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Du W, Jiang S, Yin S, Wang R, Zhang C, Yin BC, Li J, Li L, Qi N, Zhou Y, Ye BC. The microbiota-dependent tryptophan metabolite alleviates high-fat diet-induced insulin resistance through the hepatic AhR/TSC2/mTORC1 axis. Proc Natl Acad Sci U S A 2024; 121:e2400385121. [PMID: 39167602 PMCID: PMC11363250 DOI: 10.1073/pnas.2400385121] [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: 01/08/2024] [Accepted: 07/23/2024] [Indexed: 08/23/2024] Open
Abstract
Type 2 diabetes (T2D) is potentially linked to disordered tryptophan metabolism that attributes to the intricate interplay among diet, gut microbiota, and host physiology. However, underlying mechanisms are substantially unknown. Comparing the gut microbiome and metabolome differences in mice fed a normal diet (ND) and high-fat diet (HFD), we uncover that the gut microbiota-dependent tryptophan metabolite 5-hydroxyindole-3-acetic acid (5-HIAA) is present at lower concentrations in mice with versus without insulin resistance. We further demonstrate that the microbial transformation of tryptophan into 5-HIAA is mediated by Burkholderia spp. Additionally, we show that the administration of 5-HIAA improves glucose intolerance and obesity in HFD-fed mice, while preserving hepatic insulin sensitivity. Mechanistically, 5-HIAA promotes hepatic insulin signaling by directly activating AhR, which stimulates TSC2 transcription and thus inhibits mTORC1 signaling. Moreover, T2D patients exhibit decreased fecal levels of 5-HIAA. Our findings identify a noncanonical pathway of microbially producing 5-HIAA from tryptophan and indicate that 5-HIAA might alleviate the pathogenesis of T2D.
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Affiliation(s)
- Wei Du
- Lab of Biosystems and Microanalysis, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai200237, China
| | - Shanshan Jiang
- Institute of Engineering Biology and Health, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou310014, Zhejiang, China
| | - Shengxiang Yin
- Institute of Engineering Biology and Health, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou310014, Zhejiang, China
| | - Rongjiang Wang
- Institute of Engineering Biology and Health, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou310014, Zhejiang, China
| | - Chunling Zhang
- Institute of Engineering Biology and Health, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou310014, Zhejiang, China
| | - Bin-Cheng Yin
- Lab of Biosystems and Microanalysis, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai200237, China
| | - Jialin Li
- Department of Endocrinology and Metabolism, Ningbo First Hospital, Ningbo 315010, Zhejiang, China
| | - Li Li
- Department of Endocrinology and Metabolism, Ningbo First Hospital, Ningbo 315010, Zhejiang, China
| | - Nan Qi
- Institute of Engineering Biology and Health, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou310014, Zhejiang, China
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou510005, Guangdong, China
| | - Ying Zhou
- Lab of Biosystems and Microanalysis, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai200237, China
| | - Bang-Ce Ye
- Lab of Biosystems and Microanalysis, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai200237, China
- Institute of Engineering Biology and Health, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou310014, Zhejiang, China
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Zarei I, Eloranta AM, Klåvus A, Väistö J, Lehtonen M, Mikkonen S, Koistinen VM, Sallinen T, Haapala EA, Lintu N, Soininen S, Haikonen R, Atalay M, Schwab U, Auriola S, Kolehmainen M, Hanhineva K, Lakka TA. Eight-year diet and physical activity intervention affects serum metabolites during childhood and adolescence: A nonrandomized controlled trial. iScience 2024; 27:110295. [PMID: 39055945 PMCID: PMC11269805 DOI: 10.1016/j.isci.2024.110295] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 04/16/2024] [Accepted: 06/14/2024] [Indexed: 07/28/2024] Open
Abstract
Long-term lifestyle interventions in childhood and adolescence can significantly improve cardiometabolic health, but the underlying molecular mechanisms remain poorly understood. To address this knowledge gap, we conducted an 8-year diet and physical activity intervention in a general population of children. The research revealed that the intervention influenced 80 serum metabolites over two years, with 17 metabolites continuing to be affected after eight years. The intervention primarily impacted fatty amides, including palmitic amide, linoleamide, oleamide, and others, as well as unsaturated fatty acids, acylcarnitines, phospholipids, sterols, gut microbiota-derived metabolites, amino acids, and purine metabolites. Particularly noteworthy were the pronounced changes in serum fatty amides. These serum metabolite alterations could represent molecular mechanisms responsible for the observed benefits of long-term lifestyle interventions on cardiometabolic and overall health since childhood. Understanding these metabolic changes may provide valuable insights into the prevention of cardiometabolic and other non-communicable diseases since childhood.
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Affiliation(s)
- Iman Zarei
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Aino-Maija Eloranta
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Anton Klåvus
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Juuso Väistö
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Marko Lehtonen
- School of Pharmacy, Faculty of Health Science, University of Eastern Finland, Kuopio, Finland
- LC-MS Metabolomics Center, Biocenter Kuopio, Kuopio, Finland
| | - Santtu Mikkonen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, Finland
| | - Ville M. Koistinen
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Food Chemistry and Food Development Unit, Department of Biochemistry, University of Turku, Turku, Finland
| | - Taisa Sallinen
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Eero A. Haapala
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Niina Lintu
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Sonja Soininen
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Physician and Nursing Services, Health and Social Services Centre, Wellbeing Services County of North Savo, Varkaus, Finland
| | - Retu Haikonen
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mustafa Atalay
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Ursula Schwab
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Seppo Auriola
- School of Pharmacy, Faculty of Health Science, University of Eastern Finland, Kuopio, Finland
| | - Marjukka Kolehmainen
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Kati Hanhineva
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Food Chemistry and Food Development Unit, Department of Biochemistry, University of Turku, Turku, Finland
| | - Timo A. Lakka
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
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3
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Rochoń J, Kalinowski P, Szymanek-Majchrzak K, Grąt M. Role of gut-liver axis and glucagon-like peptide-1 receptor agonists in the treatment of metabolic dysfunction-associated fatty liver disease. World J Gastroenterol 2024; 30:2964-2980. [PMID: 38946874 PMCID: PMC11212696 DOI: 10.3748/wjg.v30.i23.2964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 05/08/2024] [Accepted: 05/24/2024] [Indexed: 06/21/2024] Open
Abstract
Metabolic dysfunction-associated fatty liver disease (MAFLD) is a hepatic manifestation of the metabolic syndrome. It is one of the most common liver diseases worldwide and shows increasing prevalence rates in most countries. MAFLD is a progressive disease with the most severe cases presenting as advanced fibrosis or cirrhosis with an increased risk of hepatocellular carcinoma. Gut microbiota play a significant role in the pathogenesis and progression of MAFLD by disrupting the gut-liver axis. The mechanisms involved in maintaining gut-liver axis homeostasis are complex. One critical aspect involves preserving an appropriate intestinal barrier permeability and levels of intestinal lumen metabolites to ensure gut-liver axis functionality. An increase in intestinal barrier permeability induces metabolic endotoxemia that leads to steatohepatitis. Moreover, alterations in the absorption of various metabolites can affect liver metabolism and induce liver steatosis and fibrosis. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are a class of drugs developed for the treatment of type 2 diabetes mellitus. They are also commonly used to combat obesity and have been proven to be effective in reversing hepatic steatosis. The mechanisms reported to be involved in this effect include an improved regulation of glycemia, reduced lipid synthesis, β-oxidation of free fatty acids, and induction of autophagy in hepatic cells. Recently, multiple peptide receptor agonists have been introduced and are expected to increase the effectiveness of the treatment. A modulation of gut microbiota has also been observed with the use of these drugs that may contribute to the amelioration of MAFLD. This review presents the current understanding of the role of the gut-liver axis in the development of MAFLD and use of members of the GLP-1 RA family as pleiotropic agents in the treatment of MAFLD.
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Affiliation(s)
- Jakub Rochoń
- Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw 02-097, Poland
| | - Piotr Kalinowski
- Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw 02-097, Poland
| | | | - Michał Grąt
- Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw 02-097, Poland
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4
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Kang R, Guo D, Wang J, Xie Z. Association of dietary nutrient intake with type 2 diabetes: A Mendelian randomization study. Medicine (Baltimore) 2024; 103:e38090. [PMID: 38728475 PMCID: PMC11081547 DOI: 10.1097/md.0000000000038090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/11/2024] [Indexed: 05/12/2024] Open
Abstract
Observational research suggests that the evidence linking dietary nutrient intake (encompassing minerals, vitamins, amino acids, and unsaturated fatty acids) to type 2 diabetes (T2D) is both inconsistent and limited. This study aims to explore the potential causal relationship between dietary nutrients and T2D. Causal estimation utilized Mendelian randomization techniques. Single nucleotide polymorphisms linked to dietary nutrients were identified from existing genome-wide association studies and used as instrumental variables. Genome-wide association studies data pertinent to T2D were sourced from the DIMANTE consortium and the FinnGen database. Techniques including inverse variance weighting (IVW), weighted mode, weighted median, and Mendelian randomization-Egger were employed for causal inference, complemented by sensitivity analysis. Genetically predicted higher phenylalanine (IVW: odds ratio = 1.10 95% confidence interval 1.04-1.17, P = 1.5 × 10-3, q_pval = 3.4 × 10-2) and dihomo-gamma-linolenic acid (IVW: odds ratio = 1.001 95% confidence interval 1.0006-1.003, P = 3.7 × 10-3, q_pval = 4.1 × 10-2) levels were directly associated with T2D risk. Conversely, no causal relationships between other nutrients and T2D were established. We hypothesize that phenylalanine and dihomo-gamma-linolenic acid contribute to the pathogenesis of T2D. Clinically, the use of foods with high phenylalanine content may pose potential risks for patients with a heightened risk of T2D. Our study provides evidence supporting a causal link between dietary nutrient intake and the development of T2D.
