly (p<0.05) and sufficiently (FC≤0.7 or FC≥1.3) showed good performance using p-values alone; the best of these PLS-DA models was capable of generating 73% sensitivity, 95% specificity, and an AUROC of 0.92. Metabolic profiles derived from LC-MS readily distinguish patients with HCC and HCV from those with HCV only. Differences in the metabolic profiles between high-risk individuals and HCC indicate the possibility of identifying the early development of liver cancer in at risk patients. The use of biological significance as a selection process prior to PLS-DA modeling may offer improved probabilities for translation of newly discovered biomarkers to clinical application.
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Affiliation(s)
- Jeremiah Bowers
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, United States
| | - Emma Hughes
- Mount Holyoke College, South Hadley, MA 01075, United States
| | - Nicholas Skill
- IU School of Medicine, Indianapolis, IN 46202, United States
| | - Mary Maluccio
- IU School of Medicine, Indianapolis, IN 46202, United States
| | - Daniel Raftery
- Department of Anesthesiology, University of Washington, Seattle, WA 98109, United States.
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Mullen W, Saigusa D, Abe T, Adamski J, Mischak H. Proteomics and Metabolomics as Tools to Unravel Novel Culprits and Mechanisms of Uremic Toxicity: Instrument or Hype? Semin Nephrol 2014; 34:180-90. [DOI: 10.1016/j.semnephrol.2014.02.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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Reisdorph N, Stearman R, Kechris K, Phang TL, Reisdorph R, Prenni J, Erle DJ, Coldren C, Schey K, Nesvizhskii A, Geraci M. Hands-on workshops as an effective means of learning advanced technologies including genomics, proteomics and bioinformatics. GENOMICS PROTEOMICS & BIOINFORMATICS 2013; 11:368-77. [PMID: 24316330 PMCID: PMC4049090 DOI: 10.1016/j.gpb.2013.10.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2013] [Revised: 10/02/2013] [Accepted: 10/21/2013] [Indexed: 01/08/2023]
Abstract
Genomics and proteomics have emerged as key technologies in biomedical research, resulting in a surge of interest in training by investigators keen to incorporate these technologies into their research. At least two types of training can be envisioned in order to produce meaningful results, quality publications and successful grant applications: (1) immediate short-term training workshops and (2) long-term graduate education or visiting scientist programs. We aimed to fill the former need by providing a comprehensive hands-on training course in genomics, proteomics and informatics in a coherent, experimentally-based framework. This was accomplished through a National Heart, Lung, and Blood Institute (NHLBI)-sponsored 10-day Genomics and Proteomics Hands-on Workshop held at National Jewish Health (NJH) and the University of Colorado School of Medicine (UCD). The course content included comprehensive lectures and laboratories in mass spectrometry and genomics technologies, extensive hands-on experience with instrumentation and software, video demonstrations, optional workshops, online sessions, invited keynote speakers, and local and national guest faculty. Here we describe the detailed curriculum and present the results of short- and long-term evaluations from course attendees. Our educational program consistently received positive reviews from participants and had a substantial impact on grant writing and review, manuscript submissions and publications.
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Affiliation(s)
- Nichole Reisdorph
- Department of Immunology, National Jewish Health, Denver, CO 80206, USA.
