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Chen ZZ, Lu C, Dreyfuss JM, Tiwari G, Shi X, Zheng S, Wolfs D, Pyle L, Bjornstad P, El ghormli L, Gerszten RE, Isganaitis E. Circulating Metabolite Biomarkers of Glycemic Control in Youth-Onset Type 2 Diabetes. Diabetes Care 2024; 47:1597-1607. [PMID: 38935559 PMCID: PMC11362122 DOI: 10.2337/dc23-2441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 05/31/2024] [Indexed: 06/29/2024]
Abstract
OBJECTIVE We aimed to identify metabolites associated with loss of glycemic control in youth-onset type 2 diabetes. RESEARCH DESIGN AND METHODS We measured 480 metabolites in fasting plasma samples from the TODAY (Treatment Options for Type 2 Diabetes in Adolescents and Youth) study. Participants (N = 393; age 10-17 years) were randomly assigned to metformin, metformin plus rosiglitazone, or metformin plus lifestyle intervention. Additional metabolomic measurements after 36 months were obtained in 304 participants. Cox models were used to assess baseline metabolites, interaction of metabolites and treatment group, and change in metabolites (0-36 months), with loss of glycemic control adjusted for age, sex, race, treatment group, and BMI. Metabolite prediction models of glycemic failure were generated using elastic net regression and compared with clinical risk factors. RESULTS Loss of glycemic control (HbA1c ≥8% or insulin therapy) occurred in 179 of 393 participants (mean 12.4 months). Baseline levels of 33 metabolites were associated with loss of glycemic control (q < 0.05). Associations of hexose and xanthurenic acid with treatment failure differed by treatment randomization; youths with higher baseline levels of these two compounds had a lower risk of treatment failure with metformin alone. For three metabolites, changes from 0 to 36 months were associated with loss of glycemic control (q < 0.05). Changes in d-gluconic acid and 1,5-AG/1-deoxyglucose, but not baseline levels of measured metabolites, predicted treatment failure better than changes in HbA1c or measures of β-cell function. CONCLUSIONS Metabolomics provides insight into circulating small molecules associated with loss of glycemic control and may highlight metabolic pathways contributing to treatment failure in youth-onset diabetes.
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Affiliation(s)
- Zsu-Zsu Chen
- Beth Israel Deaconess Medical Center, Boston, MA
| | - Chang Lu
- Joslin Diabetes Center, Boston, MA
- Boston Children’s Hospital, Boston, MA
| | | | | | - Xu Shi
- Beth Israel Deaconess Medical Center, Boston, MA
| | | | | | - Laura Pyle
- University of Colorado Anschutz Medical School, Aurora, CO
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Harada M, Adam J, Covic M, Ge J, Brandmaier S, Muschet C, Huang J, Han S, Rommel M, Rotter M, Heier M, Mohney RP, Krumsiek J, Kastenmüller G, Rathmann W, Zou Z, Zukunft S, Scheerer MF, Neschen S, Adamski J, Gieger C, Peters A, Ankerst DP, Meitinger T, Alderete TL, de Angelis MH, Suhre K, Wang-Sattler R. Bidirectional modulation of TCA cycle metabolites and anaplerosis by metformin and its combination with SGLT2i. Cardiovasc Diabetol 2024; 23:199. [PMID: 38867314 PMCID: PMC11170891 DOI: 10.1186/s12933-024-02288-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/28/2024] [Indexed: 06/14/2024] Open
Abstract
BACKGROUND Metformin and sodium-glucose-cotransporter-2 inhibitors (SGLT2i) are cornerstone therapies for managing hyperglycemia in diabetes. However, their detailed impacts on metabolic processes, particularly within the citric acid (TCA) cycle and its anaplerotic pathways, remain unclear. This study investigates the tissue-specific metabolic effects of metformin, both as a monotherapy and in combination with SGLT2i, on the TCA cycle and associated anaplerotic reactions in both mice and humans. METHODS Metformin-specific metabolic changes were initially identified by comparing metformin-treated diabetic mice (MET) with vehicle-treated db/db mice (VG). These findings were then assessed in two human cohorts (KORA and QBB) and a longitudinal KORA study of metformin-naïve patients with Type 2 Diabetes (T2D). We also compared MET with db/db mice on combination therapy (SGLT2i + MET). Metabolic profiling analyzed 716 metabolites from plasma, liver, and kidney tissues post-treatment, using linear regression and Bonferroni correction for statistical analysis, complemented by pathway analyses to explore the pathophysiological implications. RESULTS Metformin monotherapy significantly upregulated TCA cycle intermediates such as malate, fumarate, and α-ketoglutarate (α-KG) in plasma, and anaplerotic substrates including hepatic glutamate and renal 2-hydroxyglutarate (2-HG) in diabetic mice. Downregulated hepatic taurine was also observed. The addition of SGLT2i, however, reversed these effects, such as downregulating circulating malate and α-KG, and hepatic glutamate and renal 2-HG, but upregulated hepatic taurine. In human T2D patients on metformin therapy, significant systemic alterations in metabolites were observed, including increased malate but decreased citrulline. The bidirectional modulation of TCA cycle intermediates in mice influenced key anaplerotic pathways linked to glutaminolysis, tumorigenesis, immune regulation, and antioxidative responses. CONCLUSION This study elucidates the specific metabolic consequences of metformin and SGLT2i on the TCA cycle, reflecting potential impacts on the immune system. Metformin shows promise for its anti-inflammatory properties, while the addition of SGLT2i may provide liver protection in conditions like metabolic dysfunction-associated steatotic liver disease (MASLD). These observations underscore the importance of personalized treatment strategies.
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Affiliation(s)
- Makoto Harada
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Jonathan Adam
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Marcela Covic
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jianhong Ge
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Stefan Brandmaier
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Caroline Muschet
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jialing Huang
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Siyu Han
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Martina Rommel
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Markus Rotter
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Margit Heier
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- KORA Study Centre, University Hospital of Augsburg, Augsburg, Germany
| | | | - Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Zhongmei Zou
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Sven Zukunft
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Markus F Scheerer
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Neschen
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, Ludwig Maximilian University of Munich (LMU), Munich, Germany
| | - Donna P Ankerst
- Departments of Mathematics and Life Science Systems, Technical University of Munich (TUM), Garching, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Klinikum Rechts der Isar, TUM, Munich, Germany
| | - Tanya L Alderete
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, USA
| | - Martin Hrabe de Angelis
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Experimental Genetics, TUM School of Life Sciences, TUM, Freising, Germany
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine - Qatar, Education City - Qatar Foundation, Doha, Qatar
| | - Rui Wang-Sattler
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- German Center for Diabetes Research (DZD), Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
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3
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Yu S, Han S, Shi M, Harada M, Ge J, Li X, Cai X, Heier M, Karstenmüller G, Suhre K, Gieger C, Koenig W, Rathmann W, Peters A, Wang-Sattler R. Prediction of Myocardial Infarction Using a Combined Generative Adversarial Network Model and Feature-Enhanced Loss Function. Metabolites 2024; 14:258. [PMID: 38786735 PMCID: PMC11122941 DOI: 10.3390/metabo14050258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 04/23/2024] [Accepted: 04/24/2024] [Indexed: 05/25/2024] Open
Abstract
Accurate risk prediction for myocardial infarction (MI) is crucial for preventive strategies, given its significant impact on global mortality and morbidity. Here, we propose a novel deep-learning approach to enhance the prediction of incident MI cases by incorporating metabolomics alongside clinical risk factors. We utilized data from the KORA cohort, including the baseline S4 and follow-up F4 studies, consisting of 1454 participants without prior history of MI. The dataset comprised 19 clinical variables and 363 metabolites. Due to the imbalanced nature of the dataset (78 observed MI cases and 1376 non-MI individuals), we employed a generative adversarial network (GAN) model to generate new incident cases, augmenting the dataset and improving feature representation. To predict MI, we further utilized multi-layer perceptron (MLP) models in conjunction with the synthetic minority oversampling technique (SMOTE) and edited nearest neighbor (ENN) methods to address overfitting and underfitting issues, particularly when dealing with imbalanced datasets. To enhance prediction accuracy, we propose a novel GAN for feature-enhanced (GFE) loss function. The GFE loss function resulted in an approximate 2% improvement in prediction accuracy, yielding a final accuracy of 70%. Furthermore, we evaluated the contribution of each clinical variable and metabolite to the predictive model and identified the 10 most significant variables, including glucose tolerance, sex, and physical activity. This is the first study to construct a deep-learning approach for producing 7-year MI predictions using the newly proposed loss function. Our findings demonstrate the promising potential of our technique in identifying novel biomarkers for MI prediction.
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Affiliation(s)
- Shixiang Yu
- TUM School of Medicine and Health, Technical University of Munich, 81675 München, Germany; (S.Y.); (S.H.); (M.S.); (J.G.)
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
| | - Siyu Han
- TUM School of Medicine and Health, Technical University of Munich, 81675 München, Germany; (S.Y.); (S.H.); (M.S.); (J.G.)
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
| | - Mengya Shi
- TUM School of Medicine and Health, Technical University of Munich, 81675 München, Germany; (S.Y.); (S.H.); (M.S.); (J.G.)
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
| | - Makoto Harada
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
| | - Jianhong Ge
- TUM School of Medicine and Health, Technical University of Munich, 81675 München, Germany; (S.Y.); (S.H.); (M.S.); (J.G.)
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
| | - Xuening Li
- Biocomputing R&D Department, Beijing Huanyang Bole Consulting Co., Ltd., Beijing 100010, China;
| | - Xiang Cai
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541214, China;
| | - Margit Heier
- KORA Study Centre, University Hospital of Augsburg, 86153 Augsburg, Germany;
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
| | - Gabi Karstenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine and Director of the Bioinformatics Core, Doha 24144, Qatar;
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, 80636 München, Germany;
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University, 40225 Düsseldorf, Germany;
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Pettenkofer School of Public Health, Faculty of Medicine, Ludwig-Maximilians-Universität München, 81377 München, Germany
| | - Rui Wang-Sattler
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
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4
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Harada M, Han S, Shi M, Ge J, Yu S, Adam J, Adamski J, Scheerer MF, Neschen S, de Angelis MH, Wang-Sattler R. Metabolic effects of SGLT2i and metformin on 3-hydroxybutyric acid and lactate in db/db mice. Int J Biol Macromol 2024; 265:130962. [PMID: 38503370 DOI: 10.1016/j.ijbiomac.2024.130962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 03/15/2024] [Accepted: 03/15/2024] [Indexed: 03/21/2024]
Abstract
Combining a Sodium-Glucose-Cotransporter-2-inhibitor (SGLT2i) with metformin is recommended for managing hyperglycemia in patients with type 2 diabetes (T2D) who have cardio-renal complications. Our study aimed to investigate the metabolic effects of SGLT2i and metformin, both individually and synergistically. We treated leptin receptor-deficient (db/db) mice with these drugs for two weeks and conducted metabolite profiling, identifying 861 metabolites across kidney, liver, muscle, fat, and plasma. Using linear regression and mixed-effects models, we identified two SGLT2i-specific metabolites, X-12465 and 3-hydroxybutyric acid (3HBA), a ketone body, across all examined tissues. The levels of 3HBA were significantly higher under SGLT2i monotherapy compared to controls and were attenuated when combined with metformin. We observed similar modulatory effects on metabolites involved in protein catabolism (e.g., branched-chain amino acids) and gluconeogenesis. Moreover, combination therapy significantly raised pipecolate levels, which may enhance mTOR1 activity, while modulating GSK3, a common target of SGLT2i and 3HBA inhibition. The combination therapy also led to significant reductions in body weight and lactate levels, contrasted with monotherapies. Our findings advocate for the combined approach to better manage muscle loss, and the risks of DKA and lactic acidosis, presenting a more effective strategy for T2D treatment.
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Affiliation(s)
- Makoto Harada
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Siyu Han
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany; School of Medicine, Technical University of Munich (TUM), Munich, Germany
| | - Mengya Shi
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany; School of Medicine, Technical University of Munich (TUM), Munich, Germany
| | - Jianhong Ge
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany; School of Medicine, Technical University of Munich (TUM), Munich, Germany
| | - Shixiang Yu
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; School of Medicine, Technical University of Munich (TUM), Munich, Germany
| | - Jonathan Adam
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Markus F Scheerer
- Institute of Experimental Genetics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Neschen
- Institute of Experimental Genetics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Martin Hrabe de Angelis
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Institute of Experimental Genetics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Chair of Experimental Genetics, School of Life Sciences, Technical University of Munich (TUM), Freising, Germany
| | - Rui Wang-Sattler
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany.
