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Rizo-Roca D, Henderson JD, Zierath JR. Metabolomics in cardiometabolic diseases: Key biomarkers and therapeutic implications for insulin resistance and diabetes. J Intern Med 2025. [PMID: 40289598 DOI: 10.1111/joim.20090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/30/2025]
Abstract
Cardiometabolic diseases-including Type 2 diabetes and obesity-remain leading causes of global mortality. Recent advancements in metabolomics have facilitated the identification of metabolites that are integral to the development of insulin resistance, a characteristic feature of cardiometabolic disease. Key metabolites, such as branched-chain amino acids (BCAAs), ceramides, glycine, and glutamine, have emerged as valuable biomarkers for early diagnosis, risk stratification, and potential therapeutic targets. Elevated BCAAs and ceramides are strongly associated with insulin resistance and Type 2 diabetes, whereas glycine exhibits an inverse relationship with insulin resistance, making it a promising therapeutic target. Metabolites involved in energy stress, including ketone bodies, lactate, and nicotinamide adenine dinucleotide (NAD⁺), regulate insulin sensitivity and metabolic health, with ketogenic diets and NAD⁺ precursor supplementation showing potential benefits. Additionally, the novel biomarker N-lactoyl-phenylalanine further underscores the complexity of metabolic regulation and its therapeutic potential. This review underscores the potential of metabolite-based diagnostics and precision medicine, which could enhance efforts in the prevention, diagnosis, and treatment of cardiometabolic diseases, ultimately improving patient outcomes and quality of life.
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Affiliation(s)
- David Rizo-Roca
- Department of Physiology and Pharmacology, Integrative Physiology, Karolinska Institutet, Stockholm, Sweden
| | - John D Henderson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Juleen R Zierath
- Department of Physiology and Pharmacology, Integrative Physiology, Karolinska Institutet, Stockholm, Sweden
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Molecular Medicine and Surgery, Integrative Physiology, Karolinska Institutet, Stockholm, Sweden
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2
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Xiao M, Zhou N, Tian Z, Sun C. Endogenous Metabolites in Metabolic Diseases: Pathophysiologic Roles and Therapeutic Implications. J Nutr 2025:S0022-3166(25)00227-5. [PMID: 40250565 DOI: 10.1016/j.tjnut.2025.04.017] [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: 04/05/2025] [Accepted: 04/14/2025] [Indexed: 04/20/2025] Open
Abstract
Breakthroughs in metabolomics technology have revealed the direct regulatory role of metabolites in physiology and disease. Recent data have highlighted the bioactive metabolites involved in the etiology and prevention and treatment of metabolic diseases such as obesity, nonalcoholic fatty liver disease, type 2 diabetes mellitus, and atherosclerosis. Numerous studies reveal that endogenous metabolites biosynthesized by host organisms or gut microflora regulate metabolic responses and disorders. Lipids, amino acids, and bile acids, as endogenous metabolic modulators, regulate energy metabolism, insulin sensitivity, and immune response through multiple pathways, such as insulin signaling cascade, chemical modifications, and metabolite-macromolecule interactions. Furthermore, the gut microbial metabolites short-chain fatty acids, as signaling regulators have a variety of beneficial impacts in regulating energy metabolic homeostasis. In this review, we will summarize information about the roles of bioactive metabolites in the pathogenesis of many metabolic diseases. Furthermore, we discuss the potential value of metabolites in the promising preventive and therapeutic perspectives of human metabolic diseases.
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Affiliation(s)
- Mengjie Xiao
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, P. R. China; Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Heilongjiang, Harbin, P. R. China
| | - Ning Zhou
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, P. R. China; Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Heilongjiang, Harbin, P. R. China
| | - Zhen Tian
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, P. R. China; Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Heilongjiang, Harbin, P. R. China.
| | - Changhao Sun
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, P. R. China; Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Heilongjiang, Harbin, P. R. China.
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3
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Leite JSM, Vilas-Boas EA, Takahashi HK, Munhoz AC, Araújo LCC, Carvalho CR, Jr JD, Curi R, Carpinelli AR, Cruzat V. Liver lipid metabolism, oxidative stress, and inflammation in glutamine-supplemented ob/ob mice. J Nutr Biochem 2025; 138:109842. [PMID: 39824260 DOI: 10.1016/j.jnutbio.2025.109842] [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: 06/05/2024] [Revised: 12/21/2024] [Accepted: 01/13/2025] [Indexed: 01/20/2025]
Abstract
Glutamine availability may be reduced in chronic diseases, such as type 2 diabetes mellitus (T2DM)-induced by obesity. Herein, the antioxidant, anti-inflammatory and lipid metabolism effects of chronic oral glutamine supplementation in its free and dipeptide form were assessed in ob/ob mice. Adult male C57BL/6J ob/ob mice were supplemented with L-alanyl-L-glutamine (DIP) or free L-glutamine (GLN) in the drinking water for 40 days, whilst C57BL/6J Wild-type lean (WT) and control ob/ob mice (CTRL) received fresh water only. Plasma and tissue (skeletal muscle and liver) glutamine levels, and insulin resistance parameters (e.g., GTT, ITT, insulin) were determined. Oxidative stress (e.g., GSH system, Nrf2 translocation), inflammatory (e.g., NFkB translocation, TNF-α gene expression) and lipid metabolism parameters (e.g., plasma and liver triglyceride levels, SRBP-1, FAS, ACC, and ChRBP gene expression) were also analyzed. CTRL ob/ob mice showed lower glutamine levels in plasma and tissue, as well as increased insulin resistance and fat in the liver. Conversely, chronic DIP supplementation restored glutamine levels in plasma and tissues, improved glucose homeostasis and reduced plasma and liver lipid levels. Also, Nrf2 restoration, reduced NFkB translocation, and lower TNF-α gene expression was observed in the DIP group. Interestingly, chronic free GLN only increased muscle glutamine stores but reduced overall insulin resistance, and attenuated plasma and liver lipid metabolic biomarkers. The results presented herein indicate that restoration of body glutamine levels reduces oxidative stress and inflammation in obese and T2DM ob/ob mice. This effect attenuated hepatic lipid metabolic changes observed in obesity.
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Affiliation(s)
- Jaqueline Santos Moreira Leite
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, São Paulo, Brazil
| | - Eloisa Aparecida Vilas-Boas
- Department of Clinical and Toxicological Analysis, Faculty of Pharmaceutical Sciences, University of Sao Paulo, São Paulo, São Paulo, Brazil
| | - Hilton K Takahashi
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, São Paulo, Brazil
| | - Ana Cláudia Munhoz
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, São Paulo, Brazil
| | - Layanne C C Araújo
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, São Paulo, Brazil
| | - Carla Roberta Carvalho
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, São Paulo, Brazil
| | - Jose Donato Jr
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, São Paulo, Brazil
| | - Rui Curi
- Interdisciplinary Post-graduate Program in Health Sciences, ICAFE, Universidade Cruzeiro do Sul, São Paulo, São Paulo, Brazil; Instituto Butantan, São Paulo, São Paulo, Brazil
| | - Angelo Rafael Carpinelli
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, São Paulo, Brazil
| | - Vinicius Cruzat
- Faculty of Health, Southern Cross University, Gold Coast, Queensland, Australia.
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4
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Begzati A, Godinez-Macias KP, Long T, Watrous JD, Moranchel R, Kantz ED, Tuomilehto J, Havulinna AS, Niiranen TJ, Jousilahti P, Salomaa V, Yu B, Norby F, Rebholz CM, Selvin E, Winzeler EA, Cheng S, Alotaibi M, Goyal R, Ideker T, Jain M, Majithia AR. Plasma Lipid Metabolites, Clinical Glycemic Predictors, and Incident Type 2 Diabetes. Diabetes Care 2025; 48:473-480. [PMID: 39761415 PMCID: PMC11870283 DOI: 10.2337/dc24-2266] [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: 10/16/2024] [Accepted: 12/12/2024] [Indexed: 03/03/2025]
Abstract
OBJECTIVE Plasma metabolite profiling has uncovered several nonglycemic markers of incident type 2 diabetes (T2D). We investigated whether such biomarkers provide information about specific aspects of T2D etiology, such as impaired fasting glucose and impaired glucose tolerance, and whether their association with T2D risk varies by race. RESEARCH DESIGN AND METHODS Untargeted plasma metabolite profiling was performed of participants in the FINRISK 2002 cohort (n = 7,564). Cox regression modeling was conducted to identify metabolites associated with incident T2D during 14 years of follow-up. Metabolites were clustered into pathways using Gaussian graphical modeling. Clusters enriched for T2D biomarkers were further examined for covariation with fasting plasma glucose (FPG), 2-h postchallenge plasma glucose (2hPG), HbA1c, or fasting insulin. Validation analyses and tests of interaction with race were performed in the Atherosclerosis Risk in Communities (ARIC) study. RESULTS Two clusters of metabolites, representing diacylglycerols (DAGs) and phosphatidylcholines (PCs), contained the largest number of metabolite associations with incident T2D. DAGs associated with increased T2D incidence (hazard ratio [HR] 1.22; 95% CI 1.14-1.30) independent of FPG, HbA1c, and fasting insulin, but not 2hPG. PCs were inversely associated with T2D risk (HR 0.78; 95% CI 0.71-0.85) independent of FPG, 2hPG, HbA1c, and fasting insulin. No significant interaction between DAGs or PCs and race was observed. CONCLUSIONS Fasting DAGs may capture information regarding T2D risk similar to that represented by 2hPG; PCs may capture aspects of T2D etiology that differ from those represented by conventional biomarkers. The direction of effect and strength of DAG and PC associations with incident T2D are similar across European and African Americans.
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Affiliation(s)
- Arjana Begzati
- Department of Medicine, University of California San Diego, La Jolla, CA
| | | | - Tao Long
- Department of Medicine, University of California San Diego, La Jolla, CA
- Sapient Bioanalytics, San Diego, CA
| | - Jeramie D. Watrous
- Department of Medicine, University of California San Diego, La Jolla, CA
- Sapient Bioanalytics, San Diego, CA
| | - Rafael Moranchel
- Department of Medicine, University of California San Diego, La Jolla, CA
- Sapient Bioanalytics, San Diego, CA
| | - Edward D. Kantz
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Jaakko Tuomilehto
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Aki S. Havulinna
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Computing, University of Turku, Turku, Finland
- Institute for Molecular Medicine Finland, FIMM-HiLIFE, Helsinki, Finland
| | - Teemu J. Niiranen
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Internal Medicine, University of Turku, Turku, Finland
| | - Pekka Jousilahti
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Bing Yu
- Department of Epidemiology, School of Public Health, University of Texas School of Public Health, Houston, TX
| | - Faye Norby
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN
| | - Casey M. Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | | | - Susan Cheng
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Mona Alotaibi
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Ravi Goyal
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Trey Ideker
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Mohit Jain
- Department of Medicine, University of California San Diego, La Jolla, CA
- Sapient Bioanalytics, San Diego, CA
| | - Amit R. Majithia
- Department of Medicine, University of California San Diego, La Jolla, CA
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5
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Barovic M, Hahn JJ, Heinrich A, Adhikari T, Schwarz P, Mirtschink P, Funk A, Kabisch S, Pfeiffer AFH, Blüher M, Seissler J, Stefan N, Wagner R, Fritsche A, Jumpertz von Schwartzenberg R, Chlamydas S, Harb H, Mantzoros CS, Chavakis T, Schürmann A, Birkenfeld AL, Roden M, Solimena M, Bornstein SR, Perakakis N. Proteomic and Metabolomic Signatures in Prediabetes Progressing to Diabetes or Reversing to Normoglycemia Within 1 Year. Diabetes Care 2025; 48:405-415. [PMID: 39746149 DOI: 10.2337/dc24-1412] [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: 07/09/2024] [Accepted: 11/26/2024] [Indexed: 01/04/2025]
Abstract
OBJECTIVE Progression of prediabetes to type 2 diabetes has been associated with β-cell dysfunction, whereas its remission to normoglycemia has been related to improvement of insulin sensitivity. To understand the mechanisms and identify potential biomarkers related to prediabetes trajectories, we compared the proteomics and metabolomics profile of people with prediabetes progressing to diabetes or reversing to normoglycemia within 1 year. RESEARCH DESIGN AND METHODS The fasting plasma concentrations of 1,389 proteins and the fasting, 30-min, and 120-min post-oral glucose tolerance test (OGTT) plasma concentrations of 152 metabolites were measured in up to 134 individuals with new-onset diabetes, prediabetes, or normal glucose tolerance. For 108 participants, the analysis was repeated with samples from 1 year before, when all had prediabetes. RESULTS The plasma concentrations of 14 proteins were higher in diabetes compared with normoglycemia in a population with prediabetes 1 year before, and they correlated with indices of insulin sensitivity. Higher levels of dicarbonyl/L-xylulose reductase and glutathione S-transferase A3 in the prediabetic state were associated with an increased risk of diabetes 1 year later. Pathway analysis pointed toward differences in immune response between diabetes and normoglycemia that were already recognizable in the prediabetic state 1 year prior at baseline. The area under the curve during OGTT of the concentrations of IDL particles, IDL apolipoprotein B, and IDL cholesterol was higher in new-onset diabetes compared with normoglycemia. The concentration of glutamate increased in prediabetes progressing to diabetes. CONCLUSIONS We identify new candidates associated with the progression of prediabetes to diabetes or its remission to normoglycemia. Pathways regulating the immune response are related to prediabetes trajectories.
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Affiliation(s)
- Marko Barovic
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Joke Johanna Hahn
- German Center for Diabetes Research, Neuherberg, Germany
- Paul Langerhans Institute Dresden, Helmholtz Center Munich, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Annett Heinrich
- German Center for Diabetes Research, Neuherberg, Germany
- Paul Langerhans Institute Dresden, Helmholtz Center Munich, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Trishla Adhikari
- German Center for Diabetes Research, Neuherberg, Germany
- Paul Langerhans Institute Dresden, Helmholtz Center Munich, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Peter Schwarz
- German Center for Diabetes Research, Neuherberg, Germany
- Paul Langerhans Institute Dresden, Helmholtz Center Munich, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Peter Mirtschink
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- National Center for Tumor Diseases Partner Site Dresden, Dresden, Germany
| | - Alexander Funk
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- National Center for Tumor Diseases Partner Site Dresden, Dresden, Germany
| | - Stefan Kabisch
- German Center for Diabetes Research, Neuherberg, Germany
- Department of Endocrinology and Metabolism, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Andreas F H Pfeiffer
- German Center for Diabetes Research, Neuherberg, Germany
- Department of Endocrinology and Metabolism, Charité-Universitätsmedizin Berlin, Berlin, Germany
- German Institute of Human Nutrition Potsdam-Rehbrücke, Brandenburg, Germany
| | - Matthias Blüher
- German Center for Diabetes Research, Neuherberg, Germany
- Department of Medicine, Endocrinology and Nephrology, Universität Leipzig, Leipzig, Germany
| | - Jochen Seissler
- German Center for Diabetes Research, Neuherberg, Germany
- Diabetes Center, Department of Medicine IV, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Norbert Stefan
- German Center for Diabetes Research, Neuherberg, Germany
- Division of Diabetology, Endocrinology and Nephrology, Department of Internal Medicine IV, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Robert Wagner
- German Center for Diabetes Research, Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andreas Fritsche
- German Center for Diabetes Research, Neuherberg, Germany
- Division of Diabetology, Endocrinology and Nephrology, Department of Internal Medicine IV, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Reiner Jumpertz von Schwartzenberg
- German Center for Diabetes Research, Neuherberg, Germany
- Division of Diabetology, Endocrinology and Nephrology, Department of Internal Medicine IV, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | | | - Hani Harb
- Institute for Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Christos S Mantzoros
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
- Section of Endocrinology, Boston VA Healthcare System, Harvard Medical School, Boston, MA
| | - Triantafyllos Chavakis
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- German Center for Diabetes Research, Neuherberg, Germany
- Paul Langerhans Institute Dresden, Helmholtz Center Munich, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- National Center for Tumor Diseases Partner Site Dresden, Dresden, Germany
| | - Annette Schürmann
- German Center for Diabetes Research, Neuherberg, Germany
- German Institute of Human Nutrition Potsdam-Rehbrücke, Brandenburg, Germany
| | - Andreas L Birkenfeld
- German Center for Diabetes Research, Neuherberg, Germany
- Division of Diabetology, Endocrinology and Nephrology, Department of Internal Medicine IV, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Michael Roden
- German Center for Diabetes Research, Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michele Solimena
- German Center for Diabetes Research, Neuherberg, Germany
- Paul Langerhans Institute Dresden (PLID), Helmholtz Munich, University Hospital and Faculty of Medicine, Molecular Diabetology, Technische Universität Dresden, Dresden, Germany
| | - Stefan R Bornstein
- German Center for Diabetes Research, Neuherberg, Germany
- Paul Langerhans Institute Dresden, Helmholtz Center Munich, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Diabetes and Nutritional Sciences, King's College London, London, U.K
| | - Nikolaos Perakakis
- German Center for Diabetes Research, Neuherberg, Germany
- Paul Langerhans Institute Dresden, Helmholtz Center Munich, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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Korvyakova Y, Azarova I, Klyosova E, Postnikova M, Makarenko V, Bushueva O, Solodilova M, Polonikov A. The link between the ANPEP gene and type 2 diabetes mellitus may be mediated by the disruption of glutathione metabolism and redox homeostasis. Gene 2025; 935:149050. [PMID: 39489227 DOI: 10.1016/j.gene.2024.149050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Revised: 10/02/2024] [Accepted: 10/23/2024] [Indexed: 11/05/2024]
Abstract
Aminopeptidase N (ANPEP), a membrane-associated ectoenzyme, has been identified as a susceptibility gene for type 2 diabetes (T2D) by genome-wide association and transcriptome studies; however, the mechanisms by which this gene contributes to disease pathogenesis remain unclear. The aim of this study was to determine the comprehensive contribution of ANPEP polymorphisms to T2D risk and annotate the underlying mechanisms. A total of 3206 unrelated individuals including 1579 T2D patients and 1627 controls were recruited for the study. Twenty-three common functional single nucleotide polymorphisms (SNP) of ANPEP were genotyped by the MassArray-4 system. Six polymorphisms, rs11073891, rs12898828, rs12148357, rs9920421, rs7111, and rs25653, were found to be associated with type 2 diabetes (Pperm ≤ 0.05). Common haplotype rs9920421G-rs4932143G-rs7111T was strongly associated with increased risk of T2D (Pperm = 5.9 × 10-12), whereas two rare haplotypes such as rs9920421G-rs4932143C-rs7111T (Pperm = 6.5 × 10-40) and rs12442778A-rs12898828A-rs6496608T-rs11073891C (Pperm = 1.0 × 10-7) possessed strong protection against disease. We identified 38 and 109 diplotypes associated with T2D risk in males and females, respectively (FDR ≤ 0.05). ANPEP polymorphisms showed associations with plasma levels of fasting blood glucose, aspartate aminotransferase, total protein and glutathione (P < 0.05), and several haplotypes were strongly associated with the levels of reactive oxygen species and uric acid (P < 0.0001). A deep literature analysis has facilitated the formulation of a hypothesis proposing that increased plasma levels of ANPEP as well as liver enzymes such as aspartate aminotransferase, alanine aminotransferase and gammaglutamyltransferase serve as an adaptive response directed towards the restoration of glutathione deficiency in diabetics by stimulating the production of amino acid precursors for glutathione biosynthesis.