| | - Robert Stearman
- Department of Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO 80045, USA
| | - Tzu Lip Phang
- Department of Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Richard Reisdorph
- Department of Pediatrics, National Jewish Health, Denver, CO 80206, USA
| | - Jessica Prenni
- Department of Biochemistry and Molecular Biology, Proteomics and Metabolomics Facility, Colorado State University, Fort Collins, CO 80523, USA
| | - David J Erle
- Lung Biology Center, Department of Medicine, University of California, San Francisco, CA 94143, USA
| | - Christopher Coldren
- Department of Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Kevin Schey
- Department of Biochemistry and Mass Spectrometry Research Center, Vanderbilt School of Medicine, Nashville, TN 37027, USA
| | - Alexey Nesvizhskii
- Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Mark Geraci
- Department of Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
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Wang B, Goodpaster AM, Kennedy MA. Coefficient of Variation, Signal-to-Noise Ratio, and Effects of Normalization in Validation of Biomarkers from NMR-based Metabonomics Studies. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS : AN INTERNATIONAL JOURNAL SPONSORED BY THE CHEMOMETRICS SOCIETY 2013; 128:9-16. [PMID: 24678137 PMCID: PMC3963315 DOI: 10.1016/j.chemolab.2013.07.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
A primary goal of metabonomics research is biomarker discovery for human diseases based on differences in metabolic profiles between healthy and diseased patient populations. One of the most significant challenges in biomarker discovery is validation, which implicitly depends on the coefficient of variation (CV) associated with the measurement technique. This paper investigates how the CV of metabolite resonances measured by nuclear magnetic resonance spectroscopy (NMR) depends on signal-to-noise ratio (SNR) and normalization method. CVs were calculated for NMR resonance peaks in a series of NMR spectra of five synthetic urine samples collected over an eight-month period. An inverse correlation was detected between SNR and CV for all normalization methods. Small peaks with SNR<15 tended to have larger CVs (15-30%) compared to peaks with the highest SNR>150, which typically had smaller CVs (5-10%). The inverse relationship between CV and SNR roughly obeyed a log10 dependence. Quotient normalization (QN) tended to produce smaller CVs for smaller peaks, but larger CVs for the strongest peaks in the data, compared to no normalization, normalization to total intensity (NTI) or normalization to an internal standard (NIS). Consequently, quotient normalization appears optimal for validating low concentration metabolites. NTI or NIS appear superior to QN for samples that have very small variation in total signal intensity. While the inverse relationship between CV and log10(SNR) did not strictly hold for all metabolites, weaker concentration metabolites will likely require more rigorous validation as potential biomarkers since they tend to have poorer reproducibility.
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Affiliation(s)
| | | | - Michael A. Kennedy
- Contact Info: Michael A. Kennedy, Eminent Scholar and Professor, 106 Hughes Laboratory, Department of Chemistry and Biochemistry, Miami University, Oxford, OH 45056, 513-529-8267,
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Leung TF, Ko FWS, Wong GWK. Recent advances in asthma biomarker research. Ther Adv Respir Dis 2013; 7:297-308. [PMID: 23907809 DOI: 10.1177/1753465813496863] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Asthma is characterized by recurrent and reversible airflow obstruction, which is routinely monitored by history and physical examination, spirometry and home peak flow diaries. As airway inflammation is central to asthma pathogenesis, its monitoring should be part of patient management plans. Fractional exhaled nitric oxide level (FeNO) is the most extensively studied biomarker of airway inflammation, and FeNO references were higher in Chinese (Asians) than Whites. Published evidence was inconclusive as to whether FeNO is a useful management strategy for asthma. Other biomarkers include direct (histamine, methacholine) and indirect (adenosine, hypertonic saline) challenges of bronchial hyperresponsiveness (BHR), induced sputum and exhaled breath condensate (EBC). A management strategy that normalized sputum eosinophils among adult patients resulted in reductions of BHR and asthma exacerbations. However, subsequent adult and pediatric studies failed to replicate these benefits. Asthma phenotypes as defined by inflammatory cell populations in sputum were also not stable over a 12-month period. A recent meta-analysis concluded that induced sputum is not accurate enough to be applied in routine monitoring of childhood asthma. There is poor correlation between biomarkers that reflect different asthma dimensions: spirometry (airway caliber), BHR (airway reactivity) and FeNO or induced sputum (airway inflammation). Lastly, EBC is easily obtained noninvasively by cooling expired air. Many biomarkers ranging from acidity (pH), leukotrienes, aldehydes, cytokines to growth factors have been described. However, significant overlap between groups and technical difficulty in measuring low levels of inflammatory molecules are the major obstacles for EBC research. Metabolomics is an emerging analytical method for EBC biomarkers. In conclusion, both FeNO and induced sputum are useful asthma biomarkers. However, they will only form part of the clinical picture. Longitudinal studies with focused hypotheses and well-designed protocols are needed to establish the roles of these biomarkers in asthma management. The measurement of biomarkers in EBC remains a research tool.