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5
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Naja K, Anwardeen N, Malki AM, Elrayess MA. Metformin increases 3-hydroxy medium chain fatty acids in patients with type 2 diabetes: a cross-sectional pharmacometabolomic study. Front Endocrinol (Lausanne) 2024; 15:1313597. [PMID: 38370354 PMCID: PMC10869496 DOI: 10.3389/fendo.2024.1313597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 01/18/2024] [Indexed: 02/20/2024] Open
Abstract
Background Metformin is a drug with a long history of providing benefits in diabetes management and beyond. The mechanisms of action of metformin are complex, and continue to be actively debated and investigated. The aim of this study is to identify metabolic signatures associated with metformin treatment, which may explain the pleiotropic mechanisms by which metformin works, and could lead to an improved treatment and expanded use. Methods This is a cross-sectional study, in which clinical and metabolomic data for 146 patients with type 2 diabetes were retrieved from Qatar Biobank. Patients were categorized into: Metformin-treated, treatment naïve, and non-metformin treated. Orthogonal partial least square discriminate analysis and linear models were used to analyze differences in the level of metabolites between the metformin treated group with each of the other two groups. Results Patients on metformin therapy showed, among other metabolites, a significant increase in 3-hydroxyoctanoate and 3-hydroxydecanoate, which may have substantial effects on metabolism. Conclusions This is the first study to report an association between 3-hydroxy medium chain fatty acids with metformin therapy in patients with type 2 diabetes. This opens up new directions towards repurposing metformin by comprehensively understanding the role of these metabolites.
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Affiliation(s)
- Khaled Naja
- Biomedical Research Center, Qatar University, Doha, Qatar
| | | | - Ahmed M. Malki
- Biomedical Science Department, College of Health Sciences, Qatar University (QU) Health, Qatar University, Doha, Qatar
| | - Mohamed A. Elrayess
- Biomedical Research Center, Qatar University, Doha, Qatar
- Biomedical Science Department, College of Health Sciences, Qatar University (QU) Health, Qatar University, Doha, Qatar
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Fuller H, Zhu Y, Nicholas J, Chatelaine HA, Drzymalla EM, Sarvestani AK, Julián-Serrano S, Tahir UA, Sinnott-Armstrong N, Raffield LM, Rahnavard A, Hua X, Shutta KH, Darst BF. Metabolomic epidemiology offers insights into disease aetiology. Nat Metab 2023; 5:1656-1672. [PMID: 37872285 PMCID: PMC11164316 DOI: 10.1038/s42255-023-00903-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 09/06/2023] [Indexed: 10/25/2023]
Abstract
Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.
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Affiliation(s)
- Harriett Fuller
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yiwen Zhu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jayna Nicholas
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Haley A Chatelaine
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Emily M Drzymalla
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Afrand K Sarvestani
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | | | - Usman A Tahir
- Department of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ali Rahnavard
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Xinwei Hua
- Department of Cardiology, Peking University Third Hospital, Beijing, China
| | - Katherine H Shutta
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Burcu F Darst
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
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7
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Haberbosch L, Kierszniowska S, Willmitzer L, Mai K, Spranger J, Maurer L. 5-Aminovaleric acid betaine predicts impaired glucose metabolism and diabetes. Nutr Diabetes 2023; 13:17. [PMID: 37730732 PMCID: PMC10511423 DOI: 10.1038/s41387-023-00245-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 08/18/2023] [Accepted: 08/29/2023] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND 5-Aminovaleric acid betaine (5-AVAB) has recently been identified as a diet and microbial-dependent factor inducing obesity and hepatic steatosis in mice fed a Western diet. Accumulating evidence suggests a role in metabolic dysfunction associated with obesity, diabetes, and fatty liver disease. However, whether 5-AVAB plays a role in human disease is unclear, and human data are sparse. METHODS We measured circulating 5-AVAB serum levels in 143 individuals with overweight or obesity participating in a randomized intervention study (NCT00850629) investigating the long-term effect of a weight maintenance strategy after diet-induced weight reduction. RESULTS Higher 5-AVAB serum levels correlate with worse estimates of obesity, glucose metabolism, and hepatic steatosis after weight loss. Furthermore, higher 5-AVAB levels after weight loss independently predict detrimental changes in glucose metabolism 18 months after the successful weight reduction. CONCLUSION Our human data supports previous findings in rodents indicating a relevant, potentially disadvantageous function of 5-AVAB in the context of metabolic dysbalance.
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Affiliation(s)
- Linus Haberbosch
- Department of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, 10117, Berlin, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Junior Digital Clinician Scientist Program, Charitéplatz 1, 10117, Berlin, Germany
| | | | | | - Knut Mai
- Department of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, 10117, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Charité Center for Cardiovascular Research, 10117, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Berlin, Berlin, Germany
| | - Joachim Spranger
- Department of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, 10117, Berlin, Germany.
- Charité - Universitätsmedizin Berlin, Charité Center for Cardiovascular Research, 10117, Berlin, Germany.
- DZHK (German Centre for Cardiovascular Research), partner site Berlin, Berlin, Germany.
| | - Lukas Maurer
- Department of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, 10117, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Charité Center for Cardiovascular Research, 10117, Berlin, Germany
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8
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Aleidi SM, Al Fahmawi H, Masoud A, Rahman AA. Metabolomics in diabetes mellitus: clinical insight. Expert Rev Proteomics 2023; 20:451-467. [PMID: 38108261 DOI: 10.1080/14789450.2023.2295866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 12/13/2023] [Indexed: 12/19/2023]
Abstract
INTRODUCTION Diabetes Mellitus (DM) is a chronic heterogeneous metabolic disorder characterized by hyperglycemia due to the destruction of insulin-producing pancreatic β cells and/or insulin resistance. It is now considered a global epidemic disease associated with serious threats to a patient's life. Understanding the metabolic pathways involved in disease pathogenesis and progression is important and would improve prevention and management strategies. Metabolomics is an emerging field of research that offers valuable insights into the metabolic perturbation associated with metabolic diseases, including DM. AREA COVERED Herein, we discussed the metabolomics in type 1 and 2 DM research, including its contribution to understanding disease pathogenesis and identifying potential novel biomarkers clinically useful for disease screening, monitoring, and prognosis. In addition, we highlighted the metabolic changes associated with treatment effects, including insulin and different anti-diabetic medications. EXPERT OPINION By analyzing the metabolome, the metabolic disturbances involved in T1DM and T2DM can be explored, enhancing our understanding of the disease progression and potentially leading to novel clinical diagnostic and effective new therapeutic approaches. In addition, identifying specific metabolites would be potential clinical biomarkers for predicting the disease and thus preventing and managing hyperglycemia and its complications.
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Affiliation(s)
- Shereen M Aleidi
- Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Hiba Al Fahmawi
- Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Afshan Masoud
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Anas Abdel Rahman
- Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh, Saudi Arabia
- Metabolomics Section, Department of Clinical Genomics, Center for Genomics Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
- Department of Chemistry, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada
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Zolkeflee NKZ, Wong PL, Maulidiani M, Ramli NS, Azlan A, Abas F. Metabolic Alterations in Streptozotocin-nicotinamide-induced Diabetic Rats Treated with Muntingia calabura Extract via 1H-NMR-based Metabolomics. PLANTA MEDICA 2023. [PMID: 36914160 DOI: 10.1055/a-2053-0950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Diabetes mellitus (DM) is a metabolic endocrine disorder caused by decreased insulin concentration or poor insulin response. Muntingia calabura (MC) has been used traditionally to reduce blood glucose levels. This study aims to support the traditional claim of MC as a functional food and blood-glucose-lowering regimen. The antidiabetic potential of MC is tested on a streptozotocin-nicotinamide (STZ-NA)-induced diabetic rat model by using the 1H-NMR-based metabolomic approach. Serum biochemical analyses reveal that treatment with 250 mg/kg body weight (bw) standardized freeze-dried (FD) 50% ethanolic MC extract (MCE 250) shows favorable serum creatinine (37.77 ± 3.53 µM), urea (5.98 ± 0.84 mM) and glucose (7.36 ± 0.57 mM) lowering capacity, which was comparable to the standard drug, metformin. The clear separation between diabetic control (DC) and normal group in principal component analysis indicates the successful induction of diabetes in the STZ-NA-induced type 2 diabetic rat model. A total of nine biomarkers, including allantoin, glucose, methylnicotinamide, lactate, hippurate, creatine, dimethylamine, citrate and pyruvate are identified in rats' urinary profile, discriminating DC and normal groups through orthogonal partial least squares-discriminant analysis. Induction of diabetes by STZ-NA is due to alteration in the tricarboxylic acid (TCA) cycle, gluconeogenesis pathway, pyruvate metabolism and nicotinate and nicotinamide metabolism. Oral treatment with MCE 250 in STZ-NA-induced diabetic rats shows improvement in the altered carbohydrate metabolism, cofactor and vitamin metabolic pathway, as well as purine and homocysteine metabolism.
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Affiliation(s)
- Nur Khaleeda Zulaikha Zolkeflee
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Pei Lou Wong
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - M Maulidiani
- Faculty of Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia
| | - Nurul Shazini Ramli
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Azrina Azlan
- Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Faridah Abas
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
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10
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Mi MY, Whitlock M, Shi X, Farrell LA, Bhambhani VM, Quadir J, Blatnik M, Wald KP, Tierney B, Kim A, Loudon P, Chen ZZ, Correa A, Gao Y, Carson AP, Bertoni AG, Roth Flach RJ, Gerszten RE. Mixed meal tolerance testing highlights in diabetes altered branched-chain ketoacid metabolism and pathways associated with all-cause mortality. Am J Clin Nutr 2023; 117:529-539. [PMID: 36811472 PMCID: PMC10356557 DOI: 10.1016/j.ajcnut.2023.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 12/22/2022] [Accepted: 01/03/2023] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Elevated BCAA levels are strongly associated with diabetes, but how diabetes affects BCAA, branched-chain ketoacids (BCKAs), and the broader metabolome after a meal is not well known. OBJECTIVE To compare quantitative BCAA and BCKA levels in a multiracial cohort with and without diabetes after a mixed meal tolerance test (MMTT) as well as to explore the kinetics of additional metabolites and their associations with mortality in self-identified African Americans. METHODS We administered an MMTT to 11 participants without obesity or diabetes and 13 participants with diabetes (treated with metformin only) and measured the levels of BCKAs, BCAAs, and 194 other metabolites at 8 time points across 5 h. We used mixed models for repeated measurements to compare between group metabolite differences at each timepoint with adjustment for baseline. We then evaluated the association of top metabolites with different kinetics with all-cause mortality in the Jackson Heart Study (JHS) (N = 2441). RESULTS BCAA levels, after adjustment for baseline, were similar at all timepoints between groups, but adjusted BCKA kinetics were different between groups for α-ketoisocaproate (P = 0.022) and α-ketoisovalerate (P = 0.021), most notably diverging at 120 min post-MMTT. An additional 20 metabolites had significantly different kinetics across timepoints between groups, and 9 of these metabolites-including several acylcarnitines-were significantly associated with mortality in JHS, irrespective of diabetes status. The highest quartile of a composite metabolite risk score was associated with higher mortality (HR:1.57; 1.20, 2.05, P = 0.00094) than the lowest quartile. CONCLUSIONS BCKA levels remained elevated after an MMTT among participants with diabetes, suggesting that BCKA catabolism may be a key dysregulated process in the interaction of BCAA and diabetes. Metabolites with different kinetics after an MMTT may be markers of dysmetabolism and associated with increased mortality in self-identified African Americans.
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Affiliation(s)
- Michael Y Mi
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA; Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | | | - Xu Shi
- Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Laurie A Farrell
- Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Juweria Quadir
- Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Kyle P Wald
- Early Clinical Development, Pfizer, Groton, CT, USA
| | | | - Albert Kim
- Internal Medicine Research Unit, Pfizer, Cambridge, MA, USA; Cytel, Cambridge, MA, USA
| | - Peter Loudon
- Early Clinical Development, Pfizer, Cambridge, UK; Tenpoint Therapeutics, Cambridge, UK
| | - Zsu-Zsu Chen
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Adolfo Correa
- Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yan Gao
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Alain G Bertoni
- Department of Epidemiology & Prevention, Wake Forest School of Medicine, Winston Salem, NC, USA
| | | | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA; Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
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11
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Bagheripour F, Jeddi S, Kashfi K, Ghasemi A. Metabolic effects of L-citrulline in type 2 diabetes. Acta Physiol (Oxf) 2023; 237:e13937. [PMID: 36645144 DOI: 10.1111/apha.13937] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 01/01/2023] [Accepted: 01/10/2023] [Indexed: 01/17/2023]
Abstract
The prevalence of type 2 diabetes (T2D) is increasing worldwide. Decreased nitric oxide (NO) bioavailability is involved in the pathophysiology of T2D and its complications. L-citrulline (Cit), a precursor of NO production, has been suggested as a novel therapeutic agent for T2D. Available data from human and animal studies indicate that Cit supplementation in T2D increases circulating levels of Cit and L-arginine while decreasing circulating glucose and free fatty acids and improving dyslipidemia. The underlying mechanisms for these beneficial effects of Cit include increased insulin secretion from the pancreatic β cells, increased glucose uptake by the skeletal muscle, as well as increased lipolysis and β-oxidation, and decreased glyceroneogenesis in the adipose tissue. Thus, Cit has antihyperglycemic, antidyslipidemic, and antioxidant effects and has the potential to be used as a new therapeutic agent in the management of T2D. This review summarizes available literature from human and animal studies to explore the effects of Cit on metabolic parameters in T2D. It also discusses the possible mechanisms underlying Cit-induced improved metabolic parameters in T2D.
