401
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Genetic architecture of insulin resistance in the mouse. Cell Metab 2015; 21:334-347. [PMID: 25651185 PMCID: PMC4349439 DOI: 10.1016/j.cmet.2015.01.002] [Citation(s) in RCA: 170] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2014] [Revised: 11/17/2014] [Accepted: 01/09/2015] [Indexed: 02/08/2023]
Abstract
Insulin resistance (IR) is a complex trait with multiple genetic and environmental components. Confounded by large differences between the sexes, environment, and disease pathology, the genetic basis of IR has been difficult to dissect. Here we examine IR and related traits in a diverse population of more than 100 unique male and female inbred mouse strains after feeding a diet rich in fat and refined carbohydrates. Our results show dramatic variation in IR among strains of mice and widespread differences between sexes that are dependent on genotype. We uncover more than 15 genome-wide significant loci and validate a gene, Agpat5, associated with IR. We also integrate plasma metabolite levels and global gene expression from liver and adipose tissue to identify metabolite quantitative trait loci (mQTL) and expression QTL (eQTL), respectively. Our results provide a resource for analysis of interactions between diet, sex, and genetic background in IR.
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402
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Parks BW, Sallam T, Mehrabian M, Psychogios N, Hui ST, Norheim F, Castellani LW, Rau CD, Pan C, Phun J, Zhou Z, Yang WP, Neuhaus I, Gargalovic PS, Kirchgessner TG, Graham M, Lee R, Tontonoz P, Gerszten RE, Hevener AL, Lusis AJ. Genetic architecture of insulin resistance in the mouse. Cell Metab 2015. [PMID: 25651185 DOI: 10.1016/j.cmet.2015.01.002.genetic] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Abstract
Insulin resistance (IR) is a complex trait with multiple genetic and environmental components. Confounded by large differences between the sexes, environment, and disease pathology, the genetic basis of IR has been difficult to dissect. Here we examine IR and related traits in a diverse population of more than 100 unique male and female inbred mouse strains after feeding a diet rich in fat and refined carbohydrates. Our results show dramatic variation in IR among strains of mice and widespread differences between sexes that are dependent on genotype. We uncover more than 15 genome-wide significant loci and validate a gene, Agpat5, associated with IR. We also integrate plasma metabolite levels and global gene expression from liver and adipose tissue to identify metabolite quantitative trait loci (mQTL) and expression QTL (eQTL), respectively. Our results provide a resource for analysis of interactions between diet, sex, and genetic background in IR.
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Affiliation(s)
- Brian W Parks
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Tamer Sallam
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Margarete Mehrabian
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nikolas Psychogios
- Cardiovascular Research Center and Cardiology Division, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Simon T Hui
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Frode Norheim
- Department of Nutrition, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317 Oslo, Norway
| | - Lawrence W Castellani
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Christoph D Rau
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Calvin Pan
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jennifer Phun
- Division of Endocrinology, Diabetes and Hypertension, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Zhenqi Zhou
- Division of Endocrinology, Diabetes and Hypertension, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Wen-Pin Yang
- Department of Applied Genomics, Bristol-Myers Squibb, Princeton, NJ 08543, USA
| | - Isaac Neuhaus
- Department of Applied Genomics, Bristol-Myers Squibb, Princeton, NJ 08543, USA
| | - Peter S Gargalovic
- Department of Cardiovascular Drug Discovery, Bristol-Myers Squibb, Princeton, NJ 08543, USA
| | - Todd G Kirchgessner
- Department of Cardiovascular Drug Discovery, Bristol-Myers Squibb, Princeton, NJ 08543, USA
| | - Mark Graham
- Isis Pharmaceuticals, Carlsbad, CA 92008, USA
| | - Richard Lee
- Isis Pharmaceuticals, Carlsbad, CA 92008, USA
| | - Peter Tontonoz
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Robert E Gerszten
- Cardiovascular Research Center and Cardiology Division, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Andrea L Hevener
- Division of Endocrinology, Diabetes and Hypertension, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Aldons J Lusis
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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403
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Pedersen ER, Tuseth N, Eussen SJ, Ueland PM, Strand E, Svingen GFT, Midttun Ø, Meyer K, Mellgren G, Ulvik A, Nordrehaug JE, Nilsen DW, Nygård O. Associations of Plasma Kynurenines With Risk of Acute Myocardial Infarction in Patients With Stable Angina Pectoris. Arterioscler Thromb Vasc Biol 2015; 35:455-62. [DOI: 10.1161/atvbaha.114.304674] [Citation(s) in RCA: 108] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Objective—
Enhanced tryptophan degradation, induced by the proinflammatory cytokine interferon-γ, has been related to cardiovascular disease progression and insulin resistance. We assessed downstream tryptophan metabolites of the kynurenine pathway as predictors of acute myocardial infarction in patients with suspected stable angina pectoris. Furthermore, we evaluated potential effect modifications according to diagnoses of pre-diabetes mellitus or diabetes mellitus.
Approach and Results—
Blood samples were obtained from 4122 patients (median age, 62 years; 72% men) who underwent elective coronary angiography. During median follow-up of 56 months, 8.3% had acute myocardial infarction. Comparing the highest quartile to the lowest, for the total cohort, multivariable adjusted hazard ratios (95% confidence intervals) were 1.68 (1.21–2.34), 1.81 (1.33–2.48), 1.68 (1.21–2.32), and 1.48 (1.10–1.99) for kynurenic acid, hydroxykynurenine, anthranilic acid, and hydroxyanthranilic acid, respectively. The kynurenines correlated with phenotypes of the metabolic syndrome, and risk associations were generally stronger in subgroups classified with pre-diabetes mellitus or diabetes mellitus at inclusion (
P
int
≤0.05). Evaluated in the total population, hydroxykynurenine and anthranilic acid provided statistically significant net reclassification improvements (0.21 [0.08–0.35] and 0.21 [0.07–0.35], respectively).
Conclusions—
In patients with suspected stable angina pectoris, elevated levels of plasma kynurenines predicted increased risk of acute myocardial infarction, and risk estimates were generally stronger in subgroups with evidence of impaired glucose homeostasis. Future studies should aim to clarify roles of the kynurenine pathway in atherosclerosis and glucose metabolism.
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Affiliation(s)
- Eva Ringdal Pedersen
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Nora Tuseth
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Simone J.P.M. Eussen
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Per Magne Ueland
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Elin Strand
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Gard Frodahl Tveitevåg Svingen
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Øivind Midttun
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Klaus Meyer
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Gunnar Mellgren
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Arve Ulvik
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Jan Erik Nordrehaug
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Dennis W. Nilsen
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
| | - Ottar Nygård
- From the Department of Clinical Science (E.R.P., N.T., P.M.U., E.S., G.F.T.S., G.M., J.E.N., D.W.N., O.N.) and Department of Global Public Health and Primary Health Care (S.J.P.M.E.), University of Bergen, Bergen, Norway; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway (N.T., O.N.); Department of Epidemiology, School for Public Health and Primary Care-CAPHRI, Maastricht University, Maastricht, The Netherlands (S.J.P.M.E.); Laboratory of Clinical Biochemistry (P.M.U.) and
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404
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Woo HI, Chun MR, Yang JS, Lim SW, Kim MJ, Kim SW, Myung WJ, Kim DK, Lee SY. Plasma amino acid profiling in major depressive disorder treated with selective serotonin reuptake inhibitors. CNS Neurosci Ther 2015; 21:417-24. [PMID: 25611566 DOI: 10.1111/cns.12372] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Revised: 11/23/2014] [Accepted: 11/28/2014] [Indexed: 12/24/2022] Open
Abstract
AIMS Amino acids are important body metabolites and seem to be helpful for understanding pathogenesis and predicting therapeutic response in major depressive disorder (MDD). We performed amino acid profiling to discover potential biomarkers in major depressive patients treated with selective serotonin reuptake inhibitors (SSRIs). METHODS Amino acid profiling using aTRAQ™ kits for Amino Acid Analysis in Physiological Fluids on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) system was performed on 158 specimens at baseline and at 6 weeks after the initiation of SSRI treatment for 68 patients with MDD and from 22 healthy controls. RESULTS Baseline alpha-aminobutyric acid (ABA) discriminated the patients according to the therapeutic response. Plasma glutamic acid concentration and glutamine/glutamic acid ratio were different between before and after SSRI treatment only in the response group. Comparing patients with MDD with healthy controls, alterations of ten amino acids, including alanine, beta-alanine, beta-aminoisobutyric acid, cystathionine, ethanolamine, glutamic acid, homocystine, methionine, O-phospho-L-serine, and sarcosine, were observed in MDD. CONCLUSION Metabolism of amino acids, including ABA and glutamic acid, has the potential to contribute to understandings of pathogenesis and predictions of therapeutic response in MDD.
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Affiliation(s)
- Hye-In Woo
- Department of Laboratory Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Korea
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405
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Affiliation(s)
| | - Frank B Hu
- Department of Nutrition and Department of Epidemiology, Harvard School of Public Health, Boston, MA; Channing Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
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406
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Melnik BC. The pathogenic role of persistent milk signaling in mTORC1- and milk-microRNA-driven type 2 diabetes mellitus. Curr Diabetes Rev 2015; 11:46-62. [PMID: 25587719 PMCID: PMC4428476 DOI: 10.2174/1573399811666150114100653] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2014] [Revised: 01/08/2015] [Accepted: 01/09/2015] [Indexed: 12/12/2022]
Abstract
Milk, the secretory product of the lactation genome, promotes growth of the newborn mammal. Milk delivers insulinotropic amino acids, thus maintains a molecular crosstalk with the pancreatic β-cell of the milk recipient. Homeostasis of β-cells and insulin production depend on the appropriate magnitude of mTORC1 signaling. mTORC1 is activated by branched-chain amino acids (BCAAs), glutamine, and palmitic acid, abundant nutrient signals of cow´s milk. Furthermore, milk delivers bioactive exosomal microRNAs. After milk consumption, bovine microRNA-29b, a member of the diabetogenic microRNA-29- family, reaches the systemic circulation and the cells of the milk consumer. MicroRNA-29b downregulates branchedchain α-ketoacid dehydrogenase, a potential explanation for increased BCAA serum levels, the metabolic signature of insulin resistance and type 2 diabetes mellitus (T2DM). In non-obese diabetic mice, microRNA-29b downregulates the antiapoptotic protein Mcl-1, which leads to early β-cell death. In all mammals except Neolithic humans, milk-driven mTORC1 signaling is physiologically restricted to the postnatal period. In contrast, chronic hyperactivated mTORC1 signaling has been associated with the development of age-related diseases of civilization including T2DM. Notably, chronic hyperactivation of mTORC1 enhances endoplasmic reticulum stress that promotes apoptosis. In fact, hyperactivated β-cell mTORC1 signaling induced early β-cell apoptosis in a mouse model. The EPIC-InterAct Study demonstrated an association between milk consumption and T2DM in France, Italy, United Kingdom, Germany, and Sweden. In contrast, fermented milk products and cheese exhibit an inverse correlation. Since the early 1950´s, refrigeration technology allowed widespread consumption of fresh pasteurized milk, which facilitates daily intake of bioactive bovine microRNAs. Persistent uptake of cow´s milk-derived microRNAs apparently transfers an overlooked epigenetic diabetogenic program that should not reach the human food chain.
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Affiliation(s)
- Bodo C Melnik
- Department of Dermatology, Environmental Medicine and Health Theory, University of Osnabruck, Sedanstraße 115, D-49090 Osnabrück, Germany.
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407
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Abu Bakar MH, Sarmidi MR, Cheng KK, Ali Khan A, Suan CL, Zaman Huri H, Yaakob H. Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes. MOLECULAR BIOSYSTEMS 2015; 11:1742-74. [DOI: 10.1039/c5mb00158g] [Citation(s) in RCA: 82] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This paper highlights the metabolomic roles in systems biology towards the elucidation of metabolic mechanisms in obesity and type 2 diabetes.
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Affiliation(s)
- Mohamad Hafizi Abu Bakar
- Department of Bioprocess Engineering
- Faculty of Chemical Engineering
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
| | - Mohamad Roji Sarmidi
- Institute of Bioproduct Development
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
- Innovation Centre in Agritechnology for Advanced Bioprocessing (ICA)
| | - Kian-Kai Cheng
- Department of Bioprocess Engineering
- Faculty of Chemical Engineering
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
| | - Abid Ali Khan
- Institute of Bioproduct Development
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
- Department of Biosciences
| | - Chua Lee Suan
- Institute of Bioproduct Development
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
| | - Hasniza Zaman Huri
- Department of Pharmacy
- Faculty of Medicine
- University of Malaya
- 50603 Kuala Lumpur
- Malaysia
| | - Harisun Yaakob
- Institute of Bioproduct Development
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
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408
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Dunn WB, Lin W, Broadhurst D, Begley P, Brown M, Zelena E, Vaughan AA, Halsall A, Harding N, Knowles JD, Francis-McIntyre S, Tseng A, Ellis DI, O’Hagan S, Aarons G, Benjamin B, Chew-Graham S, Moseley C, Potter P, Winder CL, Potts C, Thornton P, McWhirter C, Zubair M, Pan M, Burns A, Cruickshank JK, Jayson GC, Purandare N, Wu FCW, Finn JD, Haselden JN, Nicholls AW, Wilson ID, Goodacre R, Kell DB. Molecular phenotyping of a UK population: defining the human serum metabolome. Metabolomics 2015; 11:9-26. [PMID: 25598764 PMCID: PMC4289517 DOI: 10.1007/s11306-014-0707-1] [Citation(s) in RCA: 150] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2014] [Accepted: 07/09/2014] [Indexed: 02/06/2023]
Abstract
Phenotyping of 1,200 'healthy' adults from the UK has been performed through the investigation of diverse classes of hydrophilic and lipophilic metabolites present in serum by applying a series of chromatography-mass spectrometry platforms. These data were made robust to instrumental drift by numerical correction; this was prerequisite to allow detection of subtle metabolic differences. The variation in observed metabolite relative concentrations between the 1,200 subjects ranged from less than 5 % to more than 200 %. Variations in metabolites could be related to differences in gender, age, BMI, blood pressure, and smoking. Investigations suggest that a sample size of 600 subjects is both necessary and sufficient for robust analysis of these data. Overall, this is a large scale and non-targeted chromatographic MS-based metabolomics study, using samples from over 1,000 individuals, to provide a comprehensive measurement of their serum metabolomes. This work provides an important baseline or reference dataset for understanding the 'normal' relative concentrations and variation in the human serum metabolome. These may be related to our increasing knowledge of the human metabolic network map. Information on the Husermet study is available at http://www.husermet.org/. Importantly, all of the data are made freely available at MetaboLights (http://www.ebi.ac.uk/metabolights/).
