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Dhieb D, Mustafa D, Hassiba M, Alasmar M, Elsayed MH, Musa A, Zirie M, Bastaki K. Harnessing Pharmacomultiomics for Precision Medicine in Diabetes: A Comprehensive Review. Biomedicines 2025; 13:447. [PMID: 40002860 PMCID: PMC11853021 DOI: 10.3390/biomedicines13020447] [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: 11/02/2024] [Revised: 12/08/2024] [Accepted: 12/11/2024] [Indexed: 02/27/2025] Open
Abstract
Type 2 diabetes (T2D) is the fastest-growing non-communicable disease worldwide, accounting for around 90% of all diabetes cases and imposing a significant health burden globally. Due to its phenotypic heterogeneity and composite genetic underpinnings, T2D requires a precision medicine approach personalized to individual molecular profiles, thereby shifting away from the traditional "one-size-fits-all" medical methods. This review advocates for a thorough pharmacomultiomics approach to enhance precision medicine for T2D. It emphasizes personalized treatment strategies that enhance treatment efficacy while minimizing adverse effects by integrating data from genomics, proteomics, metabolomics, transcriptomics, microbiomics, and epigenomics. We summarize key findings on candidate genes impacting diabetic medication responses and explore the potential of pharmacometabolomics in predicting drug efficacy. The role of pharmacoproteomics in prognosis and discovering new therapeutic targets is discussed, along with transcriptomics' contribution to understanding T2D pathophysiology. Additionally, pharmacomicrobiomics is explored to understand gut microbiota interactions with antidiabetic drugs. Emerging evidence on utilizing epigenomic profiles in improving drug efficacy and personalized treatment is also reviewed, illustrating their implications in personalized medicine. In this paper, we discuss the integration of these layers of omics data, examining recently developed paradigms that leverage complex data to deepen our understanding of diabetes. Such integrative approaches advance precision medicine strategies to tackle the disease by better understanding its complex biology.
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Affiliation(s)
- Dhoha Dhieb
- College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar; (D.D.); (D.M.); (M.H.); (M.H.E.)
| | - Dana Mustafa
- College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar; (D.D.); (D.M.); (M.H.); (M.H.E.)
| | - Maryam Hassiba
- College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar; (D.D.); (D.M.); (M.H.); (M.H.E.)
| | - May Alasmar
- Hamad Medical Corporation, Doha P.O. Box 3050, Qatar; (M.A.); (M.Z.)
| | - Mohamed Haitham Elsayed
- College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar; (D.D.); (D.M.); (M.H.); (M.H.E.)
| | - Ameer Musa
- College of Medicine, QU Health, Qatar University, Doha P.O. Box 2713, Qatar;
| | - Mahmoud Zirie
- Hamad Medical Corporation, Doha P.O. Box 3050, Qatar; (M.A.); (M.Z.)
| | - Kholoud Bastaki
- College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar; (D.D.); (D.M.); (M.H.); (M.H.E.)
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Anwardeen NR, Naja K, Elrayess MA. Advancements in precision medicine: multi-omics approach for tailored metformin treatment in type 2 diabetes. Front Pharmacol 2024; 15:1506767. [PMID: 39669200 PMCID: PMC11634602 DOI: 10.3389/fphar.2024.1506767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2024] [Accepted: 11/20/2024] [Indexed: 12/14/2024] Open
Abstract
Metformin has become the frontline treatment in addressing the significant global health challenge of type 2 diabetes due to its proven effectiveness in lowering blood glucose levels. However, the reality is that many patients struggle to achieve their glycemic targets with the medication and the cause behind this variability has not been investigated thoroughly. While genetic factors account for only about a third of this response variability, the potential influence of metabolomics and the gut microbiome on drug efficacy opens new avenues for investigation. This review explores the different molecular signatures to uncover how the complex interplay between genetics, metabolic profiles, and gut microbiota can shape individual responses to metformin. By highlighting the insights from recent studies and identifying knowledge gaps regarding metformin-microbiota interplay, we aim to highlight the path toward more personalized and effective diabetes management strategies and moving beyond the one-size-fits-all approach.
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Affiliation(s)
| | - Khaled Naja
- Biomedical Research Center, Qatar University, Doha, Qatar
| | - Mohamed A. Elrayess
- Biomedical Research Center, Qatar University, Doha, Qatar
- College of Medicine, QU Health, Qatar University, Doha, Qatar
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Thaker VV, Kwee LC, Chen H, Bahson J, Ilkayeva O, Muehlbauer MJ, Wolfe B, Purnell JQ, Pi-Sunyer X, Newgard CB, Shah SH, Laferrère B. Metabolite signature of diabetes remission in individuals with obesity undergoing weight loss interventions. Obesity (Silver Spring) 2024; 32:304-314. [PMID: 37962326 PMCID: PMC11201087 DOI: 10.1002/oby.23943] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/25/2023] [Accepted: 09/19/2023] [Indexed: 11/15/2023]
Abstract
OBJECTIVE This observational study investigated metabolomic changes in individuals with type 2 diabetes (T2D) after weight loss. We hypothesized that metabolite changes associated with T2D-relevant phenotypes are signatures of improved health. METHODS Fasting plasma samples from individuals undergoing bariatric surgery (n = 71 Roux-en-Y gastric bypass [RYGB], n = 22 gastric banding), lifestyle intervention (n = 66), or usual care (n = 14) were profiled for 139 metabolites before and 2 years after weight loss. Principal component analysis grouped correlated metabolites into factors. Association of preintervention metabolites was tested with preintervention clinical features and changes in T2D markers. Association between change in metabolites/metabolite factors and change in T2D remission markers, homeostasis model assessment of β-cell function, homeostasis model assessment of insulin resistance, and glycated hemoglobin (HbA1c) was assessed. RESULTS Branched-chain amino acids (BCAAs) were associated with preintervention adiposity. Changes in BCAAs (valine, leucine/isoleucine) and branched-chain ketoacids were positively associated with change in HbA1c (false discovery rate q value ≤ 0.001) that persisted after adjustment for percentage weight change and RYGB (p ≤ 0.02). In analyses stratified by RYGB or other weight loss method, some metabolites showed association with non-RYGB weight loss. CONCLUSIONS This study confirmed known metabolite associations with obesity/T2D and showed an association of BCAAs with HbA1c change after weight loss, independent of the method or magnitude of weight loss.