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Affiliation(s)
- Fatemeh Bagheripour
- Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sajad Jeddi
- Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Khosrow Kashfi
- Department of Molecular, Cellular and Biomedical Sciences, Sophie Davis School of Biomedical Education, City University of New York School of Medicine, New York, New York, USA
| | - Asghar Ghasemi
- Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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12
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Top WMC, Lehert P, Schalkwijk CG, Stehouwer CDA, Kooy A. Effect of metformin on arginine and dimethylarginines in patients with advanced type 2 diabetes: A post hoc analysis of a randomized trial. Diabetes Obes Metab 2022; 24:1983-1988. [PMID: 35789192 DOI: 10.1111/dom.14784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/25/2022] [Accepted: 06/06/2022] [Indexed: 11/28/2022]
Abstract
AIM To study the effect of metformin on plasma levels of arginine, asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA), indicators of the nitric oxide pathway. MATERIALS AND METHODS In this post hoc analysis of the HOME trial, we analysed plasma levels of arginine, ADMA and SDMA during the 4.3-year follow-up (comparing the effects of metformin versus placebo on top of insulin therapy). Statistical analysis was performed with a mixed model approach, in which simultaneously constant treatment effects were estimated, as well as time-dependent treatment effects. RESULTS We found that metformin compared with placebo did not affect ADMA or SDMA plasma levels but rapidly decreased arginine plasma levels and hence the arginine to ADMA ratio. The constant treatment effect on ADMA was 0.99 (95% CI 0.97, 1.00) relative to placebo and the time-dependent treatment effect was 1.00 (95% CI 1.00, 1.01). By contrast, the constant treatment effect on arginine was 0.86 (95% CI 0.84, 0.88), with only a minimal time-dependent change of 1.01 (95% CI 1.00, 1.01). CONCLUSIONS The potential benefits of metformin on endothelial function cannot be explained by a decrease in ADMA or by improved global arginine availability. The clinical significance of the decreased arginine plasma levels is not clear and can be harmful or beneficial, depending on the mechanism involved. However, a potential effect of metformin on the nitric oxide pathway is not restricted to the studied metabolites.
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Affiliation(s)
- Wiebe M C Top
- Department of Internal Medicine, Treant Care Group, Hoogeveen, The Netherlands
- Bethesda Diabetes Research Center, Hoogeveen, The Netherlands
| | - Philippe Lehert
- Department of Statistics, Faculty of Economics, Facultés Universitaires Catholiques de Mons, Louvain Academy, Mons, Belgium
| | - Casper G Schalkwijk
- Department of Internal Medicine and Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Coen D A Stehouwer
- Department of Internal Medicine and Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Adriaan Kooy
- Department of Internal Medicine, Treant Care Group, Hoogeveen, The Netherlands
- Bethesda Diabetes Research Center, Hoogeveen, The Netherlands
- Department of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands
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13
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SIRT3 Modulates Endothelial Mitochondrial Redox State during Insulin Resistance. Antioxidants (Basel) 2022; 11:antiox11081611. [PMID: 36009329 PMCID: PMC9404744 DOI: 10.3390/antiox11081611] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 08/15/2022] [Accepted: 08/16/2022] [Indexed: 12/16/2022] Open
Abstract
Emerging evidence indicates that defects in sirtuin signaling contribute to impaired glucose and lipid metabolism, resulting in insulin resistance (IR) and endothelial dysfunction. Here, we examined the effects of palmitic acid (PA) treatment on mitochondrial sirtuins (SIRT2, SIRT3, SIRT4, and SIRT5) and oxidative homeostasis in human endothelial cells (TeloHAEC). Results showed that treatment for 48 h with PA (0.5 mM) impaired cell viability, induced loss of insulin signaling, imbalanced the oxidative status (p < 0.001), and caused negative modulation of sirtuin protein and mRNA expression, with a predominant effect on SIRT3 (p < 0.001). Restoration of SIRT3 levels by mimic transfection (SIRT3+) suppressed the PA-induced autophagy (mimic NC+PA) (p < 0.01), inflammation, and pyroptosis (p < 0.01) mediated by the NLRP3/caspase-1 axis. Moreover, the unbalanced endothelial redox state induced by PA was counteracted by the antioxidant δ-valerobetaine (δVB), which was able to upregulate protein and mRNA expression of sirtuins, reduce reactive oxygen species (ROS) accumulation, and decrease cell death. Overall, results support the central role of SIRT3 in maintaining the endothelial redox homeostasis under IR and unveil the potential of the antioxidant δVB in enhancing the defense against IR-related injuries.
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14
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Maurya M, Jaiswal A, Gupta S, Ali W, Gaikwad AN, Dikshit M, Barthwal MK. Galectin-3 S-glutathionylation regulates its effect on adipocyte insulin signaling. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2022; 1869:119234. [PMID: 35143900 DOI: 10.1016/j.bbamcr.2022.119234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 01/27/2022] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
Protein-S-glutathionylation promotes redox signaling in physiological and oxidative distress conditions. Galectin-3 (Gal-3) promotes insulin resistance by down-regulating adipocyte insulin signaling, however, its S-glutathionylation and significance is not known. In this context, we report reversible S-glutathionylation of Gal-3. Site-directed mutagenesis established Gal-3 Cys187 as the putative S-glutathionylation site. Glutathionylated Gal-3 prevents Gal-3(WT)-Insulin Receptor interaction and facilitates insulin-induced murine adipocyte p-IRS1(tyr895) and p-AKT(ser473) signaling and glucose uptake in a Gal-3 Cys187 glutathionylation dependent manner in murine adipocytes, as assessed by Western blotting and 2-NBDG uptake assay respectively. Pre-glutathionylated Gal-3 at Cys187 resisted irreversible oxidation by H2O2. M2 macrophages showed enhanced Gal-3 S-glutathionylation when compared to M1 phenotype. Serum and stromal vascular fraction (SVF) isolated from control mice showed increased Gal-3 S-glutathionylation as compared to db/db mice. A significant increase in Gal-3 S-glutathionylation was observed in metformin-treated db/db mice when compared to db/db mice alone. Similar to murine, enhanced Gal-3 S-glutathionylation is observed in primary human monocyte derived M2 macrophages when compared to the M1 macrophage phenotype and Gal-3 regulates primary human adipocyte insulin signaling in a glutathionylation dependent manner. Collectively, we identified Gal-3 S-glutathionylation as a protective phenomenon, which relieves its inhibitory effect on adipocyte insulin signaling.
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Affiliation(s)
- Mohita Maurya
- Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow 226031, India
| | - Anant Jaiswal
- Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow 226031, India
| | - Sanchita Gupta
- Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow 226031, India
| | - Wahid Ali
- King George's Medical University, Lucknow 226003, India
| | | | - Madhu Dikshit
- Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow 226031, India
| | - Manoj Kumar Barthwal
- Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow 226031, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad - 201002, India.
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15
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Artemether Alleviates Diabetic Kidney Disease by Modulating Amino Acid Metabolism. BIOMED RESEARCH INTERNATIONAL 2022; 2022:7339611. [PMID: 35601149 PMCID: PMC9117059 DOI: 10.1155/2022/7339611] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 04/08/2022] [Indexed: 11/17/2022]
Abstract
Diabetes is a worldwide metabolic disease with rapid growing incidence, characterized by hyperglycemia. Diabetic kidney disease (DKD), the leading cause of chronic kidney disease (CKD), has a high morbidity according to the constantly increasing diabetic patients and always develops irreversible deterioration of renal function. Though different in pathogenesis, clinical manifestations, and therapies, both type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) can evolve into DKD. Since amino acids are both biomarkers and causal agents, rarely report has been made about its metabolism which lies in T1DM- and T2DM-related kidney disease. This study was designed to investigate artemether in adjusting renal amino acid metabolism in T1DM and T2DM mice. Artemether was applied as treatment in streptozotocin (STZ) induced T1DM mice and db/db T2DM mice, respectively. Artemether-treated mice showed lower FBG and HbA1c and reduced urinary albumin excretion, as well as urinary NAG. Both types of diabetic mice showed enlarged kidneys, as confirmed by increased kidney weight and the ratio of kidney weight to body weight. Artemether normalized kidney size and thus attenuated renal hypertrophy. Kidney tissue UPLC-MS analysis showed that branched-chain amino acids (BCAAs) and citrulline were upregulated in diabetic mice without treatment and downregulated after being treated with artemether. Expressions of glutamine, glutamic acid, aspartic acid, ornithine, glycine, histidine, phenylalanine and threonine were decreased in both types of diabetic mice whereas they increased after artemether treatment. The study demonstrates the initial evidence that artemether exerted renal protection in DKD by modulating amino acid metabolism.
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Kärkkäinen O, Koistinen V, Hanhineva K. Inconsistent nomenclature of microbiota-associated metabolites hampers progress of the field. Nat Metab 2022; 4:406. [PMID: 35383295 DOI: 10.1038/s42255-022-00562-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Olli Kärkkäinen
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland.
| | - Ville Koistinen
- Food Chemistry and Food Development Unit, University of Turku, Turku, Finland
| | - Kati Hanhineva
- Food Chemistry and Food Development Unit, University of Turku, Turku, Finland.
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17
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Hu N, Zhang Q, Wang H, Yang X, Jiang Y, Chen R, Wang L. Comparative Evaluation of the Effect of Metformin and Insulin on Gut Microbiota and Metabolome Profiles of Type 2 Diabetic Rats Induced by the Combination of Streptozotocin and High-Fat Diet. Front Pharmacol 2022; 12:794103. [PMID: 35046817 PMCID: PMC8762251 DOI: 10.3389/fphar.2021.794103] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 11/22/2021] [Indexed: 12/12/2022] Open
Abstract
Lately, an increasing number of studies have investigated the relationship between metformin and gut microbiota, suggesting that metformin exerts part of its hypoglycemic effect through the microbes. However, its underlying mechanism remains largely undetermined. In the present study, we investigated the effects of metformin on gut microbiota and metabolome profiles in serum and compared it with insulin treatment in rats with type 2 diabetes mellitus (T2DM). Diabetic rats (DM group) were induced by a combination of streptozotocin and high-fat diet (HFD). After 7 days, DM rats were treated with metformin (MET group) or insulin (INS group) for 3 weeks. The 16S rRNA sequencing of the gut microbiota and non-targeted metabolomics analysis of serum were conducted. A total of 13 bile acids (BAs) in serum were further determined and compared among different groups. The rat model of T2DM was well established with the typical diabetic symptoms, showing significantly increased blood glucose, AUC of OGTT, HOMA-IR, TC, TG, LDL-C and TBA. Metformin or insulin treatment could ameliorate symptoms of diabetes and partly recover the abnormal biochemical indicators. Compared with DM rats, the relative abundances of 13 genera were significantly changed after metformin treatment, while only three genera were changed after insulin treatment. The metformin and insulin treatments also exhibited different serum metabolome profiles in T2DM rats. Moreover, 64 differential metabolites were identified between MET and DM groups, whereas 206 were identified between INS and DM groups. Insulin treatment showed greater influence on amino acids, glycerophospholipids/glycerolipids, and acylcarnitine compared with the metformin treatment, while metformin had an important impact on BAs. Furthermore, metformin could significantly decrease the serum levels of CA, GCA, UDCA, and GUDCA, but increase the level of TLCA in DM rats. Insulin treatment significantly decreased the levels of CA, UDCA, and CDCA. Besides, several metabolites in serum or microbiota were positively or negatively correlated with some bacteria. Collectively, our findings indicated that metformin had a stronger effect on gut microbiota than insulin, while insulin treatment showed greater influence on serum metabolites, which provided novel insights into the therapeutic effects of metformin on diabetes.