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Affiliation(s)
- Warwick B. Dunn
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Faculty of Engineering & Physical Sciences, Manchester Centre for Integrative Systems Biology, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Faculty of Medical and Human Sciences, Centre for Endocrinology and Diabetes, Institute of Human Development, The University of Manchester, Manchester, UK
- Centre for Advanced Discovery and Experimental Therapeutics (CADET), Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, M13 9WL UK
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Wanchang Lin
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Faculty of Medical and Human Sciences, Centre for Endocrinology and Diabetes, Institute of Human Development, The University of Manchester, Manchester, UK
- Centre for Advanced Discovery and Experimental Therapeutics (CADET), Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, M13 9WL UK
| | - David Broadhurst
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Department of Medicine, Katz Group Centre for Pharmacy & Health, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - Paul Begley
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Faculty of Medical and Human Sciences, Centre for Endocrinology and Diabetes, Institute of Human Development, The University of Manchester, Manchester, UK
- Centre for Advanced Discovery and Experimental Therapeutics (CADET), Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, M13 9WL UK
| | - Marie Brown
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Faculty of Medical and Human Sciences, Centre for Endocrinology and Diabetes, Institute of Human Development, The University of Manchester, Manchester, UK
- Centre for Advanced Discovery and Experimental Therapeutics (CADET), Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, M13 9WL UK
| | - Eva Zelena
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Andrew A. Vaughan
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Antony Halsall
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Nadine Harding
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Joshua D. Knowles
- Faculty of Engineering & Physical Sciences, School of Computer Science, The University of Manchester, Manchester, M13 9PL UK
| | - Sue Francis-McIntyre
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Andy Tseng
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - David I. Ellis
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Steve O’Hagan
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Gill Aarons
- Faculty of Medical & Human Sciences, Institute of Inflammation and Repair, Salford Royal Dermatopharmacology, The University of Manchester, Manchester, M6 8HD UK
| | - Boben Benjamin
- Clinical & Cognitive Neurosciences, Faculty of Medical & Human Sciences, Institute of Brain, Behaviour & Mental Health, The University of Manchester, Manchester, M13 9PT UK
| | - Stephen Chew-Graham
- Clinical & Cognitive Neurosciences, Faculty of Medical & Human Sciences, Institute of Brain, Behaviour & Mental Health, The University of Manchester, Manchester, M13 9PT UK
| | - Carly Moseley
- Faculty of Medical and Human Sciences, Institute of Cancer Sciences, Christie Hospital, The University of Manchester, Manchester, M20 4BX UK
| | - Paula Potter
- Faculty of Medical and Human Sciences, Institute of Cancer Sciences, Christie Hospital, The University of Manchester, Manchester, M20 4BX UK
| | - Catherine L. Winder
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Faculty of Engineering & Physical Sciences, Manchester Centre for Integrative Systems Biology, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Catherine Potts
- Faculty of Medical & Human Sciences, Institute of Human Development, The University of Manchester, Manchester, M13 9WL UK
| | - Paula Thornton
- Faculty of Medical and Human Sciences, Institute of Cancer Sciences, Christie Hospital, The University of Manchester, Manchester, M20 4BX UK
| | - Catriona McWhirter
- Faculty of Medical & Human Sciences, Institute of Human Development, The University of Manchester, Manchester, M13 9WL UK
| | - Mohammed Zubair
- Clinical & Cognitive Neurosciences, Faculty of Medical & Human Sciences, Institute of Brain, Behaviour & Mental Health, The University of Manchester, Manchester, M13 9PT UK
| | - Martin Pan
- Neurology and Gastrointestinal Centre of Excellence for Drug Discovery, GlaxoSmithKline, Third Avenue, Harlow, Essex, CM19 5AW UK
| | - Alistair Burns
- Clinical & Cognitive Neurosciences, Faculty of Medical & Human Sciences, Institute of Brain, Behaviour & Mental Health, The University of Manchester, Manchester, M13 9PT UK
| | - J. Kennedy Cruickshank
- Faculty of Medical & Human Sciences, Institute of Cardiovascular Sciences, The University of Manchester, Manchester, M13 9PT UK
- St Thomas’ Hospital, King’s College, University of London & King’s Health Partners, London, SE1 9NH UK
| | - Gordon C. Jayson
- Faculty of Medical and Human Sciences, Institute of Cancer Sciences, Christie Hospital, The University of Manchester, Manchester, M20 4BX UK
| | - Nitin Purandare
- Faculty of Medical & Human Sciences, Institute of Cardiovascular Sciences, The University of Manchester, Manchester, M13 9PT UK
| | - Frederick C. W. Wu
- Faculty of Medical & Human Sciences, Institute of Human Development, The University of Manchester, Manchester, M13 9WL UK
| | - Joe D. Finn
- Faculty of Medical & Human Sciences, Institute of Human Development, The University of Manchester, Manchester, M13 9WL UK
| | - John N. Haselden
- Investigative Preclinical Toxicology, GlaxoSmithKline, David Jack Centre for Research and Development, Park Road, Ware, Hertfordshire, SG12 0DP UK
| | - Andrew W. Nicholls
- Investigative Preclinical Toxicology, GlaxoSmithKline, David Jack Centre for Research and Development, Park Road, Ware, Hertfordshire, SG12 0DP UK
| | - Ian D. Wilson
- Faculty of Medicine, Department of Surgery & Cancer, Sir Alexander Fleming Building, Imperial College London, London, SW7 2AZ, UK
- DMPK Innovative Medicines, AstraZeneca, Cheshire, SK10 4TF UK
| | - Royston Goodacre
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Faculty of Engineering & Physical Sciences, Manchester Centre for Integrative Systems Biology, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
| | - Douglas B. Kell
- Faculty of Engineering and Physical Sciences, School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
- Faculty of Engineering & Physical Sciences, Manchester Centre for Integrative Systems Biology, Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK
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409
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Zheng Y, Yu B, Alexander D, Couper DJ, Boerwinkle E. Medium-term variability of the human serum metabolome in the Atherosclerosis Risk in Communities (ARIC) study. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2014; 18:364-73. [PMID: 24910946 DOI: 10.1089/omi.2014.0019] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Metabolomics is a systems biology tool providing small molecule signatures of disease etiology. In order to estimate the biologic variability of the human serum metabolome, this study calculated intraclass correlation coefficients (ICCs) for 178 stably-detected metabolites measured by untargeted chromatography/mass spectrometry. We studied a subsample of 60 participants (57% males, 70% Caucasians, aged 73.77±5.3 years) in the Atherosclerosis Risk in Communities (ARIC) Study who provided two fasting serum samples 4-6 weeks apart. The median ICC across all metabolites was 0.60, and 82% of metabolites had at least fair variability (i.e., ICC>= 0.40). There was variation in the medium-term variability among metabolites, with those in the pathways of amino acid and lipid metabolism showing relatively high ICCs, and those in the carbohydrate pathway showing relatively low ICCs. The results of this study provide a valuable resource for future study design and outcome interpretation of mass spectrometry-based metabolomic studies in epidemiology.
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Affiliation(s)
- Yan Zheng
- 1 Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston , Houston, Texas
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410
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Huynh J, Xiong G, Bentley-Lewis R. A systematic review of metabolite profiling in gestational diabetes mellitus. Diabetologia 2014; 57:2453-64. [PMID: 25193282 PMCID: PMC4221524 DOI: 10.1007/s00125-014-3371-0] [Citation(s) in RCA: 73] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 08/14/2014] [Indexed: 02/07/2023]
Abstract
AIMS/HYPOTHESIS Gestational diabetes mellitus is associated with adverse maternal and fetal outcomes during, as well as subsequent to, pregnancy, including increased risk of type 2 diabetes and cardiovascular disease. Because of the importance of early risk stratification in preventing these complications, improved first-trimester biomarker determination for diagnosing gestational diabetes would enhance our ability to optimise both maternal and fetal health. Metabolomic profiling, the systematic study of small molecule products of biochemical pathways, has shown promise in the identification of key metabolites associated with the pathogenesis of several metabolic diseases, including gestational diabetes. This article provides a systematic review of the current state of research on biomarkers and gestational diabetes and discusses the clinical relevance of metabolomics in the prediction, diagnosis and management of gestational diabetes. METHODS We conducted a systematic search of MEDLINE (PubMed) up to the end of February 2014 using the key term combinations of 'metabolomics,' 'metabonomics,' 'nuclear magnetic spectroscopy,' 'mass spectrometry,' 'metabolic profiling' and 'amino acid profile' combined (AND) with 'gestational diabetes'. Additional articles were identified through searching the reference lists from included studies. Quality assessment of included articles was conducted through the use of QUADOMICS. RESULTS This systematic review included 17 articles. The biomarkers most consistently associated with gestational diabetes were asymmetric dimethylarginine and NEFAs. After QUADOMICS analysis, 13 of the 17 included studies were classified as 'high quality'. CONCLUSIONS/INTERPRETATION Existing metabolomic studies of gestational diabetes present inconsistent findings regarding metabolite profile characteristics. Further studies are needed in larger, more racially/ethnically diverse populations.
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Affiliation(s)
- Jennifer Huynh
- Department of Medicine/Diabetes Unit, Massachusetts General Hospital, 55 Fruit Street, Bulfinch 4-415, Boston, MA, 02114, USA
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411
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Abstract
Branched-chain amino acids (BCAAs) are important nutrient signals that have direct and indirect effects. Frequently, BCAAs have been reported to mediate antiobesity effects, especially in rodent models. However, circulating levels of BCAAs tend to be increased in individuals with obesity and are associated with worse metabolic health and future insulin resistance or type 2 diabetes mellitus (T2DM). A hypothesized mechanism linking increased levels of BCAAs and T2DM involves leucine-mediated activation of the mammalian target of rapamycin complex 1 (mTORC1), which results in uncoupling of insulin signalling at an early stage. A BCAA dysmetabolism model proposes that the accumulation of mitotoxic metabolites (and not BCAAs per se) promotes β-cell mitochondrial dysfunction, stress signalling and apoptosis associated with T2DM. Alternatively, insulin resistance might promote aminoacidaemia by increasing the protein degradation that insulin normally suppresses, and/or by eliciting an impairment of efficient BCAA oxidative metabolism in some tissues. Whether and how impaired BCAA metabolism might occur in obesity is discussed in this Review. Research on the role of individual and model-dependent differences in BCAA metabolism is needed, as several genes (BCKDHA, PPM1K, IVD and KLF15) have been designated as candidate genes for obesity and/or T2DM in humans, and distinct phenotypes of tissue-specific branched chain ketoacid dehydrogenase complex activity have been detected in animal models of obesity and T2DM.
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Affiliation(s)
- Christopher J Lynch
- Cellular and Molecular Physiology Department, The Pennsylvania State University, 500 University Drive, MC-H166, Hershey, PA 17033, USA
| | - Sean H Adams
- Arkansas Children's Nutrition Center, and Department of Pediatrics, University of Arkansas for Medical Sciences, 15 Children's Way, Little Rock, AR 72202, USA
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412
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Sansbury BE, Bhatnagar A, Hill BG. Impact of nutrient excess and endothelial nitric oxide synthase on the plasma metabolite profile in mice. Front Physiol 2014; 5:453. [PMID: 25505420 PMCID: PMC4243488 DOI: 10.3389/fphys.2014.00453] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Accepted: 11/03/2014] [Indexed: 01/08/2023] Open
Abstract
An increase in calorie consumption is associated with the recent rise in obesity prevalence. However, our current understanding of the effects of nutrient excess on major metabolic pathways appears insufficient to develop safe and effective metabolic interventions to prevent obesity. Hence, we sought to identify systemic metabolic changes caused by nutrient excess and to determine how endothelial nitric oxide synthase (eNOS)—which has anti-obesogenic properties—affects systemic metabolism by measuring plasma metabolites. Wild-type (WT) and eNOS transgenic (eNOS-TG) mice were placed on low fat or high fat diets for 6 weeks, and plasma metabolites were measured using an unbiased metabolomic approach. High fat feeding in WT mice led to significant increases in fat mass, which was associated with significantly lower plasma levels of 1,5-anhydroglucitol, lysophospholipids, 3-dehydrocarnitine, and bile acids, as well as branched chain amino acids (BCAAs) and their metabolites. Plasma levels of several lipids including sphingomyelins, stearoylcarnitine, dihomo-linoleate and metabolites associated with oxidative stress were increased by high fat diet. In comparison with low fat-fed WT mice, eNOS-TG mice showed lower levels of several free fatty acids, but in contrast, the levels of bile acids, amino acids, and BCAA catabolites were increased. When placed on a high fat diet, eNOS overexpressing mice showed remarkably higher levels of plasma bile acids and elevated levels of plasma BCAAs and their catabolites compared with WT mice. Treatment with GW4064, an inhibitor of bile acid synthesis, decreased plasma bile acid levels but was not sufficient to reverse the anti-obesogenic effects of eNOS overexpression. These findings reveal unique metabolic changes in response to high fat diet and eNOS overexpression and suggest that the anti-obesity effects of eNOS are likely independent of changes in the bile acid pool.
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Affiliation(s)
- Brian E Sansbury
- Division of Cardiology, Department of Medicine, Institute of Molecular Cardiology, University of Louisville Louisville, KY, USA ; Department of Medicine, Diabetes and Obesity Center, University of Louisville Louisville, KY, USA ; Department of Physiology and Biophysics, University of Louisville Louisville, KY, USA
| | - Aruni Bhatnagar
- Division of Cardiology, Department of Medicine, Institute of Molecular Cardiology, University of Louisville Louisville, KY, USA ; Department of Medicine, Diabetes and Obesity Center, University of Louisville Louisville, KY, USA ; Department of Physiology and Biophysics, University of Louisville Louisville, KY, USA ; Department of Biochemistry and Molecular Biology, University of Louisville Louisville, KY, USA
| | - Bradford G Hill
- Division of Cardiology, Department of Medicine, Institute of Molecular Cardiology, University of Louisville Louisville, KY, USA ; Department of Medicine, Diabetes and Obesity Center, University of Louisville Louisville, KY, USA ; Department of Physiology and Biophysics, University of Louisville Louisville, KY, USA ; Department of Biochemistry and Molecular Biology, University of Louisville Louisville, KY, USA
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413
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Lin Z, Roede JR, He C, Jones DP, Filipov NM. Short-term oral atrazine exposure alters the plasma metabolome of male C57BL/6 mice and disrupts α-linolenate, tryptophan, tyrosine and other major metabolic pathways. Toxicology 2014; 326:130-41. [PMID: 25445803 DOI: 10.1016/j.tox.2014.11.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2014] [Revised: 10/28/2014] [Accepted: 11/02/2014] [Indexed: 12/15/2022]
Abstract
Overexposure to the commonly used herbicide atrazine (ATR) affects several organ systems, including the brain. Previously, we demonstrated that short-term oral ATR exposure causes behavioral deficits and dopaminergic and serotonergic dysfunction in the brains of mice. Using adult male C57BL/6 mice, the present study aimed to investigate effects of a 10-day oral ATR exposure (0, 5, 25, 125, or 250mg/kg) on the mouse plasma metabolome and to determine metabolic pathways affected by ATR that may be reflective of ATR's effects on the brain and useful to identify peripheral biomarkers of neurotoxicity. Four hours after the last dosing on day 10, plasma was collected and analyzed with high-performance, dual chromatography-Fourier-transform mass spectrometry that was followed by biostatistical and bioinformatic analyses. ATR exposure (≥5mg/kg) significantly altered plasma metabolite profile and resulted in a dose-dependent increase in the number of metabolites with ion intensities significantly different from the control group. Pathway analyses revealed that ATR exposure strongly correlated with and disrupted multiple metabolic pathways. Tyrosine, tryptophan, linoleic acid and α-linolenic acid metabolic pathways were among the affected pathways, with α-linolenic acid metabolism being affected to the greatest extent. Observed effects of ATR on plasma tyrosine and tryptophan metabolism may be reflective of the previously reported perturbations of brain dopamine and serotonin homeostasis, respectively. ATR-caused alterations in the plasma profile of α-linolenic acid metabolism are a potential novel and sensitive plasma biomarker of ATR effect and plasma metabolomics could be used to better assess the risks, including to the brain, associated with ATR overexposure.