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Affiliation(s)
- Yaroslava Korvyakova
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation; Research Centre for Medical Genetics, 1 Moskvorechie St., Moscow 115522, Russian Federation.
| | - Iuliia Azarova
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation; Department of Biological Chemistry, Kursk State Medical University, 3 Karl Marx Street, Kursk 305041, Russian Federation.
| | - Elena Klyosova
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation; Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, Kursk 305041, Russian Federation.
| | - Maria Postnikova
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation.
| | - Victor Makarenko
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation
| | - Olga Bushueva
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, Kursk 305041, Russian Federation; Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation.
| | - Maria Solodilova
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, Kursk 305041, Russian Federation.
| | - Alexey Polonikov
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, Kursk 305041, Russian Federation; Laboratory of Statistical Genetics and Bioinformatics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation.
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7
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Bandesh K, Motakis E, Nargund S, Kursawe R, Selvam V, Bhuiyan RM, Eryilmaz GN, Krishnan SN, Spracklen CN, Ucar D, Stitzel ML. Single-cell decoding of human islet cell type-specific alterations in type 2 diabetes reveals converging genetic- and state-driven β -cell gene expression defects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.17.633590. [PMID: 39896672 PMCID: PMC11785113 DOI: 10.1101/2025.01.17.633590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/04/2025]
Abstract
Pancreatic islets maintain glucose homeostasis through coordinated action of their constituent endocrine and affiliate cell types and are central to type 2 diabetes (T2D) genetics and pathophysiology. Our understanding of robust human islet cell type-specific alterations in T2D remains limited. Here, we report comprehensive single cell transcriptome profiling of 245,878 human islet cells from a 48-donor cohort spanning non-diabetic (ND), pre-diabetic (PD), and T2D states, identifying 14 distinct cell types detected in every donor from each glycemic state. Cohort analysis reveals ~25-30% loss of functional beta cell mass in T2D vs. ND or PD donors resulting from (1) reduced total beta cell numbers/proportions and (2) reciprocal loss of 'high function' and gain of senescent β -cell subpopulations. We identify in T2D β -cells 511 differentially expressed genes (DEGs), including new (66.5%) and validated genes (e.g., FXYD2, SLC2A2, SYT1), and significant neuronal transmission and vitamin A metabolism pathway alterations. Importantly, we demonstrate newly identified DEG roles in human β -cell viability and/or insulin secretion and link 47 DEGs to diabetes-relevant phenotypes in knockout mice, implicating them as potential causal islet dysfunction genes. Additionally, we nominate as candidate T2D causal genes and therapeutic targets 27 DEGs for which T2D genetic risk variants (GWAS SNPs) and pathophysiology (T2D vs. ND) exert concordant expression effects. We provide this freely accessible atlas for data exploration, analysis, and hypothesis testing. Together, this study provides new genomic resources for and insights into T2D pathophysiology and human islet dysfunction.
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Affiliation(s)
- Khushdeep Bandesh
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
| | - Efthymios Motakis
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
| | - Siddhi Nargund
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
| | - Romy Kursawe
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
| | - Vijay Selvam
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
| | - Redwan M Bhuiyan
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT 06032 USA
| | - Giray Naim Eryilmaz
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
| | - Sai Nivedita Krishnan
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT 06032 USA
| | - Cassandra N. Spracklen
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Duygu Ucar
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT 06032 USA
- Institute for Systems Genomics, UConn, Farmington, CT 06032 USA
| | - Michael L. Stitzel
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032 USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT 06032 USA
- Institute for Systems Genomics, UConn, Farmington, CT 06032 USA
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8
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López-Hernández Y, Andres-Lacueva C, Wishart DS, Torres-Calzada C, Martínez-Huélamo M, Almanza-Aguilera E, Zamora-Ros R. Prostate cancer risk biomarkers from large cohort and prospective metabolomics studies: A systematic review. Transl Oncol 2025; 51:102196. [PMID: 39580963 PMCID: PMC11625367 DOI: 10.1016/j.tranon.2024.102196] [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: 06/26/2024] [Revised: 10/07/2024] [Accepted: 11/07/2024] [Indexed: 11/26/2024] Open
Abstract
Prostate cancer (PCa) is one of the leading causes of cancer-related deaths among men. The heterogeneous nature of this disease presents challenges in its diagnosis, prognosis, and treatment. Numerous potential predictive, diagnostic, prognostic, and risk assessment biomarkers have been proposed through various population studies. However, to date, no metabolite biomarker has been approved or validated for the diagnosis, prognosis, or risk assessment of PCa. Recognizing that systematic reviews of case reports or heterogenous studies cannot reliably establish causality, this review analyzed 29 large prospective metabolomics studies that utilized harmonized criteria for patient selection, consistent methodologies for blood sample collection and storage, data analysis, and that are available in public repositories. By focusing on these large prospective studies, we identified 42 metabolites that were consistently replicated by different authors and across cohort studies. These metabolites have the potential to serve as PCa risk-assessment or predictive biomarkers. A discussion on their associations with dietary sources or dietary patterns is also provided. Further detailed exploration of the relationship with diet, supplement intake, nutrition patterns, contaminants, lifestyle factors, and pre-existing comorbidities that may predispose individuals to PCa is warranted for future research and validation.
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Affiliation(s)
- Yamilé López-Hernández
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada, T6G 2E9
| | - Cristina Andres-Lacueva
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Research Institute of Nutrition and Food Safety (INSA-UB), Faculty of Pharmacy and Food Science, University of Barcelona (UB), 08028, Barcelona, Spain; CIBER of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, 28029, Madrid, Spain.
| | - David S Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada, T6G 2E9
| | - Claudia Torres-Calzada
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada, T6G 2E9
| | - Miriam Martínez-Huélamo
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Research Institute of Nutrition and Food Safety (INSA-UB), Faculty of Pharmacy and Food Science, University of Barcelona (UB), 08028, Barcelona, Spain; CIBER of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Enrique Almanza-Aguilera
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), 08908, Barcelona, Spain
| | - Raul Zamora-Ros
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), 08908, Barcelona, Spain
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9
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Mlawer SJ, Pinto FR, Sikes KJ, Connizzo BK. Coordination of Glucose and Glutamine Metabolism in Tendon is Lost in Aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.19.629426. [PMID: 39763790 PMCID: PMC11702705 DOI: 10.1101/2024.12.19.629426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2025]
Abstract
Tendinopathy is an age-associated degenerative disease characterized by a loss in extracellular matrix (ECM). Since glucose and glutamine metabolism is critical to amino acid synthesis and known to be altered in aging, we sought to investigate if age-related changes in metabolism are linked to changes in ECM remodeling. We exposed young and aged tendon explants to various concentrations of glucose and glutamine to observe changes in metabolic processing (enzyme levels, gene expression, etc.) and matrix biosynthesis. Interestingly, we found that glutamine processing is affected by glucose levels, but this effect was lost with aging. ECM synthesis was altered in a protein-dependent manner by increased glucose and glutamine levels in young tendons. However, these changes were not conserved in aged tendons. Overall, our work suggests that glucose and glutamine metabolism is important for ECM homeostasis, and age-related changes in nutrient metabolism could be a key driver of tendon degeneration.
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Affiliation(s)
- Samuel J. Mlawer
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, United States
| | - Felicia R. Pinto
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, United States
| | - Katie J. Sikes
- Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, 80523, USA
| | - Brianne K. Connizzo
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, United States
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10
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Tan Y, Li M, Li H, Guo Y, Zhang B, Wu G, Li J, Zhang Q, Sun Y, Gao F, Yi W, Zhang X. Cardiac Urea Cycle Activation by Time-Restricted Feeding Protects Against Pressure Overload-Induced Heart Failure. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2407677. [PMID: 39467073 DOI: 10.1002/advs.202407677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Revised: 09/14/2024] [Indexed: 10/30/2024]
Abstract
Heart failure is a leading cause of mortality worldwide, necessitating the development of novel therapeutic and lifestyle interventions. Recent studies highlight a potential role of time-restricted feeding (TRF) in the prevention and treatment of cardiac diseases. Here, it is found that TRF protected against heart failure at different stages in mice. Metabolomic profiling revealed that TRF upregulated most circulating amino acids, and amino acid supplementation protected against heart failure. In contrast, TRF showed a mild effect on cardiac amino acid profile, but increased cardiac amino acid utilization and activated the cardiac urea cycle through upregulating argininosuccinate lyase (ASL) expression. Cardiac-specific ASL knockout abolished the cardioprotective effects afforded by TRF. Circulating amino acids also protected against heart failure through activation of the urea cycle. Additionally, TRF upregulated cardiac ASL expression through transcription factor Yin Yang 1, and urea cycle-derived NO contributes to TRF-afforded cardioprotection. Furthermore, arteriovenous gradients of circulating metabolites across the human hearts were measured, and found that amino acid utilization and urea cycle activity were impaired in patients with decreased cardiac function. These results suggest that TRF is a promising intervention for heart failure, and highlight the importance of urea cycle in regulation of cardiac function.
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Affiliation(s)
- Yanzhen Tan
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
- Department of Cardiovascular Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Min Li
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Han Li
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Yongzheng Guo
- Division of Cardiology, The First Affiliated Hospital, Cardiovascular Disease Laboratory, Chongqing Medical University, Chongqing, 400016, China
| | - Bing Zhang
- Department of Cardiovascular Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Guiling Wu
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Jia Li
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Qian Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Yang Sun
- Department of Geriatrics, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Wei Yi
- Department of Cardiovascular Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
- Department of Rehabilitation, Air Force Medical Center, Beijing, 100142, China
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11
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Naik AR, Save SN, Sahoo SS, Yadav SS, Kumar A, Chugh J, Sharma S. Metabolic perturbations associated with hIAPP-induced insulin resistance in skeletal muscles: Implications to the development of type 2 diabetes. Int J Biochem Cell Biol 2024; 176:106665. [PMID: 39322038 DOI: 10.1016/j.biocel.2024.106665] [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: 04/23/2024] [Revised: 09/16/2024] [Accepted: 09/18/2024] [Indexed: 09/27/2024]
Abstract
The human islet amyloid polypeptide (hIAPP) tends to misfold and self-assemble to form amyloid fibrils, which has been associated with the loss of function and viability of pancreatic β-cells in type 2 diabetes mellitus (T2DM). The role of hIAPP in the development of insulin resistance (a hallmark of T2DM) in skeletal muscles - the major sites for glucose utilization - needs further investigation. Even though, insulin-resistant conditions have been known to stimulate hIAPP aggregation, the events that lead to the development of insulin resistance due to hIAPP aggregation in skeletal muscles remain unidentified. Here, we have attempted to identify metabolic perturbations in L6 myotubes that were exposed to increasing concentrations of recombinant hIAPP for different time durations. It was observed that hIAPP exposure was associated with increased mitochondrial and cellular ROS levels, loss in mitochondrial membrane potential and viability of the myotubes. Metabolomic investigations of hIAPP-treated myotubes revealed significant perturbations in o-phosphocholine, sn-glycero-3-phosphocholine and dimethylamine levels (p < 0.05). Therefore, we anticipate that defects in glycerophospholipid metabolism and the associated oxidative stress and membrane damage may play key roles in the development of insulin resistance due to protein misfolding in skeletal muscles. In summary, the perturbed metabolites and their pathways have not only the potential to be used as early biomarkers to predict the onset of insulin resistance and T2DM but also as therapeutic targets for the effective management of the same.
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Affiliation(s)
- Arya R Naik
- Department of Biotechnology, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411007, India
| | - Shreyada N Save
- Department of Biotechnology, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411007, India
| | - Soumya S Sahoo
- Department of Chemistry, Indian Institute of Science Education and Research (IISER), Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Saurabh S Yadav
- Department of Biotechnology, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411007, India
| | - Ashutosh Kumar
- Department of Biosciences and Bioengineering, Indian institute of technology Bombay, Powai, Mumbai, Maharashtra 400076, India
| | - Jeetender Chugh
- Department of Chemistry, Indian Institute of Science Education and Research (IISER), Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Shilpy Sharma
- Department of Biotechnology, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411007, India.
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12
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Palazzo E, Marabese I, Ricciardi F, Guida F, Luongo L, Maione S. The influence of glutamate receptors on insulin release and diabetic neuropathy. Pharmacol Ther 2024; 263:108724. [PMID: 39299577 DOI: 10.1016/j.pharmthera.2024.108724] [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: 03/07/2024] [Revised: 09/09/2024] [Accepted: 09/16/2024] [Indexed: 09/22/2024]
Abstract
Diabetes causes macrovascular and microvascular complications such as peripheral neuropathy. Glutamate regulates insulin secretion in pancreatic β-cells, and its increased activity in the central nervous system is associated with peripheral neuropathy in animal models of diabetes. One strategy to modulate glutamatergic activity consists in the pharmacological manipulation of metabotropic glutamate receptors (mGluRs), which, compared to the ionotropic receptors, allow for a fine-tuning of neurotransmission that is compatible with therapeutic interventions. mGluRs are a family of eight G-protein coupled receptors classified into three groups (I-III) based on sequence homology, transduction mechanisms, and pharmacology. Activation of group II and III or inhibition of group I represents a strategy to counteract the glutamatergic hyperactivity associated with diabetic neuropathy. In this review article, we will discuss the role of glutamate receptors in the release of insulin and the development/treatment of diabetic neuropathy, with particular emphasis on their manipulation to prevent the glutamatergic hyperactivity associated with diabetic neuropathy.