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Affiliation(s)
- Vidhu V. Thaker
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY
| | | | - Haiying Chen
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Salem, NC
| | - Judy Bahson
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Salem, NC
| | - Olga Ilkayeva
- Duke Molecular Physiology Institute
- Sarah W. Stedman Nutrition and Metabolism Center
- Department of Medicine, Division of Endocrinology, Metabolism, and Nutrition, Duke University School of Medicine, Durham, NC
| | | | - Bruce Wolfe
- Departments of Surgery and Medicine, Oregon Health & Science University, Portland, OR
| | - Jonathan Q Purnell
- Departments of Surgery and Medicine, Oregon Health & Science University, Portland, OR
| | - Xavier Pi-Sunyer
- New York Obesity Research Center, Division of Endocrinology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Christopher B. Newgard
- Duke Molecular Physiology Institute
- Sarah W. Stedman Nutrition and Metabolism Center
- Department of Pharmacology & Cancer Biology and Division of Endocrinology, Department of Medicine, Duke University, Durham, NC
| | - Svati H. Shah
- Duke Molecular Physiology Institute
- Division of Cardiology, Department of Medicine, Duke University Medical Center, Durham, NC
| | - Blandine Laferrère
- New York Obesity Research Center, Division of Endocrinology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
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Liu Y, Wang D, Liu YP. Metabolite profiles of diabetes mellitus and response to intervention in anti-hyperglycemic drugs. Front Endocrinol (Lausanne) 2023; 14:1237934. [PMID: 38027178 PMCID: PMC10644798 DOI: 10.3389/fendo.2023.1237934] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Type 2 diabetes mellitus (T2DM) has become a major health problem, threatening the quality of life of nearly 500 million patients worldwide. As a typical multifactorial metabolic disease, T2DM involves the changes and interactions of various metabolic pathways such as carbohydrates, amino acid, and lipids. It has been suggested that metabolites are not only the endpoints of upstream biochemical processes, but also play a critical role as regulators of disease progression. For example, excess free fatty acids can lead to reduced glucose utilization in skeletal muscle and induce insulin resistance; metabolism disorder of branched-chain amino acids contributes to the accumulation of toxic metabolic intermediates, and promotes the dysfunction of β-cell mitochondria, stress signal transduction, and apoptosis. In this paper, we discuss the role of metabolites in the pathogenesis of T2DM and their potential as biomarkers. Finally, we list the effects of anti-hyperglycemic drugs on serum/plasma metabolic profiles.
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Affiliation(s)
| | | | - Yi-Ping Liu
- Provincial University Key Laboratory of Sport and Health Science, School of Physical Education and Sport Sciences, Fujian Normal University, Fuzhou, China
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Viggiano D. Mechanisms of Diabetic Nephropathy Not Mediated by Hyperglycemia. J Clin Med 2023; 12:6848. [PMID: 37959313 PMCID: PMC10650633 DOI: 10.3390/jcm12216848] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 10/27/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
Diabetes mellitus (DM) is characterized by the appearance of progressive kidney damage, which may progress to end-stage kidney disease. The control of hyperglycemia is usually not sufficient to halt this progression. The kidney damage is quantitatively and qualitatively different in the two forms of diabetes; the typical nodular fibrosis (Kimmelstiel Wilson nodules) appears mostly in type 1 DM, whereas glomerulomegaly is primarily present in type 2 obese DM. An analysis of the different metabolites and hormones in type 1 and type 2 DM and their differential pharmacological treatments might be helpful to advance the hypotheses on the different histopathological patterns of the kidneys and their responses to sodium/glucose transporter type 2 inhibitors (SGLT2i).
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Affiliation(s)
- Davide Viggiano
- Department of Translational Medical Sciences, University of Campania, 80131 Naples, Italy
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Shahisavandi M, Wang K, Ghanbari M, Ahmadizar F. Exploring Metabolomic Patterns in Type 2 Diabetes Mellitus and Response to Glucose-Lowering Medications-Review. Genes (Basel) 2023; 14:1464. [PMID: 37510368 PMCID: PMC10379356 DOI: 10.3390/genes14071464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023] Open
Abstract
The spectrum of information related to precision medicine in diabetes generally includes clinical data, genetics, and omics-based biomarkers that can guide personalized decisions on diabetes care. Given the remarkable progress in patient risk characterization, there is particular interest in using molecular biomarkers to guide diabetes management. Metabolomics is an emerging molecular approach that helps better understand the etiology and promises the identification of novel biomarkers for complex diseases. Both targeted or untargeted metabolites extracted from cells, biofluids, or tissues can be investigated by established high-throughput platforms, like nuclear magnetic resonance (NMR) and mass spectrometry (MS) techniques. Metabolomics is proposed as a valuable tool in precision diabetes medicine to discover biomarkers for diagnosis, prognosis, and management of the progress of diabetes through personalized phenotyping and individualized drug-response monitoring. This review offers an overview of metabolomics knowledge as potential biomarkers in type 2 diabetes mellitus (T2D) diagnosis and the response to glucose-lowering medications.
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Affiliation(s)
- Mina Shahisavandi
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands
| | - Kan Wang
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands
| | - Fariba Ahmadizar
- Department of Data Science & Biostatistics, Julius Global Health, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
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Bellerba F, Chatziioannou AC, Jasbi P, Robinot N, Keski-Rahkonen P, Trolat A, Vozar B, Hartman SJ, Scalbert A, Bonanni B, Johansson H, Sears DD, Gandini S. Metabolomic profiles of metformin in breast cancer survivors: a pooled analysis of plasmas from two randomized placebo-controlled trials. J Transl Med 2022; 20:629. [PMID: 36581893 PMCID: PMC9798585 DOI: 10.1186/s12967-022-03809-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 12/05/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Obesity is a major health concern for breast cancer survivors, being associated with high recurrence and reduced efficacy during cancer treatment. Metformin treatment is associated with reduced breast cancer incidence, recurrence and mortality. To better understand the underlying mechanisms through which metformin may reduce recurrence, we aimed to conduct metabolic profiling of overweight/obese breast cancer survivors before and after metformin treatment. METHODS Fasting plasma samples from 373 overweight or obese breast cancer survivors randomly assigned to metformin (n = 194) or placebo (n = 179) administration were collected at baseline, after 6 months (Reach For Health trial), and after 12 months (MetBreCS trial). Archival samples were concurrently analyzed using three complementary methods: untargeted LC-QTOF-MS metabolomics, targeted LC-MS metabolomics (AbsoluteIDQ p180, Biocrates), and gas chromatography phospholipid fatty acid assay. Multivariable linear regression models and family-wise error correction were used to identify metabolites that significantly changed after metformin treatment. RESULTS Participants (n = 352) with both baseline and study end point samples available were included in the analysis. After adjusting for confounders such as study center, age, body mass index and false discovery rate, we found that metformin treatment was significantly associated with decreased levels of citrulline, arginine, tyrosine, caffeine, paraxanthine, and theophylline, and increased levels of leucine, isoleucine, proline, 3-methyl-2-oxovalerate, 4-methyl-2-oxovalerate, alanine and indoxyl-sulphate. Long-chain unsaturated phosphatidylcholines (PC ae C36:4, PC ae C38:5, PC ae C36:5 and PC ae C38:6) were significantly decreased with the metformin treatment, as were phospholipid-derived long-chain n-6 fatty acids. The metabolomic profiles of metformin treatment suggest change in specific biochemical pathways known to impair cancer cell growth including activation of CYP1A2, alterations in fatty acid desaturase activity, and altered metabolism of specific amino acids, including impaired branched chain amino acid catabolism. CONCLUSIONS Our results in overweight breast cancer survivors identify new metabolic effects of metformin treatment that may mechanistically contribute to reduced risk of recurrence in this population and reduced obesity-related cancer risk reported in observational studies. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT01302379 and EudraCT Protocol #: 2015-001001-14.