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Affiliation(s)
- Zhoumeng Lin
- Department of Physiology and Pharmacology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA; Interdisciplinary Toxicology Program, University of Georgia, Athens, GA 30602, USA.
| | - James R Roede
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, GA 30322, USA.
| | - Chunla He
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA 30602, USA.
| | - Dean P Jones
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, GA 30322, USA.
| | - Nikolay M Filipov
- Department of Physiology and Pharmacology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA; Interdisciplinary Toxicology Program, University of Georgia, Athens, GA 30602, USA.
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414
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Geidenstam N, Spégel P, Mulder H, Filipsson K, Ridderstråle M, Danielsson APH. Metabolite profile deviations in an oral glucose tolerance test-a comparison between lean and obese individuals. Obesity (Silver Spring) 2014; 22:2388-95. [PMID: 25132155 DOI: 10.1002/oby.20868] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2014] [Accepted: 07/25/2014] [Indexed: 12/11/2022]
Abstract
OBJECTIVE While impaired glucose tolerance diagnosed by the oral glucose tolerance test (OGTT) is a common trait in obese individuals, less is known about changes in levels of other metabolites. The aim was to reveal the complex alterations in metabolite levels provoked by an OGTT and its perturbation in obese individuals. METHODS Gas chromatography/mass spectrometry was used to profile metabolite levels in serum from 14 obese participants (body mass index [BMI] of 43.6 ± 1.5 kg m(-2) [mean ± SEM]) at 0, 30, and 120 min during a standard 2-h 75 g OGTT. Metabolite profiles from six lean individuals (BMI of 22.4 ± 2.4 kg m(-2) ), collected from a previous study, were included for comparison. RESULTS In the obese group, 59 metabolite profiles were determined. Among these, 16 deviated from profiles in the lean group. Deviating metabolites were categorized into three groups. Delayed reduction in levels of five fatty acids. Increased levels at 30 min of five amino acids, including isoleucine and leucine. A blunted increase at 30 min of six metabolites. CONCLUSIONS Metabolomics analysis revealed distinct differences in alterations of metabolite levels during an OGTT in obese and lean subjects. To this end, our data suggests a disrupted regulation of ketogenesis, lipolysis and proteolysis in obese individuals.
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Affiliation(s)
- Nina Geidenstam
- Department of Clinical Sciences, Malmö, Clinical Obesity, Lund University Diabetes Centre, Lund University, Sweden
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415
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Zhang Y, Hu C, Hong J, Zeng J, Lai S, Lv A, Su Q, Dong Y, Zhou Z, Tang W, Zhao J, Cui L, Zou D, Wang D, Li H, Liu C, Wu G, Shen J, Zhu D, Wang W, Shen W, Ning G, Xu G. Lipid profiling reveals different therapeutic effects of metformin and glipizide in patients with type 2 diabetes and coronary artery disease. Diabetes Care 2014; 37:2804-12. [PMID: 25011952 DOI: 10.2337/dc14-0090] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We recently demonstrated a beneficial effect of metformin compared with glipizide in type 2 diabetic patients regarding cardiovascular outcomes for 3-year treatment in the SPREAD-DIMCAD study. However, the potential mechanism for the clinical effects remains unclear. Here, we performed a comprehensive lipidomics study to evaluate the different lipid metabolites in serum samples obtained from participants in this study. RESEARCH DESIGN AND METHODS Liquid chromatography-quadrupole time of flight-mass spectrometry was used to evaluate the different lipid metabolites in serum samples obtained from the participants (21 patients in glipizide group and 23 patients in metformin group) before and after each year of treatment (at 0 [baseline], 1, 2, and 3 years of study drug administration). RESULTS A total of 118 serum lipid molecular species was identified and quantified. During treatment, metformin induced a substantially greater change in serum lipid species compared with glipizide, especially at the 2- and 3-year time points (with 2, 11, and 12 lipid species being significantly different between the groups after each year of treatment [1, 2, or 3 years], P < 0.05). Among the significantly changed lipid species, three lipid metabolites were linked to long-term composite cardiovascular events (adjusted P < 0.05). After treatment, triacylglycerols (TAGs) of a relatively higher carbon number showed a clearly increased trend in metformin group compared with the glipizide group, whereas the changes in TAGs with different double bonds were minimal. CONCLUSIONS Our findings revealed the differential therapeutic effects of metformin and glipizide on comprehensive lipidomics, which were comparable with their different long-term effects on cardiovascular outcomes.
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Affiliation(s)
- Yifei Zhang
- Ruijin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Chunxiu Hu
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Jie Hong
- Ruijin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Jun Zeng
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | | | - Ankang Lv
- Ruijin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Qing Su
- Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Yan Dong
- Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Zhiguang Zhou
- Second Xiangya Hospital of Central South University, Changsha, China
| | - Weili Tang
- Second Xiangya Hospital of Central South University, Changsha, China
| | - Jiajun Zhao
- Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Lianqun Cui
- Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Dajin Zou
- Chang Hai Hospital, Second Military Medical University, Shanghai, China
| | - Dawang Wang
- First Affiliated Hospital of Wenzhou Medical College, Zhejiang Province, China
| | - Hong Li
- Sir Run Run Shaw Hospital, Zhejiang Province, China
| | - Chao Liu
- Jiangsu Province Hospital, Jiangsu Province, China
| | - Guoting Wu
- Shanghai Tenth People's Hospital of Tongji University, Shanghai, China
| | - Jie Shen
- Nanfang Hospital, Guangdong Province, China
| | - Dalong Zhu
- Nanjin Drum Tower Hospital, Jiangsu Province, China
| | - Weiqing Wang
- Ruijin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Weifeng Shen
- Ruijin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Guang Ning
- Ruijin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Guowang Xu
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
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416
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Modi H, Cornu M, Thorens B. Glutamine stimulates biosynthesis and secretion of insulin-like growth factor 2 (IGF2), an autocrine regulator of beta cell mass and function. J Biol Chem 2014; 289:31972-31982. [PMID: 25271169 DOI: 10.1074/jbc.m114.587733] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
IGF2 is an autocrine ligand for the beta cell IGF1R receptor and GLP-1 increases the activity of this autocrine loop by enhancing IGF1R expression, a mechanism that mediates the trophic effects of GLP-1 on beta cell mass and function. Here, we investigated the regulation of IGF2 biosynthesis and secretion. We showed that glutamine rapidly and strongly induced IGF2 mRNA translation using reporter constructs transduced in MIN6 cells and primary islet cells. This was followed by rapid secretion of IGF2 via the regulated pathway, as revealed by the presence of mature IGF2 in insulin granule fractions and by inhibition of secretion by nimodipine and diazoxide. When maximally stimulated by glutamine, the amount of secreted IGF2 rapidly exceeded its initial intracellular pool and tolbutamide, and high K(+) increased IGF2 secretion only marginally. This indicates that the intracellular pool of IGF2 is small and that sustained secretion requires de novo synthesis. The stimulatory effect of glutamine necessitates its metabolism but not mTOR activation. Finally, exposure of insulinomas or beta cells to glutamine induced Akt phosphorylation, an effect that was dependent on IGF2 secretion, and reduced cytokine-induced apoptosis. Thus, glutamine controls the activity of the beta cell IGF2/IGF1R autocrine loop by increasing the biosynthesis and secretion of IGF2. This autocrine loop can thus integrate changes in feeding and metabolic state to adapt beta cell mass and function.
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Affiliation(s)
- Honey Modi
- Center for Integrative Genomics, University of Lausanne, CH-1015 Lausanne, Switzerland
| | - Marion Cornu
- Center for Integrative Genomics, University of Lausanne, CH-1015 Lausanne, Switzerland
| | - Bernard Thorens
- Center for Integrative Genomics, University of Lausanne, CH-1015 Lausanne, Switzerland.
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417
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Walford GA, Porneala BC, Dauriz M, Vassy JL, Cheng S, Rhee EP, Wang TJ, Meigs JB, Gerszten RE, Florez JC. Metabolite traits and genetic risk provide complementary information for the prediction of future type 2 diabetes. Diabetes Care 2014; 37:2508-14. [PMID: 24947790 PMCID: PMC4140156 DOI: 10.2337/dc14-0560] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE A genetic risk score (GRS) comprised of single nucleotide polymorphisms (SNPs) and metabolite biomarkers have each been shown, separately, to predict incident type 2 diabetes. We tested whether genetic and metabolite markers provide complementary information for type 2 diabetes prediction and, together, improve the accuracy of prediction models containing clinical traits. RESEARCH DESIGN AND METHODS Diabetes risk was modeled with a 62-SNP GRS, nine metabolites, and clinical traits. We fit age- and sex-adjusted logistic regression models to test the association of these sources of information, separately and jointly, with incident type 2 diabetes among 1,622 initially nondiabetic participants from the Framingham Offspring Study. The predictive capacity of each model was assessed by area under the curve (AUC). RESULTS Two hundred and six new diabetes cases were observed during 13.5 years of follow-up. The AUC was greater for the model containing the GRS and metabolite measurements together versus GRS or metabolites alone (0.820 vs. 0.641, P < 0.0001, or 0.820 vs. 0.803, P = 0.01, respectively). Odds ratios for association of GRS or metabolites with type 2 diabetes were not attenuated in the combined model. The AUC was greater for the model containing the GRS, metabolites, and clinical traits versus clinical traits only (0.880 vs. 0.856, P = 0.002). CONCLUSIONS Metabolite and genetic traits provide complementary information to each other for the prediction of future type 2 diabetes. These novel markers of diabetes risk modestly improve the predictive accuracy of incident type 2 diabetes based only on traditional clinical risk factors.
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Affiliation(s)
- Geoffrey A Walford
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Diabetes Unit, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA
| | - Bianca C Porneala
- General Medicine Division, Massachusetts General Hospital, Boston, MA
| | - Marco Dauriz
- Department of Medicine, Harvard Medical School, Boston, MA General Medicine Division, Massachusetts General Hospital, Boston, MA Division of Endocrinology and Metabolic Diseases, Department of Medicine, University of Verona Medical School and Hospital Trust of Verona, Verona, Italy
| | - Jason L Vassy
- Department of Medicine, Harvard Medical School, Boston, MA Section of General Internal Medicine, VA Boston Healthcare System, Boston, MA Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA
| | - Susan Cheng
- Department of Medicine, Harvard Medical School, Boston, MA Cardiovascular Division, Brigham and Women's Hospital, Boston, MA
| | - Eugene P Rhee
- Department of Medicine, Harvard Medical School, Boston, MA Renal Division, Massachusetts General Hospital, Boston, MA
| | - Thomas J Wang
- Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN
| | - James B Meigs
- Department of Medicine, Harvard Medical School, Boston, MA General Medicine Division, Massachusetts General Hospital, Boston, MA Framingham Heart Study of the National Heart, Lung, and Blood Institute, Framingham, MA
| | - Robert E Gerszten
- Department of Medicine, Harvard Medical School, Boston, MA Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA Cardiology Division, Massachusetts General Hospital, Boston, MA
| | - Jose C Florez
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Diabetes Unit, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
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418
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Auro K, Joensuu A, Fischer K, Kettunen J, Salo P, Mattsson H, Niironen M, Kaprio J, Eriksson JG, Lehtimäki T, Raitakari O, Jula A, Tiitinen A, Jauhiainen M, Soininen P, Kangas AJ, Kähönen M, Havulinna AS, Ala-Korpela M, Salomaa V, Metspalu A, Perola M. A metabolic view on menopause and ageing. Nat Commun 2014; 5:4708. [PMID: 25144627 DOI: 10.1038/ncomms5708] [Citation(s) in RCA: 173] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2013] [Accepted: 07/16/2014] [Indexed: 12/12/2022] Open
Abstract
The ageing of the global population calls for a better understanding of age-related metabolic consequences. Here we report the effects of age, sex and menopause on serum metabolites in 26,065 individuals of Northern European ancestry. Age-specific metabolic fingerprints differ significantly by gender and, in females, a substantial atherogenic shift overlapping the time of menopausal transition is observed. In meta-analysis of 10,083 women, menopause status associates with amino acids glutamine, tyrosine and isoleucine, along with serum cholesterol measures and atherogenic lipoproteins. Among 3,204 women aged 40-55 years, menopause status associates additionally with glycine and total, monounsaturated, and omega-7 and -9 fatty acids. Our findings suggest that, in addition to lipid alterations, menopause may contribute to future metabolic and cardiovascular risk via influencing amino-acid concentrations, adding to the growing evidence of the importance of amino acids in metabolic disease progression. These observations shed light on the metabolic consequences of ageing, gender and menopause at the population level.