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Affiliation(s)
- Enza Palazzo
- Department of Experimental Medicine, Pharmacology Division, University of Campania "L. Vanvitelli", via Costantinopoli 16, 80138 Naples, Italy.
| | - Ida Marabese
- Department of Experimental Medicine, Pharmacology Division, University of Campania "L. Vanvitelli", via Costantinopoli 16, 80138 Naples, Italy
| | - Federica Ricciardi
- Department of Experimental Medicine, Pharmacology Division, University of Campania "L. Vanvitelli", via Costantinopoli 16, 80138 Naples, Italy
| | - Francesca Guida
- Department of Experimental Medicine, Pharmacology Division, University of Campania "L. Vanvitelli", via Costantinopoli 16, 80138 Naples, Italy
| | - Livio Luongo
- Department of Experimental Medicine, Pharmacology Division, University of Campania "L. Vanvitelli", via Costantinopoli 16, 80138 Naples, Italy
| | - Sabatino Maione
- Department of Experimental Medicine, Pharmacology Division, University of Campania "L. Vanvitelli", via Costantinopoli 16, 80138 Naples, Italy
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13
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Gan Z, Guo Y, Zhao M, Ye Y, Liao Y, Liu B, Yin J, Zhou X, Yan Y, Yin Y, Ren W. Excitatory amino acid transporter supports inflammatory macrophage responses. Sci Bull (Beijing) 2024; 69:2405-2419. [PMID: 38614854 DOI: 10.1016/j.scib.2024.03.055] [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: 12/20/2023] [Revised: 01/28/2024] [Accepted: 03/25/2024] [Indexed: 04/15/2024]
Abstract
Excitatory amino acid transporters (EAATs) are responsible for excitatory amino acid transportation and are associated with auto-immune diseases in the central nervous system and peripheral tissues. However, the subcellular location and function of EAAT2 in macrophages are still obscure. In this study, we demonstrated that LPS stimulation increases expression of EAAT2 (coded by Slc1a2) via NF-κB signaling. EAAT2 is necessary for inflammatory macrophage polarization through sustaining mTORC1 activation. Mechanistically, lysosomal EAAT2 mediates lysosomal glutamate and aspartate efflux to maintain V-ATPase activation, which sustains macropinocytosis and mTORC1. We also found that mice with myeloid depletion of Slc1a2 show alleviated inflammatory responses in LPS-induced systemic inflammation and high-fat diet induced obesity. Notably, patients with type II diabetes (T2D) have a higher level of expression of lysosomal EAAT2 and activation of mTORC1 in blood macrophages. Taken together, our study links the subcellular location of amino acid transporters with the fate decision of immune cells, which provides potential therapeutic targets for the treatment of inflammatory diseases.
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Affiliation(s)
- Zhending Gan
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Laboratory of Lingnan Modern Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Yan Guo
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Laboratory of Lingnan Modern Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Muyang Zhao
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Laboratory of Lingnan Modern Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Yuyi Ye
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Laboratory of Lingnan Modern Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Yuexia Liao
- School of Nursing & School of Public Health, Yangzhou University, Yangzhou 225009, China
| | - Bingnan Liu
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Laboratory of Lingnan Modern Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Jie Yin
- College of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China
| | - Xihong Zhou
- Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
| | - Yuqi Yan
- Department of Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yulong Yin
- Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
| | - Wenkai Ren
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Laboratory of Lingnan Modern Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, China.
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14
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Galli A, Moretti S, Dule N, Di Cairano ES, Castagna M, Marciani P, Battaglia C, Bertuzzi F, Fiorina P, Pastore I, La Rosa S, Davalli A, Folli F, Perego C. Hyperglycemia impairs EAAT2 glutamate transporter trafficking and glutamate clearance in islets of Langerhans: implications for type 2 diabetes pathogenesis and treatment. Am J Physiol Endocrinol Metab 2024; 327:E27-E41. [PMID: 38690938 PMCID: PMC11390119 DOI: 10.1152/ajpendo.00069.2024] [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: 02/07/2024] [Revised: 04/18/2024] [Accepted: 04/21/2024] [Indexed: 05/03/2024]
Abstract
Pancreatic endocrine cells employ a sophisticated system of paracrine and autocrine signals to synchronize their activities, including glutamate, which controls hormone release and β-cell viability by acting on glutamate receptors expressed by endocrine cells. We here investigate whether alteration of the excitatory amino acid transporter 2 (EAAT2), the major glutamate clearance system in the islet, may occur in type 2 diabetes mellitus and contribute to β-cell dysfunction. Increased EAAT2 intracellular localization was evident in islets of Langerhans from T2DM subjects as compared with healthy control subjects, despite similar expression levels. Chronic treatment of islets from healthy donors with high-glucose concentrations led to the transporter internalization in vesicular compartments and reduced [H3]-d-glutamate uptake (65 ± 5% inhibition), phenocopying the findings in T2DM pancreatic sections. The transporter relocalization was associated with decreased Akt phosphorylation protein levels, suggesting an involvement of the phosphoinositide 3-kinase (PI3K)/Akt pathway in the process. In line with this, PI3K inhibition by a 100-µM LY294002 treatment in human and clonal β-cells caused the transporter relocalization in intracellular compartments and significantly reduced the glutamate uptake compared to control conditions, suggesting that hyperglycemia changes the trafficking of the transporter to the plasma membrane. Upregulation of the glutamate transporter upon treatment with the antibiotic ceftriaxone rescued hyperglycemia-induced β-cells dysfunction and death. Our data underscore the significance of EAAT2 in regulating islet physiology and provide a rationale for potential therapeutic targeting of this transporter to preserve β-cell survival and function in diabetes.NEW & NOTEWORTHY The glutamate transporter SLC1A2/excitatory amino acid transporter 2 (EAAT2) is expressed on the plasma membrane of pancreatic β-cells and controls islet glutamate clearance and β-cells survival. We found that the EAAT2 membrane expression is lost in the islets of Langerhans from type 2 diabetes mellitus (T2DM) patients due to hyperglycemia-induced downregulation of the phosphoinositide 3-kinase/Akt pathway and modification of its intracellular trafficking. Pharmacological rescue of EAAT2 expression prevents β-cell dysfunction and death, suggesting EAAT2 as a new potential target of intervention in T2DM.
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Affiliation(s)
- Alessandra Galli
- Laboratory of Molecular and Cellular Physiology, Department of Excellence of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Stefania Moretti
- Laboratory of Molecular and Cellular Physiology, Department of Excellence of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Nevia Dule
- Laboratory of Molecular and Cellular Physiology, Department of Excellence of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Eliana Sara Di Cairano
- Laboratory of Molecular and Cellular Physiology, Department of Excellence of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Michela Castagna
- Laboratory of Molecular and Cellular Physiology, Department of Excellence of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Paola Marciani
- Laboratory of Molecular and Cellular Physiology, Department of Excellence of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Cristina Battaglia
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy
| | | | - Paolo Fiorina
- Department of Biomedical and Clinical Sciences "L. Sacco,"Università degli Studi di Milano, Milan, Italy
- Endocrinology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy
| | - Ida Pastore
- Endocrinology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy
| | - Stefano La Rosa
- Unit of Pathology, Department of Oncology, ASST Sette Laghi, Varese, Italy
- Department of Medicine and Technological Innovation, Università degli Studi dell'Insubria, Varese, Italy
| | - Alberto Davalli
- Diabetes and Endocrinology Unit, Department of Internal Medicine, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Franco Folli
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy
| | - Carla Perego
- Laboratory of Molecular and Cellular Physiology, Department of Excellence of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
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15
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Lecoutre S, Maqdasy S, Rizo-Roca D, Renzi G, Vlassakev I, Alaeddine LM, Higos R, Jalkanen J, Zhong J, Zareifi DS, Frendo-Cumbo S, Massier L, Hodek O, Juvany M, Moritz T, de Castro Barbosa T, Omar-Hmeadi M, López-Yus M, Merabtene F, Abatan JB, Marcelin G, El Hachem EJ, Rouault C, Bergo MO, Petrus P, Zierath JR, Clément K, Krook A, Mejhert N, Rydén M. Reduced adipocyte glutaminase activity promotes energy expenditure and metabolic health. Nat Metab 2024; 6:1329-1346. [PMID: 39009762 PMCID: PMC11272588 DOI: 10.1038/s42255-024-01083-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 06/14/2024] [Indexed: 07/17/2024]
Abstract
Glutamine and glutamate are interconverted by several enzymes and alterations in this metabolic cycle are linked to cardiometabolic traits. Herein, we show that obesity-associated insulin resistance is characterized by decreased plasma and white adipose tissue glutamine-to-glutamate ratios. We couple these stoichiometric changes to perturbed fat cell glutaminase and glutamine synthase messenger RNA and protein abundance, which together promote glutaminolysis. In human white adipocytes, reductions in glutaminase activity promote aerobic glycolysis and mitochondrial oxidative capacity via increases in hypoxia-inducible factor 1α abundance, lactate levels and p38 mitogen-activated protein kinase signalling. Systemic glutaminase inhibition in male and female mice, or genetically in adipocytes of male mice, triggers the activation of thermogenic gene programs in inguinal adipocytes. Consequently, the knockout mice display higher energy expenditure and improved glucose tolerance compared to control littermates, even under high-fat diet conditions. Altogether, our findings highlight white adipocyte glutamine turnover as an important determinant of energy expenditure and metabolic health.
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Affiliation(s)
- Simon Lecoutre
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
- Nutrition and Obesities: Systemic Approaches Research Group, NutriOmics, Sorbonne Université, INSERM, Paris, France
| | - Salwan Maqdasy
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - David Rizo-Roca
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Gianluca Renzi
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Ivan Vlassakev
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Lynn M Alaeddine
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Romane Higos
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Jutta Jalkanen
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Jiawei Zhong
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Danae S Zareifi
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Scott Frendo-Cumbo
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Lucas Massier
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Ondrej Hodek
- Swedish Metabolomics Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Marta Juvany
- Swedish Metabolomics Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Thomas Moritz
- Swedish Metabolomics Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Umeå, Sweden
- The Novo Nordisk Foundation Centre for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thais de Castro Barbosa
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Muhmmad Omar-Hmeadi
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Marta López-Yus
- Adipocyte and Fat Biology Laboratory (AdipoFat), Translational Research Unit, University Hospital Miguel Servet, Zaragoza, Spain
- Instituto Aragonés de Ciencias de La Salud (IACS), Zaragoza, Spain
- Instituto de Investigación Sanitaria (IIS)-Aragón, Zaragoza, Spain
| | - Fatiha Merabtene
- Nutrition and Obesities: Systemic Approaches Research Group, NutriOmics, Sorbonne Université, INSERM, Paris, France
| | - Jimon Boniface Abatan
- Nutrition and Obesities: Systemic Approaches Research Group, NutriOmics, Sorbonne Université, INSERM, Paris, France
| | - Geneviève Marcelin
- Nutrition and Obesities: Systemic Approaches Research Group, NutriOmics, Sorbonne Université, INSERM, Paris, France
| | - Elie-Julien El Hachem
- Nutrition and Obesities: Systemic Approaches Research Group, NutriOmics, Sorbonne Université, INSERM, Paris, France
| | - Christine Rouault
- Nutrition and Obesities: Systemic Approaches Research Group, NutriOmics, Sorbonne Université, INSERM, Paris, France
| | - Martin O Bergo
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
| | - Paul Petrus
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Juleen R Zierath
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Karine Clément
- Nutrition and Obesities: Systemic Approaches Research Group, NutriOmics, Sorbonne Université, INSERM, Paris, France
- Nutrition Department, Assistance Publique Hôpitaux de Paris, CRNH Ile-de-France, Pitié-Salpêtrière Hospital, Paris, France
| | - Anna Krook
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Niklas Mejhert
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden.
| | - Mikael Rydén
- Department of Medicine (Huddinge), Karolinska Institutet, ME Endokrinologi, Karolinska University Hospital Huddinge, Huddinge, Sweden.
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16
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Haley JA, Guertin DA. Adipose glutaminolysis resurfaces in metabolic disease. Nat Metab 2024; 6:1200-1201. [PMID: 39009761 DOI: 10.1038/s42255-024-01084-x] [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: 07/17/2024]
Affiliation(s)
- John A Haley
- University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - David A Guertin
- University of Massachusetts Chan Medical School, Worcester, MA, USA.
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17
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Campos JDO, Oliveira TLPSDA, Vitalis O, Pereira JG, Nogueira IDCR, Santos GCJ, Chikh K, Leandro CG, da Costa-Silva JH, Pirola L. Association between Childhood Overweight and Altered Concentrations of Circulating Amino Acids. Nutrients 2024; 16:1843. [PMID: 38931197 PMCID: PMC11206240 DOI: 10.3390/nu16121843] [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: 05/24/2024] [Revised: 06/06/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024] Open
Abstract
(1) Background: Dysregulated serum amino acids (AA) are known to be associated with obesity and risk of Type 2 Diabetes (T2D) in adults, and recent studies support the same notion in the pubertal age. It is, however, unknown whether childhood overweight may already display alterations of circulating AA. (2) Methods: We used liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS)-targeted metabolomics to determine plasma concentrations of AA and AA-related molecules in 36 children aged 7-12 years with normal weight or overweight. Clinical and anthropometric parameters were measured. (3) Results: Overweight in children is associated with an altered AA profile, with increased branched-chain amino acids (BCAA) and decreased glycine levels, with no clinically manifested metabolic conditions. Moreover, z-BMI was positively and negatively correlated with BCAA and glycine levels, respectively, even after adjustment for age and gender. We also found a correlation between the AA profile and clinical parameters such as lipids profile and glycemia. (4) Conclusions: A pattern of low glycine, and increased BCAA is correlated to z-BMI, total cholesterol, and triglycerides in overweight but otherwise healthy children. Our data suggest that, in childhood overweight, AA disturbances may precede other clinical parameters, thus providing an early indicator for the later development of metabolic disease.
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Affiliation(s)
- Jéssica de Oliveira Campos
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (J.d.O.C.); (T.L.P.S.d.A.O.); (J.G.P.); (C.G.L.); (J.H.d.C.-S.)
- Laboratory of Physical Evaluation and Signal Processing, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (I.d.C.R.N.); (G.C.J.S.)
- INSERM Unit 1060, CarMeN Laboratory, Lyon Civil Hospitals, Claude Bernard Lyon1 University, 69310 Pierre Bénite, France; (O.V.); (K.C.)
| | - Tafnes Laís Pereira Santos de Almeida Oliveira
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (J.d.O.C.); (T.L.P.S.d.A.O.); (J.G.P.); (C.G.L.); (J.H.d.C.-S.)
- Laboratory of Physical Evaluation and Signal Processing, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (I.d.C.R.N.); (G.C.J.S.)
| | - Oriane Vitalis
- INSERM Unit 1060, CarMeN Laboratory, Lyon Civil Hospitals, Claude Bernard Lyon1 University, 69310 Pierre Bénite, France; (O.V.); (K.C.)
| | - Jéssica Gonzaga Pereira
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (J.d.O.C.); (T.L.P.S.d.A.O.); (J.G.P.); (C.G.L.); (J.H.d.C.-S.)
- Laboratory of Physical Evaluation and Signal Processing, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (I.d.C.R.N.); (G.C.J.S.)
| | - Isabella da Costa Ribeiro Nogueira
- Laboratory of Physical Evaluation and Signal Processing, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (I.d.C.R.N.); (G.C.J.S.)
| | - Gabriela Carvalho Jurema Santos
- Laboratory of Physical Evaluation and Signal Processing, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (I.d.C.R.N.); (G.C.J.S.)
| | - Karim Chikh
- INSERM Unit 1060, CarMeN Laboratory, Lyon Civil Hospitals, Claude Bernard Lyon1 University, 69310 Pierre Bénite, France; (O.V.); (K.C.)
| | - Carol Gois Leandro
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (J.d.O.C.); (T.L.P.S.d.A.O.); (J.G.P.); (C.G.L.); (J.H.d.C.-S.)
- Laboratory of Physical Evaluation and Signal Processing, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (I.d.C.R.N.); (G.C.J.S.)
| | - João Henrique da Costa-Silva
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (J.d.O.C.); (T.L.P.S.d.A.O.); (J.G.P.); (C.G.L.); (J.H.d.C.-S.)
- Laboratory of Physical Evaluation and Signal Processing, Academic Center of Vitória, Universidade Federal de Pernambuco, UFPE, Vitória de Santo Antão 55608-680, PE, Brazil; (I.d.C.R.N.); (G.C.J.S.)
| | - Luciano Pirola
- INSERM Unit 1060, CarMeN Laboratory, Lyon Civil Hospitals, Claude Bernard Lyon1 University, 69310 Pierre Bénite, France; (O.V.); (K.C.)
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18
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He Q, Li J, Tao C, Zeng C, Liu C, Zheng Z, Mou S, Liu W, Zhang B, Yu X, Zhai Y, Wang J, Zhang Q, Zhang Y, Zhang D, Zhao J, Ge P. High glutamine increases stroke risk by inducing the endothelial-to-mesenchymal transition in moyamoya disease. MedComm (Beijing) 2024; 5:e525. [PMID: 38628905 PMCID: PMC11018113 DOI: 10.1002/mco2.525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 02/04/2024] [Accepted: 02/26/2024] [Indexed: 04/19/2024] Open
Abstract
At present, there is limited research on the mechanisms underlying moyamoya disease (MMD). Herein, we aimed to determine the role of glutamine in MMD pathogenesis, and 360 adult patients were prospectively enrolled. Human brain microvascular endothelial cells (HBMECs) were subjected to Integrin Subunit Beta 4 (ITGB4) overexpression or knockdown and atorvastatin. We assessed factors associated with various signaling pathways in the context of the endothelial-to-mesenchymal transition (EndMT), and the expression level of related proteins was validated in the superficial temporal arteries of patients. We found glutamine levels were positively associated with a greater risk of stroke (OR = 1.599, p = 0.022). After treatment with glutamine, HBMECs exhibited enhanced proliferation, migration, and EndMT, all reversed by ITGB4 knockdown. In ITGB4-transfected HBMECs, the MAPK-ERK-TGF-β/BMP pathway was activated, with Smad4 knockdown reversing the EndMT. Furthermore, atorvastatin suppressed the EndMT by inhibiting Smad1/5 phosphorylation and promoting Smad4 ubiquitination in ITGB4-transfected HBMECs. We also found the protein level of ITGB4 was upregulated in the superficial temporal arteries of patients with MMD. In conclusion, our study suggests that glutamine may be an independent risk factor for hemorrhage or infarction in patients with MMD and targeting ITGB4 could potentially be therapeutic approaches for MMD.