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Affiliation(s)
- Nan Hu
- Department of Pharmacy, The Third Affiliated Hospital of Soochow University/The First People's Hospital of Changzhou, Changzhou, China
| | - Qi Zhang
- Department of Pharmacy, Changzhou No. 7 People's Hospital, Changzhou, China
| | - Hui Wang
- Department of Pathology, The Third Affiliated Hospital of Soochow University/The First People's Hospital of Changzhou, Changzhou, China
| | - Xuping Yang
- Department of Pharmacy, The Third Affiliated Hospital of Soochow University/The First People's Hospital of Changzhou, Changzhou, China
| | - Yan Jiang
- Department of Pharmacy, The Third Affiliated Hospital of Soochow University/The First People's Hospital of Changzhou, Changzhou, China
| | - Rong Chen
- Department of Pharmacy, The Third Affiliated Hospital of Soochow University/The First People's Hospital of Changzhou, Changzhou, China
| | - Liying Wang
- Department of Pharmacy, The Third Affiliated Hospital of Soochow University/The First People's Hospital of Changzhou, Changzhou, China
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18
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Taya N, Katakami N, Omori K, Arakawa S, Hosoe S, Watanabe H, Takahara M, Miyashita K, Nishizawa H, Matsuoka T, Furuno M, Bamba T, Iida J, Fukusaki E, Shimomura I. Evaluation of change in metabolome caused by comprehensive diabetes treatment: A prospective observational study of diabetes inpatients with gas chromatography/mass spectrometry-based non-target metabolomic analysis. J Diabetes Investig 2021; 12:2232-2241. [PMID: 34032389 PMCID: PMC8668060 DOI: 10.1111/jdi.13600] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 04/17/2021] [Accepted: 05/20/2021] [Indexed: 11/28/2022] Open
Abstract
AIMS/INTRODUCTION Diabetes patients develop a variety of metabolic abnormalities in addition to hyperglycemia. However, details regarding change in various metabolites after comprehensive diabetes treatment remain unknown. This study aimed to identify the short-term change in metabolome in inpatients who were subject to comprehensive diabetes treatment, using gas chromatography/mass spectrometry-based non-target metabolomics techniques. MATERIALS AND METHODS Participants of the present study were randomly recruited from the patients with type 2 diabetes hospitalized due to problems with glycemic control (n = 31) and volunteers without diabetes (n = 30), both of whom were aged between 20 and 75 years. A metabolomic analysis of fasting plasma samples on the 2nd (pre-treatment) and 16th hospital (post-treatment) day with gas chromatography/mass spectrometry using a multiple reaction monitoring mode was carried out. RESULTS A principal component analysis showed that metabolome of fasting plasma was different between individuals with and without diabetes. The metabolome of fasting plasma in diabetes patients after treatment was different from that of pre-treatment, as well as individuals without diabetes. Many amino acids (proline, glycine, serine, threonine, methionine, pyroglutamic acid, glutamine and lysine) were significantly increased by >10% after administering the inpatient diabetes treatment. A hierarchical clustering analysis showed that in the case of patients with markedly decreased monosaccharide levels and increased 1,5-anhydroglucitol, the levels of amino acids increased more significantly. CONCLUSIONS After a 2-week comprehensive treatment, the plasma levels of various amino acids increased in conjunction with the reduction in monosaccharide levels in poorly controlled type 2 diabetes patients.
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Affiliation(s)
- Naohiro Taya
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Naoto Katakami
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
- Department of Metabolism and AtherosclerosisOsaka University Graduate School of MedicineOsakaJapan
| | - Kazuo Omori
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Shoya Arakawa
- Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
| | - Shigero Hosoe
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Hirotaka Watanabe
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Mitsuyoshi Takahara
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
- Department of Diabetes Care MedicineGraduate School of MedicineOsaka UniversityOsakaJapan
| | - Kazuyuki Miyashita
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Hitoshi Nishizawa
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Taka‐Aki Matsuoka
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Masahiro Furuno
- Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
| | - Takeshi Bamba
- Division of MetabolomicsResearch Center for Transomics MedicineMedical Institute of BioregulationKyushu UniversityFukuokaJapan
| | - Junko Iida
- Shimadzu CorporationKyotoJapan
- Osaka University Shimadzu Omics Innovation Research LaboratoriesGraduate School of EngineeringOsaka UniversityOsakaJapan
| | - Eiichiro Fukusaki
- Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
| | - Iichiro Shimomura
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
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19
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Pontifex MG, Mushtaq A, Le Gall G, Rodriguez-Ramiro I, Blokker BA, Hoogteijling MEM, Ricci M, Pellizzon M, Vauzour D, Müller M. Differential Influence of Soluble Dietary Fibres on Intestinal and Hepatic Carbohydrate Response. Nutrients 2021; 13:nu13124278. [PMID: 34959832 PMCID: PMC8706546 DOI: 10.3390/nu13124278] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/25/2021] [Accepted: 11/25/2021] [Indexed: 12/16/2022] Open
Abstract
Refined foods are commonly depleted in certain bioactive components that are abundant in 'natural' (plant) foods. Identification and addition of these 'missing' bioactives in the diet is, therefore, necessary to counteract the deleterious impact of convenience food. In this study, multiomics approaches were employed to assess the addition of the popular supplementary soluble dietary fibers inulin and psyllium, both in isolation and in combination with a refined animal feed. A 16S rRNA sequencing and 1H NMR metabolomic investigation revealed that, whilst inulin mediated an increase in Bifidobacteria, psyllium elicited a broader microbial shift, with Parasutterella and Akkermansia being increased and Enterorhabdus and Odoribacter decreased. Interestingly, the combination diet benefited from both inulin and psyllium related microbial changes. Psyllium mediated microbial changes correlated with a reduction of glucose (R -0.67, -0.73, respectively, p < 0.05) and type 2 diabetes associated metabolites: 3-methyl-2-oxovaleric acid (R -0.72, -0.78, respectively, p < 0.05), and citrulline (R -0.77, -0.71, respectively, p < 0.05). This was in line with intestinal and hepatic carbohydrate response (e.g., Slc2a2, Slc2a5, Khk and Fbp1) and hepatic lipogenesis (e.g., Srebf1 and Fasn), which were significantly reduced under psyllium addition. Although established in the liver, the intestinal response associated with psyllium was absent in the combination diet, placing greater significance upon the established microbial, and subsequent metabolomic, shift. Our results therefore highlight the heterogeneity that exists between distinct dietary fibers in the context of carbohydrate uptake and metabolism, and supports psyllium containing combination diets, for their ability to negate the impact of a refined diet.
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Affiliation(s)
- Matthew G. Pontifex
- Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK; (M.G.P.); (A.M.); (G.L.G.); (I.R.-R.); (B.A.B.); (M.E.M.H.); (D.V.)
| | - Aleena Mushtaq
- Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK; (M.G.P.); (A.M.); (G.L.G.); (I.R.-R.); (B.A.B.); (M.E.M.H.); (D.V.)
| | - Gwenaëlle Le Gall
- Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK; (M.G.P.); (A.M.); (G.L.G.); (I.R.-R.); (B.A.B.); (M.E.M.H.); (D.V.)
| | - Ildefonso Rodriguez-Ramiro
- Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK; (M.G.P.); (A.M.); (G.L.G.); (I.R.-R.); (B.A.B.); (M.E.M.H.); (D.V.)
| | - Britt Anne Blokker
- Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK; (M.G.P.); (A.M.); (G.L.G.); (I.R.-R.); (B.A.B.); (M.E.M.H.); (D.V.)
| | - Mara E. M. Hoogteijling
- Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK; (M.G.P.); (A.M.); (G.L.G.); (I.R.-R.); (B.A.B.); (M.E.M.H.); (D.V.)
| | - Matthew Ricci
- Research Diets, Inc., New Brunswick, NJ 08901, USA; (M.R.); (M.P.)
| | | | - David Vauzour
- Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK; (M.G.P.); (A.M.); (G.L.G.); (I.R.-R.); (B.A.B.); (M.E.M.H.); (D.V.)
| | - Michael Müller
- Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK; (M.G.P.); (A.M.); (G.L.G.); (I.R.-R.); (B.A.B.); (M.E.M.H.); (D.V.)
- Correspondence: ; Tel.: +44-160-359-3047
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20
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Metabolomic Approaches to Investigate the Effect of Metformin: An Overview. Int J Mol Sci 2021; 22:ijms221910275. [PMID: 34638615 PMCID: PMC8508882 DOI: 10.3390/ijms221910275] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/21/2021] [Accepted: 09/22/2021] [Indexed: 12/13/2022] Open
Abstract
Metformin is the first-line antidiabetic drug that is widely used in the treatment of type 2 diabetes mellitus (T2DM). Even though the various therapeutic potential of metformin treatment has been reported, as well as the improvement of insulin sensitivity and glucose homeostasis, the mechanisms underlying those benefits are still not fully understood. In order to explain the beneficial effects on metformin treatment, various metabolomics analyses have been applied to investigate the metabolic alterations in response to metformin treatment, and significant systemic metabolome changes were observed in biofluid, tissues, and cells. In this review, we compare the latest metabolomic research including clinical trials, animal models, and in vitro studies comprehensively to understand the overall changes of metabolome on metformin treatment.
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21
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Dahabiyeh LA, Mujammami M, Arafat T, Benabdelkamel H, Alfadda AA, Abdel Rahman AM. A Metabolic Pattern in Healthy Subjects Given a Single Dose of Metformin: A Metabolomics Approach. Front Pharmacol 2021; 12:705932. [PMID: 34335266 PMCID: PMC8319764 DOI: 10.3389/fphar.2021.705932] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 06/28/2021] [Indexed: 01/27/2023] Open
Abstract
Metformin is a widely prescribed medication for the treatment of type 2 diabetes mellitus (T2DM). It possesses effective roles in various disorders, including cancer, dyslipidemia, and obesity. However, the underlying mechanisms of metformin's multiple benefits are not fully understood. Herein, a mass spectrometry-based untargeted metabolomics approach was used to investigate the metabolic changes associated with the administration of a single dose of metformin in the plasma of 26 healthy subjects at five-time points; pre-dose, before the maximum concentration of metformin (Cmax), Cmax, after Cmax, and 36 h post-dose. A total of 111 metabolites involved in various biochemical processes were perturbed, with branched-chain amino acid (BCAA) being the most significantly altered pathway. Additionally, the Pearson similarity test revealed that 63 metabolites showed a change in their levels dependent on metformin level. Out of these 63, the level of 36 metabolites was significantly altered by metformin. Significantly altered metformin-dependent metabolites, including hydroxymethyl uracil, propionic acid, glycerophospholipids, and eicosanoids, pointed to fundamental biochemical processes such as lipid network signaling, energy homeostasis, DNA lesion repair mechanisms, and gut microbiota functions that could be linked to the multiple beneficial roles of metformin. Thus, the distinctive metabolic pattern linked to metformin administration can be used as a metabolic signature to predict the potential effect and mechanism of actions of new chemical entities during drug development.
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Affiliation(s)
- Lina A Dahabiyeh
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Muhammad Mujammami
- Endocrinology and Diabetes Unit, Department of Medicine, College of Medicine, King Saud University, Riyadh, Saudi Arabia.,University Diabetes Center, King Saud University Medical City, King Saud University, Riyadh, Saudi Arabia
| | - Tawfiq Arafat
- Jordan Center for Pharmaceutical Research, Amman, Jordan
| | - Hicham Benabdelkamel
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Assim A Alfadda
- Endocrinology and Diabetes Unit, Department of Medicine, College of Medicine, King Saud University, Riyadh, Saudi Arabia.,Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Anas M Abdel Rahman
- Metabolomics Section, Department of Clinical Genomics, Center for Genome Medicine, King Faisal Specialist Hospital and Research Centre (KFSHRC), Riyadh, Saudi Arabia.,Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh, Saudi Arabia.,Department of Chemistry, Memorial University of Newfoundland, St. John's, NL, Canada
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22
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A Cross-Talk between the Erythrocyte L-Arginine/ADMA/Nitric Oxide Metabolic Pathway and the Endothelial Function in Subjects with Type 2 Diabetes Mellitus. Nutrients 2021; 13:nu13072306. [PMID: 34371816 PMCID: PMC8308357 DOI: 10.3390/nu13072306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/02/2021] [Accepted: 07/02/2021] [Indexed: 11/16/2022] Open
Abstract
(1) Background: Type-2-diabetes-mellitus (DM) is one the most important cardiovascular-risk-factors. Among many molecules regulating vascular tone, nitric oxide appears to be the most pivotal. Although micro- and macrovascular-abnormalities are extensively studied, the alterations in the nitric-oxide-metabolic-pathway require further investigations. Additionally, the role of erythrocytes in the vascular tone regulation has not been extensively explored. The aim of this study was to evaluate the endothelial-function and the nitric-oxide-metabolic-pathway in erythrocytes and plasma of diabetic individuals. (2) Methods: A total of 80 subjects were enrolled in this cross-sectional study, including 35 patients with DM and 45 healthy individuals. The endothelial-function was evaluated in response to different stimuli. (3) Results: In the DM group, decreased Arginine and citrulline concentrations in the plasma compartment with reduced Arginine/ADMA and ADMA/DMA-ratios were observed. Preserved nitric-oxide-metabolism in erythrocytes with reduced citrulline level and significantly higher NO-bioavailability were noted. Significant endothelial dysfunction in DM individuals was proved in response to the heat-stimulus. (4) Conclusions: DM patients at an early stage of disease show significant differences in the nitric-oxide-metabolic-pathway, which are more pronounced in the plasma compartment. Erythrocytes constitute a buffer with a higher nitric-oxide-bioavailability, less affected by the DM-related deviations. Patients at an early-stage of DM reveal endothelial-dysfunction, which could be diagnosed earlier using the laser-Doppler-flowmetry.