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Affiliation(s)
- Ruixiang Kang
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Dong Guo
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jiawei Wang
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zhencong Xie
- Shandong University of Traditional Chinese Medicine, Jinan, China
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5
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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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6
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Margara-Escudero HJ, Paz-Graniel I, García-Gavilán J, Ruiz-Canela M, Sun Q, Clish CB, Toledo E, Corella D, Estruch R, Ros E, Castañer O, Arós F, Fiol M, Guasch-Ferré M, Lapetra J, Razquin C, Dennis C, Deik A, Li J, Gómez-Gracia E, Babio N, Martínez-González MA, Hu FB, Salas-Salvadó J. Plasma metabolite profile of legume consumption and future risk of type 2 diabetes and cardiovascular disease. Cardiovasc Diabetol 2024; 23:38. [PMID: 38245716 PMCID: PMC10800064 DOI: 10.1186/s12933-023-02111-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: 10/31/2023] [Accepted: 12/29/2023] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Legume consumption has been linked to a reduced risk of type 2 diabetes (T2D) and cardiovascular disease (CVD), while the potential association between plasma metabolites associated with legume consumption and the risk of cardiometabolic diseases has never been explored. Therefore, we aimed to identify a metabolite signature of legume consumption, and subsequently investigate its potential association with the incidence of T2D and CVD. METHODS The current cross-sectional and longitudinal analysis was conducted in 1833 PREDIMED study participants (mean age 67 years, 57.6% women) with available baseline metabolomic data. A subset of these participants with 1-year follow-up metabolomics data (n = 1522) was used for internal validation. Plasma metabolites were assessed through liquid chromatography-tandem mass spectrometry. Cross-sectional associations between 382 different known metabolites and legume consumption were performed using elastic net regression. Associations between the identified metabolite profile and incident T2D and CVD were estimated using multivariable Cox regression models. RESULTS Specific metabolic signatures of legume consumption were identified, these included amino acids, cortisol, and various classes of lipid metabolites including diacylglycerols, triacylglycerols, plasmalogens, sphingomyelins and other metabolites. Among these identified metabolites, 22 were negatively and 18 were positively associated with legume consumption. After adjustment for recognized risk factors and legume consumption, the identified legume metabolite profile was inversely associated with T2D incidence (hazard ratio (HR) per 1 SD: 0.75, 95% CI 0.61-0.94; p = 0.017), but not with CVD incidence risk (1.01, 95% CI 0.86-1.19; p = 0.817) over the follow-up period. CONCLUSIONS This study identified a set of 40 metabolites associated with legume consumption and with a reduced risk of T2D development in a Mediterranean population at high risk of cardiovascular disease. TRIAL REGISTRATION ISRCTN35739639.
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Affiliation(s)
- Hernando J Margara-Escudero
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Indira Paz-Graniel
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Jesús García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Miguel Ruiz-Canela
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitario de Navarra (IdiSNA), Pamplona, Spain
| | - Qi Sun
- 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, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Clary B Clish
- The Broad Institute of Harvard and MIT, Boston, MA, 02142, USA
| | - Estefania Toledo
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitario de Navarra (IdiSNA), Pamplona, Spain
- Navarra Institute for Health Research, IdiSNA, Pamplona, Navarre, Spain
| | - Dolores Corella
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramón Estruch
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La 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
| | - Emilio Ros
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Endocrinology and Nutrition, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Lipid Clinic, Hospital Clínic, Barcelona, Spain
| | - Olga Castañer
- Centro de Investigación Biomédica en Red (CIBERESP) de Epidemiología y Salud Pública, Instituto de Salud Carlos III, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Research Institute, Barcelona, Spain
| | - Fernando Arós
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Cardiology, University Hospital of Alava, Vitoria, Spain
| | - Miquel Fiol
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Illes Balears Health Research Institute (IdISBa), Hospital Son Espases, Palma, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - José Lapetra
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Cristina Razquin
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitario de Navarra (IdiSNA), Pamplona, Spain
| | - Courtney Dennis
- The Broad Institute of Harvard and MIT, Boston, MA, 02142, USA
| | - Amy Deik
- The Broad Institute of Harvard and MIT, Boston, MA, 02142, USA
| | - Jun Li
- 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
| | - Enrique Gómez-Gracia
- Preventive Medicine and Public Health Department, School of Medicine, University of Málaga, 29010, Malaga, Spain
- Biomedical Research Institute of Malaga-IBIMA Plataforma BIONAND, 29010, Malaga, Spain
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Miguel A Martínez-González
- Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitario de Navarra (IdiSNA), Pamplona, 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, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
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Wang M, Ou Y, Yuan XL, Zhu XF, Niu B, Kang Z, Zhang B, Ahmed A, Xing GQ, Su H. Heterogeneously elevated branched-chain/aromatic amino acids among new-onset type-2 diabetes mellitus patients are potentially skewed diabetes predictors. World J Diabetes 2024; 15:53-71. [PMID: 38313852 PMCID: PMC10835491 DOI: 10.4239/wjd.v15.i1.53] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/03/2023] [Accepted: 12/13/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND The lack of specific predictors for type-2 diabetes mellitus (T2DM) severely impacts early intervention/prevention efforts. Elevated branched-chain amino acids (BCAAs: Isoleucine, leucine, valine) and aromatic amino acids (AAAs: Tyrosine, tryptophan, phenylalanine)) show high sensitivity and specificity in predicting diabetes in animals and predict T2DM 10-19 years before T2DM onset in clinical studies. However, improvement is needed to support its clinical utility. AIM To evaluate the effects of body mass index (BMI) and sex on BCAAs/AAAs in new-onset T2DM individuals with varying body weight. METHODS Ninety-seven new-onset T2DM patients (< 12 mo) differing in BMI [normal weight (NW), n = 33, BMI = 22.23 ± 1.60; overweight, n = 42, BMI = 25.9 ± 1.07; obesity (OB), n = 22, BMI = 31.23 ± 2.31] from the First People's Hospital of Yunnan Province, Kunming, China, were studied. One-way and 2-way ANOVAs were conducted to determine the effects of BMI and sex on BCAAs/AAAs. RESULTS Fasting serum AAAs, BCAAs, glutamate, and alanine were greater and high-density lipoprotein (HDL) was lower (P < 0.05, each) in OB-T2DM patients than in NW-T2DM patients, especially in male OB-T2DM patients. Arginine, histidine, leucine, methionine, and lysine were greater in male patients than in female patients. Moreover, histidine, alanine, glutamate, lysine, valine, methionine, leucine, isoleucine, tyrosine, phenylalanine, and tryptophan were significantly correlated with abdominal adiposity, body weight and BMI, whereas isoleucine, leucine and phenylalanine were negatively correlated with HDL. CONCLUSION Heterogeneously elevated amino acids, especially BCAAs/AAAs, across new-onset T2DM patients in differing BMI categories revealed a potentially skewed prediction of T2DM development. The higher BCAA/AAA levels in obese T2DM patients would support T2DM prediction in obese individuals, whereas the lower levels of BCAAs/AAAs in NW-T2DM individuals may underestimate T2DM risk in NW individuals. This potentially skewed T2DM prediction should be considered when BCAAs/AAAs are to be used as the T2DM predictor.