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Affiliation(s)
- Federica Bellerba
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | | | - Paniz Jasbi
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA
- School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Nivonirina Robinot
- International Agency for Research on Cancer, Nutrition and Metabolism Branch, Lyon, France
| | - Pekka Keski-Rahkonen
- International Agency for Research on Cancer, Nutrition and Metabolism Branch, Lyon, France
| | - Amarine Trolat
- International Agency for Research on Cancer, Nutrition and Metabolism Branch, Lyon, France
| | - Béatrice Vozar
- International Agency for Research on Cancer, Nutrition and Metabolism Branch, Lyon, France
| | - Sheri J Hartman
- Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, CA, USA
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Augustin Scalbert
- International Agency for Research on Cancer, Nutrition and Metabolism Branch, Lyon, France
| | - Bernardo Bonanni
- Division of Cancer Prevention and Genetics, IEO, European Institute of Oncology IRCCS, Via Giuseppe Ripamonti 435, 20141, Milan, Italy
| | - Harriet Johansson
- Division of Cancer Prevention and Genetics, IEO, European Institute of Oncology IRCCS, Via Giuseppe Ripamonti 435, 20141, Milan, Italy.
| | - Dorothy D Sears
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
- Department of Medicine, UC San Diego, La Jolla, CA, USA
| | - Sara Gandini
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milan, Italy
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Dekkers KF, Sayols-Baixeras S, Baldanzi G, Nowak C, Hammar U, Nguyen D, Varotsis G, Brunkwall L, Nielsen N, Eklund AC, Bak Holm J, Nielsen HB, Ottosson F, Lin YT, Ahmad S, Lind L, Sundström J, Engström G, Smith JG, Ärnlöv J, Orho-Melander M, Fall T. An online atlas of human plasma metabolite signatures of gut microbiome composition. Nat Commun 2022; 13:5370. [PMID: 36151114 PMCID: PMC9508139 DOI: 10.1038/s41467-022-33050-0] [Citation(s) in RCA: 102] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 08/26/2022] [Indexed: 11/27/2022] Open
Abstract
Human gut microbiota produce a variety of molecules, some of which enter the bloodstream and impact health. Conversely, dietary or pharmacological compounds may affect the microbiota before entering the circulation. Characterization of these interactions is an important step towards understanding the effects of the gut microbiota on health. In this cross-sectional study, we used deep metagenomic sequencing and ultra-high-performance liquid chromatography linked to mass spectrometry for a detailed characterization of the gut microbiota and plasma metabolome, respectively, of 8583 participants invited at age 50 to 64 from the population-based Swedish CArdioPulmonary bioImage Study. Here, we find that the gut microbiota explain up to 58% of the variance of individual plasma metabolites and we present 997 associations between alpha diversity and plasma metabolites and 546,819 associations between specific gut metagenomic species and plasma metabolites in an online atlas (https://gutsyatlas.serve.scilifelab.se/). We exemplify the potential of this resource by presenting novel associations between dietary factors and oral medication with the gut microbiome, and microbial species strongly associated with the uremic toxin p-cresol sulfate. This resource can be used as the basis for targeted studies of perturbation of specific metabolites and for identification of candidate plasma biomarkers of gut microbiota composition. Here, Dekkers et al. characterize associations of 1528 gut metagenomic species with the plasma metabolome in 8583 participants of the SCAPIS Study, and find that gut microbiota explain up to 58% of the variance of individual plasma metabolites.
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Affiliation(s)
- Koen F Dekkers
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Sergi Sayols-Baixeras
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.,CIBER Cardiovascular diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
| | - Gabriel Baldanzi
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Christoph Nowak
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institute, Huddinge, Sweden
| | - Ulf Hammar
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Diem Nguyen
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Georgios Varotsis
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | | | | | | | | | | | - Filip Ottosson
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Yi-Ting Lin
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Shafqat Ahmad
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Johan Sundström
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden.,The George Institute for Global Health, University of New South Wales, Sydney, Australia
| | - Gunnar Engström
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - J Gustav Smith
- The Wallenberg Laboratory/Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg University and the Department of Cardiology, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden.,Wallenberg Center for Molecular Medicine and Lund University Diabetes Center, Lund University, Lund, Sweden
| | - Johan Ärnlöv
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institute, Huddinge, Sweden.,School of Health and Social Studies, Dalarna University, Falun, Sweden
| | | | - Tove Fall
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
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Pharmacokinetic-Pharmacometabolomic Approach in Early-Phase Clinical Trials: A Way Forward for Targeted Therapy in Type 2 Diabetes. Pharmaceutics 2022; 14:pharmaceutics14061268. [PMID: 35745841 PMCID: PMC9231303 DOI: 10.3390/pharmaceutics14061268] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 12/20/2022] Open
Abstract
Pharmacometabolomics in early phase clinical trials demonstrate the metabolic profiles of a subject responding to a drug treatment in a controlled environment, whereas pharmacokinetics measure the drug plasma concentration in human circulation. Application of the personalized peak plasma concentration from pharmacokinetics in pharmacometabolomic studies provides insights into drugs’ pharmacological effects through dysregulation of metabolic pathways or pharmacodynamic biomarkers. This proof-of-concept study integrates personalized pharmacokinetic and pharmacometabolomic approaches to determine the predictive pharmacodynamic response of human metabolic pathways for type 2 diabetes. In this study, we use metformin as a model drug. Metformin is a first-line glucose-lowering agent; however, the variation of metabolites that potentially affect the efficacy and safety profile remains inconclusive. Seventeen healthy subjects were given a single dose of 1000 mg of metformin under fasting conditions. Fifteen sampling time-points were collected and analyzed using the validated bioanalytical LCMS method for metformin quantification in plasma. The individualized peak-concentration plasma samples determined from the pharmacokinetic parameters calculated using Matlab Simbiology were further analyzed with pre-dose plasma samples using an untargeted metabolomic approach. Pharmacometabolomic data processing and statistical analysis were performed using MetaboAnalyst with a functional meta-analysis peaks-to-pathway approach to identify dysregulated human metabolic pathways. The validated metformin calibration ranged from 80.4 to 2010 ng/mL for accuracy, precision, stability and others. The median and IQR for Cmax was 1248 (849–1391) ng/mL; AUC0-infinity was 9510 (7314–10,411) ng·h/mL, and Tmax was 2.5 (2.5–3.0) h. The individualized Cmax pharmacokinetics guided the untargeted pharmacometabolomics of metformin, suggesting a series of provisional predictive human metabolic pathways, which include arginine and proline metabolism, branched-chain amino acid (BCAA) metabolism, glutathione metabolism and others that are associated with metformin’s pharmacological effects of increasing insulin sensitivity and lipid metabolism. Integration of pharmacokinetic and pharmacometabolomic approaches in early-phase clinical trials may pave a pathway for developing targeted therapy. This could further reduce variability in a controlled trial environment and aid in identifying surrogates for drug response pathways, increasing the prediction of responders for dose selection in phase II clinical trials.