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Affiliation(s)
- Kirsi Auro
- 1] Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Biomedicum 1, Haartmaninkatu 8, Helsinki 00290, Finland [2] Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum 2, Tukholmankatu 8, Helsinki 00290, Finland [3] Department of Obstetrics and Gynecology, Helsinki University Central Hospital and University of Helsinki, Haartmaninkatu 2, Helsinki 00290, Finland [4]
| | - Anni Joensuu
- 1] Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Biomedicum 1, Haartmaninkatu 8, Helsinki 00290, Finland [2] Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum 2, Tukholmankatu 8, Helsinki 00290, Finland [3]
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Riia 23b, Tartu 51010, Estonia
| | - Johannes Kettunen
- 1] Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Biomedicum 1, Haartmaninkatu 8, Helsinki 00290, Finland [2] Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum 2, Tukholmankatu 8, Helsinki 00290, Finland [3] Computational Medicine, Institute of Health Sciences, University of Oulu, Pentti Kaiteran katu 1, Oulu 90570, Finland
| | - Perttu Salo
- 1] Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Biomedicum 1, Haartmaninkatu 8, Helsinki 00290, Finland [2] Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum 2, Tukholmankatu 8, Helsinki 00290, Finland
| | - Hannele Mattsson
- 1] Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Biomedicum 1, Haartmaninkatu 8, Helsinki 00290, Finland [2] Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum 2, Tukholmankatu 8, Helsinki 00290, Finland
| | - Marjo Niironen
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Biomedicum 1, Haartmaninkatu 8, Helsinki 00290, Finland
| | - Jaakko Kaprio
- 1] Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum 2, Tukholmankatu 8, Helsinki 00290, Finland [2] Departmentof Public Health, Hjelt Institute, University of Helsinki, PO Box 41 Mannerheimintie 172, Helsinki 00014, Finland [3] Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, PO Box 30 (Mannerheimintie 166), Helsinki 00300, Finland
| | - Johan G Eriksson
- 1] Chronic Disease Epidemiology and Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland [2] Department of General Practice and Primary Health Care, University of Helsinki, PL 20, Tukholmankatu 8B, Helsinki 00029, Finland [3] Vasa Central Hospital, Sandviksgatan 2-4, Vasa 65130, Finland [4] Folkhälsan Research Centre, Helsingfors Universitet, PB 63, Helsinki 00014, Finland [5] Unit of General Practice, Helsinki University Central Hospital, Haartmaninkatu 4, Helsinki 00290, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere University, Kalevantie 4, Tampere 33014, Finland
| | - Olli Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, Turku University Hospital, University of Turku, Kiinamyllynkatu 4-8, Turku 20521, Finland
| | - Antti Jula
- Chronic Disease Epidemiology and Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland
| | - Aila Tiitinen
- Department of Obstetrics and Gynecology, Helsinki University Central Hospital and University of Helsinki, Haartmaninkatu 2, Helsinki 00290, Finland
| | - Matti Jauhiainen
- 1] Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Biomedicum 1, Haartmaninkatu 8, Helsinki 00290, Finland [2] Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum 2, Tukholmankatu 8, Helsinki 00290, Finland
| | - Pasi Soininen
- 1] Computational Medicine, Institute of Health Sciences, University of Oulu, Pentti Kaiteran katu 1, Oulu 90570, Finland [2] NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Yliopistonranta 1 PL 1627, Kuopio 70211, Finland
| | - Antti J Kangas
- 1] Computational Medicine, Institute of Health Sciences, University of Oulu, Pentti Kaiteran katu 1, Oulu 90570, Finland [2] NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Yliopistonranta 1 PL 1627, Kuopio 70211, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and University of Tampere School of Medicine, Tampere University, Kalevantie 4, Tampere 33014, Finland
| | - Aki S Havulinna
- Chronic Disease Epidemiology and Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland
| | - Mika Ala-Korpela
- 1] Computational Medicine, Institute of Health Sciences, University of Oulu, Pentti Kaiteran katu 1, Oulu 90570, Finland [2] NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Yliopistonranta 1 PL 1627, Kuopio 70211, Finland [3] Oulu University Hospital, Kajaanintie 50, Oulu 90220, Finland [4] Computational Medicine, School of Social and Community Medicine and Medical Research Council Integrative Epidemiology Unit, University of Bristol, Senate House, Tyndall Avenue, Bristol, City of Bristol BS8 1TH, UK
| | - Veikko Salomaa
- Chronic Disease Epidemiology and Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Riia 23b, Tartu 51010, Estonia
| | - Markus Perola
- 1] Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Biomedicum 1, Haartmaninkatu 8, Helsinki 00290, Finland [2] Institute for Molecular Medicine (FIMM), University of Helsinki, Biomedicum 2, Tukholmankatu 8, Helsinki 00290, Finland [3] Estonian Genome Center, University of Tartu, Riia 23b, Tartu 51010, Estonia
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419
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Cummins TD, Holden CR, Sansbury BE, Gibb AA, Shah J, Zafar N, Tang Y, Hellmann J, Rai SN, Spite M, Bhatnagar A, Hill BG. Metabolic remodeling of white adipose tissue in obesity. Am J Physiol Endocrinol Metab 2014; 307:E262-77. [PMID: 24918202 PMCID: PMC4121575 DOI: 10.1152/ajpendo.00271.2013] [Citation(s) in RCA: 116] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Adipose tissue metabolism is a critical regulator of adiposity and whole body energy expenditure; however, metabolic changes that occur in white adipose tissue (WAT) with obesity remain unclear. The purpose of this study was to understand the metabolic and bioenergetic changes occurring in WAT with obesity. Wild-type (C57BL/6J) mice fed a high-fat diet (HFD) showed significant increases in whole body adiposity, had significantly lower V̇(O₂), V̇(CO₂), and respiratory exchange ratios, and demonstrated worsened glucose and insulin tolerance compared with low-fat-fed mice. Metabolomic analysis of WAT showed marked changes in lipid, amino acid, carbohydrate, nucleotide, and energy metabolism. Tissue levels of succinate and malate were elevated, and metabolites that could enter the Krebs cycle via anaplerosis were mostly diminished in high-fat-fed mice, suggesting altered mitochondrial metabolism. Despite no change in basal oxygen consumption or mitochondrial DNA abundance, citrate synthase activity was decreased by more than 50%, and responses to FCCP were increased in WAT from mice fed a high-fat diet. Moreover, Pgc1a was downregulated and Cox7a1 upregulated after 6 wk of HFD. After 12 wk of high-fat diet, the abundance of several proteins in the mitochondrial respiratory chain or matrix was diminished. These changes were accompanied by increased Parkin and Pink1, decreased p62 and LC3-I, and ultrastructural changes suggestive of autophagy and mitochondrial remodeling. These studies demonstrate coordinated restructuring of metabolism and autophagy that could contribute to the hypertrophy and whitening of adipose tissue in obesity.
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Affiliation(s)
- Timothy D Cummins
- Institute of Molecular Cardiology, Department of Medicine; Diabetes and Obesity Center
| | - Candice R Holden
- Institute of Molecular Cardiology, Department of Medicine; Diabetes and Obesity Center; Department of Physiology and Biophysics; and
| | - Brian E Sansbury
- Institute of Molecular Cardiology, Department of Medicine; Diabetes and Obesity Center; Department of Physiology and Biophysics; and
| | - Andrew A Gibb
- Institute of Molecular Cardiology, Department of Medicine; Diabetes and Obesity Center; Department of Physiology and Biophysics; and
| | - Jasmit Shah
- Diabetes and Obesity Center; Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, Kentucky
| | - Nagma Zafar
- Diabetes and Obesity Center; Department of Physiology and Biophysics; and
| | | | - Jason Hellmann
- Institute of Molecular Cardiology, Department of Medicine; Diabetes and Obesity Center
| | - Shesh N Rai
- Diabetes and Obesity Center; Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, Kentucky
| | - Matthew Spite
- Institute of Molecular Cardiology, Department of Medicine; Diabetes and Obesity Center; Department of Physiology and Biophysics; and
| | - Aruni Bhatnagar
- Institute of Molecular Cardiology, Department of Medicine; Diabetes and Obesity Center; Department of Biochemistry and Molecular Biology; Department of Physiology and Biophysics; and
| | - Bradford G Hill
- Institute of Molecular Cardiology, Department of Medicine; Diabetes and Obesity Center; Department of Biochemistry and Molecular Biology; Department of Physiology and Biophysics; and
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420
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Tzoulaki I, Ebbels TMD, Valdes A, Elliott P, Ioannidis JPA. Design and analysis of metabolomics studies in epidemiologic research: a primer on -omic technologies. Am J Epidemiol 2014; 180:129-39. [PMID: 24966222 DOI: 10.1093/aje/kwu143] [Citation(s) in RCA: 133] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Metabolomics is the field of "-omics" research concerned with the comprehensive characterization of the small low-molecular-weight metabolites in biological samples. In epidemiology, it represents an emerging technology and an unprecedented opportunity to measure environmental and other exposures with improved precision and far less measurement error than with standard epidemiologic methods. Advances in the application of metabolomics in large-scale epidemiologic research are now being realized through a combination of improved sample preparation and handling, automated laboratory and processing methods, and reduction in costs. The number of epidemiologic studies that use metabolic profiling is still limited, but it is fast gaining popularity in this area. In the present article, we present a roadmap for metabolomic analyses in epidemiologic studies and discuss the various challenges these data pose to large-scale studies. We discuss the steps of data preprocessing, univariate and multivariate data analysis, correction for multiplicity of comparisons with correlated data, and finally the steps of cross-validation and external validation. As data from metabolomic studies accumulate in epidemiology, there is a need for large-scale replication and synthesis of findings, increased availability of raw data, and a focus on good study design, all of which will highlight the potential clinical impact of metabolomics in this field.
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421
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Rietman A, Schwarz J, Tomé D, Kok FJ, Mensink M. High dietary protein intake, reducing or eliciting insulin resistance? Eur J Clin Nutr 2014; 68:973-9. [DOI: 10.1038/ejcn.2014.123] [Citation(s) in RCA: 113] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2013] [Revised: 05/13/2014] [Accepted: 05/21/2014] [Indexed: 02/07/2023]
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422
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Min HK, Sookoian S, Pirola CJ, Cheng J, Mirshahi F, Sanyal AJ. Metabolic profiling reveals that PNPLA3 induces widespread effects on metabolism beyond triacylglycerol remodeling in Huh-7 hepatoma cells. Am J Physiol Gastrointest Liver Physiol 2014; 307:G66-76. [PMID: 24763554 PMCID: PMC4080161 DOI: 10.1152/ajpgi.00335.2013] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
PNPLA3 was recently associated with the susceptibility to nonalcoholic fatty liver disease, a common cause of chronic liver disease characterized by abnormal triglyceride accumulation. Although it is established that PNPLA3 has both triacylglycerol lipase and acylglycerol O-acyltransferase activities, is still unknown whether the gene has any additional role in the modulation of the human liver metabolome. To uncover the functional role of PNPLA3 on liver metabolism, we performed high-throughput metabolic profiling of PNPLA3 siRNA-silencing and overexpression of wild-type and mutant Ile148Met variants (isoleucine/methionine substitution at codon 148) in Huh-7 cells. Metabolomic analysis was performed by using GC/MS and LC/MS platforms. Silencing of PNPLA3 was associated with a global perturbation of Huh-7 hepatoma cells that resembled a catabolic response associated with protein breakdown. A significant decrease in amino- and γ-glutamyl-amino acids and dipeptides and a significant increase in cysteine sulfinic acid, myo-inositol, lysolipids, sphingolipids, and polyunsaturated fatty acids were observed. Overexpression of the PNPLA3 Met148 variant mirrored many of the metabolic changes observed during gene silencing, but in the opposite direction. These findings were replicated by the exploration of canonical pathways associated with PNPLA3 silencing and Met148 overexpression. Overexpression of the PNPLA3 Met148 variant was associated with a 1.75-fold increase in lactic acid, suggesting a shift to anaerobic metabolism and mitochondrial dysfunction. Together, these results suggest a critical role of PNPLA3 in the modulation of liver metabolism beyond its classical participation in triacylglycerol remodeling.
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Affiliation(s)
- Hae-Ki Min
- 1Division of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, Virginia; and
| | - Silvia Sookoian
- 2Department of Clinical and Molecular Hepatology and Molecular Genetics and Biology of Complex Diseases, Institute of Medical Research, IDIM, University of Buenos Aires-National Scientific and Technical Research Council (CONICET), Ciudad Autónoma de Buenos Aires, Argentina
| | - Carlos J. Pirola
- 2Department of Clinical and Molecular Hepatology and Molecular Genetics and Biology of Complex Diseases, Institute of Medical Research, IDIM, University of Buenos Aires-National Scientific and Technical Research Council (CONICET), Ciudad Autónoma de Buenos Aires, Argentina
| | - Jianfeng Cheng
- 1Division of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, Virginia; and
| | - Faridoddin Mirshahi
- 1Division of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, Virginia; and
| | - Arun J. Sanyal
- 1Division of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, Virginia; and
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423
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Vaarhorst AAM, Verhoeven A, Weller CM, Böhringer S, Göraler S, Meissner A, Deelder AM, Henneman P, Gorgels APM, van den Brandt PA, Schouten LJ, van Greevenbroek MM, Merry AHH, Verschuren WMM, van den Maagdenberg AMJM, van Dijk KW, Isaacs A, Boomsma D, Oostra BA, van Duijn CM, Jukema JW, Boer JMA, Feskens E, Heijmans BT, Slagboom PE. A metabolomic profile is associated with the risk of incident coronary heart disease. Am Heart J 2014; 168:45-52.e7. [PMID: 24952859 DOI: 10.1016/j.ahj.2014.01.019] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2013] [Accepted: 01/24/2014] [Indexed: 11/28/2022]
Abstract
BACKGROUND Metabolomics, defined as the comprehensive identification and quantification of low-molecular-weight metabolites to be found in a biological sample, has been put forward as a potential tool for classifying individuals according to their risk of coronary heart disease (CHD). Here, we investigated whether a single-point blood measurement of the metabolome is associated with and predictive for the risk of CHD. METHODS AND RESULTS We obtained proton nuclear magnetic resonance spectra in 79 cases who developed CHD during follow-up (median 8.1 years) and in 565 randomly selected individuals. In these spectra, 100 signals representing 36 metabolites were identified. Applying least absolute shrinkage and selection operator regression, we defined a weighted metabolite score consisting of 13 proton nuclear magnetic resonance signals that optimally predicted CHD. This metabolite score, including signals representing a lipid fraction, glucose, valine, ornithine, glutamate, creatinine, glycoproteins, citrate, and 1.5-anhydrosorbitol, was associated with the incidence of CHD independent of traditional risk factors (TRFs) (hazard ratio 1.50, 95% CI 1.12-2.01). Predictive performance of this metabolite score on its own was moderate (C-index 0.75, 95% CI 0.70-0.80), but after adding age and sex, the C-index was only modestly lower than that of TRFs (C-index 0.81, 95% CI 0.77-0.85 and C-index 0.82, 95% CI 0.78-0.87, respectively). The metabolite score was also associated with prevalent CHD independent of TRFs (odds ratio 1.59, 95% CI 1.19-2.13). CONCLUSION A metabolite score derived from a single-point metabolome measurement is associated with CHD, and metabolomics may be a promising tool for refining and improving the prediction of CHD.
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Affiliation(s)
- Anika A M Vaarhorst
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
| | - Aswin Verhoeven
- Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands
| | - Claudia M Weller
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Stefan Böhringer
- Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Sibel Göraler
- Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands
| | - Axel Meissner
- Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands
| | - André M Deelder
- Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands
| | - Peter Henneman
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Anton P M Gorgels
- Department of Cardiology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Piet A van den Brandt
- Department of Epidemiology (CAPHRI School for Public Health and Primary Care), Maastricht University, Maastricht, The Netherlands; Department of Epidemiology (GROW School of Oncology and Developmental Biology), Maastricht University, Maastricht, The Netherlands
| | - Leo J Schouten
- Department of Epidemiology (GROW School of Oncology and Developmental Biology), Maastricht University, Maastricht, The Netherlands
| | - Marleen M van Greevenbroek
- Department of Internal Medicine (CARIM School for Cardiovascular diseases), Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Audrey H H Merry
- Department of Epidemiology (CAPHRI School for Public Health and Primary Care), Maastricht University, Maastricht, The Netherlands
| | | | - Arn M J M van den Maagdenberg
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands; Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands; Department of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Aaron Isaacs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Dorret Boomsma
- Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Ben A Oostra
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands; The Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands; Interuniversity Cardiology Institute of the Netherlands (ICIN), Utrecht, The Netherlands
| | - Jolanda M A Boer
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Edith Feskens
- Division of Human Nutrition, Wageningen University and Research Center, Wageningen, The Netherlands
| | - Bastiaan T Heijmans
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - P Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands; Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands.