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Affiliation(s)
- Min Wang
- School of Chemical Science and Technology, Yunnan University, Kunming 650091, Yunnan Province, China
| | - Yang Ou
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Xiang-Lian Yuan
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Xiu-Fang Zhu
- School of Chemical Science and Technology, Yunnan University, Kunming 650091, Yunnan Province, China
| | - Ben Niu
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Zhuang Kang
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Bing Zhang
- Clinical Laboratory, Nanchong Central Hospital & The Second Clinical Medical College of North Sichuan Medical University, Nanchong 637000, Sichuan Province, China
| | - Anwar Ahmed
- Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, United States
| | - Guo-Qiang Xing
- The Affiliated Hospital and Second Clinical Medical College, North Sichuan Medical University, Nanchong 637000, Sichuan Province, China
- Department of Research and Development, Lotus Biotech.com LLC, Gaithersburg, MD 20878, United States
| | - Heng Su
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
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8
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Xu X, Zhang F, Ren J, Zhang H, Jing C, Wei M, Jiang Y, Xie H. Dietary intervention improves metabolic levels in patients with type 2 diabetes through the gut microbiota: a systematic review and meta-analysis. Front Nutr 2024; 10:1243095. [PMID: 38260058 PMCID: PMC10800606 DOI: 10.3389/fnut.2023.1243095] [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: 06/20/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Background Poor dietary structure plays a pivotal role in the development and progression of type 2 diabetes and is closely associated with dysbiosis of the gut microbiota. Thus, the objective of this systematic review was to assess the impact of dietary interventions on improving gut microbiota and metabolic levels in patients with type 2 diabetes. Methods We conducted a systematic review and meta-analysis following the PRISMA 2020 guidelines. Results Twelve studies met the inclusion criteria. In comparison to baseline measurements, the high-fiber diet produced substantial reductions in FBG (mean difference -1.15 mmol/L; 95% CI, -2.24 to -0.05; I2 = 94%; P = 0.04), HbA1c (mean difference -0.99%; 95% CI, -1.93 to -0.03; I2 = 89%; P = 0.04), and total cholesterol (mean difference -0.95 mmol/L; 95% CI, -1.57 to -0.33; I2 = 77%; P = 0.003); the high-fat and low-carbohydrate diet led to a significant reduction in HbA1c (mean difference -0.98; 95% CI, -1.50 to -0.46; I2 = 0%; P = 0.0002). Within the experimental group (intervention diets), total cholesterol (mean difference -0.69 mmol/L; 95% CI, -1.27 to -0.10; I2 = 52%; P = 0.02) and LDL-C (mean difference -0.45 mmol/L; 95% CI, -0.68 to -0.22; I2 = 0%; P < 0.0001) experienced significant reductions in comparison to the control group (recommended diets for type 2 diabetes). However, no statistically significant differences emerged in the case of FBG, HbA1c, HOMA-IR, and HDL-C between the experimental and control groups. The high dietary fiber diet triggered an augmented presence of short-chain fatty acid-producing bacteria in the intestines of individuals with T2DM. In addition, the high-fat and low-carbohydrate diet resulted in a notable decrease in Bacteroides abundance while simultaneously increasing the relative abundance of Eubacterium. Compared to a specific dietary pattern, personalized diets appear to result in the production of a greater variety of beneficial bacteria in the gut, leading to more effective blood glucose control in T2D patients. Conclusion Dietary interventions hold promise for enhancing metabolic profiles in individuals with T2D through modulation of the gut microbiota. Tailored dietary regimens appear to be more effective than standard diets in improving glucose metabolism. However, given the limited and highly heterogeneous nature of the current sample size, further well-designed and controlled intervention studies are warranted in the future.
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Affiliation(s)
- Xiaoyu Xu
- School of Public Health, Bengbu Medical University, Bengbu, China
| | - Fan Zhang
- School of Public Health, Bengbu Medical University, Bengbu, China
| | - Jiajia Ren
- School of Public Health, Bengbu Medical University, Bengbu, China
| | - Haimeng Zhang
- School of Public Health, Bengbu Medical University, Bengbu, China
| | - Cuiqi Jing
- School of Public Health, Bengbu Medical University, Bengbu, China
| | - Muhong Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Bengbu Medical University, Bengbu, China
| | - Yuhong Jiang
- Department of Epidemiology and Health Statistics, School of Public Health, Bengbu Medical University, Bengbu, China
| | - Hong Xie
- Department of Nutrition and Food Hygiene, School of Public Health, Bengbu Medical University, Bengbu, China
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Patel N, Dinesh S, Sharma S. From Gut to Glucose: A Comprehensive Review on Functional Foods and Dietary Interventions for Diabetes Management. Curr Diabetes Rev 2024; 20:e111023222081. [PMID: 37861021 DOI: 10.2174/0115733998266653231005072450] [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: 06/10/2023] [Revised: 07/17/2023] [Accepted: 08/25/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND In the realm of diabetes research, considerable attention has been directed toward elucidating the intricate interplay between the gastrointestinal tract and glucose regulation. The gastrointestinal tract, once exclusively considered for its role in digestion and nutrient assimilation, is presently acknowledged as a multifaceted ecosystem with regulatory supremacy over metabolic homeostasis and glucose metabolism. Recent studies indicate that alterations in the composition and functionality of the gut microbiota could potentially influence the regulation of glucose levels and glucose homeostasis in the body. Dysbiosis, characterized by perturbations in the equilibrium of gut microbial constituents, has been irrevocably linked to an augmented risk of diabetes mellitus (DM). Moreover, research has revealed the potential influence of the gut microbiota on important factors, like inflammation and insulin sensitivity, which are key contributors to the onset and progression of diabetes. The key protagonists implicated in the regulation of glucose encompass the gut bacteria, gut barrier integrity, and the gut-brain axis. A viable approach to enhance glycemic control while concurrently mitigating the burden of comorbidities associated with diabetes resides in the strategic manipulation of the gut environment through adapted dietary practices. OBJECTIVE This review aimed to provide a deep understanding of the complex relationship between gut health, glucose metabolism, and diabetes treatment. CONCLUSION This study has presented an exhaustive overview of dietary therapies and functional foods that have undergone extensive research to explore their potential advantages in the management of diabetes. It looks into the role of gut health in glucose regulation, discusses the impact of different dietary elements on the course of diabetes, and evaluates how well functional foods can help with glycemic control. Furthermore, it investigates the mechanistic aspects of these therapies, including their influence on insulin sensitivity, β-cell activity, and inflammation. It deliberates on the limitations and potential prospects associated with integrating functional foods into personalized approaches to diabetes care.
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Affiliation(s)
- Nirali Patel
- Department of Bioinformatics, BioNome, Bengaluru 560043, India
| | - Susha Dinesh
- Department of Bioinformatics, BioNome, Bengaluru 560043, India
| | - Sameer Sharma
- Department of Bioinformatics, BioNome, Bengaluru 560043, India
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10
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Paz-Graniel I, García-Gavilán JF, Ros E, Connelly MA, Babio N, Mantzoros CS, Salas-Salvadó J. Adherence to the Mediterranean diet and nuclear magnetic resonance spectroscopy biomarkers in older individuals at high cardiovascular disease risk: cross-sectional and longitudinal analyses. Am J Clin Nutr 2024; 119:108-116. [PMID: 37949173 DOI: 10.1016/j.ajcnut.2023.11.003] [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: 04/13/2023] [Revised: 10/19/2023] [Accepted: 11/06/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND The Mediterranean diet (MedDiet) has been related to a decreased risk of cardiovascular disease (CVD) and diabetes. OBJECTIVES We aimed to prospectively assess the relationship between adherence to the MedDiet and advanced lipoprotein subclass profiles and glucose metabolism and inflammation markers, as determined by nuclear magnetic resonance (NMR) spectroscopy. DESIGN We conducted cross-sectional and longitudinal analyses within the framework of the PREvención con DIeta MEDiterránea study in 196 participants from the Reus-Tarragona center. Adherence to the MedDiet was assessed using a 14-item validated questionnaire [Mediterranean Diet Adherence Score (MEDAS)]. Plasma lipoprotein subclasses and molecular metabolite profiles were determined using NMR spectra collected on a Vantera Clinical Analyzer at baseline and after 1 y of follow-up. Baseline and 1-y categories of MEDAS were related to measures of lipoprotein atherogenicity and diabetes risk using multivariable-adjusted analysis of covariance models. RESULTS Compared with participants in the lowest category of baseline MEDAS, those in the highest category showed higher concentrations of total high-density lipoprotein (HDL) particles and H1P HDL, lower concentrations of very low-density lipoprotein (VLDL)-triglyceride, smaller size of VLDL, and lower concentrations of very large VLDL, as well as lower concentrations of branched-chain amino acids, leucine, and GlycA and reduced Diabetes Risk Index (DRI) scores. In addition, participants who increased by 3 or more points in their 1-y MEDAS showed an increase in concentrations of H7P-HDL, H5P-HDL, and citrate, and reduced acetone and DRI scores compared with those with lesser adherence increases. CONCLUSIONS In older adults at high cardiometabolic risk, higher MEDAS was associated with modest beneficial changes in lipoprotein and glucose metabolism. The results suggest that lipoprotein subclass distribution and glycemic control are potential mechanisms behind the well-known salutary effects of MedDiet on CVD and diabetes risk. Future clinical trials exploring the effects of the MedDiet on advanced lipoprotein subclass profiles and glucose metabolism markers are needed to confirm the results of our study. TRIAL REGISTRATION NUMBER This trial was registered at controlled-trials.com as ISRCTN35739639.
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Affiliation(s)
- Indira Paz-Graniel
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain; CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Jesús F García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain; CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
| | - Emilio Ros
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain; Lipid Clinic, Department of Endocrinology and Nutrition, Agust Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | | | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain; CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Christos S Mantzoros
- Department of Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, United States; Section of Endocrinology, VA Boston Healthcare System, Jamaica Plain, MA, United States
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain; CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
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Luque-Córdoba D, Ledesma-Escobar CA, Priego-Capote F. Qualitative and quantitative determination of phenols and their metabolites in urine by in-syringe solid-phase extraction and LC-MS/MS analysis for evaluation of virgin olive oil metabolism. Talanta 2024; 266:125029. [PMID: 37549566 DOI: 10.1016/j.talanta.2023.125029] [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: 06/05/2023] [Revised: 07/31/2023] [Accepted: 08/02/2023] [Indexed: 08/09/2023]
Abstract
To know the bioavailability of virgin olive oil (VOO) phenols and its impact on health, it is necessary to determine the levels of phenols excreted in urine. We present here a novel strategy for in-syringe solid-phase extraction and analysis of the extract by liquid chromatography-tandem mass spectrometry (LC-MS/MS), using ammonium fluoride as ionization agent to enhance sensitivity. This approach allows avoiding additional steps such as solvent evaporation or analytes derivatization. The method can be used with a previous acid hydrolysis for quantitative determination of tyrosol and hydroxytyrosol to estimate metabolized phenols. We tested this application by analysis of a cohort of volunteers (n = 20) after a standardized intake of VOO. Additionally, the method can be used as such for metabolite profiling of phenolic derivatives in urine using LC-MS/MS in high-resolution data-independent acquisition (DIA). Information about the phenolic profile of the consumed VOO and the human metabolism is thus obtained. The proposed approach represents a simple and versatile tool for qualitative and quantitative characterization of VOO phenolic metabolism.