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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: 3.3] [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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11
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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: 1.5] [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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12
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Sriboonvorakul N, Pan-Ngum W, Poovorawan K, Muangnoicharoen S, Quinn LM, Tan BK. Low Branched Chain Amino Acids and Tyrosine in Thai Patients with Type 2 Diabetes Mellitus Treated with Metformin and Metformin-Sulfonylurea Combination Therapies. J Clin Med 2021; 10:5424. [PMID: 34830706 PMCID: PMC8621185 DOI: 10.3390/jcm10225424] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 11/09/2021] [Accepted: 11/18/2021] [Indexed: 12/15/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a growing public health challenge for Thailand (current prevalence ~10.0%). Amino acids offer novel biomarkers to predict risk of T2DM and indicate sub-optimal disease management, which could facilitate earlier treatment. We studied amino acid profiles in a Thai cohort comprising of individuals with T2DM (n = 65 single-drug-treated; n = 38 multi-drug-treated) compared to healthy controls (n = 104) using liquid chromatography-mass spectrometry. Age and BMI were significantly lower in the healthy controls compared to the single or multi-treated T2DM groups. The BCAA (leucine and valine) were significantly lower in the single and multi-treated T2DM groups compared to healthy controls (p < 0.001 and p < 0.001) and isoleucine was significantly lower in the single-treated compared to the healthy controls (p = 0.014). These findings beg the question whether BCAAs supplementation be beneficial in T2DM patients treated with single or multi-drug therapy? Tyrosine was significantly lower in the single and multi-treated T2DM groups compared to healthy controls (p < 0.001 and p = 0.002), whereas phenylalanine was significantly higher in the multi-treated T2DM group compared to the single treated T2DM group (p = 0.045). We provide novel insights into the effects of diabetes treatments on these amino acids in insulin resistant states such as T2DM in a unique but understudied Thai population.
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Affiliation(s)
- Natthida Sriboonvorakul
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; (N.S.); (K.P.); (S.M.)
| | - Wirichada Pan-Ngum
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand;
| | - Kittiyod Poovorawan
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; (N.S.); (K.P.); (S.M.)
| | - Sant Muangnoicharoen
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; (N.S.); (K.P.); (S.M.)
| | - Lauren M. Quinn
- Department of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK;
| | - Bee K. Tan
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; (N.S.); (K.P.); (S.M.)
- Department of Cardiovascular Sciences and Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK
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13
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Robinson EJ, Taddeo MC, Chu X, Shi W, Wood C, Still C, Rovnyak VG, Rovnyak D. Aqueous Metabolite Trends for the Progression of Nonalcoholic Fatty Liver Disease in Female Bariatric Surgery Patients by Targeted 1H-NMR Metabolomics. Metabolites 2021; 11:metabo11110737. [PMID: 34822395 PMCID: PMC8619318 DOI: 10.3390/metabo11110737] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 01/14/2023] Open
Abstract
Determining biomarkers and better characterizing the biochemical progression of nonalcoholic fatty liver disease (NAFLD) remains a clinical challenge. A targeted 1H-NMR study of serum, combined with clinical variables, detected and localized biomarkers to stages of NAFLD in morbidly obese females. Pre-surgery serum samples from 100 middle-aged, morbidly obese female subjects, grouped on gold-standard liver wedge biopsies (non-NAFLD; steatosis; and fibrosis) were collected, extracted, and analyzed in aqueous (D2O) buffer (1H, 600 MHz). Profiled concentrations were subjected to exploratory statistical analysis. Metabolites varying significantly between the non-NAFLD and steatosis groups included the ketone bodies 3-hydroxybutyrate (↓; p = 0.035) and acetone (↓; p = 0.012), and also alanine (↑; p = 0.004) and a putative pyruvate signal (↑; p = 0.003). In contrast, the steatosis and fibrosis groups were characterized by 2-hydroxyisovalerate (↑; p = 0.023), betaine (↓; p = 0.008), hypoxanthine (↓; p = 0.003), taurine (↓; p = 0.001), 2-hydroxybutyrate (↑; p = 0.045), 3-hydroxyisobutyrate (↑; p = 0.046), and increasing medium chain fatty acids. Exploratory classification models with and without clinical variables exhibited overall success rates ca. 75–85%. In the study conditions, inhibition of fatty acid oxidation and disruption of the hepatic urea cycle are supported as early features of NAFLD that continue in fibrosis. In fibrosis, markers support inflammation, hepatocyte damage, and decreased liver function. Complementarity of NMR concentrations and clinical information in classification models is shown. A broader hypothesis that standard-of-care sera can yield metabolomic information is supported.