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Affiliation(s)
- Qiheng He
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Junsheng Li
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Chuming Tao
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Chaofan Zeng
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Chenglong Liu
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Zhiyao Zheng
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- Research Unit of Accurate Diagnosis, Treatment, and Translational Medicine of Brain TumorsChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Department of NeurosurgeryPeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Siqi Mou
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Wei Liu
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Bojian Zhang
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Xiaofan Yu
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Yuanren Zhai
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Jia Wang
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- 3D Printing Center in Clinical NeuroscienceChina National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Qian Zhang
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Yan Zhang
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Dong Zhang
- Department of NeurosurgeryBeijing HospitalBeijingChina
| | - Jizong Zhao
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- 3D Printing Center in Clinical NeuroscienceChina National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Peicong Ge
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
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19
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Febra C, Saraiva J, Vaz F, Macedo J, Al-Hroub HM, Semreen MH, Maio R, Gil V, Soares N, Penque D. Acute venous thromboembolism plasma and red blood cell metabolomic profiling reveals potential new early diagnostic biomarkers: observational clinical study. J Transl Med 2024; 22:200. [PMID: 38402378 PMCID: PMC10894498 DOI: 10.1186/s12967-024-04883-8] [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: 10/28/2023] [Accepted: 01/10/2024] [Indexed: 02/26/2024] Open
Abstract
BACKGROUND Venous thromboembolism (VTE) is a leading cause of cardiovascular mortality. The diagnosis of acute VTE is based on complex imaging exams due to the lack of biomarkers. Recent multi-omics based research has contributed to the development of novel biomarkers in cardiovascular diseases. Our aim was to determine whether patients with acute VTE have differences in the metabolomic profile compared to non-acute VTE. METHODS This observational trial included 62 patients with clinical suspicion of acute deep vein thrombosis or pulmonary embolism, admitted to the emergency room. There were 50 patients diagnosed with acute VTE and 12 with non-acute VTE conditions and no significant differences were found between the two groups for clinical and demographic characteristics. Metabolomics assays identified and quantified a final number of 91 metabolites in plasma and 55 metabolites in red blood cells (RBCs). Plasma from acute VTE patients expressed tendency to a specific metabolomic signature, with univariate analyses revealing 23 significantly different molecules between acute VTE patients and controls (p < 0.05). The most relevant metabolic pathway with the strongest impact on the acute VTE phenotype was D-glutamine and D-glutamate (p = 0.001, false discovery rate = 0.06). RBCs revealed a specific metabolomic signature in patients with a confirmed diagnosis of DVT or PE that distinguished them from other acutely diseased patients, represented by 20 significantly higher metabolites and four lower metabolites. Three of those metabolites revealed high performant ROC curves, including adenosine 3',5'-diphosphate (AUC 0.983), glutathione (AUC 0.923), and adenine (AUC 0.91). Overall, the metabolic pathway most impacting to the differences observed in the RBCs was the purine metabolism (p = 0.000354, false discovery rate = 0.68). CONCLUSIONS Our findings show that metabolite differences exist between acute VTE and nonacute VTE patients admitted to the ER in the early phases. Three potential biomarkers obtained from RBCs showed high performance for acute VTE diagnosis. Further studies should investigate accessible laboratory methods for the future daily practice usefulness of these metabolites for the early diagnosis of acute VTE in the ER.
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Affiliation(s)
- Cláudia Febra
- Department of Intensive Care, Hospital da Luz Lisboa, Lisbon, Portugal.
- Faculty of Medicine, University of Porto, Porto, Portugal.
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal.
| | - Joana Saraiva
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal
- Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal
- NOVA School of Science and Technology, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Fátima Vaz
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal
- Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal
| | - João Macedo
- NOVA School of Science and Technology, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Hamza Mohammad Al-Hroub
- Department of Medical Chemistry, College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Mohammad Harb Semreen
- Department of Medical Chemistry, College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Rui Maio
- Department of General Surgery, Hospital da Luz Lisboa, Lisbon, Portugal
| | - Vitor Gil
- Faculty of Medicine, University of Porto, Porto, Portugal
- Center of Cardiovascular Risk and Thrombosis, Hospital da Luz Torres de Lisboa, Lisbon, Portugal
| | - Nelson Soares
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal.
- NOVA School of Science and Technology, Universidade Nova de Lisboa, Lisbon, Portugal.
- Department of Medical Chemistry, College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates.
| | - Deborah Penque
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal.
- Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal.
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20
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Semnani-Azad Z, Toledo E, Babio N, Ruiz-Canela M, Wittenbecher C, Razquin C, Wang F, Dennis C, Deik A, Clish CB, Corella D, Fitó M, Estruch R, Arós F, Ros E, García-Gavilan J, Liang L, Salas-Salvadó J, Martínez-González MA, Hu FB, Guasch-Ferré M. Plasma metabolite predictors of metabolic syndrome incidence and reversion. Metabolism 2024; 151:155742. [PMID: 38007148 PMCID: PMC10872312 DOI: 10.1016/j.metabol.2023.155742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 11/19/2023] [Accepted: 11/19/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND Metabolic Syndrome (MetS) is a progressive pathophysiological state defined by a cluster of cardiometabolic traits. However, little is known about metabolites that may be predictors of MetS incidence or reversion. Our objective was to identify plasma metabolites associated with MetS incidence or MetS reversion. METHODS The study included 1468 participants without cardiovascular disease (CVD) but at high CVD risk at enrollment from two case-cohort studies nested within the PREvención con DIeta MEDiterránea (PREDIMED) study with baseline metabolomics data. MetS was defined in accordance with the harmonized International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute criteria, which include meeting 3 or more thresholds for waist circumference, triglyceride, HDL cholesterol, blood pressure, and fasting blood glucose. MetS incidence was defined by not having MetS at baseline but meeting the MetS criteria at a follow-up visit. MetS reversion was defined by MetS at baseline but not meeting MetS criteria at a follow-up visit. Plasma metabolome was profiled by LC-MS. Multivariable-adjusted Cox regression models and elastic net regularized regressions were used to assess the association of 385 annotated metabolites with MetS incidence and MetS reversion after adjusting for potential risk factors. RESULTS Of the 603 participants without baseline MetS, 298 developed MetS over the median 4.8-year follow-up. Of the 865 participants with baseline MetS, 285 experienced MetS reversion. A total of 103 and 88 individual metabolites were associated with MetS incidence and MetS reversion, respectively, after adjusting for confounders and false discovery rate correction. A metabolomic signature comprised of 77 metabolites was robustly associated with MetS incidence (HR: 1.56 (95 % CI: 1.33-1.83)), and a metabolomic signature of 83 metabolites associated with MetS reversion (HR: 1.44 (95 % CI: 1.25-1.67)), both p < 0.001. The MetS incidence and reversion signatures included several lipids (mainly glycerolipids and glycerophospholipids) and branched-chain amino acids. CONCLUSION We identified unique metabolomic signatures, primarily comprised of lipids (including glycolipids and glycerophospholipids) and branched-chain amino acids robustly associated with MetS incidence; and several amino acids and glycerophospholipids associated with MetS reversion. These signatures provide novel insights on potential distinct mechanisms underlying the conditions leading to the incidence or reversion of MetS.
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Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Estefanía Toledo
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Nancy Babio
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere i Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain.
| | - Miguel Ruiz-Canela
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Clemens Wittenbecher
- Division of Food and Nutrition Sciences, Department of Biology, Chalmers University of Technology, Gothenburg, Sweden.
| | - Cristina Razquin
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Fenglei Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Courtney Dennis
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Amy Deik
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Clary B Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Dolores Corella
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain.
| | - Montserrat Fitó
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; IMIM Hospital del Mar Medical Research Institute, Grup de Risc Cardiovascular i Nutrició, Barcelona, Spain.
| | - Ramon Estruch
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.
| | - Fernando Arós
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, Vitoria-Gasteiz, Spain; University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain.
| | - Emilio Ros
- Lipid Clinic, Department of Endocrinology and Nutrition, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.
| | - Jesús García-Gavilan
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain.
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Jordi Salas-Salvadó
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere i Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain.
| | - Miguel A Martínez-González
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Public Health and Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), University of Copenhagen, Copenhagen, Denmark.
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21
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Hristov M, Nankova A, Andreeva-Gateva P. Alterations of the glutamatergic system in diabetes mellitus. Metab Brain Dis 2024; 39:321-333. [PMID: 37747631 DOI: 10.1007/s11011-023-01299-z] [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: 05/16/2023] [Accepted: 09/17/2023] [Indexed: 09/26/2023]
Abstract
Diabetes mellitus (DM) is a chronic disease characterized by elevated blood glucose levels caused by a lack of insulin production (type 1 diabetes) or insulin resistance (type 2 diabetes). It is well known that DM is associated with cognitive deficits and metabolic and neurophysiological changes in the brain. Glutamate is the main excitatory neurotransmitter in the central nervous system that plays a key role in synaptic plasticity, learning, and memory processes. An increasing number of studies have suggested that abnormal activity of the glutamatergic system is implicated in the pathophysiology of DM. Dysfunction of glutamatergic neurotransmission in the central nervous system can provide an important neurobiological substrate for many disorders. Magnetic resonance spectroscopy (MRS) is a non-invasive technique that allows a better understanding of the central nervous system factors by measuring in vivo the concentrations of brain metabolites within the area of interest. Here, we briefly review the MRS studies that have examined glutamate levels in the brain of patients with DM. The present article also summarizes the available data on abnormalities in glutamatergic neurotransmission observed in different animal models of DM. In addition, the role of gut microbiota in the development of glutamatergic alterations in DM is addressed. We speculate that therapeutic strategies targeting the glutamatergic system may be beneficial in the treatment of central nervous system-related changes in diabetic patients.
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Affiliation(s)
- Milen Hristov
- Department of Pharmacology and Toxicology, Faculty of Medicine, Medical University of Sofia, 2 "Zdrave" St, Sofia, 1431, Bulgaria.
| | - Anelia Nankova
- Department of Endocrinology, Faculty of Medicine, Medical University of Sofia, Sofia, 1431, Bulgaria
| | - Pavlina Andreeva-Gateva
- Department of Pharmacology and Toxicology, Faculty of Medicine, Medical University of Sofia, 2 "Zdrave" St, Sofia, 1431, Bulgaria
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22
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Chen Z, Hu Y, Hu FB, Manson JE, Rimm EB, Doria A, Sun Q. Dietary Glutamine and Glutamate in Relation to Cardiovascular Disease Incidence and Mortality in the United States Men and Women with Diabetes Mellitus. J Nutr 2023; 153:3247-3258. [PMID: 37660951 PMCID: PMC10687617 DOI: 10.1016/j.tjnut.2023.08.031] [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: 03/27/2023] [Revised: 08/03/2023] [Accepted: 08/24/2023] [Indexed: 09/05/2023] Open
Abstract
BACKGROUND Evidence regarding the potential health effects of dietary amino acids glutamine and glutamate among individuals with type 2 diabetes (T2D) is limited. OBJECTIVES The aim was to examine dietary glutamine and glutamate in relation to subsequent risk of cardiovascular disease (CVD) and mortality among individuals with T2D. METHODS We prospectively followed 15,040 men and women with T2D at baseline or diagnosed during follow-up (Nurses' Health Study: 1980-2014 and Health Professionals Follow-Up Study: 1986-2018). Diet was repeatedly assessed using validated food frequency questionnaires every 2-4 y. Associations of energy-adjusted glutamine and glutamate intake, as well as their ratio, with CVD risk and mortality, were assessed using Cox proportional-hazards models with adjustments for demographics, dietary and lifestyle factors, and medical history. RESULTS During 196,955 and 225,371 person-years of follow-up in participants with T2D, there were 2927 incident CVD cases and 4898 deaths, respectively. Higher intake of glutamine was associated with lower risk of CVD incidence, CVD mortality, and total mortality: comparing extreme quintiles, the hazard ratios (HRs) (95% confidence intervals [CIs]) were 0.88 (0.77, 0.99), 0.78 (0.65, 0.92), and 0.84 (0.76, 0.92), respectively (all P-trend < 0.05). In contrast, higher intake of glutamate was associated with a higher risk of CVD incidence, CVD mortality, and total mortality; the HRs were 1.30 (1.15, 1.46), 1.46 (1.24, 1.72), and 1.20 (1.09, 1.32), respectively (all P-trend < 0.05). Furthermore, comparing extreme quintiles, a higher dietary glutamine-to-glutamate ratio was associated with a lower risk of CVD incidence (0.84 [0.75, 0.95]), CVD mortality (0.66 [0.57, 0.77]), and total mortality (0.82 [0.75, 0.90]). In addition, compared with participants with stable or decreased consumption of glutamine-to-glutamate ratio from prediabetes to postdiabetes diagnosis, those who increased the ratio had a 17% (5%, 27%) lower CVD mortality. CONCLUSIONS In adults with T2D, dietary glutamine was associated with a lower risk of CVD incidence and mortality, whereas the opposite was observed for glutamate intake.
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Affiliation(s)
- Zhangling Chen
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Cardiovascular Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Yang Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - JoAnn E Manson
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Eric B Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Alessandro Doria
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Joslin Diabetes Center, Boston, MA, United States
| | - Qi Sun
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Joslin Diabetes Center, Boston, MA, United States.
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23
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Bodhini D, Morton RW, Santhakumar V, Nakabuye M, Pomares-Millan H, Clemmensen C, Fitzpatrick SL, Guasch-Ferre M, Pankow JS, Ried-Larsen M, Franks PW, Tobias DK, Merino J, Mohan V, Loos RJF. Impact of individual and environmental factors on dietary or lifestyle interventions to prevent type 2 diabetes development: a systematic review. COMMUNICATIONS MEDICINE 2023; 3:133. [PMID: 37794109 PMCID: PMC10551013 DOI: 10.1038/s43856-023-00363-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 09/18/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular factors modify the efficacy of dietary or lifestyle interventions to prevent T2D. METHODS We searched MEDLINE, Embase, and Cochrane databases for studies reporting on the effect of a lifestyle, dietary pattern, or dietary supplement interventions on the incidence of T2D and reporting the results stratified by any effect modifier. We extracted relevant statistical findings and qualitatively synthesized the evidence for each modifier based on the direction of findings reported in available studies. We used the Diabetes Canada Clinical Practice Scale to assess the certainty of the evidence for a given effect modifier. RESULTS The 81 publications that met our criteria for inclusion are from 33 unique trials. The evidence is low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. CONCLUSIONS We report evidence, albeit low certainty, that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.
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Affiliation(s)
| | - Robert W Morton
- Department of Pathology & Molecular Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton, ON, Canada
- Department of Translational Medicine, Medical Science, Novo Nordisk Foundation, Tuborg Havnevej 19, 2900, Hellerup, Denmark
| | - Vanessa Santhakumar
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Mariam Nakabuye
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hugo Pomares-Millan
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Christoffer Clemmensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stephanie L Fitzpatrick
- Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Marta Guasch-Ferre
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Mathias Ried-Larsen
- Centre for Physical Activity Research, Rigshospitalet, Copenhagen, Denmark
- Institute for Sports and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Paul W Franks
- Department of Translational Medicine, Medical Science, Novo Nordisk Foundation, Tuborg Havnevej 19, 2900, Hellerup, Denmark
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmo, Sweden
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Deirdre K Tobias
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jordi Merino
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation, Chennai, India
- Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Ruth J F Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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24
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Seryapina AA, Malyavko AA, Polityko YK, Yanshole LV, Tsentalovich YP, Markel AL. Metabolic profile of blood serum in experimental arterial hypertension. Vavilovskii Zhurnal Genet Selektsii 2023; 27:530-538. [PMID: 37867609 PMCID: PMC10587007 DOI: 10.18699/vjgb-23-64] [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: 11/29/2022] [Revised: 03/01/2023] [Accepted: 03/02/2023] [Indexed: 10/24/2023] Open
Abstract
The etiology of essential hypertension is intricate, since it employs simultaneously various body systems related to the regulation of blood pressure in one way or another: the sympathetic nervous system, renin-angiotensin-aldosterone and hypothalamic-pituitary-adrenal systems, renal and endothelial mechanisms. The pathogenesis of hypertension is influenced by a variety of both genetic and environmental factors, which determines the heterogeneity of the disease in human population. Hence, there is a need to perform research on experimental models - inbred animal strains, one of them being ISIAH rat strain, which is designed to simulate inherited stress-induced arterial hypertension as close as possible to primary (or essential) hypertension in humans. To determine specific markers of diseases, various omics technologies are applied, including metabolomics, which makes it possible to evaluate the content of low-molecular compounds - amino acids, lipids, carbohydrates, nucleic acids fragments - in biological samples available for clinical analysis (blood and urine). We analyzed the metabolic profile of the blood serum of male ISIAH rats with a genetic stress-dependent form of arterial hypertension in comparison with the normotensive WAG rats. Using the method of nuclear magnetic resonance spectroscopy (NMR spectroscopy), 56 metabolites in blood serum samples were identified, 18 of which were shown to have significant interstrain differences in serum concentrations. Statistical analysis of the data obtained showed that the hypertensive status of ISIAH rats is characterized by increased concentrations of leucine, isoleucine, valine, myo-inositol, isobutyrate, glutamate, glutamine, ornithine and creatine phosphate, and reduced concentrations of 2-hydroxyisobutyrate, betaine, tyrosine and tryptophan. Such a ratio of the metabolite concentrations is associated with changes in the regulation of glucose metabolism (metabolic markers - leucine, isoleucine, valine, myo-inositol), of nitric oxide synthesis (ornithine) and catecholamine pathway (tyrosine), and with inflammatory processes (metabolic markers - betaine, tryptophan), all of these changes being typical for hypertensive status. Thus, metabolic profiling of the stress-dependent form of arterial hypertension seems to be an important result for a personalized approach to the prevention and treatment of hypertensive disease.