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23
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Morais T, Seabra AL, Patrício BG, Guimarães M, Nora M, Oliveira PF, Alves MG, Monteiro MP. Visceral Adipose Tissue Displays Unique Metabolomic Fingerprints in Obesity, Pre-Diabetes and Type 2 Diabetes. Int J Mol Sci 2021; 22:5695. [PMID: 34071774 PMCID: PMC8199212 DOI: 10.3390/ijms22115695] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 05/24/2021] [Accepted: 05/24/2021] [Indexed: 11/16/2022] Open
Abstract
Visceral adipose tissue (VAT) metabolic profiling harbors the potential to disentangle molecular changes underlying obesity-related dysglycemia. In this study, the VAT exometabolome of subjects with obesity and different glycemic statuses are analyzed. The subjects (n = 19) are divided into groups according to body mass index and glycemic status: subjects with obesity and euglycemia (Ob+NGT, n = 5), subjects with obesity and pre-diabetes (Ob+Pre-T2D, n = 5), subjects with obesity and type 2 diabetes under metformin treatment (Ob+T2D, n = 5) and subjects without obesity and with euglycemia (Non-Ob, n = 4), used as controls. VATs are incubated in culture media and extracellular metabolite content is determined by proton nuclear magnetic resonance (1H-NMR). Glucose consumption is not different between the groups. Pyruvate and pyroglutamate consumption are significantly lower in all groups of subjects with obesity compared to Non-Ob, and significantly lower in Ob+Pre-T2D as compared to Ob+NGT. In contrast, isoleucine consumption is significantly higher in all groups of subjects with obesity, particularly in Ob+Pre-T2D, compared to Non-Ob. Acetate production is also significantly lower in Ob+Pre-T2D compared to Non-Ob. In sum, the VAT metabolic fingerprint is associated with pre-diabetes and characterized by higher isoleucine consumption, accompanied by lower acetate production and pyruvate and pyroglutamate consumption. We propose that glucose metabolism follows different fates within the VAT, depending on the individuals' health status.
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Affiliation(s)
- Tiago Morais
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Alexandre L. Seabra
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Bárbara G. Patrício
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Marta Guimarães
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
- Department of General Surgery, Centro Hospitalar de Entre o Douro e Vouga, 4520-220 Santa Maria da Feira, Portugal
| | - Mário Nora
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of General Surgery, Centro Hospitalar de Entre o Douro e Vouga, 4520-220 Santa Maria da Feira, Portugal
| | - Pedro F. Oliveira
- QOPNA & LAQV, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal;
| | - Marco G. Alves
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Mariana P. Monteiro
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
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24
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Tian R, Liu H, Feng S, Wang H, Wang Y, Wang Y, Liang L, Xu H, Xing H, Zhang S. Gut microbiota dysbiosis in stable coronary artery disease combined with type 2 diabetes mellitus influences cardiovascular prognosis. Nutr Metab Cardiovasc Dis 2021; 31:1454-1466. [PMID: 33810955 DOI: 10.1016/j.numecd.2021.01.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 12/29/2020] [Accepted: 01/11/2021] [Indexed: 01/06/2023]
Abstract
BACKGROUND AND AIMS Host-microbiota interactions involving metabolic pathways have been linked to the pathogenesis of atherosclerotic disease and type 2 diabetes. As stable coronary artery disease (SCAD) patients combined with type 2 diabetes have significantly increased risk for cardiac event, we focused on elucidating the role of microbiota affecting cardiometabolic disease development. METHODS AND RESULTS We used multi-omics analyses (metagenomics and metabolomics) of fecal and serum samples from a prospective cohort including stable coronary artery disease combined with diabetes mellitus (SCAD + T2DM, n = 38), SCAD (n = 71), and healthy control (HC, n = 55). We linked microbiome features to disease severity in a three-pronged association analysis and identified prognostic bacterial biomarkers. We identified that bacterial and metabolic signatures varied significantly between SCAD and SCAD + T2DM groups. SCAD + T2DM individuals were characterized by increased levels of aromatic amino acids and carbohydrates, which correlate with a gut microbiome with enriched biosynthetic potential. Our study also addressed how metformin may confound gut dysbiosis and increase the potential for nitrogen metabolism. In addition, we found that specific bacterial taxa Ruminococcus torques [HR: 2.363 (08-4.56), P = 0.03] was predictive of cardiac survival outcomes. CONCLUSION Overall, our study identified relationships between features of the gut microbiota (GM) and circulating metabolites, providing a new direction for future studies aiming to understand the host-GM interplay in atherosclerotic cardiovascular pathogenesis.
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Affiliation(s)
- Ran Tian
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Honghong Liu
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Siqin Feng
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Hui Wang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Yifei Wang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China; Department of Medicine, Tsinghua University, Haidian district, Beijing, China.
| | - Yiyang Wang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China; Department of Medicine, Tsinghua University, Haidian district, Beijing, China.
| | - Lifeng Liang
- Precision Medicine Institute, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.
| | - Haopeng Xu
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Haiping Xing
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
| | - Shuyang Zhang
- Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
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25
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Vega-Beyhart A, Iruarrizaga M, Pané A, García-Eguren G, Giró O, Boswell L, Aranda G, Flores V, Casals G, Alonso C, Mora M, Halperin I, Carmona F, Enseñat J, Vidal O, Hu T, Rojo G, Gomis R, Hanzu FA. Endogenous cortisol excess confers a unique lipid signature and metabolic network. J Mol Med (Berl) 2021; 99:1085-1099. [PMID: 33881561 DOI: 10.1007/s00109-021-02076-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 03/08/2021] [Accepted: 04/06/2021] [Indexed: 12/29/2022]
Abstract
Chronic cortisol excess induces several alterations on protein, lipid and carbohydrate metabolism resembling those found in the metabolic syndrome. However, patients exposed to prolonged high levels of cortisol in Cushing syndrome (CS) present exceeding cardiometabolic alterations not reflected by conventional biomarkers. Using 3 ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS) platforms, we aimed to characterise the serum metabolome of 25 patients with active endogenous CS and 25 control subjects matched by propensity score (sex, BMI, diabetes mellitus type 2 (T2D), high blood pressure (HBP) and dyslipidaemia) to search for potential disease-specific biomarkers and pathways associated to the clinical comorbidities. A total of 93 metabolites were significantly altered in patients with CS. Increased levels of sulfur amino acids (AA), triacylglycerols, glycerophospholipids, ceramides and cholesteryl esters were observed. Contrarily, concentrations of essential and non-essential AA, polyunsaturated fatty acids, conjugated bile acids and second messenger glycerolipids were decreased. Twenty-four-hour urinary free cortisol (24h-UFC) independently determined the concentration of 21 lipids and 4 AA. A metabolic signature composed by 10 AA and 10 lipid metabolites presented an AUC-ROC of 95% for the classification of CS patients. Through differential network analysis, 152 aberrant associations between metabolites involved in the Lands cycle and Kennedy pathway were identified. Our data indicates that chronic hypercortisolemia confers a unique lipidomic signature and several alterations in numerous AA even when compared to patients with similar metabolic comorbidities providing novel insights of the increased cardiometabolic burden of CS. KEY MESSAGES: • Cortisol excess induces metabolic alterations beyond conventional biomarkers. • The hypercortisolism extent determines the concentration of 21 lipids and 5 aa. • Cortisol excess confers a unique metabolic signature of 20 metabolites. • Kennedy and Lands cycle are profoundly disturbed by cortisol excess.
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Affiliation(s)
- Arturo Vega-Beyhart
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain.,Endocrinology and Nutrition Department, Hospital Clínic, Barcelona, Spain
| | | | - Adriana Pané
- Endocrinology and Nutrition Department, Hospital Clínic, Barcelona, Spain
| | - Guillermo García-Eguren
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain
| | - Oriol Giró
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain
| | - Laura Boswell
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain.,Endocrinology and Nutrition Department, Hospital Clínic, Barcelona, Spain
| | - Gloria Aranda
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain
| | - Vanesa Flores
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain.,Endocrinology and Nutrition Department, Hospital Clínic, Barcelona, Spain
| | - Gregori Casals
- Biomedical diagnostics Centre, Hospital Clínic, Barcelona, Spain
| | | | - Mireia Mora
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain.,Endocrinology and Nutrition Department, Hospital Clínic, Barcelona, Spain
| | - Irene Halperin
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain.,Endocrinology and Nutrition Department, Hospital Clínic, Barcelona, Spain
| | | | | | - Oscar Vidal
- Surgery Department, Hospital Clínic, Barcelona, Spain
| | - Ting Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Gemma Rojo
- Endocrinology and Nutrition Clinical Management Unit. Hospital Regional Universitario de Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain.,Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Ramon Gomis
- Endocrinology and Nutrition Department, Hospital Clínic, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.,Laboratory of Diabetes and Obesity, IDIBAPS, Barcelona, Spain.,Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Felicia A Hanzu
- Group of Endocrine Disorders, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Carrer Rosselló, 149, 08036, Barcelona, Spain. .,Endocrinology and Nutrition Department, Hospital Clínic, Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. .,Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.
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26
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Lewandowski CT, Khan MW, BenAissa M, Dubrovskyi O, Ackerman-Berrier M, LaDu MJ, Layden BT, Thatcher GRJ. Metabolomic analysis of a selective ABCA1 inducer in obesogenic challenge provides a rationale for therapeutic development. EBioMedicine 2021; 66:103287. [PMID: 33752129 PMCID: PMC8010624 DOI: 10.1016/j.ebiom.2021.103287] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 03/02/2021] [Accepted: 03/02/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Therapeutic agents with novel mechanisms of action are needed to combat the growing epidemic of type 2 diabetes (T2D) and related metabolic syndromes. Liver X receptor (LXR) agonists possess preclinical efficacy yet produce side effects due to excessive lipogenesis. Anticipating that many beneficial and detrimental effects of LXR agonists are mediated by ABCA1 and SREPB1c expression, respectively, we hypothesized that a phenotypic optimization strategy prioritizing selective ABCA1 induction would identify an efficacious lead compound with an improved side effect profile over existing LXRβ agonists. METHODS We synthesized and characterized a novel small molecule for selective induction of ABCA1 vs. SREBP1c in vitro. This compound was evaluated in both wild-type mice and a high-fat diet (HFD) mouse model of obesity-driven diabetes through functional, biochemical, and metabolomic analysis. FINDINGS Six weeks of oral administration of our lead compound attenuated weight gain, glucose intolerance, insulin signaling deficits, and adiposity. Global metabolomics revealed suppression of gluconeogenesis, free fatty acids, and pro-inflammatory metabolites. Target identification linked these beneficial effects to selective LXRβ agonism and PPAR/RXR antagonism. INTERPRETATION Our observations in the HFD model, combined with the absence of lipogenesis and neutropenia in WT mice, support this novel approach to therapeutic development for T2D and related conditions.
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Affiliation(s)
- Cutler T Lewandowski
- Department of Pharmaceutical Sciences, University of Illinois at Chicago, Chicago, IL, USA
| | - Md Wasim Khan
- Department of Medicine, University of Illinois at Chicago, 835 S. Wolcott St., Chicago, IL 60612, USA
| | - Manel BenAissa
- Department of Pharmaceutical Sciences, University of Illinois at Chicago, Chicago, IL, USA
| | - Oleksii Dubrovskyi
- Department of Pharmaceutical Sciences, University of Illinois at Chicago, Chicago, IL, USA
| | - Martha Ackerman-Berrier
- Department of Pharmacology and Toxicology, University of Arizona, 1295N. Martin, Tucson, AZ 85721, USA
| | - Mary Jo LaDu
- Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL, USA
| | - Brian T Layden
- Department of Medicine, University of Illinois at Chicago, 835 S. Wolcott St., Chicago, IL 60612, USA.
| | - Gregory R J Thatcher
- Department of Pharmacology and Toxicology, University of Arizona, 1295N. Martin, Tucson, AZ 85721, USA.
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Aleidi SM, Dahabiyeh LA, Gu X, Al Dubayee M, Alshahrani A, Benabdelkamel H, Mujammami M, Li L, Aljada A, Abdel Rahman AM. Obesity Connected Metabolic Changes in Type 2 Diabetic Patients Treated With Metformin. Front Pharmacol 2021; 11:616157. [PMID: 33664666 PMCID: PMC7921791 DOI: 10.3389/fphar.2020.616157] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Accepted: 12/30/2020] [Indexed: 12/13/2022] Open
Abstract
Metformin is widely used in the treatment of Type 2 Diabetes Mellitus (T2DM). However, it is known to have beneficial effects in many other conditions, including obesity and cancer. In this study, we aimed to investigate the metabolic effect of metformin in T2DM and its impact on obesity. A mass spectrometry (MS)-based metabolomics approach was used to analyze samples from two cohorts, including healthy lean and obese control, and lean as well as obese T2DM patients on metformin regimen in the last 6 months. The results show a clear group separation and sample clustering between the study groups due to both T2DM and metformin administration. Seventy-one metabolites were dysregulated in diabetic obese patients (30 up-regulated and 41 down-regulated), and their levels were unchanged with metformin administration. However, 30 metabolites were dysregulated (21 were up-regulated and 9 were down-regulated) and then restored to obese control levels by metformin administration in obese diabetic patients. Furthermore, in obese diabetic patients, the level of 10 metabolites was dysregulated only after metformin administration. Most of these dysregulated metabolites were dipeptides, aliphatic amino acids, nucleic acid derivatives, and urea cycle components. The metabolic pattern of 62 metabolites was persistent, and their levels were affected by neither T2DM nor metformin in obesity. Interestingly, 9 metabolites were significantly dysregulated between lean and obese cohorts due to T2DM and metformin regardless of the obesity status. These include arginine, citrulline, guanidoacetic acid, proline, alanine, taurine, 5-hydroxyindoleacetic acid, and 5-hydroxymethyluracil. Understanding the metabolic alterations taking place upon metformin treatment would shed light on possible molecular targets of metformin, especially in conditions like T2DM and obesity.