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424
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Badoud F, Lam KP, DiBattista A, Perreault M, Zulyniak MA, Cattrysse B, Stephenson S, Britz-McKibbin P, Mutch DM. Serum and adipose tissue amino acid homeostasis in the metabolically healthy obese. J Proteome Res 2014; 13:3455-66. [PMID: 24933025 DOI: 10.1021/pr500416v] [Citation(s) in RCA: 98] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
A subgroup of obese individuals, referred to as metabolically healthy obese (MHO), have preserved insulin sensitivity and a normal lipid profile despite being obese. The molecular basis for this improved cardiometabolic profile remains unclear. Our objective was to integrate metabolite and gene expression profiling to elucidate the molecular distinctions between MHO and metabolically unhealthy obese (MUO) phenotypes. A subset of individuals were selected from the Diabetes Risk Assessment study and classified into three groups using anthropometric and clinical measurements: lean healthy (LH), MHO, and MUO. Serum metabolites were profiled using gas chromatography coupled to mass spectrometry. Multivariate data analysis uncovered metabolites that differed between groups, and these were subsequently validated by capillary electrophoresis coupled to mass spectrometry. Subcutaneous adipose tissue (SAT) gene expression profiling using microarrays was performed in parallel. Amino acids were the most relevant class of metabolites distinguishing MHO from MUO individuals. Serum levels of glutamic acid, valine, and isoleucine were positively associated (i.e., LH < MHO < MUO) with homeostasis model assessment-insulin resistance (HOMA-IR) and glycated hemoglobin (HbA1c) values, while leucine was only correlated with HOMA-IR. The glutamine-to-glutamic acid ratio and glycine were inversely correlated (i.e., LH > MHO > MUO) with HbA1c values. Concomitantly, SAT gene expression profiling revealed that genes related to branched-chain amino acid catabolism and the tricarboxylic acid cycle were less down-regulated in MHO individuals compared to MUO individuals. Together, this integrated analysis revealed that MHO individuals have an intermediate amino acid homeostasis compared to LH and MUO individuals.
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Affiliation(s)
- Flavia Badoud
- Department of Human Health and Nutritional Sciences, University of Guelph , Guelph N1G 2W1, ON, Canada
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425
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Yang R, Dong J, Zhao H, Li H, Guo H, Wang S, Zhang C, Wang S, Wang M, Yu S, Chen W. Association of branched-chain amino acids with carotid intima-media thickness and coronary artery disease risk factors. PLoS One 2014; 9:e99598. [PMID: 24910999 PMCID: PMC4049830 DOI: 10.1371/journal.pone.0099598] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Accepted: 05/16/2014] [Indexed: 12/26/2022] Open
Abstract
Background Recent studies have determined that branched-chain (BCAAs) and aromatic (AAAs) amino acids are strongly correlated with obesity and atherogenic dyslipidemia and are strong predictors of diabetes. However, it is not clear if these amino acids are capable of identifying subjects with coronary artery disease (CAD), particularly with subclinical atherosclerosis who are at risk of developing CAD. Methods Four hundred and seventy two Chinese subjects (272 males and 200 females, 42–97 y of age) undergoing physical exams were recruited at random for participation in the cross-sectional study. Serum BCAAs and AAAs were measured using our previously reported isotope dilution liquid chromatography tandem mass spectrometry method. Bilateral B-mode carotid artery images for carotid intima-media thickness (cIMT) were acquired at end diastole and cIMT values more than 0.9 mm were categorized as increased. Correlations of BCAAs with cIMT and other CAD risk factors were analyzed. Results BCAAs and AAAs were significantly and positively associated with risk factors of CAD, e.g., cIMT, BMI, waist circumference, blood pressure, fasting blood glucose, TG, apoB, apoB/apoAI ratio, apoCII, apoCIII and hsCRP, and were significantly and negatively associated with HDL-C and apoAI. Stepwise multiple linear regression analysis revealed that age (β = 0.175, P<0.001), log BCAA (β = 0.147, P<0.001) and systolic blood pressure (β = 0.141, P = 0.012) were positively and independently associated with cIMT. In the logistic regression model, the most and only powerful laboratory factor correlated with increased cIMT was BCAA (the odds ratio of the fourth quartile compared to the first quartile was 2.679; P = 0.009). Conclusion BCAAs are independently correlated with increased cIMT. This correlation would open a new field of research in the mechanistic understanding and risk assessment of CAD.
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Affiliation(s)
- Ruiyue Yang
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing, China
| | - Jun Dong
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing, China
| | - Haijian Zhao
- Beijing Hospital and National Center for Clinical Laboratories, Ministry of Health, Beijing, China
| | - Hongxia Li
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing, China
| | - Hanbang Guo
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing, China
| | - Shu Wang
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing, China
| | - Chuanbao Zhang
- Beijing Hospital and National Center for Clinical Laboratories, Ministry of Health, Beijing, China
| | - Siming Wang
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing, China
| | - Mo Wang
- Beijing Hospital and National Center for Clinical Laboratories, Ministry of Health, Beijing, China
| | - Songlin Yu
- Beijing Hospital and National Center for Clinical Laboratories, Ministry of Health, Beijing, China
| | - Wenxiang Chen
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing, China
- Beijing Hospital and National Center for Clinical Laboratories, Ministry of Health, Beijing, China
- * E-mail:
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426
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Metabolomic Analysis Reveals Amino Acid Responses to an Oral Glucose Tolerance Test in Women with Prior History of Gestational Diabetes Mellitus. JOURNAL OF CLINICAL AND TRANSLATIONAL ENDOCRINOLOGY 2014; 1:38-43. [PMID: 24932438 PMCID: PMC4052833 DOI: 10.1016/j.jcte.2014.03.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Objective Although gestational diabetes mellitus (GDM) is associated with an increased risk of type 2 diabetes mellitus (T2DM) compared to normoglycemic pregnancies, the biochemical pathways underlying the progression of GDM to T2DM are not fully elucidated. The purpose of this exploratory study was to utilize metabolomics with an oral glucose tolerance test (OGTT) to examine the amino acid response in women with prior GDM to determine if a relationship between these metabolites and established risk factors for T2DM exists. Materials/methods Thirty-eight non-pregnant women without diabetes but with prior GDM within the previous 3 years were recruited from a community-based population. A 75 g-OGTT was administered; fasting and 2-h plasma samples were obtained. Metabolite profiles of 23 amino acids or amino acid derivatives were measured with gas chromatography-mass spectrometry. Measures of insulin resistance were derived from the OGTT and risk factors for T2DM were obtained by self-report. Results Twenty-two metabolite levels decreased significantly in response to the OGTT (p < 0.05). The clinical covariates most powerfully associated with metabolite level changes included race, body mass index (BMI), and duration of prior breastfeeding, (mean ± SD of standardized β-coefficients, β = −0.38 ± 0.05, 0.25 ± 0.08, and 0.44 ± 0.03, respectively, all p < 0.05). Notably, a prior history of breastfeeding was associated with the greatest number of metabolite changes. Conclusions Greater change in metabolite levels after a glucose challenge was significantly associated with a longer duration of breastfeeding and higher BMI. Further exploration of these preliminary observations and closer examination of the specific pathways implicated are warranted. We explored metabolite responses in women with prior gestational diabetes mellitus We used the oral glucose tolerance test as the provocative measure in this study Women with prior gestational diabetes mellitus were stratified by glucose tolerance We examined the relationship between metabolomic and clinical/behavioral parameters Greater change in metabolites was strongly associated with breastfeeding duration
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427
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Feuer SK, Liu X, Donjacour A, Lin W, Simbulan RK, Giritharan G, Piane LD, Kolahi K, Ameri K, Maltepe E, Rinaudo PF. Use of a mouse in vitro fertilization model to understand the developmental origins of health and disease hypothesis. Endocrinology 2014; 155:1956-69. [PMID: 24684304 PMCID: PMC3990843 DOI: 10.1210/en.2013-2081] [Citation(s) in RCA: 94] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The Developmental Origins of Health and Disease hypothesis holds that alterations to homeostasis during critical periods of development can predispose individuals to adult-onset chronic diseases such as diabetes and metabolic syndrome. It remains controversial whether preimplantation embryo manipulation, clinically used to treat patients with infertility, disturbs homeostasis and affects long-term growth and metabolism. To address this controversy, we have assessed the effects of in vitro fertilization (IVF) on postnatal physiology in mice. We demonstrate that IVF and embryo culture, even under conditions considered optimal for mouse embryo culture, alter postnatal growth trajectory, fat accumulation, and glucose metabolism in adult mice. Unbiased metabolic profiling in serum and microarray analysis of pancreatic islets and insulin sensitive tissues (liver, skeletal muscle, and adipose tissue) revealed broad changes in metabolic homeostasis, characterized by systemic oxidative stress and mitochondrial dysfunction. Adopting a candidate approach, we identify thioredoxin-interacting protein (TXNIP), a key molecule involved in integrating cellular nutritional and oxidative states with metabolic response, as a marker for preimplantation stress and demonstrate tissue-specific epigenetic and transcriptional TXNIP misregulation in selected adult tissues. Importantly, dysregulation of TXNIP expression is associated with enrichment for H4 acetylation at the Txnip promoter that persists from the blastocyst stage through adulthood in adipose tissue. Our data support the vulnerability of preimplantation embryos to environmental disturbance and demonstrate that conception by IVF can reprogram metabolic homeostasis through metabolic, transcriptional, and epigenetic mechanisms with lasting effects for adult growth and fitness. This study has wide clinical relevance and underscores the importance of continued follow-up of IVF-conceived offspring.
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Affiliation(s)
- Sky K Feuer
- Department of Obstetrics, Gynecology and Reproductive Sciences (S.K.F., X.L., A.D., W.L., R.K.S., G.G., L.D.P., K.K., P.F.R.), and Department of Pediatrics (K.A., E.M.), University of California San Francisco, San Francisco, California 94143; Nevada Center for Reproductive Medicine (G.G.), Reno, Nevada 89511; Obstetric and Gynecology Department (L.D.P.), University of Turin, Turin, Italy; and Oregon Health & Science University (K.K.), Portland, Oregon 97239
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Voros S. Leveraging next-generation phenotyping and pan-omics to identify novel biomarkers and pharmaceutical targets for cardiovascular disease. Per Med 2014; 11:239-242. [PMID: 29764059 DOI: 10.2217/pme.14.6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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429
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Sansbury BE, DeMartino AM, Xie Z, Brooks AC, Brainard RE, Watson LJ, DeFilippis AP, Cummins TD, Harbeson MA, Brittian KR, Prabhu SD, Bhatnagar A, Jones SP, Hill BG. Metabolomic analysis of pressure-overloaded and infarcted mouse hearts. Circ Heart Fail 2014; 7:634-42. [PMID: 24762972 DOI: 10.1161/circheartfailure.114.001151] [Citation(s) in RCA: 173] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cardiac hypertrophy and heart failure are associated with metabolic dysregulation and a state of chronic energy deficiency. Although several disparate changes in individual metabolic pathways have been described, there has been no global assessment of metabolomic changes in hypertrophic and failing hearts in vivo. Hence, we investigated the impact of pressure overload and infarction on myocardial metabolism. METHODS AND RESULTS Male C57BL/6J mice were subjected to transverse aortic constriction or permanent coronary occlusion (myocardial infarction [MI]). A combination of LC/MS/MS and GC/MS techniques was used to measure 288 metabolites in these hearts. Both transverse aortic constriction and MI were associated with profound changes in myocardial metabolism affecting up to 40% of all metabolites measured. Prominent changes in branched-chain amino acids were observed after 1 week of transverse aortic constriction and 5 days after MI. Changes in branched-chain amino acids after MI were associated with myocardial insulin resistance. Longer duration of transverse aortic constriction and MI led to a decrease in purines, acylcarnitines, fatty acids, and several lysolipid and sphingolipid species but a marked increase in pyrimidines as well as ascorbate, heme, and other indices of oxidative stress. Cardiac remodeling and contractile dysfunction in hypertrophied hearts were associated with large increases in myocardial, but not plasma, levels of the polyamines putrescine and spermidine as well as the collagen breakdown product prolylhydroxyproline. CONCLUSIONS These findings reveal extensive metabolic remodeling common to both hypertrophic and failing hearts that are indicative of extracellular matrix remodeling, insulin resistance and perturbations in amino acid, and lipid and nucleotide metabolism.
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Affiliation(s)
- Brian E Sansbury
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Angelica M DeMartino
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Zhengzhi Xie
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Alan C Brooks
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Robert E Brainard
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Lewis J Watson
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Andrew P DeFilippis
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Timothy D Cummins
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Matthew A Harbeson
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Kenneth R Brittian
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Sumanth D Prabhu
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Aruni Bhatnagar
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Steven P Jones
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.)
| | - Bradford G Hill
- From the Department of Medicine, Institute of Molecular Cardiology, Division of Cardiology (B.E.S., A.M.D.M., Z.X., A.C.B., R.E.B., L.J.W., A.P.D., K.R.B., A.B., S.P.J., B.G.H.), Department of Medicine, Diabetes and Obesity Center (B.E.S., Z.X., A.C.B., T.D.C., M.A.H., K.R.B., A.B., S.P.J., B.G.H.), Department of Biochemistry and Molecular Biology (A.C.B., A.B., B.G.H.), and Department of Physiology and Biophysics (B.E.S., A.M.D., R.E.B., L.J.W., A.B., S.P.J., B.G.H.), University of Louisville, KY; Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, and Birmingham VAMC, AL (S.D.P.); and Department of Medicine, Johns Hopkins University, Baltimore, MD (A.P.D.).
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430
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Wewalka M, Patti ME, Barbato C, Houten SM, Goldfine AB. Fasting serum taurine-conjugated bile acids are elevated in type 2 diabetes and do not change with intensification of insulin. J Clin Endocrinol Metab 2014; 99:1442-51. [PMID: 24432996 PMCID: PMC5393473 DOI: 10.1210/jc.2013-3367] [Citation(s) in RCA: 97] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
CONTEXT Bile acids (BAs) are newly recognized signaling molecules in glucose and energy homeostasis. Differences in BA profiles with type 2 diabetes mellitus (T2D) remain incompletely understood. OBJECTIVE The objective of the study was to assess serum BA composition in impaired glucose-tolerant, T2D, and normal glucose-tolerant persons and to monitor the effects of improving glycemia on serum BA composition in T2D patients. DESIGN AND SETTING This was a cross-sectional cohort study in a general population (cohort 1) and nonrandomized intervention (cohort 2). PATIENTS AND INTERVENTIONS Ninety-nine volunteers underwent oral glucose tolerance testing, and 12 persons with T2D and hyperglycemia underwent 8 weeks of intensification of treatment. MAIN OUTCOME MEASURES Serum free BA and respective taurine and glycine conjugates were measured by HPLC tandem mass spectrometry. RESULTS Oral glucose tolerance testing identified 62 normal-, 25 impaired glucose-tolerant, and 12 T2D persons. Concentrations of total taurine-conjugated BA were higher in T2D and intermediate in impaired- compared with normal glucose-tolerant persons (P = .009). Univariate regression revealed a positive association between total taurine-BA and fasting glucose (R = 0.37, P < .001), postload glucose (R = 0.31, P < .002), hemoglobin A1c (R = 0.26, P < .001), fasting insulin (R = 0.21, P = .03), and homeostatic model assessment-estimated insulin resistance (R = 0.26, P = .01) and an inverse association with oral disposition index (R = -0.36, P < .001). Insulin-mediated glycemic improvement in T2D patients did not change fasting serum total BA or BA composition. CONCLUSION Fasting taurine-conjugated BA concentrations are higher in T2D and intermediate in impaired compared with normal glucose-tolerant persons and are associated with fasting and postload glucose. Serum BAs are not altered in T2D in response to improved glycemia. Further study may elucidate whether this pattern of taurine-BA conjugation can be targeted to provide novel therapeutic approaches to treat T2D.