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Affiliation(s)
- A A Seryapina
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A A Malyavko
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Yu K Polityko
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - L V Yanshole
- International Tomography Center of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Yu P Tsentalovich
- International Tomography Center of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A L Markel
- Novosibirsk State University, Novosibirsk, Russia
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López-Hernández Y, Monárrez-Espino J, López DAG, Zheng J, Borrego JC, Torres-Calzada C, Elizalde-Díaz JP, Mandal R, Berjanskii M, Martínez-Martínez E, López JA, Wishart DS. The plasma metabolome of long COVID patients two years after infection. Sci Rep 2023; 13:12420. [PMID: 37528111 PMCID: PMC10394026 DOI: 10.1038/s41598-023-39049-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 07/19/2023] [Indexed: 08/03/2023] Open
Abstract
One of the major challenges currently faced by global health systems is the prolonged COVID-19 syndrome (also known as "long COVID") which has emerged as a consequence of the SARS-CoV-2 epidemic. It is estimated that at least 30% of patients who have had COVID-19 will develop long COVID. In this study, our goal was to assess the plasma metabolome in a total of 100 samples collected from healthy controls, COVID-19 patients, and long COVID patients recruited in Mexico between 2020 and 2022. A targeted metabolomics approach using a combination of LC-MS/MS and FIA MS/MS was performed to quantify 108 metabolites. IL-17 and leptin were measured in long COVID patients by immunoenzymatic assay. The comparison of paired COVID-19/long COVID-19 samples revealed 53 metabolites that were statistically different. Compared to controls, 27 metabolites remained dysregulated even after two years. Post-COVID-19 patients displayed a heterogeneous metabolic profile. Lactic acid, lactate/pyruvate ratio, ornithine/citrulline ratio, and arginine were identified as the most relevant metabolites for distinguishing patients with more complicated long COVID evolution. Additionally, IL-17 levels were significantly increased in these patients. Mitochondrial dysfunction, redox state imbalance, impaired energy metabolism, and chronic immune dysregulation are likely to be the main hallmarks of long COVID even two years after acute COVID-19 infection.
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Affiliation(s)
- Yamilé López-Hernández
- CONAHCyT-Metabolomics and Proteomics Laboratory, Academic Unit of Biological Sciences, Autonomous University of Zacatecas, 98000, Zacatecas, Mexico.
| | - Joel Monárrez-Espino
- Department of Health Research, Christus Muguerza del Parque Hospital - University of Monterrey, 31125, Chihuahua, Mexico
| | | | - Jiamin Zheng
- The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB, T6G 1C9, Canada
| | - Juan Carlos Borrego
- Departamento de Epidemiología, Hospital General de Zona #1 "Emilio Varela Luján", Instituto Mexicano del Seguro Social, Zacatecas, 98000, México
| | | | - José Pedro Elizalde-Díaz
- Laboratory of Cell Communication & Extracellular Vesicles, Division of Basic Science, Instituto Nacional de Medicina Genómica, 14610, Ciudad de México, Mexico
| | - Rupasri Mandal
- The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB, T6G 1C9, Canada
| | - Mark Berjanskii
- The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB, T6G 1C9, Canada
| | - Eduardo Martínez-Martínez
- Laboratory of Cell Communication & Extracellular Vesicles, Division of Basic Science, Instituto Nacional de Medicina Genómica, 14610, Ciudad de México, Mexico
| | - Jesús Adrián López
- MicroRNAs and Cancer Laboratory, Academic Unit of Biological Sciences, Autonomous University of Zacatecas, 98000, Zacatecas, Mexico
| | - David S Wishart
- The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB, T6G 1C9, Canada.
- Department of Biological Sciences, University of Alberta, Edmonton, AB, T6G 1C9, Canada.
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26
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Naja K, Anwardeen N, Al-Hariri M, Al Thani AA, Elrayess MA. Pharmacometabolomic Approach to Investigate the Response to Metformin in Patients with Type 2 Diabetes: A Cross-Sectional Study. Biomedicines 2023; 11:2164. [PMID: 37626661 PMCID: PMC10452592 DOI: 10.3390/biomedicines11082164] [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: 06/15/2023] [Revised: 07/14/2023] [Accepted: 07/30/2023] [Indexed: 08/27/2023] Open
Abstract
Metformin constitutes the foundation therapy in type 2 diabetes (T2D). Despite its multiple beneficial effects and widespread use, there is considerable inter-individual variability in response to metformin. Our objective is to identify metabolic signatures associated with poor and good responses to metformin, which may improve our ability to predict outcomes for metformin treatment. In this cross-sectional study, clinical and metabolic data for 119 patients with type 2 diabetes taking metformin were collected from the Qatar Biobank. Patients were empirically dichotomized according to their HbA1C levels into good and poor responders. Differences in the level of metabolites between these two groups were compared using orthogonal partial least square discriminate analysis (OPLS-DA) and linear models. Good responders showed increased levels of sphingomyelins, acylcholines, and glutathione metabolites. On the other hand, poor responders showed increased levels of metabolites resulting from glucose metabolism and gut microbiota metabolites. The results of this study have the potential to increase our knowledge of patient response variability to metformin and carry significant implications for enabling personalized medicine.
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Affiliation(s)
- Khaled Naja
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar; (K.N.); (N.A.); (A.A.A.T.)
| | - Najeha Anwardeen
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar; (K.N.); (N.A.); (A.A.A.T.)
| | | | - Asmaa A. Al Thani
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar; (K.N.); (N.A.); (A.A.A.T.)
- QU Health, Qatar University, Doha P.O. Box 2713, Qatar;
| | - Mohamed A. Elrayess
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar; (K.N.); (N.A.); (A.A.A.T.)
- QU Health, Qatar University, Doha P.O. Box 2713, Qatar;
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27
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Kwak SH, Hernandez-Cancela RB, DiCorpo DA, Condon DE, Merino J, Wu P, Brody JA, Yao J, Guo X, Ahmadizar F, Meyer M, Sincan M, Mercader JM, Lee S, Haessler J, Vy HMT, Lin Z, Armstrong ND, Gu S, Tsao NL, Lange LA, Wang N, Wiggins KL, Trompet S, Liu S, Loos RJ, Judy R, Schroeder PH, Hasbani NR, Bos MM, Morrison AC, Jackson RD, Reiner AP, Manson JE, Chaudhary NS, Carmichael LK, Chen YDI, Taylor KD, Ghanbari M, van Meurs J, Pitsillides AN, Psaty BM, Noordam R, Do R, Park KS, Jukema JW, Kavousi M, Correa A, Rich SS, Damrauer SM, Hajek C, Cho NH, Irvin MR, Pankow JS, Nadkarni GN, Sladek R, Goodarzi MO, Florez JC, Chasman DI, Heckbert SR, Kooperberg C, Dupuis J, Malhotra R, de Vries PS, Liu CT, Rotter JI, Meigs JB. Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.25.23293180. [PMID: 37546893 PMCID: PMC10402212 DOI: 10.1101/2023.07.25.23293180] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
BACKGROUND Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD. METHODS From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D. RESULTS A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance (P<5.0×10-8): rs147138607 (intergenic variant between CACNA1E and ZNF648) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, P=3.6×10-9, rs11444867 (intergenic variant near HS3ST1) with HR 1.89, 95% CI 1.52 - 2.35, P=9.9×10-9, and rs335407 (intergenic variant between TFB1M and NOX3) HR 1.25, 95% CI 1.16 - 1.35, P=1.5×10-8. Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with P<0.05, and 5 were significant after Bonferroni correction (P<0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase (P=1.0×10-16). CONCLUSIONS The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.
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Affiliation(s)
- Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | | | - Daniel A DiCorpo
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | | | - Jordi Merino
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Jie Yao
- Department of Pediatrics, Institute for Translational Genomics and Population Science, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Xiuqing Guo
- Department of Pediatrics, Institute for Translational Genomics and Population Science, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Data Science and Biostatistics, Julius Global Health, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Mariah Meyer
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Murat Sincan
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Josep M. Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Sujin Lee
- Division of Vascular Surgery and Endovascular Therapy, Massachusetts General Hospital, Boston, MA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA
| | - Ha My T. Vy
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Zhaotong Lin
- Department of Biostatistics, University of Minnesota, Minneapolis, MN
| | - Nicole D. Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL
| | - Shaopeng Gu
- Department of Internal Medicine, Sanford Health, Sioux Falls, SD
| | - Noah L. Tsao
- Corporal Michael Crescenz VA Medical Center, and Department of Surgery, Perelman School of Medicine, Philadelphia, PA
| | - Leslie A. Lange
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Ningyuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Simin Liu
- Department of Epidemiology, Brown University, Providence, RI
| | - Ruth J.F. Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Renae Judy
- Corporal Michael Crescenz VA Medical Center, and Department of Surgery, Perelman School of Medicine, Philadelphia, PA
| | - Philip H. Schroeder
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Natalie R. Hasbani
- Human Genetics Center, Department of Epidemiology Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX
| | - Maxime M. Bos
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX
| | - Rebecca D. Jackson
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, Ohio State University, Columbus, OH
| | - Alexander P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Ninad S. Chaudhary
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL
| | | | - Yii-Der Ida Chen
- Department of Pediatrics, Institute for Translational Genomics and Population Science, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Kent D. Taylor
- Department of Pediatrics, Institute for Translational Genomics and Population Science, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Joyce van Meurs
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Ron Do
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Kyong Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- The Netherlands Heart Institute, Utrecht, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
| | - Scott M. Damrauer
- Corporal Michael Crescenz VA Medical Center, and Department of Surgery, Perelman School of Medicine, Philadelphia, PA
- Department of Genetics, Perelman School of Medicine, Philadelphia, PA
| | - Catherine Hajek
- Department of Internal Medicine, Sanford Health, Sioux Falls, SD
| | - Nam H. Cho
- Department of Preventive Medicine, Ajou University School of Medicine, Suwon, Korea
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL
| | - James S. Pankow
- Department of Biostatistics, University of Minnesota, Minneapolis, MN
| | - Girish N. Nadkarni
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Robert Sladek
- Department of Medicine and Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center
| | - Jose C. Florez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Daniel I. Chasman
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division of the Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jerome I. Rotter
- Department of Pediatrics, Institute for Translational Genomics and Population Science, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - James B. Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Department of General Internal Medicine, Harvard Medical School and Massachusetts General Hospital, Boston, MA
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Lodge S, Lawler NG, Gray N, Masuda R, Nitschke P, Whiley L, Bong SH, Yeap BB, Dwivedi G, Spraul M, Schaefer H, Gil-Redondo R, Embade N, Millet O, Holmes E, Wist J, Nicholson JK. Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction. Int J Mol Sci 2023; 24:11614. [PMID: 37511373 PMCID: PMC10380980 DOI: 10.3390/ijms241411614] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/10/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023] Open
Abstract
An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.
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Affiliation(s)
- Samantha Lodge
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Nathan G. Lawler
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Nicola Gray
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Reika Masuda
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Philipp Nitschke
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Luke Whiley
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Sze-How Bong
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Bu B. Yeap
- Medical School, University of Western Australia, Perth, WA 6150, Australia; (B.B.Y.); (G.D.)
- Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | - Girish Dwivedi
- Medical School, University of Western Australia, Perth, WA 6150, Australia; (B.B.Y.); (G.D.)
- Department of Cardiology, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | | | | | - Rubén Gil-Redondo
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Nieves Embade
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Elaine Holmes
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, UK
| | - Julien Wist
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Chemistry Department, Universidad del Valle, Cali 76001, Colombia
| | - Jeremy K. Nicholson
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Institute of Global Health Innovation, Faculty of Medicine, Imperial College London, Faculty Building, South Kensington Campus, London SW7 2NA, UK
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Kaczmarski P, Sochal M, Strzelecki D, Białasiewicz P, Gabryelska A. Influence of glutamatergic and GABAergic neurotransmission on obstructive sleep apnea. Front Neurosci 2023; 17:1213971. [PMID: 37521710 PMCID: PMC10372424 DOI: 10.3389/fnins.2023.1213971] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 06/26/2023] [Indexed: 08/01/2023] Open
Abstract
Glutamate and γ-aminobutyric acid (GABA) are the two main neurotransmitters in the human brain. The balance between their excitatory and inhibitory functions is crucial for maintaining the brain's physiological functions. Disturbance of glutamatergic or GABAergic neurotransmission leads to serious health problems including neurodegeneration, affective and sleep disorders. Both GABA and glutamate are involved in the control of the sleep-wake cycle. The disturbances in their function may cause sleep and sleep-related disorders. Obstructive sleep apnea (OSA) is the most common sleep respiratory disorder and is characterized by repetitive collapse of the upper airway resulting in intermittent hypoxia and sleep fragmentation. The complex pathophysiology of OSA is the basis of the development of numerous comorbid diseases. There is emerging evidence that GABA and glutamate disturbances may be involved in the pathogenesis of OSA, as well as its comorbidities. Additionally, the GABA/glutamate targeted pharmacotherapy may also influence the course of OSA, which is important in the implementation of wildly used drugs including benzodiazepines, anesthetics, and gabapentinoids. In this review, we summarize current knowledge on the influence of disturbances in glutamatergic and GABAergic neurotransmission on obstructive sleep apnea.
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Affiliation(s)
- Piotr Kaczmarski
- Department of Sleep Medicine and Metabolic Disorders, Medical University of Łódź, Łódź, Poland
| | - Marcin Sochal
- Department of Sleep Medicine and Metabolic Disorders, Medical University of Łódź, Łódź, Poland
| | - Dominik Strzelecki
- Department of Affective and Psychotic Disorders, Medical University of Łódź, Łódź, Poland
| | - Piotr Białasiewicz
- Department of Sleep Medicine and Metabolic Disorders, Medical University of Łódź, Łódź, Poland
| | - Agata Gabryelska
- Department of Sleep Medicine and Metabolic Disorders, Medical University of Łódź, Łódź, Poland
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30
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Cui M, Yu P, Liu TC, Liu J, Li K, Zhou P, Liu X. Dose-dependent effects of xylooligosaccharides on glycemic regulation with L. rhamnosus CCFM1060 in diabetic mice. Food Funct 2023. [PMID: 37325857 DOI: 10.1039/d3fo00162h] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Dietary intervention with the probiotic Lactobacillus rhamnosus CCFM1060 has been proved to be effective on glycemic regulation in diabetic mice. Therefore characterization of the potential symbiotic effect of prebiotic xylooligosaccharides (XOS) with L. rhamnosus CCFM1060 would be desirable. In this study, we evaluated any dose-dependent relationship between XOS and L. rhamnosus CCFM1060, and the potential impact on glycemic regulation. Diabetic mice were randomly assigned to receive 5 × 109 CFU mL-1L. rhamnosus CCFM1060, 5 × 109 CFU mL-1L. rhamnosus CCFM1060 with 250 mg kg-1 XOS (L-LXOS), or 5 × 109 CFU mL-1L. rhamnosus CCFM1060 with 500 mg kg-1 XOS (L-HXOS) for 7 weeks. In addition to characterization of the host metabolism, the intestinal microbiota were analyzed using 16S rRNA gene sequencing. The results showed that L. rhamnosus alone and L-LXOS intervention significantly alleviated diabetes symptoms and increased the populations of short-chain fatty acid (SCFA)-producing bacteria. The intake of L-HXOS had an adverse effect on glucose metabolism, causing increased insulin resistance and inflammation. Although a significant increase in the relative abundance of Bifidobacterium was observed in the L-HXOS group, the abundance of SCFA-producing bacteria, such as Romboutsia and Clostrudium sensu stricto 1, decreased. KEGG pathway analysis revealed that the adverse effects of L-HXOS intervention might be attributed to the metabolic pathways involved in amino acid, cofactor, and vitamin metabolism. This study revealed that L. rhamnosus CCFM1060 combined with different doses of XOS exerted dose-dependent effects on glucose metabolism. Therefore, the type and dose of prebiotics should be carefully evaluated when developing individualized symbiotic formula.