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Affiliation(s)
- Shereen M Aleidi
- Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Lina A Dahabiyeh
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Xinyun Gu
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Mohammed Al Dubayee
- College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Awad Alshahrani
- College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Hicham Benabdelkamel
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Muhammad Mujammami
- Endocrinology and Diabetes Unit, Department of Medicine, College of Medicine, King Saud University, Riyadh, Saudi Arabia.,University Diabetes Center, King Saud University Medical City, King Saud University, Riyadh, Saudi Arabia
| | - Liang Li
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Ahmad Aljada
- Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh, Saudi Arabia
| | - Anas M Abdel Rahman
- Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh, Saudi Arabia.,Metabolomics Section, Department of Clinical Genomics, Center for Genomics Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.,Department of Chemistry, Memorial University of Newfoundland, St. John's, NL, Canada
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28
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Mohammed I, Hollenberg MD, Ding H, Triggle CR. A Critical Review of the Evidence That Metformin Is a Putative Anti-Aging Drug That Enhances Healthspan and Extends Lifespan. Front Endocrinol (Lausanne) 2021; 12:718942. [PMID: 34421827 PMCID: PMC8374068 DOI: 10.3389/fendo.2021.718942] [Citation(s) in RCA: 119] [Impact Index Per Article: 39.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 07/15/2021] [Indexed: 12/11/2022] Open
Abstract
The numerous beneficial health outcomes associated with the use of metformin to treat patients with type 2 diabetes (T2DM), together with data from pre-clinical studies in animals including the nematode, C. elegans, and mice have prompted investigations into whether metformin has therapeutic utility as an anti-aging drug that may also extend lifespan. Indeed, clinical trials, including the MILES (Metformin In Longevity Study) and TAME (Targeting Aging with Metformin), have been designed to assess the potential benefits of metformin as an anti-aging drug. Preliminary analysis of results from MILES indicate that metformin may induce anti-aging transcriptional changes; however it remains controversial as to whether metformin is protective in those subjects free of disease. Furthermore, despite clinical use for over 60 years as an anti-diabetic drug, the cellular mechanisms by which metformin exerts either its actions remain unclear. In this review, we have critically evaluated the literature that has investigated the effects of metformin on aging, healthspan and lifespan in humans as well as other species. In preparing this review, particular attention has been placed on the strength and reproducibility of data and quality of the study protocols with respect to the pharmacokinetic and pharmacodynamic properties of metformin. We conclude that despite data in support of anti-aging benefits, the evidence that metformin increases lifespan remains controversial. However, via its ability to reduce early mortality associated with various diseases, including diabetes, cardiovascular disease, cognitive decline and cancer, metformin can improve healthspan thereby extending the period of life spent in good health. Based on the available evidence we conclude that the beneficial effects of metformin on aging and healthspan are primarily indirect via its effects on cellular metabolism and result from its anti-hyperglycemic action, enhancing insulin sensitivity, reduction of oxidative stress and protective effects on the endothelium and vascular function.
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Affiliation(s)
- Ibrahim Mohammed
- Department of Medical Education, Weill Cornell Medicine-Qatar, Al-Rayyan, Qatar
- *Correspondence: Chris R. Triggle, ; Ibrahim Mohammed,
| | - Morley D. Hollenberg
- Inflammation Research Network and Snyder Institute for Chronic Diseases, Department of Physiology & Pharmacology, University of Calgary Cumming School of Medicine, Calgary, AB, Canada
- Department of Medicine, University of Calgary Cumming School of Medicine, Calgary, AB, Canada
| | - Hong Ding
- Department of Medical Education, Weill Cornell Medicine-Qatar, Al-Rayyan, Qatar
- Departments of Medical Education and Pharmacology, Weill Cornell Medicine-Qatar, Al-Rayyan, Qatar
| | - Chris R. Triggle
- Department of Medical Education, Weill Cornell Medicine-Qatar, Al-Rayyan, Qatar
- Departments of Medical Education and Pharmacology, Weill Cornell Medicine-Qatar, Al-Rayyan, Qatar
- *Correspondence: Chris R. Triggle, ; Ibrahim Mohammed,
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Pre-diagnostic biomarkers of type 2 diabetes identified in the UAE's obese national population using targeted metabolomics. Sci Rep 2020; 10:17616. [PMID: 33077739 PMCID: PMC7572402 DOI: 10.1038/s41598-020-73384-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 09/16/2020] [Indexed: 12/14/2022] Open
Abstract
Currently, type 2 diabetes mellitus (T2DM) and obesity are major global public health issues, and their prevalence in the United Arab Emirates (UAE) are among the highest in the world. In 2019, The UAE diabetes national prevalence was 15.4%. In recent years there has been a considerable investigation of predictive biomarkers associated with these conditions. This study analysed fasting (8 h) blood samples from an obese, normoglycemic cohort and an obese, T2DM cohort of UAE nationals, employing clinical chemistry analysis, 1D 1H NMR and mass spectroscopy (FIA-MS/MS and LC-MS/MS) techniques. The novel findings reported for the first time in a UAE population revealed significant differences in a number of metabolites in the T2DM cohort. Metabolic fingerprints identified by NMR included BCAAs, trimethylamine N-oxide, β-hydroxybutyrate, trimethyl uric acid, and alanine. A targeted MS approach showed significant differences in lysophosphatidylcholines, phosphatidylcholines, acylcarnitine, amino acids and sphingomyelins; Lyso.PC.a.C18.0, PC.ae.C34.2, C3.DC..C4.OH, glutamine and SM.C16.1, being the most significant metabolites. Pearson's correlation studies showed associations between these metabolites and the clinical chemistry parameters across both cohorts. This report identified differences in metabolites in response to T2DM in agreement with many published population studies. This contributes to the global search for a bank of metabolite biomarkers that can predict the advent of T2DM and give insight to its pathogenic mechanisms.
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Sun L, Li FH, Li T, Min Z, Yang LD, Gao HE, Wu DS, Xie T. Effects of high-intensity interval training on adipose tissue lipolysis, inflammation, and metabolomics in aged rats. Pflugers Arch 2020; 472:245-258. [PMID: 32006095 DOI: 10.1007/s00424-020-02351-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/08/2020] [Accepted: 01/20/2020] [Indexed: 12/21/2022]
Abstract
High-intensity interval training (HIIT) is a time-efficient alternative to moderate-intensity continuous training (MICT) to improve metabolic health in older individuals. However, differences in adipose tissue metabolism between these two approaches are unclear. Here, we evaluated the effects of HIIT and MICT on metabolic phenotypes in aged rats. HIIT significantly decreased fat mass, increased percent lean mass, decreased fat-to-lean ratio, reduced serum high-sensitivity C-reactive protein, increased serum interleukin-10 levels, and decreased perirenal adipose tissue leptin compared with rats in the sedentary (SED) group. HIIT also increased pregnenolone, cortisol, and corticosterone in both adipose tissue and serum. Both exercise modalities enhanced hormone-sensitive lipase and adipose triglyceride lipase expression compared with the SED group and decreased palmitic acid, stearic acid, octadecadienoic acid, urea, 1-heptadecanol, and α-tocopherol. MICT was related to glycerolipid metabolism, whereas HIIT was related to steroid hormone biosynthesis. Overall, HIIT showed more favorable regulation of anti-inflammatory activity than MICT.
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Affiliation(s)
- Lei Sun
- School of Sport Sciences, Nanjing Normal University, No. 1 Wenyuan Road Qixia District, Nanjing, 210046, People's Republic of China
| | - Fang-Hui Li
- School of Sport Sciences, Nanjing Normal University, No. 1 Wenyuan Road Qixia District, Nanjing, 210046, People's Republic of China.
| | - Tao Li
- Laboratory of Laser Sports Medicine, South China Normal University, Guangzhou, China
| | - Zhu Min
- School of Sport Sciences, Nanjing Normal University, No. 1 Wenyuan Road Qixia District, Nanjing, 210046, People's Republic of China
| | - Luo-Dan Yang
- Laboratory of Laser Sports Medicine, South China Normal University, Guangzhou, China
| | - Hao-En Gao
- School of Sport Sciences, Nanjing Normal University, No. 1 Wenyuan Road Qixia District, Nanjing, 210046, People's Republic of China
| | - Da-Shuai Wu
- School of Sport Sciences, Nanjing Normal University, No. 1 Wenyuan Road Qixia District, Nanjing, 210046, People's Republic of China
| | - Tian Xie
- School of Sport Sciences, Nanjing Normal University, No. 1 Wenyuan Road Qixia District, Nanjing, 210046, People's Republic of China
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31
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Lalande C, Drouin-Chartier JP, Tremblay AJ, Couture P, Veilleux A. Plasma biomarkers of small intestine adaptations in obesity-related metabolic alterations. Diabetol Metab Syndr 2020; 12:31. [PMID: 32292494 PMCID: PMC7144049 DOI: 10.1186/s13098-020-00530-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 03/13/2020] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Evidence suggests that pathophysiological conditions such as obesity and type 2 diabetes (T2D) are associated with morphologic and metabolic alterations in the small intestinal mucosa. Exploring these alterations generally requires invasive methods, limiting data acquisition to subjects with enteropathies or undergoing bariatric surgery. We aimed to evaluate small intestine epithelial cell homeostasis in a cohort of men covering a wide range of adiposity and glucose homoeostasis statuses. METHODS Plasma levels of citrulline, a biomarker of enterocyte mass, and I-FABP, a biomarker of enterocyte death, were measured by UHPLC‑MS and ELISA in 154 nondiabetic men and 67 men with a T2D diagnosis. RESULTS Plasma citrulline was significantly reduced in men with insulin resistance and T2D compared to insulin sensitive men. Decreased citrulline levels were, however, not observed in men with uncontrolled metabolic parameters during T2D. Plasma I-FABP was significantly higher in men with T2D, especially in presence of uncontrolled glycemic and lipid profile parameters. Integration of both parameters, which estimate enterocyte turnover, was associated with glucose homeostasis as well as with T2D diagnosis. Differences in biomarkers levels were independent of age and BMI and glucose filtration rates. CONCLUSIONS Our study supports a decreased functional enterocyte mass and an increased enterocyte death rate in presence of metabolic alterations but emphasizes that epithelial cell homeostasis is especially altered in presence of severe insulin resistance and T2D. The marked changes in small intestine cellularity observed in obesity and diabetes are thus suggested to be part of gut dysfunctions, mainly at an advanced stage of the disease.
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Affiliation(s)
- Catherine Lalande
- École de nutrition, Faculté des sciences de l’agriculture et de l’alimentation, Université Laval, 2440, boulevard Hochelaga, Québec, QC G1V 0A6 Canada
- Centre Nutrition, santé et société (NUTRISS), Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec, QC Canada
| | - Jean-Philippe Drouin-Chartier
- École de nutrition, Faculté des sciences de l’agriculture et de l’alimentation, Université Laval, 2440, boulevard Hochelaga, Québec, QC G1V 0A6 Canada
- Centre Nutrition, santé et société (NUTRISS), Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec, QC Canada
| | - André J. Tremblay
- Centre Nutrition, santé et société (NUTRISS), Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec, QC Canada
| | - Patrick Couture
- Centre Nutrition, santé et société (NUTRISS), Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec, QC Canada
- Centre des maladies lipidiques, Centre Hospitalier Universitaire (CHU) de Québec, Québec, QC Canada
| | - Alain Veilleux
- École de nutrition, Faculté des sciences de l’agriculture et de l’alimentation, Université Laval, 2440, boulevard Hochelaga, Québec, QC G1V 0A6 Canada
- Centre Nutrition, santé et société (NUTRISS), Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec, QC Canada
- Centre de Recherche de l’Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, QC Canada
- Canada Excellence Research Chair in the Microbiome-Endocannabinoidome Axis in Metabolic Health, Québec, QC Canada
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Abstract
PURPOSE OF REVIEW Protein homeostasis is crucial for maintaining cell functions. Citrulline, an endogenous amino acid, is considered as an efficient source of arginine at systemic and cellular level. Accumulating evidence, obtained from citrulline supplementation studies, suggest anabolic properties especially in malnourished rodents and human. Although these studies might suggest a key role for citrulline in protein homeostasis, the supraphysiological concentrations of citrulline do not allow to conclude on a physiological role. This review aimed to assess the role of endogenous citrulline production on protein homeostasis. RECENT FINDINGS According to recent studies, endogenous citrulline, through its regulating effect on nitric oxide production, seems to play a key role in regulating endothelial and immune functions. We can assume that citrulline-dependent endothelial vasodilation could improve organ perfusion and thus amino acid and insulin supply. Furthermore, citrulline regulates immune cells and thus could regulate inflammation and indirectly protein metabolism. SUMMARY Although we have currently no direct evidence of a regulating role of endogenous citrulline production on protein homeostasis, we can hypothesize that physiologically through its role in endothelial and immune function, citrulline could indirectly participate to protein homeostasis.