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Affiliation(s)
- D Luque-Córdoba
- Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Córdoba, Córdoba, Spain; Chemical Institute for Energy and Environment (IQUEMA), Campus of Rabanales, University of Córdoba, Córdoba, Spain; Maimónides Institute of Biomedical Research (IMIBIC), Reina Sofía University Hospital, University of Córdoba, Córdoba, Spain; Consortium for Biomedical Research in Frailty & Healthy Ageing, CIBERFES, Carlos III Institute of Health, Spain
| | - C A Ledesma-Escobar
- Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Córdoba, Córdoba, Spain; Chemical Institute for Energy and Environment (IQUEMA), Campus of Rabanales, University of Córdoba, Córdoba, Spain; Maimónides Institute of Biomedical Research (IMIBIC), Reina Sofía University Hospital, University of Córdoba, Córdoba, Spain; Consortium for Biomedical Research in Frailty & Healthy Ageing, CIBERFES, Carlos III Institute of Health, Spain.
| | - F Priego-Capote
- Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Córdoba, Córdoba, Spain; Chemical Institute for Energy and Environment (IQUEMA), Campus of Rabanales, University of Córdoba, Córdoba, Spain; Maimónides Institute of Biomedical Research (IMIBIC), Reina Sofía University Hospital, University of Córdoba, Córdoba, Spain; Consortium for Biomedical Research in Frailty & Healthy Ageing, CIBERFES, Carlos III Institute of Health, Spain.
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12
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García-Gavilán JF, Babio N, Toledo E, Semnani-Azad Z, Razquin C, Dennis C, Deik A, Corella D, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Lapetra J, Lamuela-Raventos R, Clish C, Ruiz-Canela M, Martínez-González MÁ, Hu F, Salas-Salvadó J, Guasch-Ferré M. Olive oil consumption, plasma metabolites, and risk of type 2 diabetes and cardiovascular disease. Cardiovasc Diabetol 2023; 22:340. [PMID: 38093289 PMCID: PMC10720204 DOI: 10.1186/s12933-023-02066-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 11/14/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Olive oil consumption has been inversely associated with the risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, the impact of olive oil consumption on plasma metabolites remains poorly understood. This study aims to identify plasma metabolites related to total and specific types of olive oil consumption, and to assess the prospective associations of the identified multi-metabolite profiles with the risk of T2D and CVD. METHODS The discovery population included 1837 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) trial with available metabolomics data at baseline. Olive oil consumption was determined through food-frequency questionnaires (FFQ) and adjusted for total energy. A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation sample. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known candidate metabolites and olive oil consumption were assessed using elastic net regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite-weighted models and FFQ-derived olive oil consumption in each pair of training-validation data sets within the discovery sample. We further estimated the prospective associations of the identified plasma multi-metabolite profile with incident T2D and CVD using multivariable Cox regression models. RESULTS We identified a metabolomic signature for the consumption of total olive oil (with 74 metabolites), VOO (with 78 metabolites), and COO (with 17 metabolites), including several lipids, acylcarnitines, and amino acids. 10-CV Pearson correlation coefficients between total olive oil consumption derived from FFQs and the multi-metabolite profile were 0.40 (95% CI 0.37, 0.44) and 0.27 (95% CI 0.22, 0.31) for the discovery and validation sample, respectively. We identified several overlapping and distinct metabolites according to the type of olive oil consumed. The baseline metabolite profiles of total and extra virgin olive oil were inversely associated with CVD incidence (HR per 1SD: 0.79; 95% CI 0.67, 0.92 for total olive oil and 0.70; 0.59, 0.83 for extra virgin olive oil) after adjustment for confounders. However, no significant associations were observed between these metabolite profiles and T2D incidence. CONCLUSIONS This study reveals a panel of plasma metabolites linked to the consumption of total and specific types of olive oil. The metabolite profiles of total olive oil consumption and extra virgin olive oil were associated with a decreased risk of incident CVD in a high cardiovascular-risk Mediterranean population, though no associations were observed with T2D incidence. TRIAL REGISTRATION The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).
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Affiliation(s)
- Jesús F García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Estefanía Toledo
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Cristina Razquin
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | | | - Amy Deik
- The Broad Institute of Harvard and MIT, Boston, MA, USA
| | - Dolores Corella
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramón Estruch
- CIBER de Fisiopatología de la Obesidad y Nutrición, 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
- Institut de Nutrició I Seguretat Alimentària (INSA-UB), Universitat de Barcelona, Barcelona, Spain
| | - Emilio Ros
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Endocrinology and Nutrition, Lipid Clinic, IDIBAPS, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Montserrat Fitó
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Cardiovascular and Nutrition Research Group, Institut de Recerca Hospital del Mar, Barcelona, Spain
| | - Fernando Arós
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01009, Vitoria-Gasteiz, Spain
| | - Miquel Fiol
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Plataforma de Ensayos Clínicos, Instituto de Investigación Sanitaria Illes Balears (IdISBa), Hospital Universitario Son Espases, 07120, Palma, Spain
| | - José Lapetra
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Rosa Lamuela-Raventos
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Institut de Nutrició I Seguretat Alimentària (INSA-UB), Universitat de Barcelona, Barcelona, Spain
- Polyphenol Research Group, Departament de Nutrició, Ciències de L'Alimentació I Gastronomia, Universitat de Barcelon (UB), Av. de Joan XXII, 27-31, 08028, Barcelona, Spain
| | - Clary Clish
- The Broad Institute of Harvard and MIT, Boston, MA, USA
| | - Miguel Ruiz-Canela
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Miguel Ángel Martínez-González
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Frank 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
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen, Denmark.
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13
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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: 3] [Impact Index Per Article: 3.0] [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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14
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Rios S, García-Gavilán JF, Babio N, Paz-Graniel I, Ruiz-Canela M, Liang L, Clish CB, Toledo E, Corella D, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Guasch-Ferré M, Santos-Lozano JM, Li J, Razquin C, Martínez-González MÁ, Hu FB, Salas-Salvadó J. Plasma metabolite profiles associated with the World Cancer Research Fund/American Institute for Cancer Research lifestyle score and future risk of cardiovascular disease and type 2 diabetes. Cardiovasc Diabetol 2023; 22:252. [PMID: 37716984 PMCID: PMC10505328 DOI: 10.1186/s12933-023-01912-6] [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: 04/24/2023] [Accepted: 07/01/2023] [Indexed: 09/18/2023] Open
Abstract
BACKGROUND A healthy lifestyle (HL) has been inversely related to type 2 diabetes (T2D) and cardiovascular disease (CVD). However, few studies have identified a metabolite profile associated with HL. The present study aims to identify a metabolite profile of a HL score and assess its association with the incidence of T2D and CVD in individuals at high cardiovascular risk. METHODS In a subset of 1833 participants (age 55-80y) of the PREDIMED study, we estimated adherence to a HL using a composite score based on the 2018 Word Cancer Research Fund/American Institute for Cancer Research recommendations. Plasma metabolites were analyzed using LC-MS/MS methods at baseline (discovery sample) and 1-year of follow-up (validation sample). Cross-sectional associations between 385 known metabolites and the HL score were assessed using elastic net regression. A 10-cross-validation procedure was used, and correlation coefficients or AUC were assessed between the identified metabolite profiles and the self-reported HL score. We estimated the associations between the identified metabolite profiles and T2D and CVD using multivariable Cox regression models. RESULTS The metabolite profiles that identified HL as a dichotomous or continuous variable included 24 and 58 metabolites, respectively. These are amino acids or derivatives, lipids, and energy intermediates or xenobiotic compounds. After adjustment for potential confounders, baseline metabolite profiles were associated with a lower risk of T2D (hazard ratio [HR] and 95% confidence interval (CI): 0.54, 0.38-0.77 for dichotomous HL, and 0.22, 0.11-0.43 for continuous HL). Similar results were observed with CVD (HR, 95% CI: 0.59, 0.42-0.83 for dichotomous HF and HR, 95%CI: 0.58, 0.31-1.07 for continuous HL). The reduction in the risk of T2D and CVD was maintained or attenuated, respectively, for the 1-year metabolomic profile. CONCLUSIONS In an elderly population at high risk of CVD, a set of metabolites was selected as potential metabolites associated with the HL pattern predicting the risk of T2D and, to a lesser extent, CVD. These results support previous findings that some of these metabolites are inversely associated with the risk of T2D and CVD. TRIAL REGISTRATION The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).