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Affiliation(s)
- Ting F Leung
- Department of Pediatrics, The Chinese University of Hong Kong 6/F, Lui Che Woo Clinical Sciences Building, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
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Appiah-Amponsah E, Owusu-Sarfo K, Gowda GN, Ye T, Raftery D. Combining Hydrophilic Interaction Chromatography (HILIC) and Isotope Tagging for Off-Line LC-NMR Applications in Metabolite Analysis. Metabolites 2013; 3:575-591. [PMID: 24860727 PMCID: PMC3901292 DOI: 10.3390/metabo3030575] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2013] [Revised: 07/06/2013] [Accepted: 07/15/2013] [Indexed: 11/16/2022] Open
Abstract
The complementary use of liquid chromatography (LC) and nuclear magnetic resonance (NMR) has shown high utility in a variety of fields. While the significant benefit of spectral simplification can be achieved for the analysis of complex samples, other limitations remain. For example, (1)H LC-NMR suffers from pH dependent chemical shift variations, especially during urine analysis, owing to the high physiological variation of urine pH. Additionally, large solvent signals from the mobile phase in LC can obscure lower intensity signals and severely limit the number of metabolites detected. These limitations, along with sample dilution, hinder the ability to make reliable chemical shift assignments. Recently, stable isotopic labeling has been used to detect quantitatively specific classes of metabolites of interest in biofluids. Here we present a strategy that explores the combined use of two-dimensional hydrophilic interaction chromatography (HILIC) and isotope tagged NMR for the unambiguous identification of carboxyl containing metabolites present in human urine. The ability to separate structurally related compounds chromatographically, in off-line mode, followed by detection using (1)H-(15)N 2D HSQC (two-dimensional heteronuclear single quantum coherence) spectroscopy, resulted in the assignment of low concentration carboxyl-containing metabolites from a library of isotope labeled compounds. The quantitative nature of this strategy is also demonstrated.
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Affiliation(s)
- Emmanuel Appiah-Amponsah
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA; E-Mails: (E.A.-A.); (K.O.-S.); (G.A.N.G.); (T.Y.)
| | - Kwadwo Owusu-Sarfo
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA; E-Mails: (E.A.-A.); (K.O.-S.); (G.A.N.G.); (T.Y.)
| | - G.A. Nagana Gowda
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA; E-Mails: (E.A.-A.); (K.O.-S.); (G.A.N.G.); (T.Y.)
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109, USA
| | - Tao Ye
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA; E-Mails: (E.A.-A.); (K.O.-S.); (G.A.N.G.); (T.Y.)
| | - Daniel Raftery
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA; E-Mails: (E.A.-A.); (K.O.-S.); (G.A.N.G.); (T.Y.)
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109, USA
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
- Author to whom correspondence should be addressed; E-Mail: ; Tel: +206-543-9709; Fax: +206-616-4819
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Schönig S, Recke A, Hirose M, Ludwig RJ, Seeger K. Metabolite analysis distinguishes between mice with epidermolysis bullosa acquisita and healthy mice. Orphanet J Rare Dis 2013; 8:93. [PMID: 23800341 PMCID: PMC3703300 DOI: 10.1186/1750-1172-8-93] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2013] [Accepted: 06/23/2013] [Indexed: 01/09/2023] Open
Abstract
Background Epidermolysis bullosa acquisita (EBA) is a rare skin blistering disease with a prevalence of 0.2/ million people. EBA is characterized by autoantibodies against type VII collagen. Type VII collagen builds anchoring fibrils that are essential for the dermal-epidermal junction. The pathogenic relevance of antibodies against type VII collagen subdomains has been demonstrated both in vitro and in vivo. Despite the multitude of clinical and immunological data, no information on metabolic changes exists. Methods We used an animal model of EBA to obtain insights into metabolomic changes during EBA. Sera from mice with immunization-induced EBA and control mice were obtained and metabolites were isolated by filtration. Proton nuclear magnetic resonance (NMR) spectra were recorded and analyzed by principal component analysis (PCA), partial least squares discrimination analysis (PLS-DA) and random forest. Results The metabolic pattern of immunized mice and control mice could be clearly distinguished with PCA and PLS-DA. Metabolites that contribute to the discrimination could be identified via random forest. The observed changes in the metabolic pattern of EBA sera, i.e. increased levels of amino acid, point toward an increased energy demand in EBA. Conclusions Knowledge about metabolic changes due to EBA could help in future to assess the disease status during treatment. Confirming the metabolic changes in patients needs probably large cohorts.