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Affiliation(s)
- Antonin Ginguay
- Nutrition Biology Laboratory, EA 4466 PRETRAM, Paris Descartes University, USPC
- Clinical Chemistry Department, Cochin Hospital, Paris Centre University Hospitals, AP-HP, Paris, France
| | - Jean-Pascal De Bandt
- Nutrition Biology Laboratory, EA 4466 PRETRAM, Paris Descartes University, USPC
- Clinical Chemistry Department, Cochin Hospital, Paris Centre University Hospitals, AP-HP, Paris, France
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Li YY, Stewart DA, Ye XM, Yin LH, Pathmasiri WW, McRitchie SL, Fennell TR, Cheung HY, Sumner SJ. A Metabolomics Approach to Investigate Kukoamine B-A Potent Natural Product With Anti-diabetic Properties. Front Pharmacol 2019; 9:1575. [PMID: 30723413 PMCID: PMC6350459 DOI: 10.3389/fphar.2018.01575] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 12/31/2018] [Indexed: 12/11/2022] Open
Abstract
Due to the surge in type 2 diabetes mellitus (T2DM), treatments for chronic metabolic dysregulations with fewer side-effects are sought. Lycii Cortex (LyC), a traditional Chinese Medicine (TCM) herb has a long history of being widely prescribed to treat T2DM as alternative medicine; however, the bioactive molecules and working mechanism remained unknown. Previous studies revealed kukoamine B (KB) as a major and featured compound for LyC with bioactivities for anti-oxidation and acute inflammation, which may be related to anti-diabetes properties. This study aims to understand the efficacy and the mode of action of KB in the diabetic (db/db) mouse model using a metabolomics approach. Parallel comparison was conducted using the first-line anti-diabetic drugs, metformin and rosligtazone, as positive controls. The db/db mice were treated with KB (50 mg kg-1 day-1) for 9 weeks. Bodyweight and fasting blood glucose were monitored every 5 and 7 days, respectively. Metabolomics and high-throughput molecular approaches, including lipidomics, targeted metabolomics (Biocrates p180), and cytokine profiling were applied to measure the alteration of serum metabolites and inflammatory biomarkers between different treatments vs. control (db/db mice treated with vehicle). After 9 weeks of treatment, KB lowered blood glucose, without the adverse effects of bodyweight gain and hepatomegaly shown after rosiglitazone treatment. Lipidomics analysis revealed that KB reduced levels of circulating triglycerides, cholesterol, phosphatidylethanolamine, and increased levels of phosphatidylcholines. KB also increased acylcarnitines, and reduced systemic inflammation (cytokine array). Pathway analysis suggested that KB may regulate nuclear transcription factors (e.g., NF-κB and/or PPAR) to reduce inflammation and facilitate a shift toward metabolic and inflammatory homeostasis. Comparison of KB with first-line drugs suggests that rosiglitazone may over-regulate lipid metabolism and anti-inflammatory responses, which may be associated with adverse side effects, while metformin had less impact on lipid and anti-inflammation profiles. Our research from holistic and systemic views supports the conclusion that KB is the bioactive compound of LyC for managing T2DM, and suggests KB as a nutraceutical or a pharmaceutical candidate for T2D treatment. In addition, our research provides insights related to metformin and rosiglitazone action, beyond lowering blood glucose.
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Affiliation(s)
- Yuan-Yuan Li
- NIH Eastern Regional Comprehensive Metabolomics Resource Core, Nutrition Research Institute, Department of Nutrition, University of North Carolina at Chapel Hill, Kannapolis, NC, United States
| | - Delisha A Stewart
- NIH Eastern Regional Comprehensive Metabolomics Resource Core, Nutrition Research Institute, Department of Nutrition, University of North Carolina at Chapel Hill, Kannapolis, NC, United States
| | - Xiao-Min Ye
- Department of Pharmacology, Wuhan Institute for Drug and Medical Device Control, Wuhan, China
| | - Li-Hua Yin
- Department of Pharmacology, Wuhan Institute for Drug and Medical Device Control, Wuhan, China
| | - Wimal W Pathmasiri
- NIH Eastern Regional Comprehensive Metabolomics Resource Core, Nutrition Research Institute, Department of Nutrition, University of North Carolina at Chapel Hill, Kannapolis, NC, United States
| | - Susan L McRitchie
- NIH Eastern Regional Comprehensive Metabolomics Resource Core, Nutrition Research Institute, Department of Nutrition, University of North Carolina at Chapel Hill, Kannapolis, NC, United States
| | - Timothy R Fennell
- Analytical Chemistry and Pharmaceutics, RTI International, Research Triangle Park, Durham, NC, United States
| | - Hon-Yeung Cheung
- Department of Biomedical Science, City University of Hong Kong, Kowloon, Hong Kong
| | - Susan J Sumner
- NIH Eastern Regional Comprehensive Metabolomics Resource Core, Nutrition Research Institute, Department of Nutrition, University of North Carolina at Chapel Hill, Kannapolis, NC, United States
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Huhtala MS, Tertti K, Pellonperä O, Rönnemaa T. Amino acid profile in women with gestational diabetes mellitus treated with metformin or insulin. Diabetes Res Clin Pract 2018; 146:8-17. [PMID: 30227169 DOI: 10.1016/j.diabres.2018.09.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Revised: 08/24/2018] [Accepted: 09/13/2018] [Indexed: 01/20/2023]
Abstract
AIMS We compared the effects of metformin and insulin treatments of gestational diabetes mellitus (GDM) on amino acid metabolism. METHODS 217 pregnant women diagnosed with GDM were randomized to receive either metformin or insulin. 1H nuclear magnetic spectroscopy was used to determine serum concentrations of alanine, glutamine, glycine, isoleucine, leucine, valine, histidine, phenylalanine, tyrosine, glucose and lactate at the time of diagnosis and at 36 gestational weeks (gw). RESULTS Majority of the amino acid concentrations increased from 30 to 36 gw. The rise in alanine (16% vs. 8%, p < 0.0001), isoleucine (11% vs. 5%, p = 0.035) and lactate (29% vs. 14% p = 0.015) was larger in the metformin group compared to insulin group. Baseline alanine, glycine, isoleucine, leucine, valine and tyrosine were positively related to slightly earlier delivery. Alanine at 36 gw was positively associated with birth weight and glutamine with gestational hypertension or preeclampsia. Lactate at 36 gw was not associated with any adverse outcome. CONCLUSIONS Compared to insulin metformin caused a greater increase in serum alanine, isoleucine and lactate concentrations. Although the observed differences in the metabolic variables were relatively small and not outright concerning, additional studies and follow-up data are required to ensure the safety of metformin use in pregnancy. The trial was registered in Clinicaltrials.gov, NCT01240785; http://clinicaltrials.gov/ct2/show/NCT01240785.
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Affiliation(s)
- Mikael S Huhtala
- Department of Obstetrics and Gynecology, University of Turku, 20014 Turku, Finland.
| | - Kristiina Tertti
- Department of Obstetrics and Gynecology, Turku University Hospital, Kiinamyllynkatu 4-8, 20521 Turku, Finland
| | - Outi Pellonperä
- Department of Obstetrics and Gynecology, Turku University Hospital, Kiinamyllynkatu 4-8, 20521 Turku, Finland
| | - Tapani Rönnemaa
- Department of Medicine, University of Turku, 20014 Turku, Finland,; Division of Medicine, Turku University Hospital, Kiinamyllynkatu 4-8, 20521 Turku, Finland
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Haukka JK, Sandholm N, Forsblom C, Cobb JE, Groop PH, Ferrannini E. Metabolomic Profile Predicts Development of Microalbuminuria in Individuals with Type 1 Diabetes. Sci Rep 2018; 8:13853. [PMID: 30217994 PMCID: PMC6138633 DOI: 10.1038/s41598-018-32085-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 08/13/2018] [Indexed: 12/28/2022] Open
Abstract
Elevated urinary albumin excretion (microalbuminuria) is an early marker of diabetic nephropathy, but there is an unmet need for better biomarkers that capture the individuals at risk with higher accuracy and earlier than the current markers do. We performed an untargeted metabolomic study to assess baseline differences between individuals with type 1 diabetes who either developed microalbuminuria or remained normoalbuminuric. A total of 102 individuals progressed to microalbuminuria during a median follow-up of 3.2 years, whereas 98 sex-, age- and body mass index (BMI) matched non-progressors remained normoalbuminuric during a median follow-up of 7.1 years. Metabolomic screening identified 1,242 metabolites, out of which 111 differed significantly between progressors and non-progressors after adjustment for age of diabetes onset, baseline glycosylated hemoglobin A1c (HbA1c), and albumin excretion rate (AER). The metabolites that predicted development of microalbumiuria included several uremic toxins and carnitine metabolism related molecules. Iterative variable selection indicated erythritol, 3-phenylpropionate, and N-trimethyl-5-aminovalerate as the best set of variables to predict development of microalbuminuria. A metabolomic index based on these metabolites improved the prediction of incident microalbuminuria on top of the clinical variables age of diabetes onset, baseline HbA1c and AER (ROCAUC = 0.842 vs 0.797), highlighting their ability to predict early-phase diabetic nephropathy.
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Affiliation(s)
- Jani K Haukka
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Diabetes & Obesity Research Program, Research Program's Unit, University of Helsinki, Helsinki, Finland
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Diabetes & Obesity Research Program, Research Program's Unit, University of Helsinki, Helsinki, Finland
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Diabetes & Obesity Research Program, Research Program's Unit, University of Helsinki, Helsinki, Finland
| | | | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Diabetes & Obesity Research Program, Research Program's Unit, University of Helsinki, Helsinki, Finland.
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, Victoria, Australia.
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36
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Ottosson F, Smith E, Melander O, Fernandez C. Altered Asparagine and Glutamate Homeostasis Precede Coronary Artery Disease and Type 2 Diabetes. J Clin Endocrinol Metab 2018; 103:3060-3069. [PMID: 29788285 DOI: 10.1210/jc.2018-00546] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Accepted: 05/11/2018] [Indexed: 02/05/2023]
Abstract
CONTEXT Type 2 diabetes mellitus (T2DM) is accompanied by an increased risk for coronary artery disease (CAD), but the overlapping metabolic disturbances preceding both diseases are insufficiently described. OBJECTIVE We hypothesized that alterations in metabolism occur years before clinical manifestation of T2DM and CAD and that these alterations are reflected in the plasma metabolome. We thus aimed to identify plasma metabolites that predict future T2DM and CAD. DESIGN Through use of targeted liquid chromatography-mass spectrometry, 35 plasma metabolites (amino acid metabolites and acylcarnitines) were quantified in 1049 individuals without CAD and diabetes, drawn from a population sample of 5386 in the Malmö Preventive Project (mean age, 69.5 years; 31% women). The sample included 204 individuals who developed T2DM, 384 who developed CAD, and 496 who remained T2DM and CAD free during a mean follow-up of 6.1 years. RESULTS In total, 16 metabolites were significantly associated with risk for developing T2DM according to logistic regression models. Glutamate (OR, 1.96; P = 5.4e-12) was the most strongly associated metabolite, followed by increased levels of branched-chain amino acids. Incident CAD was predicted by three metabolites: glutamate (OR, 1.28; P = 6.6e-4), histidine (OR, 0.76; P = 5.1e-4), and asparagine (OR, 0.80; P = 2.2e-3). Glutamate (OR, 1.48; P = 1.6e-8) and asparagine (OR, 0.75; P = 1.8e-5) were both associated with a composite endpoint of developing T2DM or CAD. CONCLUSION Several plasma metabolites were associated with incidence of T2DM and CAD; elevated glutamate and reduced asparagine levels were associated with both diseases. We thus discovered associations that might help shed additional light on why T2DM and CAD commonly co-occur.