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Affiliation(s)
- Santiago Rios
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Jesús F García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Indira Paz-Graniel
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Miguel Ruiz-Canela
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, 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
| | - Clary B Clish
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Estefania Toledo
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Dolores Corella
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramón Estruch
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Emilio Ros
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Endocrinology and Nutrition, Lipid Clinic, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Montserrat Fitó
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d'Investigació Médica (IMIM), Barcelona, Spain
| | - Fernando Arós
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Cardiology, Hospital Universitario de Álava, Vitoria, Spain
| | - Miquel Fiol
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Hospital Son Espases, Palma de Mallorca, Spain
| | - 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, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - José M Santos-Lozano
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Department of Family Medicine, Distrito Sanitario Atención Primaria Sevilla, Sevilla, Spain
| | - Jun Li
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Hospital Son Espases, Palma de Mallorca, Spain
| | - Cristina Razquin
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Miguel Ángel Martínez-González
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
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15
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Ding Y, Wang S, Lu J. Unlocking the Potential: Amino Acids' Role in Predicting and Exploring Therapeutic Avenues for Type 2 Diabetes Mellitus. Metabolites 2023; 13:1017. [PMID: 37755297 PMCID: PMC10535527 DOI: 10.3390/metabo13091017] [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: 08/10/2023] [Revised: 09/08/2023] [Accepted: 09/13/2023] [Indexed: 09/28/2023] Open
Abstract
Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), imposes a significant global burden with adverse clinical outcomes and escalating healthcare expenditures. Early identification of biomarkers can facilitate better screening, earlier diagnosis, and the prevention of diabetes. However, current clinical predictors often fail to detect abnormalities during the prediabetic state. Emerging studies have identified specific amino acids as potential biomarkers for predicting the onset and progression of diabetes. Understanding the underlying pathophysiological mechanisms can offer valuable insights into disease prevention and therapeutic interventions. This review provides a comprehensive summary of evidence supporting the use of amino acids and metabolites as clinical biomarkers for insulin resistance and diabetes. We discuss promising combinations of amino acids, including branched-chain amino acids, aromatic amino acids, glycine, asparagine and aspartate, in the prediction of T2DM. Furthermore, we delve into the mechanisms involving various signaling pathways and the metabolism underlying the role of amino acids in disease development. Finally, we highlight the potential of targeting predictive amino acids for preventive and therapeutic interventions, aiming to inspire further clinical investigations and mitigate the progression of T2DM, particularly in the prediabetic stage.
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Affiliation(s)
- Yilan Ding
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.D.); (S.W.)
- Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Shuangyuan Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.D.); (S.W.)
- Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.D.); (S.W.)
- Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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16
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Gan L, Inamura Y, Shimizu Y, Yokoi Y, Ohnishi Y, Song Z, Kumaki Y, Kikukawa T, Demura M, Ito M, Ayabe T, Nakamura K, Aizawa T. A Basic Study of the Effects of Mulberry Leaf Administration to Healthy C57BL/6 Mice on Gut Microbiota and Metabolites. Metabolites 2023; 13:1003. [PMID: 37755283 PMCID: PMC10535692 DOI: 10.3390/metabo13091003] [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: 08/12/2023] [Revised: 09/05/2023] [Accepted: 09/05/2023] [Indexed: 09/28/2023] Open
Abstract
Mulberry leaves contain α-glucosidase inhibitors, which have hypoglycemic effects and are considered functional foods. However, few reports have covered the effects of mulberry leaf components on normal gut microbiota and gut metabolites. Herein, gut microbiota analysis and NMR-based metabolomics were performed on the feces of mulberry leaf powder (MLP)-treated mice to determine the effects of long-term MLP consumption. Gut microbiota in the mouse were analyzed using 16S-rRNA gene sequencing, and no significant differences were revealed in the diversity and community structure of the gut microbiota in the C57BL/6 mice with or without MLP supplementation. Thirty-nine metabolites were identified via 1H-NMR analysis, and carbohydrates and amino acids were significantly (p < 0.01-0.05) altered upon MLP treatment. In the MLP-treated group, there was a marked increase and decrease in maltose and glucose concentrations, respectively, possibly due to the degradation inhibitory activity of oligosaccharides. After 5 weeks, all amino acid concentrations decreased. Furthermore, despite clear fluctuations in fecal saccharide concentrations, short-chain fatty acid production via intestinal bacterial metabolism was not strongly affected. This study provides the knowledge that MLP administration can alter the gut metabolites without affecting the normal gut microbiota, which is useful for considering MLP as a healthy food source.
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Affiliation(s)
- Li Gan
- Laboratory of Protein Science, Graduate School of Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
| | - Yuga Inamura
- Laboratory of Protein Science, Graduate School of Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
- Laboratory of Biological Information Analysis Science, Faculty of Advanced Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
| | - Yu Shimizu
- Innate Immunity Laboratory, Faculty of Advanced Life Science, Hokkaido University, Sapporo 001-0021, Hokkaido, Japan
| | - Yuki Yokoi
- Innate Immunity Laboratory, Faculty of Advanced Life Science, Hokkaido University, Sapporo 001-0021, Hokkaido, Japan
| | - Yuki Ohnishi
- Laboratory of Protein Science, Graduate School of Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
| | - Zihao Song
- Laboratory of Protein Science, Graduate School of Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
| | - Yasuhiro Kumaki
- Laboratory of Protein Science, Graduate School of Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
| | - Takashi Kikukawa
- Laboratory of Biological Information Analysis Science, Faculty of Advanced Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
| | - Makoto Demura
- Laboratory of Biological Information Analysis Science, Faculty of Advanced Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
| | - Masaaki Ito
- National Institute of Technology, Okinawa College, Nago 905-2192, Okinawa, Japan
| | - Tokiyoshi Ayabe
- Innate Immunity Laboratory, Faculty of Advanced Life Science, Hokkaido University, Sapporo 001-0021, Hokkaido, Japan
| | - Kiminori Nakamura
- Innate Immunity Laboratory, Faculty of Advanced Life Science, Hokkaido University, Sapporo 001-0021, Hokkaido, Japan
| | - Tomoyasu Aizawa
- Laboratory of Protein Science, Graduate School of Life Science, Hokkaido University, Sapporo 060-0810, Hokkaido, Japan
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17
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Yao X, Kong X, Ren J, Cui Y, Chen S, Cheng J, Gao J, Sun J, Xu X, Hu W, Li H, Che F, Wan Q. Transcranial direct-current stimulation confers neuroprotection by regulating isoleucine-dependent signalling after rat cerebral ischemia-reperfusion injury. Eur J Neurosci 2023; 58:3330-3346. [PMID: 37452630 DOI: 10.1111/ejn.16091] [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: 04/22/2023] [Revised: 06/25/2023] [Accepted: 06/28/2023] [Indexed: 07/18/2023]
Abstract
Isoleucine is a branched chain amino acid. The role of isoleucine in cerebral ischemia-reperfusion injury remains unclear. Here, we show that the concentration of isoleucine is decreased in cerebrospinal fluid in a rat model of cerebral ischemia-reperfusion injury, the rat middle cerebral artery occlusion (MCAO). To our surprise, the level of intraneuronal isoleucine is increased in an in vitro model of cerebral ischemia injury, the oxygen-glucose deprivation (OGD). We found that the increased activity of LAT1, an L-type amino acid transporter 1, leads to the elevation of intraneuronal isoleucine after OGD insult. Reducing the level of intraneuronal isoleucine promotes cell survival after cerebral ischemia-reperfusion injury, but supplementing isoleucine aggravates the neuronal damage. To understand how isoleucine promotes ischemia-induced neuronal death, we reveal that isoleucine acts upstream to reduce the expression of CBFB (core binding factor β, a transcript factor involved in cell development and growth) and that the phosphatase PTEN acts downstream of CBFB to mediate isoleucine-induced neuronal damage after OGD insult. Interestingly, we demonstrate that direct-current stimulation reduces the level of intraneuronal isoleucine in cortical cultures subjected to OGD and that transcranial direct-current stimulation (tDCS) decreases the cerebral infarct volume of MCAO rat through reducing LAT1-depencent increase of intraneuronal isoleucine. Together, these results lead us to conclude that LAT1 over activation-dependent isoleucine-CBFB-PTEN signal transduction pathway may mediate ischemic neuronal injury and that tDCS exerts its neuroprotective effect by suppressing LAT1 over activation-dependent signalling after cerebral ischemia-reperfusion injury.