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Affiliation(s)
- Marlene Wewalka
- Joslin Diabetes Center (M.W., M.-E.P., C.B., A.B.G.), Boston, Massachusetts 02215; Harvard Medical School (M.W., M.-E.P., A.B.G.), Harvard University, Boston, Massachusetts 02115; and Laboratory Genetic Metabolic Diseases (S.M.H.), Departments of Clinical Chemistry and Pediatrics, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
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431
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Moore SC, Matthews CE, Sampson JN, Stolzenberg-Solomon RZ, Zheng W, Cai Q, Tan YT, Chow WH, Ji BT, Liu DK, Xiao Q, Boca SM, Leitzmann MF, Yang G, Xiang YB, Sinha R, Shu XO, Cross AJ. Human metabolic correlates of body mass index. Metabolomics 2014; 10:259-269. [PMID: 25254000 PMCID: PMC4169991 DOI: 10.1007/s11306-013-0574-1] [Citation(s) in RCA: 138] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND A high body mass index (BMI) is a major risk factor for several chronic diseases, but the biology underlying these associations is not well-understood. Dyslipidemia, inflammation, and elevated levels of growth factors and sex steroid hormones explain some of the increased disease risk, but other metabolic factors not yet identified may also play a role. DESIGN In order to discover novel metabolic biomarkers of BMI, we used non-targeted metabolomics to assay 317 metabolites in blood samples from 947 participants and examined the cross-sectional associations between metabolite levels and BMI. Participants were from three studies in the United States and China. Height, weight, and potential confounders were ascertained by questionnaire (US studies) or direct measurement (Chinese study). Metabolite levels were measured using liquid-phase chromatography and gas chromatography coupled with mass spectrometry. We evaluated study-specific associations using linear regression, adjusted for age, gender, and smoking, and we estimated combined associations using random effects meta-analysis. RESULTS The meta-analysis revealed 37 metabolites significantly associated with BMI, including 19 lipids, 12 amino acids, and 6 others, at the Bonferroni significance threshold (p<0.00016). Eighteen of these associations had not been previously reported, including histidine, an amino acid neurotransmitter, and butyrylcarnitine, a lipid marker of whole-body fatty acid oxidation. Heterogeneity by study was minimal (all Pheterogeneity >0.05). In total, 110 metabolites were associated with BMI at the p<0.05 level. CONCLUSION These findings establish a baseline for the BMI metabolome, and suggest new targets for researchers attempting to clarify mechanistic links between high BMIs and disease risk.
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Affiliation(s)
- Steven C. Moore
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Charles E. Matthews
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Joshua N. Sampson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | | | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
| | | | - Wong-Ho Chow
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Bu-Tian Ji
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Da Ke Liu
- Shanghai Cancer Institute, Shanghai, China
| | - Qian Xiao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Simina M. Boca
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Michael F. Leitzmann
- Department of Epidemiology and Preventive Medicine, Regensburg University Medical Center, Franz-Josef-Strauss-Allee 11, 93053 Regensburg, Germany
| | - Gong Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
| | | | - Rashmi Sinha
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Xiao Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Amanda J. Cross
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
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Gao J, Yang H, Chen J, Fang J, Chen C, Liang R, Yang G, Wu H, Wu C, Li S. Analysis of serum metabolites for the discovery of amino acid biomarkers and the effect of galangin on cerebral ischemia. MOLECULAR BIOSYSTEMS 2014; 9:2311-21. [PMID: 23793526 DOI: 10.1039/c3mb70040b] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Ischemic stroke, a devastating disease with a complex pathophysiology, is a leading cause of death and disability worldwide. In our previous study, we reported that galangin provided direct protection against ischemic injury and acted as a potential neuroprotective agent. However, its associated neuroprotective mechanism has not yet been clarified. In this paper, we explored the potential AA biomarkers in the acute phase of cerebral ischemia and the effect of galangin on those potential biomarkers. In our study, 12 AAs were quantified in rat serum and found to be impaired by middle cerebral artery occlusion (MCAO)-induced focal cerebral ischemia. Using partial least squares discriminate analysis (PLS-DA), we identified the following amino acids as potential biomarkers of cerebral ischemia: glutamic acid (Glu), homocysteine (Hcy), methionine (Met), tryptophan (Trp), aspartic acid (Asp), alanine (Ala) and tyrosine (Tyr). Moreover, four amino acids (Hcy, Met, Glu and Trp) showed significant change in galangin-treated (100 and 50 mg kg(-1)) groups compared to vehicle groups. Furthermore, we identified three pathway-related enzymes tyrosine aminotransferase (TAT), glutamine synthetase (GLUL) and monocarboxylate transporter (SLC16A10) by multiplex interactions with Glu and Hcy, which have been previously reported to be closely related to cerebral ischemia. Through an analysis of the metabolite-protein network analysis, we identified 16 proteins that were associated with two amino acids by multiple interactions with three enzymes; five of them may become potential biomarkers of galangin for acute ischemic stroke as the result of molecule docking. Our results may help develop novel strategies to explore the mechanism of cerebral ischemia, discover potential targets for drug candidates and elucidate the related regulatory signal network.
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Affiliation(s)
- Jian Gao
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, PR China
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Hanzu FA, Vinaixa M, Papageorgiou A, Párrizas M, Correig X, Delgado S, Carmona F, Samino S, Vidal J, Gomis R. Obesity rather than regional fat depots marks the metabolomic pattern of adipose tissue: an untargeted metabolomic approach. Obesity (Silver Spring) 2014; 22:698-704. [PMID: 23804579 DOI: 10.1002/oby.20541] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2012] [Revised: 05/25/2013] [Accepted: 05/26/2013] [Indexed: 01/04/2023]
Abstract
OBJECTIVE This study compares the patterns of visceral (VIS) and subcutaneous (SC) adipose tissue (AT)-derived metabolites from non-obese (BMI 24-26 kg/m2) and obese subjects (BMI > 40 kg/m2) with no major metabolic risk factors other than BMI. METHODS SC- and VIS- AT obtained from obese (Ob) and non-obese (NOb) subjects during surgery were incubated to obtain their metabolites. Differences related to obesity or anatomical provenances of AT were assessed using an untargeted metabolomics approach based on gas chromatography-mass spectrometry. RESULTS The overall effect of obesity on the metabolite profile resulted more remarkable than the effect of regional AT. Only the depletion of 2-ketoisocaproic (2-KIC) acid reached statistical significance for the SC-AT alone, although it was observed in both depots. Obesity induced more significant changes in several amino acids levels of the VIS-AT metabolites. On the one hand, higher released levels of glutamine and alanine were detected in the VIS- obese AT, whereas on the other, the VIS- obese AT presented a diminished uptake of essential amino acids (methionine, threonine, lysine), BCAAs, leucine, and serine. CONCLUSION This study shows that obesity markedly affects the amino acid metabolic signature of the AT before the clinical onset of other significant metabolic alterations aside from BMI.
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Affiliation(s)
- F A Hanzu
- Department of Endocrinology and Nutrition, Diabetes and Obesity Research Laboratory, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Spain
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Increased metabolite levels of glycolysis and pentose phosphate pathway in rabbit atherosclerotic arteries and hypoxic macrophage. PLoS One 2014; 9:e86426. [PMID: 24466087 PMCID: PMC3900532 DOI: 10.1371/journal.pone.0086426] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2013] [Accepted: 12/10/2013] [Indexed: 02/04/2023] Open
Abstract
AIMS Inflammation and possibly hypoxia largely affect glucose utilization in atherosclerotic arteries, which could alter many metabolic systems. However, metabolic changes in atherosclerotic plaques remain unknown. The present study aims to identify changes in metabolic systems relative to glucose uptake and hypoxia in rabbit atherosclerotic arteries and cultured macrophages. METHODS Macrophage-rich or smooth muscle cell (SMC)-rich neointima was created by balloon injury in the iliac-femoral arteries of rabbits fed with a 0.5% cholesterol diet or a conventional diet. THP-1 macrophages stimulated with lipopolysaccharides (LPS) and interferon-γ (INFγ) were cultured under normoxic and hypoxic conditions. We evaluated comprehensive arterial and macrophage metabolism by performing metabolomic analyses using capillary electrophoresis-time of flight mass spectrometry. We evaluated glucose uptake and its relationship to vascular hypoxia using (18)F-fluorodeoxyglucose ((18)F-FDG) and pimonidazole, a marker of hypoxia. RESULTS The levels of many metabolites increased in the iliac-femoral arteries with macrophage-rich neointima, compared with those that were not injured and those with SMC-rich neointima (glycolysis, 4 of 9; pentose phosphate pathway, 4 of 6; tricarboxylic acid cycle, 4 of 6; nucleotides, 10 of 20). The uptake of (18)F-FDG in arterial walls measured by autoradiography positively correlated with macrophage- and pimonidazole-immunopositive areas (r = 0.76, and r = 0.59 respectively; n = 69 for both; p<0.0001). Pimonidazole immunoreactivity was closely localized with the nuclear translocation of hypoxia inducible factor-1α and hexokinase II expression in macrophage-rich neointima. The levels of glycolytic (8 of 8) and pentose phosphate pathway (4 of 6) metabolites increased in LPS and INFγ stimulated macrophages under hypoxic but not normoxic condition. Plasminogen activator inhibitor-1 protein levels in the supernatant were closely associated with metabolic pathways in the macrophages. CONCLUSION Infiltrative macrophages in atherosclerotic arteries might affect metabolic systems, and hypoxia but not classical activation might augment glycolytic and pentose phosphate pathways in macrophages.
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435
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Campbell C, Grapov D, Fiehn O, Chandler CJ, Burnett DJ, Souza EC, Casazza GA, Gustafson MB, Keim NL, Newman JW, Hunter GR, Fernandez JR, Garvey WT, Harper ME, Hoppel CL, Meissen JK, Take K, Adams SH. Improved metabolic health alters host metabolism in parallel with changes in systemic xeno-metabolites of gut origin. PLoS One 2014; 9:e84260. [PMID: 24416208 PMCID: PMC3885560 DOI: 10.1371/journal.pone.0084260] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2013] [Accepted: 11/13/2013] [Indexed: 12/18/2022] Open
Abstract
Novel plasma metabolite patterns reflective of improved metabolic health (insulin sensitivity, fitness, reduced body weight) were identified before and after a 14–17 wk weight loss and exercise intervention in sedentary, obese insulin-resistant women. To control for potential confounding effects of diet- or microbiome-derived molecules on the systemic metabolome, sampling was during a tightly-controlled feeding test week paradigm. Pairwise and multivariate analysis revealed intervention- and insulin-sensitivity associated: (1) Changes in plasma xeno-metabolites (“non-self” metabolites of dietary or gut microbial origin) following an oral glucose tolerance test (e.g. higher post-OGTT propane-1,2,3-tricarboxylate [tricarballylic acid]) or in the overnight-fasted state (e.g., lower γ-tocopherol); (2) Increased indices of saturated very long chain fatty acid elongation capacity; (3) Increased post-OGTT α-ketoglutaric acid (α-KG), fasting α-KG inversely correlated with Matsuda index, and altered patterns of malate, pyruvate and glutamine hypothesized to stem from improved mitochondrial efficiency and more robust oxidation of glucose. The results support a working model in which improved metabolic health modifies host metabolism in parallel with altering systemic exposure to xeno-metabolites. This highlights that interpretations regarding the origins of peripheral blood or urinary “signatures” of insulin resistance and metabolic health must consider the potentially important contribution of gut-derived metabolites toward the host's metabolome.
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Affiliation(s)
- Caitlin Campbell
- USDA-ARS Western Human Nutrition Research Center, Davis, California, United States of America
| | - Dmitry Grapov
- West Coast Metabolomics Center, University of California Davis, Davis, California, United States of America
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, California, United States of America
- Genome Center, University of California Davis, Davis, California, United States of America
- * E-mail: (SHA); (OF)
| | - Carol J. Chandler
- USDA-ARS Western Human Nutrition Research Center, Davis, California, United States of America
| | - Dustin J. Burnett
- USDA-ARS Western Human Nutrition Research Center, Davis, California, United States of America
| | - Elaine C. Souza
- USDA-ARS Western Human Nutrition Research Center, Davis, California, United States of America
| | - Gretchen A. Casazza
- Sports Medicine Program, University of California, Davis School of Medicine, Sacramento, California, United States of America
| | - Mary B. Gustafson
- USDA-ARS Western Human Nutrition Research Center, Davis, California, United States of America
| | - Nancy L. Keim
- USDA-ARS Western Human Nutrition Research Center, Davis, California, United States of America
- Department of Nutrition, University of California Davis, Davis, California, United States of America
| | - John W. Newman
- USDA-ARS Western Human Nutrition Research Center, Davis, California, United States of America
- Department of Nutrition, University of California Davis, Davis, California, United States of America
| | - Gary R. Hunter
- Department of Nutrition Sciences, University of Alabama, Birmingham, Alabama, United States of America
- Human Studies Department, University of Alabama, Birmingham, Alabama, United States of America
| | - Jose R. Fernandez
- Department of Nutrition Sciences, University of Alabama, Birmingham, Alabama, United States of America
| | - W. Timothy Garvey
- Department of Nutrition Sciences, University of Alabama, Birmingham, Alabama, United States of America
| | - Mary-Ellen Harper
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada
| | - Charles L. Hoppel
- Pharmacology Department, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - John K. Meissen
- Genome Center, University of California Davis, Davis, California, United States of America
| | - Kohei Take
- Genome Center, University of California Davis, Davis, California, United States of America
| | - Sean H. Adams
- USDA-ARS Western Human Nutrition Research Center, Davis, California, United States of America
- Department of Nutrition, University of California Davis, Davis, California, United States of America
- * E-mail: (SHA); (OF)
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Dumas ME, Kinross J, Nicholson JK. Metabolic phenotyping and systems biology approaches to understanding metabolic syndrome and fatty liver disease. Gastroenterology 2014; 146:46-62. [PMID: 24211299 DOI: 10.1053/j.gastro.2013.11.001] [Citation(s) in RCA: 132] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2013] [Revised: 11/01/2013] [Accepted: 11/05/2013] [Indexed: 12/17/2022]
Abstract
Metabolic syndrome, a cluster of risk factors for type 2 diabetes mellitus and cardiovascular disease, is becoming an increasing global health concern. Insulin resistance is often associated with metabolic syndrome and also typical hepatic manifestations such as nonalcoholic fatty liver disease. Profiling of metabolic products (metabolic phenotyping or metabotyping) has provided new insights into metabolic syndrome and nonalcoholic fatty liver disease. Data from nuclear magnetic resonance spectroscopy and mass spectrometry combined with statistical modeling and top-down systems biology have allowed us to analyze and interpret metabolic signatures in terms of metabolic pathways and protein interaction networks and to identify the genomic and metagenomic determinants of metabolism. For example, metabolic phenotyping has shown that relationships between host cells and the microbiome affect development of the metabolic syndrome and fatty liver disease. We review recent developments in metabolic phenotyping and systems biology technologies and how these methodologies have provided insights into the mechanisms of metabolic syndrome and nonalcoholic fatty liver disease. We discuss emerging areas of research in this field and outline our vision for how metabolic phenotyping could be used to study metabolic syndrome and fatty liver disease.