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Affiliation(s)
- Sarah Schönig
- Excellence Cluster Inflammation at Interfaces, Schleswig-Holstein, Germany
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Wei S, Liu L, Zhang J, Bowers J, Gowda GAN, Seeger H, Fehm T, Neubauer HJ, Vogel U, Clare SE, Raftery D. Metabolomics approach for predicting response to neoadjuvant chemotherapy for breast cancer. Mol Oncol 2013; 7:297-307. [PMID: 23142658 PMCID: PMC5528483 DOI: 10.1016/j.molonc.2012.10.003] [Citation(s) in RCA: 109] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2012] [Revised: 10/10/2012] [Accepted: 10/11/2012] [Indexed: 01/18/2023] Open
Abstract
Breast cancer is a clinically heterogeneous disease, which necessitates a variety of treatments and leads to different outcomes. As an example, only some women will benefit from chemotherapy. Identifying patients who will respond to chemotherapy and thereby improve their long-term survival has important implications to treatment protocols and outcomes, while identifying non responders may enable these patients to avail themselves of other investigational approaches or other potentially effective treatments. In this study, serum metabolite profiling was performed to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy for breast cancer. Metabolic profiles of serum from patients with complete (n = 8), partial (n = 14) and no response (n = 6) to chemotherapy were studied using a combination of nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography-mass spectrometry (LC-MS) and statistical analysis methods. The concentrations of four metabolites, three (threonine, isoleucine, glutamine) from NMR and one (linolenic acid) from LC-MS were significantly different when comparing response to chemotherapy. A prediction model developed by combining NMR and MS derived metabolites correctly identified 80% of the patients whose tumors did not show complete response to chemotherapy. These results show promise for larger studies that could result in more personalized treatment protocols for breast cancer patients.
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Affiliation(s)
- Siwei Wei
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA
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Ang JE, Kaye S, Banerji U. Tissue-based approaches to study pharmacodynamic endpoints in early phase oncology clinical trials. Curr Drug Targets 2013; 13:1525-34. [PMID: 22974395 PMCID: PMC3531821 DOI: 10.2174/138945012803530062] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2010] [Revised: 01/12/2010] [Accepted: 09/07/2012] [Indexed: 01/10/2023]
Abstract
Anti-cancer clinical drug development is currently costly and slow with a high attrition rate. There is thus an urgent and unmet need to integrate pharmacodynamic biomarkers into early phase clinical trials in the framework provided by the “pharmacologic audit trail” in order to overcome this challenge. This review discusses the rationale, advantages and disadvantages, as well as the practical considerations of various tissue-based approaches to perform pharmacodynamic studies in early phase oncology clinical trials using case histories of molecular targeting agents such as PI3K, m-TOR, HSP90, HDAC and PARP inhibitors. These approaches include the use of normal “surrogate” tissues such as peripheral blood mononuclear cells, platelet-rich plasma, plucked hair follicles, skin biopsies, plasma-based endocrine assays, proteomics, metabolomics and circulating endothelial cells. In addition, the review discusses the use of neoplastic tissues including tumor biopsies, circulating tumor DNA and tumor cells and metabolomic approaches. The utilization of these tissues and technology platforms to study biomarkers will help accelerate the development of molecularly targeted agents for the treatment of cancer.