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Affiliation(s)
- Xujin Yao
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
| | - Xiangyi Kong
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
| | - Jinyang Ren
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
| | - Yu Cui
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
| | - Songfeng Chen
- Department of Physiology, School of Medicine, Wuhan University, Wuhan, China
| | - Jing Cheng
- Department of Physiology, School of Medicine, Wuhan University, Wuhan, China
| | - Jingchen Gao
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
| | - Jiangdong Sun
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
| | - Xiangyu Xu
- Department of Rehabilitation, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Wenjie Hu
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
| | - Huanting Li
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
| | - Fengyuan Che
- Central Laboratory, Department of Neurology, Linyi People's Hospital, Qingdao University, Linyi, Shandong, China
| | - Qi Wan
- Institute of Neuroregeneration and Neurorehabilitation, Department of Pathophysiology, Qingdao University, Qingdao, China
- Qingdao Gui-Hong Intelligent Medical Technology Co. Ltd, Qingdao, China
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18
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Isaakidis A, Maghariki JE, Carvalho-Barros S, Gomes AM, Correia M. Is There More to Olive Oil than Healthy Lipids? Nutrients 2023; 15:3625. [PMID: 37630815 PMCID: PMC10459315 DOI: 10.3390/nu15163625] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 07/21/2023] [Accepted: 07/27/2023] [Indexed: 08/27/2023] Open
Abstract
The Mediterranean diet is a healthy dietary pattern whose main characteristic is olive oil consumption. The potential health benefits of olive oil have been extensively investigated and the present review provides the more recent clinical evidence supporting the positive impact of olive oil intake on human health. PubMed (n = 227) and Scopus (n = 308) databases were searched for published clinical studies in English over the past six years (October 2016 to December 2022), following key word searches of "olive oil" and "health". Major findings associated olive oil with antioxidant and anti-inflammatory effects, improvement in endothelial function and lipid profile, prevention of obesity, diabetes, cardiovascular and neurodegenerative diseases, and modulation of the gut microbiota. These benefits are attributed to the nutritional composition of olive oil, which has a high content of monounsaturated fatty acids (MUFA) (oleic acid in particular) and minor compounds such as polyphenols (oleuropein and hydroxytyrosol). Although additional research continues to be required, the more recently generated evidence supports the potential of olive oil to contribute beneficially to health and to the prevention and management of a variety of non-communicable diseases, as a consequence of the synergism between its components' complexity.
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Affiliation(s)
- Akritas Isaakidis
- Centro de Biotecnologia e Química Fina (CBQF)-Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Diogo Botelho 1327, 4169-005 Porto, Portugal (J.E.M.); (M.C.)
- Department of Nutritional Sciences and Dietetics, International Hellenic University of Thessaloniki, Sindos, 57400 Thessaloniki, Greece
| | - Jane El Maghariki
- Centro de Biotecnologia e Química Fina (CBQF)-Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Diogo Botelho 1327, 4169-005 Porto, Portugal (J.E.M.); (M.C.)
| | - Sérgio Carvalho-Barros
- Centro de Biotecnologia e Química Fina (CBQF)-Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Diogo Botelho 1327, 4169-005 Porto, Portugal (J.E.M.); (M.C.)
| | - Ana Maria Gomes
- Centro de Biotecnologia e Química Fina (CBQF)-Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Diogo Botelho 1327, 4169-005 Porto, Portugal (J.E.M.); (M.C.)
| | - Marta Correia
- Centro de Biotecnologia e Química Fina (CBQF)-Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Diogo Botelho 1327, 4169-005 Porto, Portugal (J.E.M.); (M.C.)
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19
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Zheng XX, Li DX, Li YT, Chen YL, Zhao YL, Ji S, Guo MZ, Du Y, Tang DQ. Mulberry leaf water extract alleviates type 2 diabetes in mice via modulating gut microbiota-host co-metabolism of branched-chain amino acid. Phytother Res 2023; 37:3195-3210. [PMID: 37013717 DOI: 10.1002/ptr.7822] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/21/2023] [Accepted: 03/24/2023] [Indexed: 04/05/2023]
Abstract
Elevations in circling branched-chain amino acids (BCAAs) levels associated with insulin resistance and type 2 diabetes mellitus (T2DM). Morus alba L. water extracts (MLE) show hypoglycemic function, but the precise mechanism remains obscure. This study is designed to investigate the association of the antidiabetes effect of MLE with the BCAAs co-metabolism modulated by host and gut microbiota. Tissue-specific expressions of BCAA-catabolizing enzymes were detected by RT-PCR and western blot, respectively. The components of the intestinal microflora were analyzed by high-throughput 16S rRNA gene sequencing. The results showed that MLE administration improved blood glucose and insulin level, decreased inflammatory cytokines expression, and lowered serum and feces BCAAs levels. Furthermore, MLE reversed the abundance changes of the bacterial genera correlated with serum and feces BCAAs, such as Anaerovorax, Bilophila, Blautia, Colidextribacter, Dubosiella, Intestinimonas, Lachnoclostridium, Lachnospiraceae_NK4A136, Oscillibacter, and Roseburia. Functionality prediction indicated that MLE potentially inhibited bacterial BCAAs biosynthesis, and promoted the tissue-specific expression of BCAAs catabolic enzyme. More importantly, MLE had obvious impacts on BCAA catabolism in germ-free-mimic T2DM mice. Those results indicated that MLE improving T2DM-related biochemical abnormalities is associated with not only gut microbiota modification but also the tissue-specific expression of BCAAs catabolic enzyme.
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Affiliation(s)
- Xiao-Xiao Zheng
- Department of Pharmacy, Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University, Xuzhou, 221116, China
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Ding-Xiang Li
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Ya-Ting Li
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Yu-Lang Chen
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Yan-Lin Zhao
- Department of Pharmaceutical Analysis, Xuzhou Medical University, Xuzhou, 221204, China
| | - Shuai Ji
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
- Department of Pharmacy, Suining People's Hospital Affiliated to Xuzhou Medical University, Suining, 221202, China
| | - Meng-Zhe Guo
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
- Department of Pharmacy, Suining People's Hospital Affiliated to Xuzhou Medical University, Suining, 221202, China
| | - Yan Du
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
- State Key Laboratory of Pharmaceutical Biotechnology, Chemistry and Biomedicine Innovation Center (ChemBIC), Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, 210093, China
| | - Dao-Quan Tang
- Department of Pharmacy, Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University, Xuzhou, 221116, China
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
- Department of Pharmaceutical Analysis, Xuzhou Medical University, Xuzhou, 221204, China
- Department of Pharmacy, Suining People's Hospital Affiliated to Xuzhou Medical University, Suining, 221202, China
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20
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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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21
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Mediterranean diet related metabolite profiles and cognitive performance. Clin Nutr 2023; 42:173-181. [PMID: 36599272 DOI: 10.1016/j.clnu.2022.12.012] [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: 10/05/2022] [Revised: 12/13/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND & AIMS Evidence suggests that adherence to the Mediterranean diet (MedDiet) affects human metabolism and may contribute to better cognitive performance. However, the underlying mechanisms are not clear. OBJECTIVE We generated a metabolite profile for adherence to MedDiet and evaluated its cross-sectional association with aspects of cognitive performance. METHODS A total of 1250 healthy Greek middle-aged adults from the Epirus Health Study cohort were included in the analysis. Adherence to the MedDiet was assessed using the 14-point Mediterranean Diet Adherence Screener (MEDAS); cognition was measured using the Trail Making Test, the Verbal Fluency test and the Logical Memory test. A targeted metabolite profiling (n = 250 metabolites) approach was applied, using a high-throughput nuclear magnetic resonance platform. We used elastic net regularized regressions, with a 10-fold cross-validation procedure, to identify a metabolite profile for MEDAS. We evaluated the associations of the identified metabolite profile and MEDAS with cognitive tests, using multivariable linear regression models. RESULTS We identified a metabolite profile composed of 42 metabolites, mainly lipoprotein subclasses and fatty acids, significantly correlated with MedDiet adherence (Pearson r = 0.35, P-value = 5.5 × 10-37). After adjusting for known risk factors and accounting for multiple testing, the metabolite profile and MEDAS were not associated with the cognitive tests. CONCLUSIONS A plasma metabolite profile related to better adherence to the MedDiet was not associated with the tested aspects of cognitive performance, in a middle-aged Mediterranean population.
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22
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Dietary Strawberries Improve Serum Metabolites of Cardiometabolic Risks in Adults with Features of the Metabolic Syndrome in a Randomized Controlled Crossover Trial. Int J Mol Sci 2023; 24:ijms24032051. [PMID: 36768375 PMCID: PMC9916764 DOI: 10.3390/ijms24032051] [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: 12/15/2022] [Revised: 01/17/2023] [Accepted: 01/18/2023] [Indexed: 01/22/2023] Open
Abstract
Dietary strawberries have been shown to improve cardiometabolic risks in multiple clinical trials. However, no studies have reported effects on serum metabolomic profiles that may identify the target pathways affected by strawberries as underlying mechanisms. We conducted a 14-week randomized, controlled crossover study in which participants with features of metabolic syndrome were assigned to one of the three arms for four weeks separated by a one-week washout period: control powder, 1 serving (low dose: 13 g strawberry powder/day), or 2.5 servings (high dose: 32 g strawberry powder/day). Blood samples, anthropometric measures, blood pressure, and dietary and physical activity data were collected at baseline and at the end of each four-week phase of intervention. Serum samples were analyzed for primary metabolites and complex lipids using different mass spectrometry methods. Mixed-model ANOVA was used to examine differences in the targeted metabolites between treatment phases, and LASSO logistic regression was used to examine differences in the untargeted metabolites at end of the strawberry intervention vs. the baseline. The findings revealed significant differences in the serum branched-chain amino acids valine and leucine following strawberry intervention (high dose) compared with the low-dose and control phases. Untargeted metabolomic profiles revealed several metabolites, including serum phosphate, benzoic acid, and hydroxyphenyl propionic acid, that represented improved energy-metabolism pathways, compliance measures, and microbial metabolism of strawberry polyphenols, respectively. Thus, dietary supplementation of strawberries significantly improves the serum metabolic profiles of cardiometabolic risks in adults.