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Affiliation(s)
- Marc-Emmanuel Dumas
- Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, South Kensington, London, England.
| | - James Kinross
- Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, South Kensington, London, England; Section of Biosurgery and Surgical Technology, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, St. Mary's Hospital, Imperial College London, London, England
| | - Jeremy K Nicholson
- Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, South Kensington, London, England
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437
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Roberts LD, Koulman A, Griffin JL. Towards metabolic biomarkers of insulin resistance and type 2 diabetes: progress from the metabolome. Lancet Diabetes Endocrinol 2014; 2:65-75. [PMID: 24622670 DOI: 10.1016/s2213-8587(13)70143-8] [Citation(s) in RCA: 192] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The complex aetiology of type 2 diabetes makes effective screening, diagnosis and prognosis a substantial challenge for the physician. The rapidly developing area of metabolomics, which uses analytical techniques such as mass spectrometry and nuclear magnetic resonance, has emerged as a promising approach to identify biomarkers of diabetes and the insulin-resistant state that precedes overt pathology. Initial successes with metabolomic studies have indicated potential biomarkers for insulin resistance and for identifying people at risk of developing diabetes, with particular focus on aminoacids and lipid metabolism. These biomarkers will help to improve research and management of diabetes. In particular, several biomarkers identified could be used for early identification of diabetes risk. Furthermore, changes in selected biomarkers can indicate effectiveness of therapeutic interventions for type 2 diabetes and the metabolic syndrome. Indeed, there is much promise that branched-chain aminoacids might provide a screening biomarker for type 2 diabetes risk, allowing early dietary and exercise interventions to treat or even prevent the disease.
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Affiliation(s)
- Lee D Roberts
- Medical Research Council (MRC) Human Nutrition Research (HNR), Cambridge CB1 9NL, UK; Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
| | - Albert Koulman
- Medical Research Council (MRC) Human Nutrition Research (HNR), Cambridge CB1 9NL, UK; Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
| | - Julian L Griffin
- Medical Research Council (MRC) Human Nutrition Research (HNR), Cambridge CB1 9NL, UK; Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
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438
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Lustgarten MS, Price LL, Phillips EM, Fielding RA. Serum glycine is associated with regional body fat and insulin resistance in functionally-limited older adults. PLoS One 2013; 8:e84034. [PMID: 24391874 PMCID: PMC3877144 DOI: 10.1371/journal.pone.0084034] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2013] [Accepted: 11/11/2013] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Metabolic profiling may provide insight into biologic mechanisms related to age-related increases in regional adiposity and insulin resistance. OBJECTIVES The objectives of the current study were to characterize the association between mid-thigh intermuscular and subcutaneous adipose tissue (IMAT, SCAT, respectively) and, abdominal adiposity with the serum metabolite profile, to identify significant metabolites as further associated with the homeostasis model assessment of insulin resistance (HOMA-IR), and, to develop a HOMA-IR associated metabolite predictor set representative of regional adiposity, in 73 functionally-limited (short physical performance battery ≤10; SPPB) older adults (age range, 70-85 y). METHODS Fasting levels of 181 total metabolites, including amino acids, fatty acids and acylcarnitines were measured with use of an untargeted mass spectrometry-based metabolomic approach. Multivariable-adjusted linear regression was used in all analyses. RESULTS Thirty-two, seven and one metabolite(s) were found to be associated with IMAT, abdominal adiposity and, SCAT, respectively, including the amino acid glycine, which was positively associated with SCAT and, negatively associated with both IMAT and abdominal adiposity. Glycine and four metabolites found to be significantly associated with regional adiposity were additionally associated with HOMA-IR. Separate stepwise regression models identified glycine as a HOMA-IR associated marker of both IMAT (model R(2) = 0.51, p<0.0001) and abdominal adiposity (model R(2) = 0.41, p<0.0001). CONCLUSION Our findings for a positive association between glycine with SCAT but, a negative association between glycine with IMAT and abdominal adiposity supports the hypothesis that SCAT metabolic processes are different from that found in other fat depots. In addition, because of the significant associations found between glycine with HOMA-IR, IMAT, SCAT and abdominal adiposity, our results suggest glycine as a serum biomarker of both insulin sensitivity and regional fat mass in functionally-limited older adults.
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Affiliation(s)
- Michael S. Lustgarten
- Nutrition, Exercise Physiology, and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center, Tufts University, Boston, Massachusetts, United States of America
| | - Lori Lyn Price
- The Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, and Tufts Clinical and Translational Science Institute, Tufts University, Boston, Massachusetts, United States of America
| | - Edward M. Phillips
- Nutrition, Exercise Physiology, and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center, Tufts University, Boston, Massachusetts, United States of America
| | - Roger A. Fielding
- Nutrition, Exercise Physiology, and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center, Tufts University, Boston, Massachusetts, United States of America
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Ferguson AA, Roy S, Kormanik KN, Kim Y, Dumas KJ, Ritov VB, Matern D, Hu PJ, Fisher AL. TATN-1 mutations reveal a novel role for tyrosine as a metabolic signal that influences developmental decisions and longevity in Caenorhabditis elegans. PLoS Genet 2013; 9:e1004020. [PMID: 24385923 PMCID: PMC3868569 DOI: 10.1371/journal.pgen.1004020] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2013] [Accepted: 10/28/2013] [Indexed: 11/18/2022] Open
Abstract
Recent work has identified changes in the metabolism of the aromatic amino acid tyrosine as a risk factor for diabetes and a contributor to the development of liver cancer. While these findings could suggest a role for tyrosine as a direct regulator of the behavior of cells and tissues, evidence for this model is currently lacking. Through the use of RNAi and genetic mutants, we identify tatn-1, which is the worm ortholog of tyrosine aminotransferase and catalyzes the first step of the conserved tyrosine degradation pathway, as a novel regulator of the dauer decision and modulator of the daf-2 insulin/IGF-1-like (IGFR) signaling pathway in Caenorhabditis elegans. Mutations affecting tatn-1 elevate tyrosine levels in the animal, and enhance the effects of mutations in genes that lie within the daf-2/insulin signaling pathway or are otherwise upstream of daf-16/FOXO on both dauer formation and worm longevity. These effects are mediated by elevated tyrosine levels as supplemental dietary tyrosine mimics the phenotypes produced by a tatn-1 mutation, and the effects still occur when the enzymes needed to convert tyrosine into catecholamine neurotransmitters are missing. The effects on dauer formation and lifespan require the aak-2/AMPK gene, and tatn-1 mutations increase phospho-AAK-2 levels. In contrast, the daf-16/FOXO transcription factor is only partially required for the effects on dauer formation and not required for increased longevity. We also find that the controlled metabolism of tyrosine by tatn-1 may function normally in dauer formation because the expression of the TATN-1 protein is regulated both by daf-2/IGFR signaling and also by the same dietary and environmental cues which influence dauer formation. Our findings point to a novel role for tyrosine as a developmental regulator and modulator of longevity, and support a model where elevated tyrosine levels play a causal role in the development of diabetes and cancer in people.
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Affiliation(s)
- Annabel A. Ferguson
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Sudipa Roy
- Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America
- Center for Healthy Aging, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America
| | - Kaitlyn N. Kormanik
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Yongsoon Kim
- Life Sciences Institute, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Kathleen J. Dumas
- Life Sciences Institute, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Vladimir B. Ritov
- Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Dietrich Matern
- Biochemical Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota, United States of America
| | - Patrick J. Hu
- Life Sciences Institute, University of Michigan, Ann Arbor, Michigan, United States of America
- Departments of Internal Medicine and Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Alfred L. Fisher
- Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America
- Center for Healthy Aging, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America
- GRECC, South Texas VA Health Care System, San Antonio, Texas, United States of America
- * E-mail:
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440
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Liu Z, Que S, Ning H, Wang L, Peng T. Elevated alanine aminotransferase is strongly associated with incident metabolic syndrome: a meta-analysis of prospective studies. PLoS One 2013; 8:e80596. [PMID: 24324614 PMCID: PMC3851461 DOI: 10.1371/journal.pone.0080596] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2013] [Accepted: 10/04/2013] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The incidence of metabolic syndrome (MetS) is rapidly increasing worldwide and associated with alanine aminotransferase (ALT) activity. However, the impact of ALT activity on MetS incidence is inconsistent in published literature. We therefore estimated the association between elevated ALT activity and incident MetS through a meta-analysis of prospective cohort studies. METHODS/PRINCIPAL FINDINGS All published prospective cohort studies on the association between elevated ALT activity and incident MetS were retrieved from Pubmed, Embase, and the Institute for Scientific Information (ISI). In all, seven prospective cohort studies, with 31545 participants and 2873 cases of incident MetS were recruited. If there was insignificant heterogeneity (P-value>0.05 and I(2)<50%), the fixed-effect model was used to calculate the pooled relative risks (RRs) of incident MetS induced by raised ALT. Otherwise, the random-effect model was used. The calculated RR was 1.81 (95% confidence interval [CI]: 1.49-2.14) when the incidence of MetS was compared between the highest versus the lowest classification of ALT activities. The pooled RR was 1.13 (95% CI: 1.11-1.16) in dose-response analysis with 5 units per liter (U/l) of ALT increment. Subgroup analysis suggested that gender disparity might be the main origin of heterogeneity in overall analysis (P = 0.007 between RRs of gender-specific subgroups evaluated with 5 U/l increments of ALT). Women had a higher dose-response risk of MetS incidence (1.38, 95% CI: 1.20-1.55) than men. Furthermore, sensitivity analysis confirmed the stability of results. No publication bias was found in our meta-analysis. CONCLUSIONS/SIGNIFICANCE Current evidence from prospective studies supports the association between ALT elevation and increasing MetS incidence. This association is closer and more consistent in female population. Further studies are needed to confirm this association and to investigate the potential mechanism of ALT activity on MetS occurrence.
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Affiliation(s)
- Zhengtao Liu
- Department of Hepatobiliary Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province, China
| | - Shuping Que
- Department of Pediatrics, Women and children’s hospital of Guangxi, Nanning, Guangxi Province, China
- Department of Pediatrics, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province, China
| | - Huaijun Ning
- Department of Pediatrics, Women and children’s hospital of Guangxi, Nanning, Guangxi Province, China
| | - Linlin Wang
- Department of Pediatrics, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province, China
| | - Tao Peng
- Department of Hepatobiliary Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province, China
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Bhattacharya S, Granger CB, Craig D, Haynes C, Bain J, Stevens RD, Hauser ER, Newgard CB, Kraus WE, Newby LK, Shah SH. Validation of the association between a branched chain amino acid metabolite profile and extremes of coronary artery disease in patients referred for cardiac catheterization. Atherosclerosis 2013; 232:191-6. [PMID: 24401236 DOI: 10.1016/j.atherosclerosis.2013.10.036] [Citation(s) in RCA: 104] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Revised: 10/18/2013] [Accepted: 10/31/2013] [Indexed: 10/26/2022]
Abstract
OBJECTIVE To validate independent associations between branched-chain amino acids (BCAA) and other metabolites with coronary artery disease (CAD). METHODS We conducted mass-spectrometry-based profiling of 63 metabolites in fasting plasma from 1983 sequential patients undergoing cardiac catheterization. Significant CAD was defined as CADindex ≥ 32 (at least one vessel with ≥ 95% stenosis; N = 995) and no CAD as CADindex ≤ 23 and no previous cardiac events (N = 610). Individuals (N = 378) with CAD severity between these extremes were excluded. Principal components analysis (PCA) reduced large numbers of correlated metabolites into uncorrelated factors. Association between metabolite factors and significant CAD vs. no CAD was tested using logistic regression; and between metabolite factors and severity of CAD was tested using linear regression. RESULTS Of twelve PCA-derived metabolite factors, two were associated with CAD in multivariable models: factor 10, composed of BCAA (adjusted odds ratio, OR, 1.20; 95% CI 1.05-1.35, p = 0.005) and factor 7, composed of short-chain acylcarnitines, which include byproducts of BCAA metabolism (adjusted OR 1.30; 95% CI 1.14-1.48, p = 0.001). After adjustment for glycated albumin (marker of insulin resistance [IR]) both factors 7 (p = 0.0001) and 10 (p = 0.004) remained associated with CAD. Severity of CAD as a continuous variable (including patients with non-obstructive disease) was associated with metabolite factors 2, 3, 6, 7, 8 and 9; only factors 7 and 10 were associated in multivariable models. CONCLUSIONS We validated the independent association of metabolites involved in BCAA metabolism with CAD extremes. These metabolites may be reporting on novel mechanisms of CAD pathogenesis that are independent of IR and diabetes.
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Affiliation(s)
- Sayanti Bhattacharya
- Duke Global Health Institute, Durham, NC, USA; Duke Institute of Molecular Physiology, Durham, NC, USA.
| | - Christopher B Granger
- Division of Cardiovascular Medicine, Duke University School of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA.
| | - Damian Craig
- Duke Institute of Molecular Physiology, Durham, NC, USA.
| | - Carol Haynes
- Duke Institute of Molecular Physiology, Durham, NC, USA.
| | - James Bain
- Duke Institute of Molecular Physiology, Durham, NC, USA.
| | | | | | | | | | - L Kristin Newby
- Division of Cardiovascular Medicine, Duke University School of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA.
| | - Svati H Shah
- Duke Global Health Institute, Durham, NC, USA; Duke Institute of Molecular Physiology, Durham, NC, USA; Division of Cardiovascular Medicine, Duke University School of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA.
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442
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The complex role of branched chain amino acids in diabetes and cancer. Metabolites 2013; 3:931-45. [PMID: 24958258 PMCID: PMC3937834 DOI: 10.3390/metabo3040931] [Citation(s) in RCA: 93] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2013] [Revised: 09/03/2013] [Accepted: 10/08/2013] [Indexed: 02/07/2023] Open
Abstract
The obesity and diabetes epidemics are continuing to spread across the globe. There is increasing evidence that diabetes leads to a significantly higher risk for certain types of cancer. Both diabetes and cancer are characterized by severe metabolic perturbations and the branched chain amino acids (BCAAs) appear to play a significant role in both of these diseases. These essential amino acids participate in a wide variety of metabolic pathways, but it is now recognized that they are also critical regulators of a number of cell signaling pathways. An elevation in branched chain amino acids has recently been shown to be significantly correlated with insulin resistance and the future development of diabetes. In cancer, the normal demands for BCAAs are complicated by the conflicting needs of the tumor and the host. The severe muscle wasting syndrome experience by many cancer patients, known as cachexia, has motivated the use of BCAA supplementation. The desired improvement in muscle mass must be balanced by the need to avoid providing materials for tumor proliferation. A better understanding of the complex functions of BCAAs could lead to their use as biomarkers of the progression of certain cancers in diabetic patients.