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Affiliation(s)
- Mengjun Cui
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, Jiangsu, China.
| | - Peng Yu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, Jiangsu, China.
| | - Tristan C Liu
- Taicang Port Economic and Technological Development Zone New Zone, Standard Foods (China) Co., Ltd, No. 88 Dalian West Road, Suzhou, Jiangsu, P. R. China
| | - Jianguo Liu
- Taicang Port Economic and Technological Development Zone New Zone, Standard Foods (China) Co., Ltd, No. 88 Dalian West Road, Suzhou, Jiangsu, P. R. China
| | - Kexin Li
- Le Bonta Wellness Co., Ltd, Room 5, 4th Floor, Building 1, No. 39, Jiatai Road, Pilot Free Trade Zone, Shanghai, China
| | - Peng Zhou
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, Jiangsu, China.
| | - Xiaoming Liu
- School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu 214122, China.
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31
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Bodhini D, Morton RW, Santhakumar V, Nakabuye M, Pomares-Millan H, Clemmensen C, Fitzpatrick SL, Guasch-Ferre M, Pankow JS, Ried-Larsen M, Franks PW, Tobias DK, Merino J, Mohan V, Loos RJF. Role of sociodemographic, clinical, behavioral, and molecular factors in precision prevention of type 2 diabetes: a systematic review. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.03.23289433. [PMID: 37205385 PMCID: PMC10187453 DOI: 10.1101/2023.05.03.23289433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular characteristics modify the efficacy of dietary or lifestyle interventions to prevent T2D. Among the 80 publications that met our criteria for inclusion, the evidence was low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. We found evidence, albeit low certainty, to support conclusions that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.
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Sun J, Ma X, Yang L, Jin X, Zhao M, Xi B, Song S. The number of metabolic syndrome risk factors predicts alterations in gut microbiota in Chinese children from the Huantai study. BMC Pediatr 2023; 23:191. [PMID: 37085796 PMCID: PMC10120097 DOI: 10.1186/s12887-023-04017-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: 06/16/2022] [Accepted: 04/14/2023] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND Evidence on the effect of gut microbiota on the number of metabolic syndrome (MetS) risk factors among children is scarce. We aimed to examine the alterations of gut microbiota with different numbers of MetS risk factors among children. METHODS Data were collected from a nested case-control study at the baseline of the Huantai Childhood Cardiovascular Health Cohort Study in Zibo, China. We compared the differences in gut microbiota based on 16S rRNA gene sequencing among 72 children with different numbers of MetS risk factors matched by age and sex (i.e., none, one, and two-or-more MetS risk factors; 24 children for each group). RESULTS The community richness (i.e., the total number of species in the community) and diversity (i.e., the richness and evenness of species in the community) of gut microbiota decreased with an increased number of MetS risk factors in children (P for trend < 0.05). Among genera with a relative abundance greater than 0.01%, the relative abundance of Lachnoclostridium (PFDR = 0.009) increased in the MetS risk groups, whereas Alistipes (PFDR < 0.001) and Lachnospiraceae_NK4A136_group (PFDR = 0.043) decreased in the MetS risk groups compared to the non-risk group. The genus Christensenellaceae_R-7_group excelled at distinguishing one and two-or-more risk groups from the non-risk group (area under the ROC curve [AUC]: 0.84 - 0.92), while the genera Family_XIII_AD3011_group (AUC: 0.73 - 0.91) and Lachnoclostridium (AUC: 0.77 - 0.80) performed moderate abilities in identifying none, one, and two-or-more MetS risk factors in children. CONCLUSIONS Based on the nested case-control study and the 16S rRNA gene sequencing technology, we found that dysbiosis of gut microbiota, particularly for the genera Christensenellaceae_R-7_group, Family_XIII_AD3011_group, and Lachnoclostridium may contribute to the early detection and the accumulation of MetS risk factors in childhood.
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Affiliation(s)
- Jiahong Sun
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen Hua Xi Road, Jinan, 250012, China
| | - Xiaoyun Ma
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen Hua Xi Road, Jinan, 250012, China
| | - Liu Yang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen Hua Xi Road, Jinan, 250012, China
| | - Xuli Jin
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen Hua Xi Road, Jinan, 250012, China
| | - Min Zhao
- Department of Nutrition and Food Hygiene, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Bo Xi
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen Hua Xi Road, Jinan, 250012, China.
| | - Suhang Song
- Taub Institute for Research in Alzheimer 's disease and the Aging Brain, Columbia University, New York, NY, USA
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Okut H, Lu Y, Palmer ND, Chen YDI, Taylor KD, Norris JM, Lorenzo C, Rotter JI, Langefeld CD, Wagenknecht LE, Bowden DW, Ng MCY. Metabolomic profiling of glucose homeostasis in African Americans: the Insulin Resistance Atherosclerosis Family Study (IRAS-FS). Metabolomics 2023; 19:35. [PMID: 37005925 PMCID: PMC10068644 DOI: 10.1007/s11306-023-01984-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 03/04/2023] [Indexed: 04/04/2023]
Abstract
INTRODUCTION African Americans are at increased risk for type 2 diabetes. OBJECTIVES This work aimed to examine metabolomic signature of glucose homeostasis in African Americans. METHODS We used an untargeted liquid chromatography-mass spectrometry metabolomic approach to comprehensively profile 727 plasma metabolites among 571 African Americans from the Insulin Resistance Atherosclerosis Family Study (IRAS-FS) and investigate the associations between these metabolites and both the dynamic (SI, insulin sensitivity; AIR, acute insulin response; DI, disposition index; and SG, glucose effectiveness) and basal (HOMA-IR and HOMA-B) measures of glucose homeostasis using univariate and regularized regression models. We also compared the results with our previous findings in the IRAS-FS Mexican Americans. RESULTS We confirmed increased plasma metabolite levels of branched-chain amino acids and their metabolic derivatives, 2-aminoadipate, 2-hydroxybutyrate, glutamate, arginine and its metabolic derivatives, carbohydrate metabolites, and medium- and long-chain fatty acids were associated with insulin resistance, while increased plasma metabolite levels in the glycine, serine and threonine metabolic pathway were associated with insulin sensitivity. We also observed a differential ancestral effect of glutamate on glucose homeostasis with significantly stronger effects observed in African Americans than those previously observed in Mexican Americans. CONCLUSION We extended the observations that metabolites are useful biomarkers in the identification of prediabetes in individuals at risk of type 2 diabetes in African Americans. We revealed, for the first time, differential ancestral effect of certain metabolites (i.e., glutamate) on glucose homeostasis traits. Our study highlights the need for additional comprehensive metabolomic studies in well-characterized multiethnic cohorts.
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Affiliation(s)
- Hayrettin Okut
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Population Health, University of Kansas School of Medicine-Wichita, Wichita, KS, USA
| | - Yingchang Lu
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Nicholette D Palmer
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yii-Der Ida Chen
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jill M Norris
- Departments of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA
| | - Carlos Lorenzo
- Department of Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Donald W Bowden
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Maggie C Y Ng
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
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Yang J, Wu J, Tekola-Ayele F, Li LJ, Bremer AA, Lu R, Rahman ML, Weir NL, Pang WW, Chen Z, Tsai MY, Zhang C. Plasma Amino Acids in Early Pregnancy and Midpregnancy and Their Interplay With Phospholipid Fatty Acids in Association With the Risk of Gestational Diabetes Mellitus: Results From a Longitudinal Prospective Cohort. Diabetes Care 2023; 46:722-732. [PMID: 36701229 PMCID: PMC10090921 DOI: 10.2337/dc22-1892] [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: 09/28/2022] [Accepted: 12/29/2022] [Indexed: 01/27/2023]
Abstract
OBJECTIVE We prospectively evaluated plasma amino acids (AAs) in early pregnancy and midpregnancy and their interplay with phospholipid fatty acids (FAs) in association with gestational diabetes mellitus (GDM) risk. RESEARCH DESIGN AND METHODS From a longitudinal pregnancy cohort of 2,802 individuals, concentrations of 24 plasma AAs at 10-14 and 15-26 gestational weeks (GW) were assessed among 107 GDM case subjects and 214 non-GDM control subjects. We estimated adjusted odds ratios (OR) and 95% CI for the associations of plasma AAs and the joint associations of plasma AAs and phospholipid FAs with GDM risk, adjusting for risk factors including age, prepregnancy BMI, and family history of diabetes. RESULTS Glycine at 10-14 GW was inversely associated with GDM (adjusted OR [95% CI] per SD increment: 0.55 [0.39-0.79]). Alanine, aspartic acid, and glutamic acid at 10-14 GW were positively associated with GDM (1.43 [1.08-1.88], 1.41 [1.11-1.80], and 1.39 [0.98-1.98]). At 15-26 GW, findings for glycine, alanine, aspartic acid, and the glutamine-to-glutamic acid ratio were consistent with the directions observed at 10-14 GW. Isoleucine, phenylalanine, and tyrosine were positively associated with GDM (1.64 [1.19-2.27], 1.15 [0.87-1.53], and 1.56 [1.16-2.09]). All P values for linear trend were <0.05. Several AAs and phospholipid FAs were significantly and jointly associated with GDM. For instance, the lowest risk was observed among women with higher glycine and lower even-chain saturated FAs at 10-14 GW (adjusted OR [95% CI] 0.15 [0.06, 0.37]). CONCLUSIONS Plasma AAs may be implicated in GDM development starting in early pregnancy. Associations of AAs with GDM may be enhanced in the copresence of phospholipid FA profile.
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Affiliation(s)
- Jiaxi Yang
- Global Centre for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jing Wu
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Fasil Tekola-Ayele
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Ling-Jun Li
- Global Centre for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Andrew A. Bremer
- Division of Extramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Ruijin Lu
- Division of Biostatistics, School of Medicine, Washington University in St. Louis, St. Louis, MO
| | - Mohammad L. Rahman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD
| | - Natalie L. Weir
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Wei Wei Pang
- Global Centre for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Zhen Chen
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Cuilin Zhang
- Global Centre for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
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Rothwell JA, Bešević J, Dimou N, Breeur M, Murphy N, Jenab M, Wedekind R, Viallon V, Ferrari P, Achaintre D, Gicquiau A, Rinaldi S, Scalbert A, Huybrechts I, Prehn C, Adamski J, Cross AJ, Keun H, Chadeau-Hyam M, Boutron-Ruault MC, Overvad K, Dahm CC, Nøst TH, Sandanger TM, Skeie G, Zamora-Ros R, Tsilidis KK, Eichelmann F, Schulze MB, van Guelpen B, Vidman L, Sánchez MJ, Amiano P, Ardanaz E, Smith-Byrne K, Travis R, Katzke V, Kaaks R, Derksen JWG, Colorado-Yohar S, Tumino R, Bueno-de-Mesquita B, Vineis P, Palli D, Pasanisi F, Eriksen AK, Tjønneland A, Severi G, Gunter MJ. Circulating amino acid levels and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition and UK Biobank cohorts. BMC Med 2023; 21:80. [PMID: 36855092 PMCID: PMC9976469 DOI: 10.1186/s12916-023-02739-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 01/16/2023] [Indexed: 03/02/2023] Open
Abstract
BACKGROUND Amino acid metabolism is dysregulated in colorectal cancer patients; however, it is not clear whether pre-diagnostic levels of amino acids are associated with subsequent risk of colorectal cancer. We investigated circulating levels of amino acids in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts. METHODS Concentrations of 13-21 amino acids were determined in baseline fasting plasma or serum samples in 654 incident colorectal cancer cases and 654 matched controls in EPIC. Amino acids associated with colorectal cancer risk following adjustment for the false discovery rate (FDR) were then tested for associations in the UK Biobank, for which measurements of 9 amino acids were available in 111,323 participants, of which 1221 were incident colorectal cancer cases. RESULTS Histidine levels were inversely associated with colorectal cancer risk in EPIC (odds ratio [OR] 0.80 per standard deviation [SD], 95% confidence interval [CI] 0.69-0.92, FDR P-value=0.03) and in UK Biobank (HR 0.93 per SD, 95% CI 0.87-0.99, P-value=0.03). Glutamine levels were borderline inversely associated with colorectal cancer risk in EPIC (OR 0.85 per SD, 95% CI 0.75-0.97, FDR P-value=0.08) and similarly in UK Biobank (HR 0.95, 95% CI 0.89-1.01, P=0.09) In both cohorts, associations changed only minimally when cases diagnosed within 2 or 5 years of follow-up were excluded. CONCLUSIONS Higher circulating levels of histidine were associated with a lower risk of colorectal cancer in two large prospective cohorts. Further research to ascertain the role of histidine metabolism and potentially that of glutamine in colorectal cancer development is warranted.
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Affiliation(s)
- Joseph A Rothwell
- Centre for Epidemiology and Population Health (Inserm U1018), Exposome and Heredity team, Faculté de Médecine, Université Paris-Saclay, UVSQ, Gustave Roussy, F-94805, Villejuif, France.
| | - Jelena Bešević
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Niki Dimou
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Marie Breeur
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Neil Murphy
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Mazda Jenab
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Roland Wedekind
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Vivian Viallon
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Pietro Ferrari
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - David Achaintre
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Audrey Gicquiau
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Sabina Rinaldi
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Augustin Scalbert
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Inge Huybrechts
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Cornelia Prehn
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, 85764, Neuherberg, Germany
| | - Jerzy Adamski
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia
| | - Amanda J Cross
- School of Public Health, Imperial College London, London, UK
| | - Hector Keun
- Department of Surgery & Cancer, Imperial College London, London, UK
| | | | - Marie-Christine Boutron-Ruault
- Centre for Epidemiology and Population Health (Inserm U1018), Exposome and Heredity team, Faculté de Médecine, Université Paris-Saclay, UVSQ, Gustave Roussy, F-94805, Villejuif, France
| | - Kim Overvad
- Department of Public Health, Aarhus University, Bartholins Allé 2, DK-8000, Aarhus, Denmark
| | - Christina C Dahm
- Department of Public Health, Aarhus University, Bartholins Allé 2, DK-8000, Aarhus, Denmark
| | - Therese Haugdahl Nøst
- Faculty of Health Sciences, Department of Community Medicine, UiT the Arctic University of Norway, N-9037, Tromsø, Norway
| | - Torkjel M Sandanger
- Faculty of Health Sciences, Department of Community Medicine, UiT the Arctic University of Norway, N-9037, Tromsø, Norway
| | - Guri Skeie
- Faculty of Health Sciences, Department of Community Medicine, UiT the Arctic University of Norway, N-9037, Tromsø, Norway
| | - Raul Zamora-Ros
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
| | - Kostas K Tsilidis
- School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Fabian Eichelmann
- German Center for Diabetes Research (DZD), Munchen-Neuherberg, Germany
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Bethany van Guelpen
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Linda Vidman
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden
| | - Maria-José Sánchez
- Escuela Andaluza de Salud Pública (EASP), 18011, Granada, Spain
- Instituto de Investigación Biosanitaria ibs. GRANADA, 18012, Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, 18071, Granada, Spain
| | - Pilar Amiano
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, San Sebastián, Spain
- Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, San Sebastián, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Eva Ardanaz
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
- Navarra Public Health Institute, Leyre 15, 31003, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Karl Smith-Byrne
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
| | - Ruth Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Verena Katzke
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Rudolf Kaaks
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Jeroen W G Derksen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Sandra Colorado-Yohar
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP), Ragusa, Italy
| | - Bas Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720, BA, Bilthoven, The Netherlands
| | - Paolo Vineis
- School of Public Health, Imperial College London, London, UK
- Italian Institute of Technology, Genova, Italy
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy
| | - Fabrizio Pasanisi
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Anne Kirstine Eriksen
- Danish Cancer Society Research Center, Diet, Genes and Environment, Strandboulevarden 49, DK-2100, Copenhagen, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Diet, Genes and Environment, Strandboulevarden 49, DK-2100, Copenhagen, Denmark
| | - Gianluca Severi
- Centre for Epidemiology and Population Health (Inserm U1018), Exposome and Heredity team, Faculté de Médecine, Université Paris-Saclay, UVSQ, Gustave Roussy, F-94805, Villejuif, France
- Department of Statistics, Computer Science, Applications "G. Parenti" University of Florence, Florence, Italy
| | - Marc J Gunter
- International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69008, Lyon, France
- School of Public Health, Imperial College London, London, UK
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Shah RV, Steffen LM, Nayor M, Reis JP, Jacobs DR, Allen NB, Lloyd-Jones D, Meyer K, Cole J, Piaggi P, Vasan RS, Clish CB, Murthy VL. Dietary metabolic signatures and cardiometabolic risk. Eur Heart J 2023; 44:557-569. [PMID: 36424694 PMCID: PMC10169425 DOI: 10.1093/eurheartj/ehac446] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 06/23/2022] [Accepted: 07/28/2022] [Indexed: 11/27/2022] Open
Abstract
AIMS Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood. METHODS AND RESULTS In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32-1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12-2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study. CONCLUSION Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD.