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23
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Bao Y, Han X, Liu D, Tan Z, Deng Y. Gut microbiota: The key to the treatment of metabolic syndrome in traditional Chinese medicine - a case study of diabetes and nonalcoholic fatty liver disease. Front Immunol 2022; 13:1072376. [PMID: 36618372 PMCID: PMC9816483 DOI: 10.3389/fimmu.2022.1072376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 12/09/2022] [Indexed: 12/25/2022] Open
Abstract
Metabolic syndrome mainly includes obesity, type 2 diabetes (T2DM), alcoholic fatty liver (NAFLD) and cardiovascular diseases. According to the ancient experience philosophy of Yin-Yang, monarch-minister compatibility of traditional Chinese medicine, prescription is given to treat diseases, which has the advantages of small toxic and side effects and quick effect. However, due to the diversity of traditional Chinese medicine ingredients and doubts about the treatment theory of traditional Chinese medicine, the mechanism of traditional Chinese medicine is still in doubt. Gastrointestinal tract is an important part of human environment, and participates in the occurrence and development of diseases. In recent years, more and more TCM researches have made intestinal microbiome a new frontier for understanding and treating diseases. Clinically, nonalcoholic fatty liver disease (NAFLD) and diabetes mellitus (DM) often co-occur. Our aim is to explain the mechanism of interaction between gastrointestinal microbiome and traditional Chinese medicine (TCM) or traditional Chinese medicine formula to treat DM and NAFLD. Traditional Chinese medicine may treat these two diseases by influencing the composition of intestinal microorganisms, regulating the metabolism of intestinal microorganisms and transforming Chinese medicinal compounds.
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Affiliation(s)
- Yang Bao
- Department of Endosecretory Metabolic Diseases, Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, Jilin, China
| | - Xiao Han
- Department of Endosecretory Metabolic Diseases, Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, Jilin, China
| | - Da Liu
- School of Pharmacy, Changchun University of Chinese Medicine, Changchun, Jilin, China,*Correspondence: Yongzhi Deng, ; Zhaolin Tan, ; Da Liu,
| | - Zhaolin Tan
- School of Pharmacy, Changchun University of Chinese Medicine, Changchun, Jilin, China,*Correspondence: Yongzhi Deng, ; Zhaolin Tan, ; Da Liu,
| | - Yongzhi Deng
- Department of Acupuncture and Massage, The Third Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, Jilin, China,*Correspondence: Yongzhi Deng, ; Zhaolin Tan, ; Da Liu,
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24
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Doestzada M, Zhernakova DV, C L van den Munckhof I, Wang D, Kurilshikov A, Chen L, Bloks VW, van Faassen M, Rutten JHW, Joosten LAB, Netea MG, Wijmenga C, Riksen NP, Zhernakova A, Kuipers F, Fu J. Systematic analysis of relationships between plasma branched-chain amino acid concentrations and cardiometabolic parameters: an association and Mendelian randomization study. BMC Med 2022; 20:485. [PMID: 36522747 PMCID: PMC9753387 DOI: 10.1186/s12916-022-02688-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Branched-chain amino acids (BCAAs; valine, leucine, and isoleucine) are essential amino acids that are associated with an increased risk of cardiometabolic diseases (CMD). However, there are still only limited insights into potential direct associations between BCAAs and a wide range of CMD parameters, especially those remaining after correcting for covariates and underlying causal relationships. METHODS To shed light on these relationships, we systematically characterized the associations between plasma BCAA concentrations and a large panel of 537 CMD parameters (including atherosclerosis-related parameters, fat distribution, plasma cytokine concentrations and cell counts, circulating concentrations of cardiovascular-related proteins and plasma metabolites) in 1400 individuals from the Dutch population cohort LifeLines DEEP and 294 overweight individuals from the 300OB cohort. After correcting for age, sex, and BMI, we assessed associations between individual BCAAs and CMD parameters. We further assessed the underlying causality using Mendelian randomization. RESULTS A total of 838 significant associations were detected for 409 CMD parameters. BCAAs showed both common and specific associations, with the most specific associations being detected for isoleucine. Further, we found that obesity status substantially affected the strength and direction of associations for valine, which cannot be corrected for using BMI as a covariate. Subsequent univariable Mendelian randomization (UVMR), after removing BMI-associated SNPs, identified seven significant causal relationships from four CMD traits to BCAA levels, mostly for diabetes-related parameters. However, no causal effects of BCAAs on CMD parameters were supported. CONCLUSIONS Our cross-sectional association study reports a large number of associations between BCAAs and CMD parameters. Our results highlight some specific associations for isoleucine, as well as obesity-specific effects for valine. MR-based causality analysis suggests that altered BCAA levels can be a consequence of diabetes and alteration in lipid metabolism. We found no MR evidence to support a causal role for BCAAs in CMD. These findings provide evidence to (re)evaluate the clinical importance of individual BCAAs in CMD diagnosis, prevention, and treatment.
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Affiliation(s)
- Marwah Doestzada
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.,Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Daria V Zhernakova
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.,Laboratory of Genomic Diversity, Center for Computer Technologies, ITMO University, St. Petersburg, Russia
| | - Inge C L van den Munckhof
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Daoming Wang
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.,Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Alexander Kurilshikov
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Lianmin Chen
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.,Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Vincent W Bloks
- Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Martijn van Faassen
- Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Joost H W Rutten
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Leo A B Joosten
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Mihai G Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.,Department for Genomics Immunoregulation, Life and Medical Sciences Institute, University of Bonn, Bonn, Germany.,Human Genomics Laboratory, Craiova University of Medicine and Pharmacy, Craiova, Romania
| | - Cisca Wijmenga
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Niels P Riksen
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Folkert Kuipers
- Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.,University of Groningen, University Medical Center Groningen, European Institute of Healthy Ageing (ERIBA), Groningen, the Netherlands
| | - Jingyuan Fu
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. .,Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
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25
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García‐Gavilán J, Nishi SK, Paz‐Graniel I, Guasch‐Ferré M, Razquin C, Clish CB, Toledo E, Ruiz‐Canela M, Corella D, Deik A, Drouin‐Chartier J, Wittenbecher C, Babio N, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Serra‐Majem L, Liang L, Martínez‐González MA, Hu FB, Salas‐Salvadó J. Plasma Metabolite Profiles Associated with the Amount and Source of Meat and Fish Consumption and the Risk of Type 2 Diabetes. Mol Nutr Food Res 2022; 66:e2200145. [PMID: 36214069 PMCID: PMC9722604 DOI: 10.1002/mnfr.202200145] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 09/12/2022] [Indexed: 01/18/2023]
Abstract
SCOPE Consumption of meat has been associated with a higher risk of type 2 diabetes (T2D), but if plasma metabolite profiles associated with these foods reflect this relationship is unknown. The objective is to identify a metabolite signature of consumption of total meat (TM), red meat (RM), processed red meat (PRM), and fish and examine if they are associated with T2D risk. METHODS AND RESULTS The discovery population includes 1833 participants from the PREDIMED trial. The internal validation sample includes 1522 participants with available 1-year follow-up metabolomic data. Associations between metabolites and TM, RM, PRM, and fish are evaluated with elastic net regression. Associations between the profiles and incident T2D are estimated using Cox regressions. The profiles included 72 metabolites for TM, 69 for RM, 74 for PRM, and 66 for fish. After adjusting for T2D risk factors, only profiles of TM (Hazard Ratio (HR): 1.25, 95% CI: 1.06-1.49), RM (HR: 1.27, 95% CI: 1.07-1.52), and PRM (HR: 1.27, 95% CI: 1.07-1.51) are associated with T2D. CONCLUSIONS The consumption of TM, its subtypes, and fish is associated with different metabolites, some of which have been previously associated with T2D. Scores based on the identified metabolites for TM, RM, and PRM show a significant association with T2D risk.