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Affiliation(s)
- Emma J. Robinson
- Department of Chemistry, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (E.J.R.); (M.C.T.)
| | - Matthew C. Taddeo
- Department of Chemistry, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (E.J.R.); (M.C.T.)
| | - Xin Chu
- The Obesity Institute, Geisinger, Danville, PA 17822, USA; (X.C.); (W.S.); (C.W.); (C.S.)
| | - Weixing Shi
- The Obesity Institute, Geisinger, Danville, PA 17822, USA; (X.C.); (W.S.); (C.W.); (C.S.)
| | - Craig Wood
- The Obesity Institute, Geisinger, Danville, PA 17822, USA; (X.C.); (W.S.); (C.W.); (C.S.)
| | - Christopher Still
- The Obesity Institute, Geisinger, Danville, PA 17822, USA; (X.C.); (W.S.); (C.W.); (C.S.)
| | | | - David Rovnyak
- Department of Chemistry, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (E.J.R.); (M.C.T.)
- Correspondence:
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14
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Kim HW. Metabolomic Approaches to Investigate the Effect of Metformin: An Overview. Int J Mol Sci 2021; 22:10275. [PMID: 34638615 PMCID: PMC8508882 DOI: 10.3390/ijms221910275] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [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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Affiliation(s)
- Hyun Woo Kim
- Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92093, USA
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15
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Hu C, Jia W. Multi-omics profiling: the way towards precision medicine in metabolic diseases. J Mol Cell Biol 2021; 13:mjab051. [PMID: 34406397 PMCID: PMC8697344 DOI: 10.1093/jmcb/mjab051] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/19/2021] [Accepted: 06/21/2021] [Indexed: 12/12/2022] Open
Abstract
Metabolic diseases including type 2 diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD), and metabolic syndrome (MetS) are alarming health burdens around the world, while therapies for these diseases are far from satisfying as their etiologies are not completely clear yet. T2DM, NAFLD, and MetS are all complex and multifactorial metabolic disorders based on the interactions between genetics and environment. Omics studies such as genetics, transcriptomics, epigenetics, proteomics, and metabolomics are all promising approaches in accurately characterizing these diseases. And the most effective treatments for individuals can be achieved via omics pathways, which is the theme of precision medicine. In this review, we summarized the multi-omics studies of T2DM, NAFLD, and MetS in recent years, provided a theoretical basis for their pathogenesis and the effective prevention and treatment, and highlighted the biomarkers and future strategies for precision medicine.
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Affiliation(s)
- Cheng Hu
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus,
Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth
People's Hospital, Shanghai 200233, China
- Institute for Metabolic Disease, Fengxian Central Hospital, The Third School of
Clinical Medicine, Southern Medical University, Shanghai 201499, China
| | - Weiping Jia
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus,
Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth
People's Hospital, Shanghai 200233, China
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16
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Wang QY, You LH, Xiang LL, Zhu YT, Zeng Y. Current progress in metabolomics of gestational diabetes mellitus. World J Diabetes 2021; 12:1164-1186. [PMID: 34512885 PMCID: PMC8394228 DOI: 10.4239/wjd.v12.i8.1164] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/20/2021] [Accepted: 07/07/2021] [Indexed: 02/06/2023] Open
Abstract
Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders of pregnancy and can cause short- and long-term adverse effects in both pregnant women and their offspring. However, the etiology and pathogenesis of GDM are still unclear. As a metabolic disease, GDM is well suited to metabolomics study, which can monitor the changes in small molecular metabolites induced by maternal stimuli or perturbations in real time. The application of metabolomics in GDM can be used to discover diagnostic biomarkers, evaluate the prognosis of the disease, guide the application of diet or drugs, evaluate the curative effect, and explore the mechanism. This review provides comprehensive documentation of metabolomics research methods and techniques as well as the current progress in GDM research. We anticipate that the review will contribute to identifying gaps in the current knowledge or metabolomics technology, provide evidence-based information, and inform future research directions in GDM.
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Affiliation(s)
- Qian-Yi Wang
- School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 21000, Jiangsu Province, China
| | - Liang-Hui You
- Nanjing Maternity and Child Health Care Institute, Women’s Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing 21000, Jiangsu Province, China
| | - Lan-Lan Xiang
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing 21000, Jiangsu Province, China
| | - Yi-Tian Zhu
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing 21000, Jiangsu Province, China
| | - Yu Zeng
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing 21000, Jiangsu Province, China
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17
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Gadgil MD, Kanaya AM, Sands C, Lewis MR, Kandula NR, Herrington DM. Circulating metabolites and lipids are associated with glycaemic measures in South Asians. Diabet Med 2021; 38:e14494. [PMID: 33617033 PMCID: PMC8115216 DOI: 10.1111/dme.14494] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 11/30/2020] [Accepted: 12/03/2020] [Indexed: 12/30/2022]
Abstract
BACKGROUND South Asians are at higher risk for diabetes (DM) than many other racial/ethnic groups. Circulating metabolites are measurable products of metabolic processes that may explain the aetiology of elevated risk. We characterized metabolites associated with prevalent DM and glycaemic measures in South Asians. METHODS We included 717 participants from the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study, aged 40-84 years. We used baseline fasting serum for metabolomics and demographic, behavioural, glycaemic data from baseline and at 5 years. We performed LC-MS untargeted metabolomic and lipidomic analysis with targeted integration of known signals. Individual linear and ordinal logistic regression models were adjusted for age, sex, BMI, diet, exercise, alcohol, smoking and family history of DM followed by elastic net regression to identify metabolites most associated with the outcome. RESULTS There were 258 metabolites with detectable signal in >98% of samples. Thirty-four metabolites were associated with prevalent DM in an elastic net model. Predominant metabolites associated with DM were sphingomyelins, proline (OR 15.86; 95% CI 4.72, 53.31) and betaine (OR 0.03; 0.004, 0.14). Baseline tri- and di-acylglycerols [DG (18:0/16:0) (18.36; 11.79, 24.92)] were positively associated with fasting glucose and long-chain acylcarnitines [CAR 26:1 (-0.40; -0.54, -0.27)] were inversely associated with prevalent DM and HbA1c at follow-up. DISCUSSION A metabolomic signature in South Asians may help determine the unique aetiology of diabetes in this high-risk ethnic group. Future work will externally validate our findings and determine the effects of modifiable risk factors for DM.