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Affiliation(s)
- Ravi V Shah
- Vanderbilt University Medical Center, Vanderbilt Clinical and Translational Research Center (VTRACC), Nashville, TN, USA
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Matthew Nayor
- Cardiology Division, Boston University School of Medicine, Boston, MA, USA
| | - Jared P Reis
- Epidemiology Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - David R Jacobs
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Norrina B Allen
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Katie Meyer
- Nutrition Department, UNC Chapel Hill, Chapel Hill, NC, USA
| | - Joanne Cole
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Paolo Piaggi
- Department of Information Engineering, University of Pisa, Pisa, Italy
| | - Ramachandran S Vasan
- Sections of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, and Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Clary B Clish
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Venkatesh L Murthy
- Department of Medicine and Radiology, University of Michigan, 1338 Cardiovascular Center, Ann Arbor, MI 48109-5873, USA
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Jeong S, Jang HB, Kim HJ, Lee HJ. Identification of Biomarkers Related to Metabolically Unhealthy Obesity in Korean Obese Adolescents: A Cross-Sectional Study. CHILDREN (BASEL, SWITZERLAND) 2023; 10:children10020322. [PMID: 36832451 PMCID: PMC9955165 DOI: 10.3390/children10020322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 01/25/2023] [Accepted: 02/02/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND The current study aimed to screen for relationships and different potential metabolic biomarkers involved between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) in adolescents. METHODS The study included 148 obese adolescents aged between 14 and 16. The study participants were divided into MUO and MHO groups based on the age-specific adolescent metabolic syndrome (MetS) criteria of the International Diabetes Federation. The current study was conducted to investigate the clinical and metabolic differences between the MHO and MUO groups. Multivariate analyses were conducted to investigate the metabolites as independent predictors for the odds ratio and the presence of the MetS. RESULTS There were significant differences in the three acylcarnitines, five amino acids, glutamine/glutamate ratio, three biogenic amines, two glycerophospholipids, and the triglyceride-glucose index between the MUO group and those in the MHO group. Moreover, several metabolites were associated with the prevalence of MUO. Additionally, several metabolites were inversely correlated with MHO in the MUO group. CONCLUSIONS In this study, the biomarkers found in this study have the potential to reflect the clinical outcomes of the MUO group. These biomarkers will lead to a better understanding of MetS in obese adolescents.
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Affiliation(s)
| | | | | | - Hye-Ja Lee
- Correspondence: ; Tel.: +82-43-719-8452; Fax: +82-43-719-8709
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Shen Z, Li ZY, Yu MT, Tan KL, Chen S. Metabolic perspective of astrocyte dysfunction in Alzheimer's disease and type 2 diabetes brains. Biomed Pharmacother 2023; 158:114206. [PMID: 36916433 DOI: 10.1016/j.biopha.2022.114206] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/30/2022] [Accepted: 12/30/2022] [Indexed: 01/06/2023] Open
Abstract
The term type III diabetes (T3DM) has been proposed for Alzheimer's disease (AD) due to the shared molecular and cellular features between type 2 diabetes (T2DM) and insulin resistance-associated memory deficits and cognitive decline in elderly individuals. Astrocytes elicit neuroprotective or deleterious effects in AD progression and severity. Patients with T2DM are at a high risk of cognitive impairment, and targeting astrocytes might be promising in alleviating neurodegeneration in the diabetic brain. Recent studies focusing on cell-specific activities in the brain have revealed the important role of astrocytes in brain metabolism (e.g., glucose metabolism, lipid metabolism), neurovascular coupling, synapses, and synaptic plasticity. In this review, we discuss how astrocytes and their dysfunction result in multiple pathological and clinical features of AD and T2DM from a metabolic perspective and the potential comorbid mechanism in these two diseases from the perspective of astrocytes.
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Affiliation(s)
- Zheng Shen
- Zunyi Medical University, Zhuhai Campus, Zhuhai, Guangdong 519041, China
| | - Zheng-Yang Li
- Zunyi Medical University, Zhuhai Campus, Zhuhai, Guangdong 519041, China
| | - Meng-Ting Yu
- Zunyi Medical University, Zhuhai Campus, Zhuhai, Guangdong 519041, China
| | - Kai-Leng Tan
- Institute of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou, Guangdong 510006, China.
| | - Si Chen
- Zunyi Medical University, Zhuhai Campus, Zhuhai, Guangdong 519041, China.
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Zhang Y, Ngo D, Yu B, Shah NA, Chen H, Ramos AR, Zee PC, Tracy R, Durda P, Kaplan R, Daviglus ML, Rich SS, Rotter JI, Cai J, Clish C, Gerszten R, Kristal BS, Gharib SA, Redline S, Sofer T. Development and validation of a metabolite index for obstructive sleep apnea across race/ethnicities. Sci Rep 2022; 12:21805. [PMID: 36526671 PMCID: PMC9758170 DOI: 10.1038/s41598-022-26321-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation, and associated with increased risk of adverse health outcomes. Metabolites are being increasingly used for biomarker discovery and evaluation of disease processes and progression. Studying metabolomic associations with OSA in a diverse community-based cohort may provide insights into the pathophysiology of OSA. We aimed to develop and replicate a metabolite index for OSA and identify individual metabolites associated with OSA. We studied 219 metabolites and their associations with the apnea hypopnea index (AHI) and with moderate-severe OSA (AHI ≥ 15) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n = 3507) using two methods: (1) association analysis of individual metabolites, and (2) least absolute shrinkage and selection operator (LASSO) regression to identify a subset of metabolites jointly associated with OSA, which was used to develop a metabolite index for OSA. Results were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) (n = 475). When assessing the associations with individual metabolites, we identified seven metabolites significantly positively associated with OSA in HCHS/SOL (FDR p < 0.05), of which four associations-glutamate, oleoyl-linoleoyl-glycerol (18:1/18:2), linoleoyl-linoleoyl-glycerol (18:2/18:2) and phenylalanine, were replicated in MESA (one sided-p < 0.05). The OSA metabolite index, composed of 14 metabolites, was associated with a 50% increased risk for moderate-severe OSA (OR = 1.50 [95% CI 1.21-1.85] per 1 SD of OSA metabolite index, p < 0.001) in HCHS/SOL and 55% increased risk (OR = 1.55 [95% CI 1.10-2.20] per 1 SD of OSA metabolite index, p = 0.013) in MESA, both adjusted for demographics, lifestyle, and comorbidities. Similar albeit less significant associations were observed for AHI. Replication of the metabolite index in an independent multi-ethnic dataset demonstrates the robustness of metabolomic-based OSA index to population heterogeneity. Replicated metabolite associations may provide insights into OSA-related molecular and metabolic mechanisms.
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Affiliation(s)
- Ying Zhang
- Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Debby Ngo
- Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Cardiovascular Institute, Boston, MA, 02215, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Neomi A Shah
- Department of Medicine, Albert Einstein College of Medicine, New York, NY, 10029, USA
| | - Han Chen
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Alberto R Ramos
- Sleep Medicine Program, Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Phyllis C Zee
- Division of Sleep Medicine, Department of Neurology, Northwestern University, Chicago, IL, 60611, USA
| | - Russell Tracy
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, 05405, USA
| | - Peter Durda
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, 05405, USA
| | - Robert Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Martha L Daviglus
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60612, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Jianwen Cai
- Department of Biostatistics, Collaborative Studies Coordinating Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Clary Clish
- Metabolite Profiling Platform, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Robert Gerszten
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Bruce S Kristal
- Department of Medicine, Sleep and Circadian Disorders, Harvard Medical School, Boston, MA, 02115, USA
- Department of Medicine, Division of Sleep Medicine and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Sina A Gharib
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, 98195, USA
| | - Susan Redline
- Department of Medicine, Division of Sleep Medicine and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Tamar Sofer
- Department of Medicine, Sleep and Circadian Disorders, Harvard Medical School, Boston, MA, 02115, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
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40
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Gonzalez Izundegui D, Miller PE, Shah RV, Clish CB, Walker ME, Mitchell GF, Gerszten RE, Larson MG, Vasan RS, Nayor M. Response of circulating metabolites to an oral glucose challenge and risk of cardiovascular disease and mortality in the community. Cardiovasc Diabetol 2022; 21:213. [PMID: 36243866 PMCID: PMC9568897 DOI: 10.1186/s12933-022-01647-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 09/29/2022] [Indexed: 11/17/2022] Open
Abstract
Background New biomarkers to identify cardiovascular disease (CVD) risk earlier in its course are needed to enable targeted approaches for primordial prevention. We evaluated whether intraindividual changes in blood metabolites in response to an oral glucose tolerance test (OGTT) may provide incremental information regarding the risk of future CVD and mortality in the community. Methods An OGTT (75 g glucose) was administered to a subsample of Framingham Heart Study participants free from diabetes (n = 361). Profiling of 211 plasma metabolites was performed from blood samples drawn before and 2 h after OGTT. The log2(post/pre) metabolite levels (Δmetabolites) were related to incident CVD and mortality in Cox regression models adjusted for age, sex, baseline metabolite level, systolic blood pressure, hypertension treatment, body mass index, smoking, and total/high-density lipoprotein cholesterol. Select metabolites were related to subclinical cardiometabolic phenotypes using Spearman correlations adjusted for age, sex, and fasting metabolite level. Results Our sample included 42% women, with a mean age of 56 ± 9 years and a body mass index of 30.2 ± 5.3 kg/m2. The pre- to post-OGTT changes (Δmetabolite) were non-zero for 168 metabolites (at FDR ≤ 5%). A total of 132 CVD events and 144 deaths occurred during median follow-up of 24.9 years. In Cox models adjusted for clinical risk factors, four Δmetabolites were associated with incident CVD (higher glutamate and deoxycholate, lower inosine and lysophosphatidylcholine 18:2) and six Δmetabolites (higher hydroxyphenylacetate, triacylglycerol 56:5, alpha-ketogluturate, and lower phosphatidylcholine 32:0, glucuronate, N-monomethyl-arginine) were associated with death (P < 0.05). Notably, baseline metabolite levels were not associated with either outcome in models excluding Δmetabolites. The Δmetabolites exhibited varying cross-sectional correlation with subclinical risk factors such as visceral adiposity, insulin resistance, and vascular stiffness, but overall relations were modest. Significant Δmetabolites included those with established roles in cardiometabolic disease (e.g., glutamate, alpha-ketoglutarate) and metabolites with less defined roles (e.g., glucuronate, lipid species). Conclusions Dynamic changes in metabolite levels with an OGTT are associated with incident CVD and mortality and have potential relevance for identifying CVD risk earlier in its development and for discovering new potential therapeutic targets. Supplementary Information The online version contains supplementary material available at 10.1186/s12933-022-01647-w.
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Affiliation(s)
| | - Patricia E Miller
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ravi V Shah
- Vanderbilt Translational and Clinical Research Center, Cardiology Division, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Clary B Clish
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maura E Walker
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, 72 E Concord Street, Suite L-516, Boston, MA, 02118, USA.,Department of Health Sciences, Program in Nutrition, Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA, USA.,Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | | | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.,Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Ramachandran S Vasan
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, 72 E Concord Street, Suite L-516, Boston, MA, 02118, USA.,Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA.,Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, 72 E Concord Street, Suite L-516, Boston, MA, 02118, USA.,Department of Epidemiology, Boston University Schools of Medicine and Public Health, Center for Computing and Data Sciences, Boston University, Boston, MA, USA
| | - Matthew Nayor
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, 72 E Concord Street, Suite L-516, Boston, MA, 02118, USA. .,Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA. .,Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, 72 E Concord Street, Suite L-516, Boston, MA, 02118, USA.
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41
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Kumar R, Kumar V, Arya R, Anand U, Priyadarshi RN. Association of COVID-19 with hepatic metabolic dysfunction. World J Virol 2022; 11:237-251. [PMID: 36188741 PMCID: PMC9523326 DOI: 10.5501/wjv.v11.i5.237] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 04/25/2022] [Accepted: 06/20/2022] [Indexed: 02/05/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic continues to be a global problem with over 438 million cases reported so far. Although it mostly affects the respiratory system, the involvement of extrapulmonary organs, including the liver, is not uncommon. Since the beginning of the pandemic, metabolic com-orbidities, such as obesity, diabetes, hypertension, and dyslipidemia, have been identified as poor prognostic indicators. Subsequent metabolic and lipidomic studies have identified several metabolic dysfunctions in patients with COVID-19. The metabolic alterations appear to be linked to the course of the disease and inflammatory reaction in the body. The liver is an important organ with high metabolic activity, and a significant proportion of COVID-19 patients have metabolic comorbidities; thus, this factor could play a key role in orchestrating systemic metabolic changes during infection. Evidence suggests that metabolic dysregulation in COVID-19 has both short- and long-term metabolic implications. Furthermore, COVID-19 has adverse associations with metabolic-associated fatty liver disease. Due to the ensuing effects on the renin-angiotensin-aldosterone system and ammonia metabolism, COVID-19 can have significant implications in patients with advanced chronic liver disease. A thorough understanding of COVID-19-associated metabolic dysfunction could lead to the identification of important plasma biomarkers and novel treatment targets. In this review, we discuss the current understanding of metabolic dysfunction in COVID-19, focusing on the liver and exploring the underlying mechanistic pathogenesis and clinical implications.
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Affiliation(s)
- Ramesh Kumar
- Department of Gastroenterology, All India Institute of Medical Sciences, Patna, Patna 801507, Bihar, India
| | - Vijay Kumar
- Department of Medicine, All India Institute of Medical Sciences, Patna, Patna 801507, Bihar, India
| | - Rahul Arya
- Department of Gastroenterology, All India Institute of Medical Sciences, Patna, Patna 801507, Bihar, India
| | - Utpal Anand
- Department of Surgical Gastroenterology, All India Institute of Medical Sciences, Patna, Patna 801507, Bihar, India
| | - Rajeev Nayan Priyadarshi
- Department of Radiodiagnosis, All India Institute of Medical Sciences, Patna, Patna 801507, Bihar, India
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Wang S, Li M, Lin H, Wang G, Xu Y, Zhao X, Hu C, Zhang Y, Zheng R, Hu R, Shi L, Du R, Su Q, Wang J, Chen Y, Yu X, Yan L, Wang T, Zhao Z, Liu R, Wang X, Li Q, Qin G, Wan Q, Chen G, Xu M, Dai M, Zhang D, Tang X, Gao Z, Shen F, Luo Z, Qin Y, Chen L, Huo Y, Li Q, Ye Z, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Zhao J, Lai S, Mu Y, Chen L, Li D, Xu G, Ning G, Wang W, Bi Y, Lu J. Amino acids, microbiota-related metabolites, and the risk of incident diabetes among normoglycemic Chinese adults: Findings from the 4C study. Cell Rep Med 2022; 3:100727. [PMID: 35998626 PMCID: PMC9512668 DOI: 10.1016/j.xcrm.2022.100727] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 06/16/2022] [Accepted: 07/22/2022] [Indexed: 11/26/2022]
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Giskeødegård GF, Madssen TS, Sangermani M, Lundgren S, Wethal T, Andreassen T, Reidunsdatter RJ, Bathen TF. Longitudinal Changes in Circulating Metabolites and Lipoproteins After Breast Cancer Treatment. Front Oncol 2022; 12:919522. [PMID: 35785197 PMCID: PMC9245384 DOI: 10.3389/fonc.2022.919522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/05/2022] [Indexed: 02/06/2023] Open
Abstract
The multimodal treatment of breast cancer may induce long term effects on the metabolic profile and increase the risk of future cardiovascular disease. In this study, we characterized longitudinal changes in serum lipoprotein subfractions and metabolites after breast cancer treatment, aiming to determine the long-term effect of different treatment modalities. Further, we investigated the prognostic value of treatment-induced changes in breast cancer-specific and overall 10-year survival. In this study, serum samples from breast cancer patients (n = 250) were collected repeatedly before and after radiotherapy, and serum metabolites and lipoprotein subfractions were quantified by NMR spectroscopy. Longitudinal changes were assessed by univariate and multivariate data analysis methods applicable for repeated measures. Distinct changes were detectable in levels of lipoprotein subfractions and circulating metabolites during the first year, with similar changes despite large differences in treatment regimens. We detect increased free cholesterol and decreased esterified cholesterol levels of HDL subfractions, a switch towards larger LDL particles and higher total LDL-cholesterol, in addition to a switch in the glutamine-glutamate ratio. Non-survivors had different lipid profiles from survivors already at baseline. To conclude, our results show development towards an atherogenic lipid profile in breast cancer patients with different treatment regimens.