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Affiliation(s)
- Joo Ern Ang
- The Institute of Cancer Research, Sutton, UK
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Jia HM, Feng YF, Liu YT, Chang X, Chen L, Zhang HW, Ding G, Zou ZM. Integration of ¹H NMR and UPLC-Q-TOF/MS for a comprehensive urinary metabonomics study on a rat model of depression induced by chronic unpredictable mild stress. PLoS One 2013; 8:e63624. [PMID: 23696839 PMCID: PMC3656962 DOI: 10.1371/journal.pone.0063624] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2012] [Accepted: 04/04/2013] [Indexed: 12/03/2022] Open
Abstract
Depression is a type of complex psychiatric disorder with long-term, recurrent bouts, and its etiology remains largely unknown. Here, an integrated approach utilizing 1H NMR and UPLC-Q-TOF/MS together was firstly used for a comprehensive urinary metabonomics study on chronic unpredictable mild stress (CUMS) treated rats. More than twenty-nine metabolic pathways were disturbed after CUMS treatment and thirty-six potential biomarkers were identified by using two complementary analytical technologies. Among the identified biomarkers, nineteen (10, 11,16, 17, 21–25, and 27–36) were firstly reported as potential biomarkers of CUMS-induced depression. Obviously, this paper presented a comprehensive map of the metabolic pathways perturbed by CUMS and expanded on the multitude of potential biomarkers that have been previously reported in the CUMS model. Four metabolic pathways, including valine, leucine and isoleucine biosynthesis; phenylalanine, tyrosine and tryptophan biosynthesis; tryptophan metabolism; synthesis and degradation of ketone bodies had the deepest influence in the pathophysiologic process of depression. Fifteen potential biomarkers (1–2, 4–6, 15, 18, 20–23, 27, 32, 35–36) involved in the above four metabolic pathways might become the screening criteria in clinical diagnosis and predict the development of depression. Moreover, the results of Western blot analysis of aromatic L-amino acid decarboxylase (DDC) and indoleamine 2, 3-dioxygenase (IDO) in the hippocampus of CUMS-treated rats indicated that depletion of 5-HT and tryptophan, production of 5-MT and altered expression of DDC and IDO together played a key role in the initiation and progression of depression. In addition, none of the potential biomarkers were detected by NMR and LC-MS simultaneously which indicated the complementary of the two kinds of detection technologies. Therefore, the integration of 1H NMR and UPLC-Q-TOF/MS in metabonomics study provided an approach to identify the comprehensive potential depression-related biomarkers and helpful in further understanding the underlying molecular mechanisms of depression through the disturbance of metabolic pathways.
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Affiliation(s)
- Hong-mei Jia
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Yu-fei Feng
- Department of Pharmacy, Beijing Hospital, Ministry of Public Health, Beijing, PR China
| | - Yue-tao Liu
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Xing Chang
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Lin Chen
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Hong-wu Zhang
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Gang Ding
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Zhong-mei Zou
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
- * E-mail:
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Zhao YY. Metabolomics in chronic kidney disease. Clin Chim Acta 2013; 422:59-69. [PMID: 23570820 DOI: 10.1016/j.cca.2013.03.033] [Citation(s) in RCA: 172] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2013] [Revised: 03/23/2013] [Accepted: 03/27/2013] [Indexed: 12/24/2022]
Abstract
Chronic kidney disease (CKD) represents a major challenge to public healthcare. Traditional clinical biomarkers of renal function (blood urea nitrogen and serum creatinine) are not sensitive or specific enough and only increase significantly after the presence of substantial CKD. Therefore, more sensitive biomarkers of CKD are needed. CKD-specific biomarkers at an early disease stage and early diagnosis of specific renal diseases would enable improved therapeutic treatment and reduced the personal and financial burdens. The goal of metabolomics is to identify non-targeted, global small-molecule metabolite profiles of complex samples, such as biofluids and tissues. This method offers the potential for a holistic approach to clinical medicine, as well as improvements in disease diagnoses and the understanding of pathological mechanisms. This review article presents an overview of the recent developments in the field of metabolomics, followed by an in-depth discussion of its application to the study of CKD (primary, chronic glomerulonephritis such as IgA nephropathy; secondary, chronic renal injury such as diabetic nephropathy; chronic renal failure including end-stage kidney disease with and without undergoing replacement therapies, etc), including metabolomic analytical technologies, chemometrics, and metabolomics in experimental and clinical research. We describe the current status of the identification of metabolic biomarkers in CKD. Several markers have been confirmed across multiple studies to detect CKD earlier than traditional clinical chemical and histopathological methods. The application of metabolomics in CKD studies provides researchers the opportunity to gain new insights into metabolic profiling and pathophysiological mechanisms. Particular challenges in the field are presented and placed within the context of future applications of metabolomic approaches to the studies of CKD.