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Affiliation(s)
- Meghana D. Gadgil
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, CA; 1545 Divisadero Street, Suite 320, San Francisco, CA 94143-0320
| | - Alka M. Kanaya
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, CA; 1545 Divisadero Street, Suite 320, San Francisco, CA 94143-0320
| | - Caroline Sands
- National Phenome Centre, Imperial College London, IRDB Building 5th Floor, Hammersmith Hospital Campus, London, W12 0NN
| | - Matthew R. Lewis
- National Phenome Centre, Imperial College London, IRDB Building 5th Floor, Hammersmith Hospital Campus, London, W12 0NN
| | - Namratha R. Kandula
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; Rubloff Building 10th Floor 750 N Lake Shore Chicago IL 60611
| | - David M. Herrington
- Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest School of Medicine; Medical Center Boulevard, Winston-Salem, NC 27157
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18
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Chung ST, Matta ST, Meyers AG, Cravalho CK, Villalobos-Perez A, Dawson JM, Sharma VR, Sampson ML, Otvos JD, Magge SN. Nuclear Magnetic Resonance Derived Biomarkers for Evaluating Cardiometabolic Risk in Youth and Young Adults Across the Spectrum of Glucose Tolerance. Front Endocrinol (Lausanne) 2021; 12:665292. [PMID: 34084151 PMCID: PMC8167058 DOI: 10.3389/fendo.2021.665292] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 04/08/2021] [Indexed: 12/17/2022] Open
Abstract
UNLABELLED Youth with obesity have an increased risk for cardiometabolic disease, but identifying those at highest risk remains a challenge. Four biomarkers that might serve this purpose are "by products" of clinical NMR LipoProfile® lipid testing: LPIR (Lipoprotein Insulin Resistance Index), GlycA (inflammation marker), BCAA (total branched-chain amino acids), and glycine. All are strongly related to insulin resistance and type 2 diabetes (T2DM) in adults (glycine inversely) and are independent of biological and methodological variations in insulin assays. However, their clinical utility in youth is unclear. We compared fasting levels of these biomarkers in 186 youth (42 lean normal glucose tolerant (NGT), 88 obese NGT, 23 with prediabetes (PreDM), and 33 with T2DM. All four biomarkers were associated with obesity and glycemia in youth. LPIR and GlycA were highest in youth with PreDM and T2DM, whereas glycine was lowest in youth with T2DM. While all four were correlated with HOMA-IR (Homeostatic Model Assessment for Insulin Resistance), LPIR had the strongest correlation (LPIR: r = 0.6; GlycA: r = 0.4, glycine: r = -0.4, BCAA: r = 0.2, all P < 0.01). All four markers correlated with HbA1c (LPIR, GlycA, BCAA: r ≥ 0.3 and glycine: r = -0.3, all P < 0.001). In multi-variable regression models, LPIR, GlycA, and glycine were independently associated with HOMA-IR (Adjusted R2 = 0.473, P < 0.001) and LPIR, glycine, and BCAA were independently associated with HbA1c (Adjusted R2 = 0.33, P < 0.001). An LPIR index of >44 was associated with elevated blood pressure, BMI, and dyslipidemia. Plasma NMR-derived markers were related to adverse markers of cardiometabolic risk in youth. LPIR, either alone or in combination with GlycA, should be explored as a non-insulin dependent predictive tool for development of insulin resistance and diabetes in youth. CLINICAL TRIAL REGISTRATION Clinicaltrials.gov, identifier NCT:02960659.
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Affiliation(s)
- Stephanie T. Chung
- Diabetes, Endocrinology and Obesity Branch, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
- *Correspondence: Stephanie T. Chung,
| | - Samantha T. Matta
- Diabetes, Endocrinology and Obesity Branch, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Abby G. Meyers
- Department of Endocrinology and Diabetes, Children’s National Hospital, Washington, DC, United States
| | - Celeste K. Cravalho
- Diabetes, Endocrinology and Obesity Branch, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Alfredo Villalobos-Perez
- Diabetes, Endocrinology and Obesity Branch, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Joshua M. Dawson
- Diabetes, Endocrinology and Obesity Branch, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Vandhna R. Sharma
- Diabetes, Endocrinology and Obesity Branch, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Maureen L. Sampson
- National Institutes of Health Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - James D. Otvos
- Laboratory Corporation of America Holdings (LabCorp), Morrisville, NC, United States
| | - Sheela N. Magge
- Division of Pediatric Endocrinology and Diabetes, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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19
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Yoshida N, Kitahama S, Yamashita T, Hirono Y, Tabata T, Saito Y, Shinohara R, Nakashima H, Emoto T, Hirota Y, Takahashi T, Ogawa W, Hirata K. Metabolic alterations in plasma after laparoscopic sleeve gastrectomy. J Diabetes Investig 2021; 12:123-129. [PMID: 32563200 PMCID: PMC7779268 DOI: 10.1111/jdi.13328] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 05/30/2020] [Accepted: 06/14/2020] [Indexed: 02/06/2023] Open
Abstract
Laparoscopic sleeve gastrectomy (LSG) is an important therapeutic option for morbidly obese patients. Although LSG promotes sufficient weight loss, how LSG changes plasma metabolites remains unclear. We assessed changes in plasma metabolite levels after LSG. We collected plasma samples from 15 morbidly obese Japanese patients before and 3 months after LSG. A total of 48 metabolites were quantified using capillary electrophoresis time-of-flight mass spectrometry-based metabolomic profiling. Branched chain amino acids, several essential amino acids, choline, 2-hydroxybutyric acid, 2-oxoisovaleric acid and hypoxanthine were significantly decreased after LSG. Tricarboxylic acid cycle metabolites, including citric acid, succinic acid and malic acid, were significantly elevated after LSG. This is the first report to show dynamic alterations in plasma metabolite concentrations, as assessed using capillary electrophoresis time-of-flight mass spectrometry, in morbidly obese patients after LSG. Our results might show how LSG helps improve obesity, in part through metabolic status changes, and propose novel therapeutic targets to ameliorate obesity.