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443
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Du J, Li Z, Li QZ, Guan T, Yang Q, Xu H, Pritchard KA, Camara AKS, Shi Y. Enoyl coenzyme a hydratase domain-containing 2, a potential novel regulator of myocardial ischemia injury. J Am Heart Assoc 2013; 2:e000233. [PMID: 24108764 PMCID: PMC3835224 DOI: 10.1161/jaha.113.000233] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background We reported previously that Brown Norway (BN) rats are more resistant to myocardial ischemia/reperfusion (I/R) injury than are Dahl S (SS) rats. To identify the unique genes differentially expressed in the hearts of these rats, we used DNA microarray analysis and observed that enoyl coenzyme A hydratase–containing domain 2 (ECHDC2) is highly expressed (≈18‐fold) in the SS hearts compared with the BN hearts. Methods and Results RT‐PCR, Western blot, and immunohistochemistry analyses verified that ECHDC2 was highly expressed in SS hearts compared with the BN hearts. ECHDC2 gene locates at chromosome 5 of rat and is expressed in mitochondria of the heart, mainly in cardiomyocytes but not in cardiofibroblasts. Overexpression of ECHDC2 in cells increased susceptibility to I/R injury while knockdown of ECHDC2 enhanced resistance to I/R injury. Furthermore, we observed that left anterior descending coronary artery ligation–induced myocardial infarction was more severe in the SS hearts than in the BN hearts or SSBN5 hearts, which was built on SS rats but had the substitution of chromosome 5 from BN rats. We also demonstrated that ECHDC2 did not alter mitochondrial O2 consumption, metabolic intermediates and ATP production. By gas chromatography–mass spectrometry, we found that ECHDC2 overexpression increased the levels of the cellular branched chain amino acids leucine and valine. Conclusion ECHDC2, a mitochondrial protein, may be involved in regulating cell death and myocardial injury. Its deficiency in BN rats contributes to their increased resistance to myocardial I/R compared with SS rats. ECHDC2 increases branched chain amino acid metabolism and appears to be a novel regulator linking cell metabolism with cardiovascular disease.
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Affiliation(s)
- Jianhai Du
- Department of Surgery, Medical College of Wisconsin, Milwaukee, WI
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444
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Zhou Y, Qiu L, Xiao Q, Wang Y, Meng X, Xu R, Wang S, Na R. Obesity and diabetes related plasma amino acid alterations. Clin Biochem 2013; 46:1447-52. [DOI: 10.1016/j.clinbiochem.2013.05.045] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2013] [Revised: 05/04/2013] [Accepted: 05/06/2013] [Indexed: 01/19/2023]
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445
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Cornelis MC, Hu FB. Systems Epidemiology: A New Direction in Nutrition and Metabolic Disease Research. Curr Nutr Rep 2013; 2. [PMID: 24278790 DOI: 10.1007/s13668-013-0052-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Systems epidemiology applied to the field of nutrition has potential to provide new insight into underlying mechanisms and ways to study the health effects of specific foods more comprehensively. Human intervention and population-based studies have identified i) common genetic factors associated with several nutrition-related traits and ii) dietary factors altering the expression of genes and levels of proteins and metabolites related to inflammation, lipid metabolism and/or gut microbial metabolism, results of high relevance to metabolic disease. System-level tools applied type 2 diabetes and related conditions have revealed new pathways that are potentially modified by diet and thus offer additional opportunities for nutritional investigations. Moving forward, harnessing the resources of existing large prospective studies within which biological samples have been archived and diet and lifestyle have been measured repeatedly within individual will enable systems-level data to be integrated, the outcome of which will be improved personalized optimal nutrition for prevention and treatment of disease.
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Affiliation(s)
- Marilyn C Cornelis
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA
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446
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Qi L, Qi Q, Prudente S, Mendonca C, Andreozzi F, di Pietro N, Sturma M, Novelli V, Mannino GC, Formoso G, Gervino EV, Hauser TH, Muehlschlegel JD, Niewczas MA, Krolewski AS, Biolo G, Pandolfi A, Rimm E, Sesti G, Trischitta V, Hu F, Doria A. Association between a genetic variant related to glutamic acid metabolism and coronary heart disease in individuals with type 2 diabetes. JAMA 2013; 310:821-8. [PMID: 23982368 PMCID: PMC3858847 DOI: 10.1001/jama.2013.276305] [Citation(s) in RCA: 103] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Diabetes is associated with an elevated risk of coronary heart disease (CHD). Previous studies have suggested that the genetic factors predisposing to excess cardiovascular risk may be different in diabetic and nondiabetic individuals. OBJECTIVE To identify genetic determinants of CHD that are specific to patients with diabetes. DESIGN, SETTING, AND PARTICIPANTS We studied 5 independent sets of CHD cases and CHD-negative controls from the Nurses' Health Study (enrolled in 1976 and followed up through 2008), Health Professionals Follow-up Study (enrolled in 1986 and followed up through 2008), Joslin Heart Study (enrolled in 2001-2008), Gargano Heart Study (enrolled in 2001-2008), and Catanzaro Study (enrolled in 2004-2010). Included were a total of 1517 CHD cases and 2671 CHD-negative controls, all with type 2 diabetes. Results in diabetic patients were compared with those in 737 nondiabetic CHD cases and 1637 nondiabetic CHD-negative controls from the Nurses' Health Study and Health Professionals Follow-up Study cohorts. Exposures included 2,543,016 common genetic variants occurring throughout the genome. MAIN OUTCOMES AND MEASURES Coronary heart disease--defined as fatal or nonfatal myocardial infarction, coronary artery bypass grafting, percutaneous transluminal coronary angioplasty, or angiographic evidence of significant stenosis of the coronary arteries. RESULTS A variant on chromosome 1q25 (rs10911021) was consistently associated with CHD risk among diabetic participants, with risk allele frequencies of 0.733 in cases vs 0.679 in controls (odds ratio, 1.36 [95% CI, 1.22-1.51]; P = 2 × 10(-8)). No association between this variant and CHD was detected among nondiabetic participants, with risk allele frequencies of 0.697 in cases vs 0.696 in controls (odds ratio, 0.99 [95% CI, 0.87-1.13]; P = .89), consistent with a significant gene × diabetes interaction on CHD risk (P = 2 × 10(-4)). Compared with protective allele homozygotes, rs10911021 risk allele homozygotes were characterized by a 32% decrease in the expression of the neighboring glutamate-ammonia ligase (GLUL) gene in human endothelial cells (P = .0048). A decreased ratio between plasma levels of γ-glutamyl cycle intermediates pyroglutamic and glutamic acid was also shown in risk allele homozygotes (P = .029). CONCLUSION AND RELEVANCE A single-nucleotide polymorphism (rs10911021) was identified that was significantly associated with CHD among persons with diabetes but not in those without diabetes and was functionally related to glutamic acid metabolism, suggesting a mechanistic link.
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Affiliation(s)
- Lu Qi
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Qibin Qi
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
| | - Sabrina Prudente
- IRCSS Casa Sollievo della Sofferenza-Mendel Laboratory, San Giovanni Rotondo, Italy
| | | | - Francesco Andreozzi
- Department of Medical and Surgical Sciences, University Magna Græcia, Catanzaro, Italy
| | - Natalia di Pietro
- Department of Experimental and Clinical Sciences, University ‘G. d'Annunzio’, Aging Research Center, Ce.S.I., ‘G. d'Annunzio’ University Foundation, Chieti-Pescara, Italy
| | - Mariella Sturma
- Department of Medical, Surgical and Health Sciences, University of Trieste, Italy
| | - Valeria Novelli
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Gaia Chiara Mannino
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medical and Surgical Sciences, University Magna Græcia, Catanzaro, Italy
| | - Gloria Formoso
- Department of Medicine and Aging Sciences, University ‘G. d'Annunzio’, Aging Research Center, Ce.S.I., ‘G. d'Annunzio’ University Foundation, Chieti-Pescara, Italy
| | - Ernest V. Gervino
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Cardiovascular Division, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Thomas H. Hauser
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Cardiovascular Division, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Jochen D. Muehlschlegel
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Monika A. Niewczas
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Andrzej S. Krolewski
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Gianni Biolo
- Department of Medical, Surgical and Health Sciences, University of Trieste, Italy
| | - Assunta Pandolfi
- Department of Experimental and Clinical Sciences, University ‘G. d'Annunzio’, Aging Research Center, Ce.S.I., ‘G. d'Annunzio’ University Foundation, Chieti-Pescara, Italy
| | - Eric Rimm
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Giorgio Sesti
- Department of Medical and Surgical Sciences, University Magna Græcia, Catanzaro, Italy
| | - Vincenzo Trischitta
- IRCSS Casa Sollievo della Sofferenza-Mendel Laboratory, San Giovanni Rotondo, Italy
- Research Unit of Diabetes and Endocrine Diseases, IRCSS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
- Department of Experimental Medicine, Sapienza University, Rome, Italy
| | - Frank Hu
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Alessandro Doria
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
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447
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Affiliation(s)
- James R Bain
- Sarah W Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, North Carolina, USA.
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448
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Townsend MK, Clish CB, Kraft P, Wu C, Souza AL, Deik AA, Tworoger SS, Wolpin BM. Reproducibility of metabolomic profiles among men and women in 2 large cohort studies. Clin Chem 2013; 59:1657-67. [PMID: 23897902 DOI: 10.1373/clinchem.2012.199133] [Citation(s) in RCA: 167] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
BACKGROUND Rigorous studies are necessary to demonstrate suitability of metabolomics platforms to profile metabolites in archived plasma within epidemiologic studies of human disease, for which attenuation of effect estimates due to measurement error is a key concern. METHODS Using a liquid chromatography-tandem mass spectrometry platform, we quantified 257 metabolites from archived plasma to evaluate metabolite interassay reproducibility, reproducibility with delayed processing, and within-person reproducibility over time. Interassay reproducibility was assessed with CVs from 60 duplicate plasma samples donated by participants in the Nurses' Health Study and Health Professionals Follow-up Study, and 20 QC pool plasma replicates. Metabolite reproducibility over a 24- to 48-h processing delay (n = 48 samples) and within-person reproducibility over 1-2 years (n = 80 samples) were assessed using Spearman and intraclass correlation coefficients (ICCs). RESULTS CVs were <20% for 92% of metabolites and generally were similar by plasma anticoagulant type (heparin or EDTA) and fasting time. Approximately 75% of metabolites were reproducible over delays in processing of blood samples (Spearman correlation or ICC ≥ 0.75, comparing immediate and 24-h delayed processing). Carbohydrates and purine/pyrimidine derivatives were most adversely affected by the processing delay. Ninety percent of metabolites were reproducible over 1-2 years within individuals (Spearman correlation or ICC ≥ 0.4). CONCLUSIONS For potential use in epidemiologic studies, the majority of plasma metabolites had low CVs and were reproducible over a 24-h processing delay and within individuals over 1-2 years. Certain metabolites, such as carbohydrates and purine/pyrimidine derivatives, may be challenging to evaluate if samples have delayed processing.
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Affiliation(s)
- Mary K Townsend
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
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449
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Poulain-Godefroy O, Eury E, Leloire A, Hennart B, Guillemin GJ, Allorge D, Froguel P. Induction of TDO2 and IDO2 in Liver by High-Fat Feeding in Mice: Discrepancies with Human Obesity. Int J Tryptophan Res 2013; 6:29-37. [PMID: 26882470 PMCID: PMC3729279 DOI: 10.4137/ijtr.s11717] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Low-grade and chronic inflammation is elicited in white adipose tissue in human obesity. The presence of inflammatory molecules leads to an increased tryptophan catabolism through the induction of indoleamine-2,3-dioxygenase-1 (IDO1). In order to characterize the mechanisms underlying this dysregulation, we have studied 2 mouse models of obesity. Unexpectedly, we did not detect any IDO1 expression in obese or lean mice adipose tissue. In a previous study, we did not find any significant difference in the liver for IDO2 and tryptophan-2,3-dioxygenase (TDO2) gene expression between normal weight and obese patients. IDO2 and TDO2 expression was increased in the liver of high-fat fed mice, but not in ob/ob mice, and was strongly correlated with hydroxysteroid-(11-beta) dehydrogenase-1 (HSD11B1) expression, an enzyme that generates active cortisol within tissues. In conclusion, despite a dysregulation of tryptophan metabolism, obese mice display discrepancies with human obesity metabolism, rendering them inappropriate for further investigations in this animal model.
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Affiliation(s)
- Odile Poulain-Godefroy
- European Genomic Institute for Diabetes (EGID), Lille, France.; University of Lille, Lille, France.; CNRS UMR 8199, Lille, France.; CHRU Lille, Lille, France.; IPL, Lille, France
| | - Elodie Eury
- European Genomic Institute for Diabetes (EGID), Lille, France.; University of Lille, Lille, France.; CNRS UMR 8199, Lille, France.; CHRU Lille, Lille, France.; IPL, Lille, France
| | - Audrey Leloire
- European Genomic Institute for Diabetes (EGID), Lille, France.; University of Lille, Lille, France.; CNRS UMR 8199, Lille, France.; CHRU Lille, Lille, France.; IPL, Lille, France
| | - Benjamin Hennart
- University of Lille, Lille, France.; CHRU Lille, Lille, France.; EA4483, Faculty of Medicine, Lille, France
| | - Gilles J Guillemin
- MND and Neurodegenerative Diseases Research Group, Australian School of Advanced Medicine, Macquarie University, Australia
| | - Delphine Allorge
- University of Lille, Lille, France.; CHRU Lille, Lille, France.; EA4483, Faculty of Medicine, Lille, France
| | - Philippe Froguel
- European Genomic Institute for Diabetes (EGID), Lille, France.; University of Lille, Lille, France.; CNRS UMR 8199, Lille, France.; CHRU Lille, Lille, France.; IPL, Lille, France.; Department of Genomics of Common Disease, School of Public Health, Imperial College London, United Kingdom
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450
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Olson KC, Chen G, Lynch CJ. Quantification of branched-chain keto acids in tissue by ultra fast liquid chromatography-mass spectrometry. Anal Biochem 2013; 439:116-22. [PMID: 23684523 DOI: 10.1016/j.ab.2013.05.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Revised: 05/03/2013] [Accepted: 05/06/2013] [Indexed: 01/16/2023]
Abstract
Branched-chain keto acids (BCKAs) are associated with increased susceptibility to several degenerative diseases. However, BCKA concentrations in tissues or the amounts of tissue available are frequently at the limit of detection for standard plasma methods. To accurately and quickly determine tissue BCKAs, we have developed a sensitive ultra fast liquid chromatography-mass spectrometry (UFLC-MS) method. BCKAs from deproteinized tissue extractions were o-phenylenediamine (OPD) derivatized, ethyl acetate extracted, lyophilized in a vacuum centrifuge, and reconstituted in 200 mM ammonium acetate. Samples were injected onto a Shimadzu UFLC system coupled to an AB-Sciex 5600 Triple TOF mass spectrometer instrument that detected masses of the OPD BCKA products using a multiple reaction monitoring method. An OPD-derivatized (13)C-labeled keto acid was used as an internal standard. Application of the method for C57BL/6J (wild-type) and PP2Cm knockout mouse tissues, including kidney, adipose tissue, liver, gastrocnemius, and hypothalamus, is shown. The lowest tissue concentration measured by this method was 20 nM, with the standard curve covering a wide range (7.8-32,000 nM). Liquid chromatography-mass spectrometry run times for this assay were less than 5 min, facilitating high throughput, and the OPD derivatives were found to be stable over several days.
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Affiliation(s)
- Kristine C Olson
- Department of Cellular and Molecular Physiology, Penn State College of Medicine, Hershey, PA 17033, USA
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