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Affiliation(s)
- Ying-Yong Zhao
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, the College of Life Sciences, Northwest University, Xi'an, Shaanxi 710069, PR China.
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Cuperlovic-Culf M, Belacel N, Culf A. Integrated analysis of transcriptomics and metabolomics profiles. ACTA ACUST UNITED AC 2013; 2:497-509. [PMID: 23495739 DOI: 10.1517/17530059.2.5.497] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND Integrated analysis of transcriptomics and metabolomics data has the potential greatly to increase our understanding of metabolic networks and biological systems leading to various potential clinical applications. OBJECTIVE The aim is to present different applications as well as analysis tools utilized for the parallel study of gene and metabolite expressions. METHODS Publications dealing with integrated analysis of gene and metabolite expression data as well as publications describing tools that can be used for integrated analysis are reviewed. RESULTS/CONCLUSION The full benefit of integrated analysis can be achieved only if data from all utilized methods are treated equally by multidisciplinary teams. This approach can lead to advances in functional genomics with possible clinical developments in diagnostics and improved drug target selection.
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Affiliation(s)
- Miroslava Cuperlovic-Culf
- Institute for Information Technology, National Research Council of Canada, 55 Crowley Farm Road, Suit 1100, Moncton, NB E1A 7R1, Canada +1 506 861 0952 ; +1 506 851 3630 ;
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Bradshaw-Pierce EL, Pitts TM, Kulikowski G, Selby H, Merz AL, Gustafson DL, Serkova NJ, Eckhardt SG, Weekes CD. Utilization of quantitative in vivo pharmacology approaches to assess combination effects of everolimus and irinotecan in mouse xenograft models of colorectal cancer. PLoS One 2013; 8:e58089. [PMID: 23520486 PMCID: PMC3592886 DOI: 10.1371/journal.pone.0058089] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2012] [Accepted: 01/31/2013] [Indexed: 12/12/2022] Open
Abstract
Purpose The PI3K/AKT/mTOR pathway is frequently dysregulated in cancers and inhibition of mTOR has demonstrated the ability to modulate pro-survival pathways. As such, we sought to determine the ability of the mTOR inhibitor everolimus to potentiate the antitumor effects of irinotecan in colorectal cancer (CRC). Experimental Design The combinatorial effects of everolimus and irinotecan were evaluated in vitro and in vivo in CRC cell lines harboring commonly found mutations in PIK3CA, KRAS and/or BRAF. Pharmacokinetically-directed dosing protocols of everolimus and irinotecan were established and used to assess the in vivo antitumor effects of the agents. At the end of treatment, 3–6 tumors per treatment arm were harvested for biomarker analysis by NMR metabolomics. Results Everolimus and irinotecan/SN38 demonstrated synergistic anti-proliferative effects in multiple CRC cell lines in vitro. Combination effects of everolimus and irinotecan were determined in CRC xenograft models using clinically-relevant dosing protocols. Everolimus demonstrated significant tumor growth inhibition alone and when combined with irinotecan in HT29 and HCT116 tumor xenografts. Metabolomic analysis showed that HT29 tumors were more metabolically responsive than HCT116 tumors. Everolimus caused a decrease in glycolysis in both tumor types whilst irinotecan treatment resulted in a profound accumulation of lipids in HT29 tumors indicating a cytotoxic effect. Conclusions Quantitative analysis of tumor growth and metabolomic data showed that the combination of everolimus and irinotecan was more beneficial in the BRAF/PIK3CA mutant HT29 tumor xenografts, which had an additive effect, than the KRAS/PIK3CA mutant HCT116 tumor xenografts, which had a less than additive effect.
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Affiliation(s)
- Erica L Bradshaw-Pierce
- Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America.
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