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Affiliation(s)
- Naofumi Yoshida
- Division of Cardiovascular MedicineDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
| | - Seiichi Kitahama
- Department of Bariatric and Metabolic SurgeryCenter for Obesity, Diabetes and EndocrinologyChibune General HospitalOsakaJapan
| | - Tomoya Yamashita
- Division of Cardiovascular MedicineDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
| | - Yasuko Hirono
- Department of Bariatric and Metabolic SurgeryCenter for Obesity, Diabetes and EndocrinologyChibune General HospitalOsakaJapan
| | - Tokiko Tabata
- Division of Cardiovascular MedicineDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
| | - Yoshihiro Saito
- Division of Cardiovascular MedicineDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
| | | | | | - Takuo Emoto
- Division of Cardiovascular MedicineDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
| | - Yushi Hirota
- Division of Diabetes and EndocrinologyDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
| | - Tetsuya Takahashi
- Division of Diabetes and EndocrinologyDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
- Department of Diabetes and EndocrinologyCenter for Obesity, Diabetes and EndocrinologyChibune General HospitalOsakaJapan
| | - Wataru Ogawa
- Division of Diabetes and EndocrinologyDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
| | - Ken‐ichi Hirata
- Division of Cardiovascular MedicineDepartment of Internal MedicineKobe University Graduate School of MedicineKobeJapan
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20
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Huhtala MS, Tertti K, Rönnemaa T. Serum lipids and their association with birth weight in metformin and insulin treated patients with gestational diabetes. Diabetes Res Clin Pract 2020; 170:108456. [PMID: 32979417 DOI: 10.1016/j.diabres.2020.108456] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 08/14/2020] [Accepted: 09/15/2020] [Indexed: 12/13/2022]
Abstract
AIMS To compare the effects of metformin and insulin treatment on maternal serum lipids in patients with gestational diabetes (GDM), and to analyse the associations between individual lipids and birth weight (BW). METHODS This is a secondary analysis of a randomized trial comparing metformin (n = 110) and insulin (n = 107) treatment of GDM. Fasting serum lipidome was measured at baseline (the time of diagnosis, mean 30 gestational weeks, gw) and at 36 gw using nuclear magnetic resonance spectroscopy. RESULTS Total and VLDL triglycerides, and VLDL cholesterol increased from baseline to 36 gw in both treatment groups. The rise in triglycerides was greater in the metformin treated patients (p < 0.01). Baseline total and VLDL triglycerides, VLDL cholesterol, and apolipoprotein B to A-1 ratio (apoB/apoA-1) associated positively with BW, more strongly in the metformin group. Among patients in the highest baseline VLDL cholesterol or apoB/apoA-1 quartile, those treated with insulin had lower BWs than those treated with metformin (p < 0.03). CONCLUSION Compared to insulin, metformin treatment of GDM led to higher maternal serum concentrations of triglyceride-rich lipoproteins. Especially triglycerides and cholesterol in VLDL were positively associated with BW. Women with high VLDL cholesterol or high apoB/apoA-1 may benefit from insulin treatment over metformin with respect to offspring BW.
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Affiliation(s)
- Mikael S Huhtala
- Department of Obstetrics and Gynecology, University of Turku, 20014 Turku, Finland; Department of Obstetrics and Gynecology, Turku University Hospital, Kiinamyllynkatu 4-8, 20521 Turku, Finland.
| | - Kristiina Tertti
- Department of Obstetrics and Gynecology, University of Turku, 20014 Turku, Finland; 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; Department of Medicine, Turku University Hospital, Kiinamyllynkatu 4-8, 20521 Turku, Finland
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21
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Brittain EL, Niswender K, Agrawal V, Chen X, Fan R, Pugh ME, Rice TW, Robbins IM, Song H, Thompson C, Ye F, Yu C, Zhu H, West J, Newman JH, Hemnes AR. Mechanistic Phase II Clinical Trial of Metformin in Pulmonary Arterial Hypertension. J Am Heart Assoc 2020; 9:e018349. [PMID: 33167773 PMCID: PMC7763730 DOI: 10.1161/jaha.120.018349] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 09/22/2020] [Indexed: 02/07/2023]
Abstract
Background Metabolic dysfunction is highly prevalent in pulmonary arterial hypertension (PAH) and likely contributes to both pulmonary vascular disease and right ventricular (RV) failure in part because of increased oxidant stress. Currently, there is no cure for PAH and human studies of metabolic interventions, generally well tolerated in other diseases, are limited in PAH. Metformin is a commonly used oral antidiabetic that decreases gluconeogenesis, increases fatty acid oxidation, and reduces oxidant stress and thus may be relevant to PAH. Methods and Results We performed a single-center, open-label 8-week phase II trial of up to 2 g/day of metformin in patients with idiopathic or heritable PAH with the co-primary end points of safety, including development of lactic acidosis and study withdrawal, and plasma oxidant stress markers. Exploratory end points included RV function via echocardiography, plasma metabolomic analysis performed before and after metformin therapy, and RV triglyceride content by magnetic resonance spectroscopy in a subset of 9 patients. We enrolled 20 patients; 19/20 reached the target dose and all completed the study protocol. There was no clinically significant lactic acidosis or change in oxidant stress markers. Metformin did not change 6-minute walk distance but did significantly improve RV fractional area change (23±8% to 26±6%, P=0.02), though other echocardiographic parameters were unchanged. RV triglyceride content decreased in 8/9 patients (3.2±1.8% to 1.6±1.4%, P=0.015). In an exploratory metabolomic analysis, plasma metabolomic correlates of ≥50% reduction in RV lipid included dihydroxybutyrate, acetylputrescine, hydroxystearate, and glucuronate (P<0.05 for all). In the entire cohort, lipid metabolites were among the most changed by metformin. Conclusions Metformin therapy was safe and well tolerated in patients with PAH in this single-arm, open-label phase II study. Exploratory analyses suggest that metformin may be associated with improved RV fractional area change and, in a subset of patients, reduced RV triglyceride content that correlated with altered lipid and glucose metabolism markers. Registration URL: http://www.clinicaltrials.gov; Unique identifier: NCT01884051.
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Affiliation(s)
- Evan L. Brittain
- Division of Cardiovascular MedicineVanderbilt University Medical CenterNashvilleTN
| | - Kevin Niswender
- Division of Diabetes, Endocrinology, and MetabolismVanderbilt University Medical CenterNashvilleTN
| | - Vineet Agrawal
- Division of Cardiovascular MedicineVanderbilt University Medical CenterNashvilleTN
| | - Xinping Chen
- Division of Allergy, Pulmonary and Critical Care MedicineVanderbilt University Medical CenterNashvilleTN
| | - Run Fan
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTN
| | - Meredith E. Pugh
- Division of Allergy, Pulmonary and Critical Care MedicineVanderbilt University Medical CenterNashvilleTN
| | - Todd W. Rice
- Division of Allergy, Pulmonary and Critical Care MedicineVanderbilt University Medical CenterNashvilleTN
| | - Ivan M. Robbins
- Division of Allergy, Pulmonary and Critical Care MedicineVanderbilt University Medical CenterNashvilleTN
| | - Haocan Song
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTN
| | - Christopher Thompson
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTN
| | - Fei Ye
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTN
| | - Chang Yu
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTN
| | - He Zhu
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTN
| | - James West
- Division of Allergy, Pulmonary and Critical Care MedicineVanderbilt University Medical CenterNashvilleTN
| | - John H. Newman
- Division of Allergy, Pulmonary and Critical Care MedicineVanderbilt University Medical CenterNashvilleTN
| | - Anna R. Hemnes
- Division of Allergy, Pulmonary and Critical Care MedicineVanderbilt University Medical CenterNashvilleTN
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22
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Mokkala K, Vahlberg T, Houttu N, Koivuniemi E, Laitinen K. Distinct Metabolomic Profile Because of Gestational Diabetes and its Treatment Mode in Women with Overweight and Obesity. Obesity (Silver Spring) 2020; 28:1637-1644. [PMID: 32705820 DOI: 10.1002/oby.22882] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 03/18/2020] [Accepted: 04/24/2020] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Whether the presence of gestational diabetes (GDM) and its treatment mode influence the serum metabolic profile in women with overweight or obesity was studied. METHODS The serum metabolic profiles of 352 women with overweight or obesity participating in a mother-infant clinical study were analyzed with a targeted NMR approach (at 35.1 median gestational weeks). GDM was diagnosed with a 2-hour 75-g oral glucose tolerance test. RESULTS The metabolomic profile of the women with GDM (n = 100) deviated from that of women without GDM (n = 252). Differences were seen in 70 lipid variables, particularly higher concentrations of very low-density lipoprotein particles and serum triglycerides were related to GDM. Furthermore, levels of branched-chain amino acids and glycoprotein acetylation, a marker of low-grade inflammation, were higher in women with GDM. Compared with women with GDM treated with diet only, the women treated with medication (n = 19) had higher concentrations of severalizes of VLDL particles and their components, leucine, and isoleucine, as well as glycoprotein acetylation. CONCLUSIONS A clearly distinct metabolic profile was detected in GDM, which deviated even more if the patient was receiving medical treatment. This suggests a need for more intense follow-up and therapy for women with GDM during pregnancy and postpartum to reduce their long-term adverse health risks.