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Affiliation(s)
- Guro F. Giskeødegård
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Clinic of Surgery, St. Olavs University Hospital, Trondheim, Norway
| | - Torfinn S. Madssen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Matteo Sangermani
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Steinar Lundgren
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Torgeir Wethal
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Medicine, Stroke Unit, St. Olavs University Hospital, Trondheim, Norway
| | - Trygve Andreassen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Randi J. Reidunsdatter
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Tone F. Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
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Pan X, Tao S, Tong N. Potential Therapeutic Targeting Neurotransmitter Receptors in Diabetes. Front Endocrinol (Lausanne) 2022; 13:884549. [PMID: 35669692 PMCID: PMC9163348 DOI: 10.3389/fendo.2022.884549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Accepted: 04/19/2022] [Indexed: 12/04/2022] Open
Abstract
Neurotransmitters are signaling molecules secreted by neurons to coordinate communication and proper function among different sections in the central neural system (CNS) by binding with different receptors. Some neurotransmitters as well as their receptors are found in pancreatic islets and are involved in the regulation of glucose homeostasis. Neurotransmitters can act with their receptors in pancreatic islets to stimulate or inhibit the secretion of insulin (β cell), glucagon (α cell) or somatostatin (δ cell). Neurotransmitter receptors are either G-protein coupled receptors or ligand-gated channels, their effects on blood glucose are mainly decided by the number and location of them in islets. Dysfunction of neurotransmitters receptors in islets is involved in the development of β cell dysfunction and type 2 diabetes (T2D).Therapies targeting different transmitter systems have great potential in the prevention and treatment of T2D and other metabolic diseases.
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Affiliation(s)
- Xiaohui Pan
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Diabetes and Islet Transplantation, Center for Diabetes and Metabolism Research, West China Hospital, Sichuan University, Chengdu, China
| | - Shibing Tao
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
- Department of Endocrinology, Ziyang First People’s Hospital, Ziyang, China
| | - Nanwei Tong
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Diabetes and Islet Transplantation, Center for Diabetes and Metabolism Research, West China Hospital, Sichuan University, Chengdu, China
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Morze J, Wittenbecher C, Schwingshackl L, Danielewicz A, Rynkiewicz A, Hu FB, Guasch-Ferré M. Metabolomics and Type 2 Diabetes Risk: An Updated Systematic Review and Meta-analysis of Prospective Cohort Studies. Diabetes Care 2022; 45:1013-1024. [PMID: 35349649 PMCID: PMC9016744 DOI: 10.2337/dc21-1705] [Citation(s) in RCA: 147] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 01/20/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND Due to the rapidly increasing availability of metabolomics data in prospective studies, an update of the meta evidence on metabolomics and type 2 diabetes risk is warranted. PURPOSE To conduct an updated systematic review and meta-analysis of plasma, serum, and urine metabolite markers and incident type 2 diabetes. DATA SOURCES We searched PubMed and Embase until 6 March 2021. STUDY SELECTION We selected prospective observational studies where investigators used high-throughput techniques to investigate the relationship between plasma, serum, or urine metabolites and incident type 2 diabetes. DATA EXTRACTION Baseline metabolites per-SD risk estimates and 95% CIs for incident type 2 diabetes were extracted from all eligible studies. DATA SYNTHESIS A total of 61 reports with 71,196 participants and 11,771 type 2 diabetes cases/events were included in the updated review. Meta-analysis was performed for 412 metabolites, of which 123 were statistically significantly associated (false discovery rate-corrected P < 0.05) with type 2 diabetes risk. Higher plasma and serum levels of certain amino acids (branched-chain, aromatic, alanine, glutamate, lysine, and methionine), carbohydrates and energy-related metabolites (mannose, trehalose, and pyruvate), acylcarnitines (C4-DC, C4-OH, C5, C5-OH, and C8:1), the majority of glycerolipids (di- and triacylglycerols), (lyso)phosphatidylethanolamines, and ceramides included in meta-analysis were associated with higher risk of type 2 diabetes (hazard ratio 1.07-2.58). Higher levels of glycine, glutamine, betaine, indolepropionate, and (lyso)phosphatidylcholines were associated with lower type 2 diabetes risk (hazard ratio 0.69-0.90). LIMITATIONS Substantial heterogeneity (I2 > 50%, τ2 > 0.1) was observed for some of the metabolites. CONCLUSIONS Several plasma and serum metabolites, including amino acids, lipids, and carbohydrates, are associated with type 2 diabetes risk.
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Affiliation(s)
- Jakub Morze
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Cardiology and Internal Medicine, School of Medicine, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
- Department of Human Nutrition, Faculty of Food Sciences, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - Clemens Wittenbecher
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Lukas Schwingshackl
- Institute for Evidence in Medicine, Medical Centre—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Anna Danielewicz
- Department of Human Nutrition, Faculty of Food Sciences, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - Andrzej Rynkiewicz
- Department of Cardiology and Internal Medicine, School of Medicine, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - Frank B. Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division for Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division for Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
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Murthy VL, Nayor M, Carnethon M, Reis JP, Lloyd-Jones D, Allen NB, Kitchen R, Piaggi P, Steffen LM, Vasan RS, Freedman JE, Clish CB, Shah RV. Circulating metabolite profile in young adulthood identifies long-term diabetes susceptibility: the Coronary Artery Risk Development in Young Adults (CARDIA) study. Diabetologia 2022; 65:657-674. [PMID: 35041022 PMCID: PMC8969893 DOI: 10.1007/s00125-021-05641-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/10/2021] [Indexed: 12/19/2022]
Abstract
AIMS/HYPOTHESIS The aim of this work was to define metabolic correlates and pathways of diabetes pathogenesis in young adults during a subclinical latent phase of diabetes development. METHODS We studied 2083 young adults of Black and White ethnicity in the prospective observational cohort Coronary Artery Risk Development in Young Adults (CARDIA) study (mean ± SD age 32.1 ± 3.6 years; 43.9% women; 42.7% Black; mean ± SD BMI 25.6 ± 4.9 kg/m2) and 1797 Framingham Heart Study (FHS) participants (mean ± SD age 54.7 ± 9.7 years; 52.1% women; mean ± SD BMI 27.4 ± 4.8 kg/m2), examining the association of comprehensive metabolite profiles with endophenotypes of diabetes susceptibility (adipose and muscle tissue phenotypes and systemic inflammation). Statistical learning techniques and Cox regression were used to identify metabolite signatures of incident diabetes over a median of nearly two decades of follow-up across both cohorts. RESULTS We identified known and novel metabolites associated with endophenotypes that delineate the complex pathophysiological architecture of diabetes, spanning mechanisms of muscle insulin resistance, inflammatory lipid signalling and beta cell metabolism (e.g. bioactive lipids, amino acids and microbe- and diet-derived metabolites). Integrating endophenotypes of diabetes susceptibility with the metabolome generated two multi-parametric metabolite scores, one of which (a proinflammatory adiposity score) was associated with incident diabetes across the life course in participants from both the CARDIA study (young adults; HR in a fully adjusted model 2.10 [95% CI 1.72, 2.55], p<0.0001) and FHS (middle-aged and older adults; HR 1.33 [95% CI 1.14, 1.56], p=0.0004). A metabolite score based on the outcome of diabetes was strongly related to diabetes in CARDIA study participants (fully adjusted HR 3.41 [95% CI 2.85, 4.07], p<0.0001) but not in the older FHS population (HR 1.15 [95% CI 0.99, 1.33], p=0.07). CONCLUSIONS/INTERPRETATION Selected metabolic abnormalities in young adulthood identify individuals with heightened diabetes risk independent of race, sex and traditional diabetes risk factors. These signatures replicate across the life course.
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Affiliation(s)
- Venkatesh L Murthy
- Department of Medicine and Radiology, University of Michigan, Ann Arbor, MI, USA.
| | - Matthew Nayor
- Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | | | - Jared P Reis
- National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | | | | | - Robert Kitchen
- Simches Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Paolo Piaggi
- Department of Information Engineering, University of Pisa, Pisa, Italy
| | - Lyn M Steffen
- University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Ramachandran S Vasan
- Section of Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Jane E Freedman
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Clary B Clish
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Ravi V Shah
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.
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Zhou F, Sun L, Shao Y, Zhang X, Li C. AMPK-mediated glutaminolysis maintains coelomocytes redox homeostasis in Vibrio splendidus-challenged Apostichopus japonicus. FISH & SHELLFISH IMMUNOLOGY 2022; 122:170-180. [PMID: 35150828 DOI: 10.1016/j.fsi.2022.02.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 02/02/2022] [Accepted: 02/07/2022] [Indexed: 06/14/2023]
Abstract
Glutaminolysis has been proved to play an irreplaceable role in vertebrate immunity, including effects on cytokine production, bacterial killing, and redox homeostasis maintenance. Our previous metabolomics analysis indicated that glutaminolysis metabolic substrates glutamine (Gln) and metabolites glutamate (Glu) were significantly lower in Skin ulceration syndrome (SUS)-diseased Apostichopus japonicus. To further delineate the role of glutaminolysis, we assayed the levels of Gln and Glu. We found that their contents in coelomocytes were decreased, accompanied by an increase in glutathione (GSH) in pathogen-challenged Apostichopus japonicus. Consistently, the mRNA transcripts of three key genes in glutaminolysis (AjASCT2, AjGOT, and AjGCS) were significantly induced. Moreover, the increased MDA and NADPH/NADP + levels in response to pathogen infection indicated that oxidative stress occurs during the immune response. The metabolic regulator AMPKβ could regulate glutaminolysis in vertebrates by inducing cells to take up extracellular Gln. To explore the underlying regulatory mechanism behind glutaminolysis that occurred in coelomocytes, the full-length cDNA of AMPKβ was identified from A. japonicus (designated as AjAMPKβ). AjAMPKβ expression was significantly induced in the coelomocytes after pathogen challenge, which was consistent with the expression of key genes of glutaminolysis. A functional assay indicated that AjAMPKβ silencing by siRNA transfection could increase the levels of Gln and Glu and depress the production of GSH. Moreover, the expression of glutaminolysis-related genes was significantly inhibited, and the reduction of redox homeostasis indexes (MDA and NADPH/NADP+) was also observed. Contrastingly, AjAMPKβ overexpression promoted redox homeostasis balance. Intracellular ROS is mostly responsible for breaking redox homeostasis and leading to oxidative stress, contributing to cell fate changes in immune cells. Exogenous Gln and GSH treatments could significantly reduce ROS level while the AjAMPKβ silencing induced the level of ROS and accelerated the necrosis rate. All these results collectively revealed that AjAMPKβ could modulate cellular redox homeostasis by affecting the glutaminolysis in A. japonicus.
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Affiliation(s)
- Fangyuan Zhou
- State Key Laboratory for Quality and Safety of Agro-products, Ningbo University, Ningbo, 315211, PR China; Yantai Marine Economic Research Institute, Yantai, 264034, PR China
| | - Lianlian Sun
- State Key Laboratory for Quality and Safety of Agro-products, Ningbo University, Ningbo, 315211, PR China; State-Province Joint Laboratory of Marine Biotechnology and Engineering, Ningbo University, Ningbo, 315211, China.
| | - Yina Shao
- State Key Laboratory for Quality and Safety of Agro-products, Ningbo University, Ningbo, 315211, PR China; State-Province Joint Laboratory of Marine Biotechnology and Engineering, Ningbo University, Ningbo, 315211, China
| | - Xiumei Zhang
- Yantai Marine Economic Research Institute, Yantai, 264034, PR China
| | - Chenghua Li
- State Key Laboratory for Quality and Safety of Agro-products, Ningbo University, Ningbo, 315211, PR China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266071, PR China; Yantai Marine Economic Research Institute, Yantai, 264034, PR China.
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Izundegui DG, Nayor M. Metabolomics of Type 1 and Type 2 Diabetes: Insights into Risk Prediction and Mechanisms. Curr Diab Rep 2022; 22:65-76. [PMID: 35113332 PMCID: PMC8934149 DOI: 10.1007/s11892-022-01449-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/21/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE OF REVIEW Metabolomics enables rapid interrogation of widespread metabolic processes making it well suited for studying diabetes. Here, we review the current status of metabolomic investigation in diabetes, highlighting its applications for improving risk prediction and mechanistic understanding. RECENT FINDINGS Findings of metabolite associations with type 2 diabetes risk have confirmed experimental observations (e.g., branched-chain amino acids) and also pinpointed novel pathways of diabetes risk (e.g., dimethylguanidino valeric acid). In type 1 diabetes, abnormal metabolite patterns are observed prior to the development of autoantibodies and hyperglycemia. Diabetes complications display specific metabolite signatures that are distinct from the metabolic derangements of diabetes and differ across vascular beds. Lastly, metabolites respond acutely to pharmacologic treatment, providing opportunities to understand inter-individual treatment responses. Metabolomic studies have elucidated biological mechanisms underlying diabetes development, complications, and therapeutic response. While not yet ready for clinical translation, metabolomics is a powerful and promising precision medicine tool.
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Affiliation(s)
| | - Matthew Nayor
- Sections of Cardiology and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, 72 E Concord Street, Suite L-516, Boston, MA, 02118, USA.
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Wang X, Yang R, Zhang W, Wang S, Mu H, Li H, Dong J, Chen W, Yu X, Ji F. Serum glutamate and glutamine-to-glutamate ratio are associated with coronary angiography defined coronary artery disease. Nutr Metab Cardiovasc Dis 2022; 32:186-194. [PMID: 34906414 DOI: 10.1016/j.numecd.2021.09.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 09/15/2021] [Accepted: 09/18/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND AIMS Serum concentrations of glutamate (Glu), Glutamine (Gln) and Gln/Glu ratio have consistently been reported to be associated with metabolic disorders and diabetes. The aim of this study was to examine the relationship between these metabolites with the presence of coronary artery disease (CAD) and CAD severity in Chinese patients. METHODS AND RESULTS 2970 Chinese patients undergoing coronary angiography (CAG) in Beijing Hospital were enrolled. Baseline demographics and medical history data was recorded by questionnaires. Serum Glu and Gln concentrations were analyzed by isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS). Statistical analysis showed that CAD patients had significantly higher levels of Glu and lower Gln/Glu ratios compared with non-CAD control group. Glu was significantly positively associated with body mass index (BMI), fasting blood glucose (FBG), triglycerides (TG), creatinine (Crea), and uric acid (UA), and negatively associated with high-density lipoprotein cholesterol (HDL-C), while inverse associations between Gln/Glu ratio and these risk factors were observed. Glu levels increased and Gln/Glu decreased with the increase of CAD severity as represented by either the number of stenosed vessels or the Gensini scores. Logistic regression analysis demonstrated that, after adjusting for smoking status, obesity or overweight, hypertension, dyslipidemia, diabetes, stroke and family history of premature CAD, high Glu level and low Gln/Glu ratio were positively associated with CAG defined CAD as well as CAD severity expressed by Gensini score. CONCLUSIONS We identified Glu and Gln/Glu ratio independently associated with CAG defined CAD as well as CAD severity in Chinese patients undergoing CAG.
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Affiliation(s)
- Xinyue Wang
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, 100730, PR China
| | - Ruiyue Yang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Wenduo Zhang
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, 100730, PR China
| | - Siming Wang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Hongna Mu
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Hongxia Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Jun Dong
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Wenxiang Chen
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Xue Yu
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, 100730, PR China.
| | - Fusui Ji
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, 100730, PR China.
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Ikeda H. The Effect of Mild Renal Dysfunction on the Assessment of Plasma Amino Acid Concentration and Insulin Resistance in Patients with Type 2 Diabetes Mellitus. J Diabetes Res 2022; 2022:2048300. [PMID: 35734236 PMCID: PMC9208954 DOI: 10.1155/2022/2048300] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 05/23/2022] [Accepted: 05/25/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND An increase in the levels of branched-chain amino acids (BCAAs) and certain aromatic amino acids, such as alanine, in plasma is correlated with insulin resistance (IR) in type 2 diabetes mellitus (T2DM). T2DM is a leading risk factor for chronic kidney disease. Meanwhile, renal dysfunction causes changes in plasma amino acid levels. To date, no study has examined how mild renal dysfunction and IR interact with plasma amino acid levels. This study examines the effects of IR and renal dysfunction on plasma amino acid concentrations in T2DM. METHODS Data were collected from healthy male participants (controls) and male patients with T2DM between May 2018 and February 2022. Blood samples were collected after overnight fasting. IR and renal function were evaluated using the homeostasis model assessment of IR (HOMA-IR) and serum cystatin C (CysC), respectively. RESULTS A total of 49 and 93 participants were included in the control and T2DM groups, respectively. In the T2DM group, eight amino acids (alanine, glutamic acid, glutamine, glycine, isoleucine, leucine, tyrosine, and valine) and total BCAA showed a significant correlation with HOMA-IR (p < 0.01), whereas six amino acids (γ-aminobutyric acid, citrulline, cysteine, glycine, methionine, and valine) and total BCAA showed a significant correlation with 1/CysC (p < 0.02). However, only alanine, glutamic acid, and each BCAA showed significant differences between the control group and the IR T2DM subgroup. Increases in the BCAA levels with T2DM were canceled by renal dysfunction (CysC ≥ 0.93) in patients with intermediate IR. CONCLUSION To use plasma BCAA concentration as a marker of IR, renal function must be considered, even in mild renal dysfunction. Increased alanine and glutamic acid levels indicate IR, regardless of mild renal dysfunction.
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Affiliation(s)
- Hideki Ikeda
- Department of Internal Medicine, Sanyudo Hospital, Chuo 6 Chome-1-219, Yonezawa, Yamagata 992-0045, Japan
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