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Affiliation(s)
- Filip Ottosson
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Einar Smith
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Malmö, Sweden
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Allerton TD, Proctor DN, Stephens JM, Dugas TR, Spielmann G, Irving BA. l-Citrulline Supplementation: Impact on Cardiometabolic Health. Nutrients 2018; 10:nu10070921. [PMID: 30029482 PMCID: PMC6073798 DOI: 10.3390/nu10070921] [Citation(s) in RCA: 116] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 07/09/2018] [Accepted: 07/16/2018] [Indexed: 12/12/2022] Open
Abstract
Diminished bioavailability of nitric oxide (NO), the gaseous signaling molecule involved in the regulation of numerous vital biological functions, contributes to the development and progression of multiple age- and lifestyle-related diseases. While l-arginine is the precursor for the synthesis of NO by endothelial-nitric oxide synthase (eNOS), oral l-arginine supplementation is largely ineffective at increasing NO synthesis and/or bioavailability for a variety of reasons. l-citrulline, found in high concentrations in watermelon, is a neutral alpha-amino acid formed by enzymes in the mitochondria that also serves as a substrate for recycling l-arginine. Unlike l-arginine, l-citrulline is not quantitatively extracted from the gastrointestinal tract (i.e., enterocytes) or liver and its supplementation is therefore more effective at increasing l-arginine levels and NO synthesis. Supplementation with l-citrulline has shown promise as a blood pressure lowering intervention (both resting and stress-induced) in adults with pre-/hypertension, with pre-clinical (animal) evidence for atherogenic-endothelial protection. Preliminary evidence is also available for l-citrulline-induced benefits to muscle and metabolic health (via vascular and non-vascular pathways) in susceptible/older populations. In this review, we examine the impact of supplementing this important urea cycle intermediate on cardiovascular and metabolic health outcomes and identify future directions for investigating its therapeutic impact on cardiometabolic health.
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Affiliation(s)
| | - David N Proctor
- Department of Kinesiology, Pennsylvania State University, University Park, PA 16802, USA.
| | | | - Tammy R Dugas
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803, USA.
| | - Guillaume Spielmann
- Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA.
- Department of Kinesiology, Louisiana State University, Baton Rouge, LA 70803, USA.
| | - Brian A Irving
- Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA.
- Department of Kinesiology, Louisiana State University, Baton Rouge, LA 70803, USA.
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38
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Safai N, Suvitaival T, Ali A, Spégel P, Al-Majdoub M, Carstensen B, Vestergaard H, Ridderstråle M. Effect of metformin on plasma metabolite profile in the Copenhagen Insulin and Metformin Therapy (CIMT) trial. Diabet Med 2018; 35:944-953. [PMID: 29633349 DOI: 10.1111/dme.13636] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/29/2018] [Indexed: 12/12/2022]
Abstract
AIM Metformin is the first-line treatment for Type 2 diabetes. However, not all people benefit from this drug. Our aim was to investigate the effects of metformin on the plasma metabolome and whether the pretreatment metabolite profile can predict HbA1c outcome. METHODS Post hoc analysis of the Copenhagen Insulin and Metformin Therapy (CIMT) trial, a multicentre study from May 2008 to December 2012, was carried out. We used a non-target method to analyse 87 plasma metabolites in participants with Type 2 diabetes (n = 370) who were randomized in a 1 : 1 ratio to 18 months of metformin or placebo treatment. Metabolites were measured by liquid chromatography-mass spectrometry at baseline and at 18-month follow-up and the data were analysed using a linear mixed-effect model. RESULTS At baseline, participants who were on metformin before the trial (n = 312) had higher levels of leucine/isoleucine and five lysophosphatidylethanolamines (LPEs), and lower levels of carnitine and valine compared with metformin-naïve participants (n = 58). At follow-up, participants randomized to metformin (n = 188) had elevated levels of leucine/isoleucine and reduced carnitine, tyrosine and valine compared with placebo (n = 182). At baseline, participants on metformin treatment with the highest levels of carnitine C10:1 and leucine/isoleucine had the lowest HbA1c (P-interaction = 0.02 and 0.03, respectively). This association was not significant with HbA1c at follow-up. CONCLUSIONS Metformin treatment is associated with decreased levels of valine, tyrosine and carnitine, and increased levels of leucine/isoleucine. None of the identified metabolites can predict the HbA1c -lowering effect of metformin. Further studies of the association between metformin, carnitine and leucine/isoleucine are warranted.
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Affiliation(s)
- N Safai
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - T Suvitaival
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - A Ali
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - P Spégel
- Unit of Molecular Metabolism, Department of Clinical Sciences Malmö, Lund University, Malmö
- Centre for Analysis and Synthesis, Department of Chemistry, Lund University, Lund, Sweden
| | - M Al-Majdoub
- Unit of Molecular Metabolism, Department of Clinical Sciences Malmö, Lund University, Malmö
| | - B Carstensen
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - H Vestergaard
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- Novo Nordisk Foundation of Basic Metabolic Research, University of Copenhagen, Copenhagen
| | - M Ridderstråle
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- Unit of Molecular Metabolism, Department of Clinical Sciences Malmö, Lund University, Malmö
- Novo Nordisk A/S, Søborg, Denmark
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Tam ZY, Ng SP, Tan LQ, Lin CH, Rothenbacher D, Klenk J, Boehm BO. Metabolite profiling in identifying metabolic biomarkers in older people with late-onset type 2 diabetes mellitus. Sci Rep 2017; 7:4392. [PMID: 28663594 PMCID: PMC5491522 DOI: 10.1038/s41598-017-01735-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Accepted: 03/30/2017] [Indexed: 12/31/2022] Open
Abstract
Regulation of blood glucose requires precise coordination between different endocrine systems and multiple organs. Type 2 diabetes mellitus (T2D) arises from a dysregulated response to elevated glucose levels in the circulation. Globally, the prevalence of T2D has increased dramatically in all age groups. T2D in older adults is associated with higher mortality and reduced functional status, leading to higher rate of institutionalization. Despite the potential healthcare challenges associated with the presence of T2D in the elderly, the pathogenesis and phenotype of late-onset T2D is not well studied. Here we applied untargeted metabolite profiling of urine samples from people with and without late-onset T2D using ultra-performance liquid-chromatography mass-spectrometry (UPLC-MS) to identify urinary biomarkers for late-onset T2D in the elderly. Statistical modeling of measurements and thorough validation of structural assignment using liquid chromatography tandem mass-spectrometry (LC-MS/MS) have led to the identification of metabolite biomarkers associated with late-onset T2D. Lower levels of phenylalanine, acetylhistidine, and cyclic adenosine monophosphate (cAMP) were found in urine samples of T2D subjects validated with commercial standards. Elevated levels of 5′-methylthioadenosine (MTA), which previously has only been implicated in animal model of diabetes, was found in urine of older people with T2D.
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Affiliation(s)
- Zhi Yang Tam
- Singapore Phenome Center, Experimental Medicine Building, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore
| | - Sean Pin Ng
- Singapore Phenome Center, Experimental Medicine Building, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore
| | - Ling Qiao Tan
- Singapore Phenome Center, Experimental Medicine Building, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore
| | - Chih-Hsien Lin
- Singapore Phenome Center, Experimental Medicine Building, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore
| | - Dietrich Rothenbacher
- Institute of Epidemiology and Medical Biometry, Ulm University, Helmholtzstrasse 22, 89081, Ulm, Germany
| | - Jochen Klenk
- Institute of Epidemiology and Medical Biometry, Ulm University, Helmholtzstrasse 22, 89081, Ulm, Germany.,Department of Clinical Gerontology, Robert-Bosch-Hospital, Auerbachstrasse 110, 70376, Stuttgart, Germany
| | - Bernhard Otto Boehm
- Singapore Phenome Center, Experimental Medicine Building, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore. .,Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921, Singapore. .,Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, UK. .,Department of Internal Medicine I, Ulm University Medical Centre, Ulm University, Albert-Einstein-Allee 23, 89081, Ulm, Germany.
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40
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Jegatheesan P, De Bandt JP, Cynober L. Comment on Adam et al. Metformin Effect on Nontargeted Metabolite Profiles in Patients With Type 2 Diabetes and in Multiple Murine Tissues. Diabetes 2016;65:3776-3785. Diabetes 2017; 66:e1-e2. [PMID: 28507215 DOI: 10.2337/db16-1592] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
| | - Jean-Pascal De Bandt
- EA4466 Prévention et Traitement de la Résistance à l'Anabolisme Musculaire, Faculté de Pharmacie de Paris, Université Paris Descartes, Université Sorbonne Paris Cité, Paris, France
- Service de Biochimie, Hôpital Cochin, Hôpitaux Universitaires Paris Centre, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Luc Cynober
- EA4466 Prévention et Traitement de la Résistance à l'Anabolisme Musculaire, Faculté de Pharmacie de Paris, Université Paris Descartes, Université Sorbonne Paris Cité, Paris, France
- Service de Biochimie, Hôpital Cochin, Hôpitaux Universitaires Paris Centre, Assistance Publique-Hôpitaux de Paris, Paris, France
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Adam J, Brandmaier S, Troll M, Rotter M, Mohney RP, Heier M, Adamski J, Li Y, Neschen S, Kastenmüller G, Suhre K, Ankerst D, Meitinger T, Wang-Sattler R. Response to Comment on Adam et al. Metformin Effect on Nontargeted Metabolite Profiles in Patients With Type 2 Diabetes and in Multiple Murine Tissues. Diabetes 2016;65:3776-3785. Diabetes 2017; 66:e3-e4. [PMID: 28507216 DOI: 10.2337/dbi17-0010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Jonathan Adam
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Stefan Brandmaier
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Martina Troll
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Markus Rotter
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | | | - Margit Heier
- Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jerzy Adamski
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Experimental Genetics, Center of Life and Food Sciences Weihenstephan, Technische Universität München, Freising, Germany
| | - Yixue Li
- Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Susanne Neschen
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Gabi Kastenmüller
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar (WCMC-Q), Education City-Qatar Foundation, Doha, Qatar
| | - Donna Ankerst
- Lehrstuhl für Mathematische Modelle Biologischer Systeme, Technische Universität München, Garching, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, Munich, Germany
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
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Rotter M, Brandmaier S, Prehn C, Adam J, Rabstein S, Gawrych K, Brüning T, Illig T, Lickert H, Adamski J, Wang-Sattler R. Stability of targeted metabolite profiles of urine samples under different storage conditions. Metabolomics 2017; 13:4. [PMID: 27980503 PMCID: PMC5126183 DOI: 10.1007/s11306-016-1137-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Accepted: 10/28/2016] [Indexed: 11/25/2022]
Abstract
INTRODUCTION Few studies have investigated the influence of storage conditions on urine samples and none of them used targeted mass spectrometry (MS). OBJECTIVES We investigated the stability of metabolite profiles in urine samples under different storage conditions using targeted metabolomics. METHODS Pooled, fasting urine samples were collected and stored at -80 °C (biobank standard), -20 °C (freezer), 4 °C (fridge), ~9 °C (cool pack), and ~20 °C (room temperature) for 0, 2, 8 and 24 h. Metabolite concentrations were quantified with MS using the AbsoluteIDQ™ p150 assay. We used the Welch-Satterthwaite-test to compare the concentrations of each metabolite. Mixed effects linear regression was used to assess the influence of the interaction of storage time and temperature. RESULTS The concentrations of 63 investigated metabolites were stable at -20 and 4 °C for up to 24 h when compared to samples immediately stored at -80 °C. When stored at ~9 °C for 24 h, few amino acids (Arg, Val and Leu/Ile) significantly decreased by 40% in concentration (P < 7.9E-04); for an additional three metabolites (Ser, Met, Hexose H1) when stored at ~20 °C reduced up to 60% in concentrations. The concentrations of four more metabolites (Glu, Phe, Pro, and Thr) were found to be significantly influenced when considering the interaction between exposure time and temperature. CONCLUSION Our findings indicate that 78% of quantified metabolites were stable for all examined storage conditions. Particularly, some amino acid concentrations were sensitive to changes after prolonged storage at room temperature. Shipping or storing urine samples on cool packs or at room temperature for more than 8 h and multiple numbers of freeze and thaw cycles should be avoided.
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Affiliation(s)
- Markus Rotter
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
| | - Stefan Brandmaier
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
| | - Cornelia Prehn
- Genome Analysis Center, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 München-Neuherberg, Germany
| | - Jonathan Adam
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
| | - Sylvia Rabstein
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), 44789 Bochum, Germany
| | - Katarzyna Gawrych
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), 44789 Bochum, Germany
| | - Thomas Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), 44789 Bochum, Germany
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, 30625 Hannover, Germany
| | - Heiko Lickert
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
- Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany
| | - Jerzy Adamski
- Genome Analysis Center, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 München-Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany
- Experimental Genetics, Center of Life and Food Sciences Weihenstephan, Technische Universität München, 85354 Freising-Weihenstephan, Germany
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 München-Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany
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Irving BA, Spielmann G. Does Citrulline Sit at the Nexus of Metformin's Pleotropic Effects on Metabolism and Mediate Its Salutatory Effects in Individuals With Type 2 Diabetes? Diabetes 2016; 65:3537-3540. [PMID: 27879405 DOI: 10.2337/dbi16-0050] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Brian A Irving
- School of Kinesiology, Louisiana State University, and Pennington Biomedical Research Center, Baton Rouge, LA
| | - Guillaume Spielmann
- School of Kinesiology, Louisiana State University, and Pennington Biomedical Research Center, Baton Rouge, LA
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