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Affiliation(s)
- Kati Mokkala
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
| | - Tero Vahlberg
- Department of Clinical Medicine, Biostatistics, University of Turku, Turku, Finland
| | - Noora Houttu
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
| | - Ella Koivuniemi
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
| | - Kirsi Laitinen
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
- Turku University Hospital, Turku, Finland
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Tokgözoglu L, Zamorano JL. Current perspectives on the use of statins in the treatment of dyslipidaemic patients: focus on pitavastatin. Drugs Context 2020; 9:dic-2020-4-4. [PMID: 32587627 PMCID: PMC7295107 DOI: 10.7573/dic.2020-4-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 05/18/2020] [Accepted: 05/20/2020] [Indexed: 01/14/2023] Open
Abstract
A meeting entitled 'Current Perspective on the Use of Statins in the Treatment of Dyslipidemic Patients' was held in Stresa, Italy, on 27-28th June 2019. The presentations covered the 2019 European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) guidelines on dyslipidaemia, with discussion about the importance of controlling low-density lipoprotein cholesterol (LDL-C) and the pharmacological opportunities to reach the novel lipid goals. The roles of statins to manage dyslipidaemia in patients with different cardiovascular risks were also discussed. In particular, the efficacy and safety of pitavastatin for the treatment of dyslipidaemia were reviewed, highlighting its further advantages beyond LDL-C reduction. Therefore, the impact of statins on the glycaemic profile was discussed in view of the null/lower effect of pitavastatin as compared with other statins, as well as the interaction profile with other drugs commonly used. This meeting report summarizes the main messages of the discussion with a special focus on pitavastatin, whose main features in different settings are described.
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Metabolomics profiles associated with HbA1c levels in patients with type 2 diabetes. PLoS One 2019; 14:e0224274. [PMID: 31697702 PMCID: PMC6837371 DOI: 10.1371/journal.pone.0224274] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 10/09/2019] [Indexed: 01/05/2023] Open
Abstract
Glycated hemoglobin (HbA1c) is an indicator of the average blood glucose concentration. Failing to control HbA1c levels can accelerate the development of complications in patients with diabetes. Although metabolite profiles associated with HbA1c level in diabetes patients have been characterized using different platforms, more studies using high-throughput technology will be helpful to identify additional metabolites related to diabetes. Type 2 diabetes (T2D) patients were divided into two groups based on the HbA1c level: normal (HbA1c ≤6%) and high (HbA1c ≥9%) in both discovery and replication sets. A targeted metabolomics approach was used to quantify serum metabolites and multivariate logistic regression was used to identify significant differences between groups. The concentrations of 22 metabolites differed significantly between the two groups in the discovery set. In the replication set, the levels of 21 metabolites, including 16 metabolites identified in the discovery set, differed between groups. Among these, concentrations of eleven amino acids and one phosphatidylcholine (PC), lysoPC a C16:1, were higher and four metabolites, including three PCs (PC ae C36:1, PC aa C26:0, PC aa C34:2) and hexose, were lower in the group with normal HbA1c group than in the group with high HbA1c. Metabolites with high concentrations in the normal HbA1c group, such as glycine, valine, and PCs, may contribute to reducing HbA1c levels in patients with T2D. The metabolite signatures identified in this study provide insight into the mechanisms underlying changes in HbA1c levels in T2D.
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NMR-Based Metabolomic Approach Tracks Potential Serum Biomarkers of Disease Progression in Patients with Type 2 Diabetes Mellitus. J Clin Med 2019; 8:jcm8050720. [PMID: 31117294 PMCID: PMC6571571 DOI: 10.3390/jcm8050720] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 05/10/2019] [Accepted: 05/15/2019] [Indexed: 12/15/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia associated with alterations in carbohydrate, lipid, and protein metabolism. The prognosis of T2DM patients is highly dependent on the development of complications, and therefore the identification of biomarkers of T2DM progression, with minimally invasive techniques, is a huge need. In the present study, we applied a 1H-Nuclear Magnetic Resonance (1H-NMR)-based metabolomic approach coupled with multivariate data analysis to identify serum metabolite profiles associated with T2DM development and progression. To perform this, we compared the serum metabolome of non-diabetic subjects, treatment-naïve non-complicated T2DM patients, and T2DM patients with complications in insulin monotherapy. Our analysis revealed a significant reduction of alanine, glutamine, glutamate, leucine, lysine, methionine, tyrosine, and phenylalanine in T2DM patients with respect to non-diabetic subjects. Moreover, isoleucine, leucine, lysine, tyrosine, and valine levels distinguished complicated patients from patients without complications. Overall, the metabolic pathway analysis suggested that branched-chain amino acid (BCAA) metabolism is significantly compromised in T2DM patients with complications, while perturbation in the metabolism of gluconeogenic amino acids other than BCAAs characterizes both early and advanced T2DM stages. In conclusion, we identified a metabolic serum signature associated with T2DM stages. These data could be integrated with clinical characteristics to build a composite T2DM/complications risk score to be validated in a prospective cohort.
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