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Affiliation(s)
- Jesús García‐Gavilán
- Departament de Bioquímica i BiotecnologiaUnitat de Nutrició Humana, Hospital Universitari San Joan de ReusUniversitat Rovira i VirgiliReus43202Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)Reus43204Spain
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - Stephanie K. Nishi
- Departament de Bioquímica i BiotecnologiaUnitat de Nutrició Humana, Hospital Universitari San Joan de ReusUniversitat Rovira i VirgiliReus43202Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)Reus43204Spain
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials UnitTorontoONM5C 2T2Canada
- Clinical Nutrition and Risk Factor Modification CentreSt. Michael's Hospital, Unity Health TorontoTorontoONM5C 2T2Canada
| | - Indira Paz‐Graniel
- Departament de Bioquímica i BiotecnologiaUnitat de Nutrició Humana, Hospital Universitari San Joan de ReusUniversitat Rovira i VirgiliReus43202Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)Reus43204Spain
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - Marta Guasch‐Ferré
- Department of NutritionHarvard TH Chan School of Public HealthBostonMA02115USA
- Channing Division for Network Medicine, Department of MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMA02115USA
| | - Cristina Razquin
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA)University of NavarraPamplona31008Spain
| | | | - Estefanía Toledo
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA)University of NavarraPamplona31008Spain
| | - Miguel Ruiz‐Canela
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA)University of NavarraPamplona31008Spain
| | - Dolores Corella
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Department of Preventive MedicineUniversity of ValenciaValencia46020Spain
| | - Amy Deik
- The Broad Institute of Harvard and MITBostonMA02142USA
| | - Jean‐Philippe Drouin‐Chartier
- Centre Nutrition, Santé et Société, Institut sur la Nutrition et les Aliments FonctionnelsFaculté de Pharmacie, Université LavalQuébecG1V 0A6Canada
| | - Clemens Wittenbecher
- Department of NutritionHarvard TH Chan School of Public HealthBostonMA02115USA
- Department of Molecular EpidemiologyGerman Institute of Human Nutrition Potsdam‐Rehbruecke14558NuthetalGermany
- German Center for Diabetes Research85764NeuherbergGermany
| | - Nancy Babio
- Departament de Bioquímica i BiotecnologiaUnitat de Nutrició Humana, Hospital Universitari San Joan de ReusUniversitat Rovira i VirgiliReus43202Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)Reus43204Spain
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - Ramon Estruch
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi SunyerHospital ClinicUniversity of BarcelonaBarcelona08036Spain
| | - Emilio Ros
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Lipid Clinic, Department of Endocrinology and Nutrition, Agust Pi i Sunyer Biomedical Research Institute (IDIBAPS)Hospital Clinic, University of BarcelonaBarcelona08036Spain
| | - Montserrat Fitó
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Cardiovascular and Nutrition Research GroupInstitut de Recerca Hospital del MarBarcelona08003Spain
| | - Fernando Arós
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Department of CardiologyUniversity Hospital of AlavaVitoria01009Spain
| | - Miquel Fiol
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Health Research Institute of the Balearic Islands (Idisba)University of Balearic Islands and Hospital Son EspasesPalma de Mallorca07122Spain
| | - Lluís Serra‐Majem
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Research Institute of Biomedical and Health Sciences IUIBSUniversity of Las Palmas de Gran CanariaLas Palmas35001Spain
| | - Liming Liang
- Department of EpidemiologyHarvard T. H. Chan School of Public HealthBostonMA02115USA
- Department of StatisticsHarvard T. H. Chan School of Public HealthBostonMA02115USA
| | - Miguel A. Martínez‐González
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
- Department of NutritionHarvard TH Chan School of Public HealthBostonMA02115USA
- Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA)University of NavarraPamplona31008Spain
| | - Frank B. Hu
- Department of NutritionHarvard TH Chan School of Public HealthBostonMA02115USA
- Channing Division for Network Medicine, Department of MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMA02115USA
- Department of EpidemiologyHarvard T. H. Chan School of Public HealthBostonMA02115USA
| | - Jordi Salas‐Salvadó
- Departament de Bioquímica i BiotecnologiaUnitat de Nutrició Humana, Hospital Universitari San Joan de ReusUniversitat Rovira i VirgiliReus43202Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)Reus43204Spain
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
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Bartova S, Madrid-Gambin F, Fernández L, Carayol J, Meugnier E, Segrestin B, Delage P, Vionnet N, Boizot A, Laville M, Vidal H, Marco S, Hager J, Moco S. Grape polyphenols decrease circulating branched chain amino acids in overfed adults. Front Nutr 2022; 9:998044. [PMID: 36386937 PMCID: PMC9643885 DOI: 10.3389/fnut.2022.998044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 10/10/2022] [Indexed: 12/02/2022] Open
Abstract
Introduction and aims Dietary polyphenols have long been associated with health benefits, including the prevention of obesity and related chronic diseases. Overfeeding was shown to rapidly induce weight gain and fat mass, associated with mild insulin resistance in humans, and thus represents a suitable model of the metabolic complications resulting from obesity. We studied the effects of a polyphenol-rich grape extract supplementation on the plasma metabolome during an overfeeding intervention in adults, in two randomized parallel controlled clinical trials. Methods Blood plasma samples from 40 normal weight to overweight male adults, submitted to a 31-day overfeeding (additional 50% of energy requirement by a high calorie-high fructose diet), given either 2 g/day grape polyphenol extract or a placebo at 0, 15, 21, and 31 days were analyzed (Lyon study). Samples from a similarly designed trial on females (20 subjects) were collected in parallel (Lausanne study). Nuclear magnetic resonance (NMR)-based metabolomics was conducted to characterize metabolome changes induced by overfeeding and associated effects from polyphenol supplementation. The clinical trials are registered under the numbers NCT02145780 and NCT02225457 at ClinicalTrials.gov. Results Changes in plasma levels of many metabolic markers, including branched chain amino acids (BCAA), ketone bodies and glucose in both placebo as well as upon polyphenol intervention were identified in the Lyon study. Polyphenol supplementation counterbalanced levels of BCAA found to be induced by overfeeding. These results were further corroborated in the Lausanne female study. Conclusion Administration of grape polyphenol-rich extract over 1 month period was associated with a protective metabolic effect against overfeeding in adults.
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Affiliation(s)
- Simona Bartova
- Nestlé Research, EPFL Innovation Park, Lausanne, Switzerland
| | - Francisco Madrid-Gambin
- Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Luis Fernández
- Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Electronics and Biomedical Engineering, Universitat de Barcelona, Barcelona, Spain
| | - Jerome Carayol
- Nestlé Research, EPFL Innovation Park, Lausanne, Switzerland
| | - Emmanuelle Meugnier
- University of Lyon, CarMeN Laboratory and Centre de Recherche en Nutrition Humaine Rhône-Alpes (CRNH-RA), INSERM, INRAE, Claude Bernard University Lyon 1, Pierre-Bénite, France
| | - Bérénice Segrestin
- University of Lyon, CarMeN Laboratory and Centre de Recherche en Nutrition Humaine Rhône-Alpes (CRNH-RA), INSERM, INRAE, Claude Bernard University Lyon 1, Pierre-Bénite, France
| | - Pauline Delage
- University of Lyon, CarMeN Laboratory and Centre de Recherche en Nutrition Humaine Rhône-Alpes (CRNH-RA), INSERM, INRAE, Claude Bernard University Lyon 1, Pierre-Bénite, France
| | - Nathalie Vionnet
- Service d’Endocrinologie, Diabétologie et Métabolisme, CHU de Lausanne (CHUV), Lausanne, Switzerland
| | - Alexia Boizot
- Service d’Endocrinologie, Diabétologie et Métabolisme, CHU de Lausanne (CHUV), Lausanne, Switzerland
| | - Martine Laville
- University of Lyon, CarMeN Laboratory and Centre de Recherche en Nutrition Humaine Rhône-Alpes (CRNH-RA), INSERM, INRAE, Claude Bernard University Lyon 1, Pierre-Bénite, France
| | - Hubert Vidal
- University of Lyon, CarMeN Laboratory and Centre de Recherche en Nutrition Humaine Rhône-Alpes (CRNH-RA), INSERM, INRAE, Claude Bernard University Lyon 1, Pierre-Bénite, France
| | - Santiago Marco
- Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Electronics and Biomedical Engineering, Universitat de Barcelona, Barcelona, Spain
| | - Jörg Hager
- Nestlé Research, EPFL Innovation Park, Lausanne, Switzerland
| | - Sofia Moco
- Nestlé Research, EPFL Innovation Park, Lausanne, Switzerland
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Ye J, Wu Z, Zhao Y, Zhang S, Liu W, Su Y. Role of gut microbiota in the pathogenesis and treatment of diabetes mullites: Advanced research-based review. Front Microbiol 2022; 13:1029890. [PMID: 36338058 PMCID: PMC9627042 DOI: 10.3389/fmicb.2022.1029890] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 09/26/2022] [Indexed: 02/05/2023] Open
Abstract
Gut microbiota plays an important role in the proper functioning of human organisms, while its dysbiosis is associated with disease in various body organs. Diabetes mellitus (DM) is a set of heterogeneous metabolic diseases characterized by hyperglycemia caused by direct or indirect insulin deficiency. There is growing evidence that gut microbiota dysbiosis is closely linked to the development of DM. Gut microbiota composition changes in type 1 diabetes mullites (T1DM) and type 2 diabetes mullites (T2DM) patients, which may cause gut leakiness and uncontrolled entry of antigens into the circulation system, triggering an immune response that damages the isle β cells or metabolic disorders. This review summarizes gut microbiota composition in healthy individuals and compares it to diabetes mullites patients. The possible pathogenesis by which gut microbiota dysbiosis causes DM, particularly gut leakiness and changes in gut microbiota metabolites is also discussed. It also presents the process of microbial-based therapies of DM.
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Affiliation(s)
- Junjun Ye
- Department of Endocrine and Metabolic Diseases, Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Zezhen Wu
- Department of Endocrine and Metabolic Diseases, Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Yifei Zhao
- School of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Shuo Zhang
- Department of Endocrine and Metabolic Diseases, Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Weiting Liu
- School of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Yu Su
- Center of Teaching Evaluation and Faculty Development, Anhui University of Chinese Medicine, Hefei, China
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Kivelä J, Meinilä J, Uusitupa M, Tuomilehto J, Lindström J. Longitudinal Branched-Chain Amino Acids, Lifestyle Intervention, and Type 2 Diabetes in the Finnish Diabetes Prevention Study. J Clin Endocrinol Metab 2022; 107:2844-2853. [PMID: 35917829 PMCID: PMC9516128 DOI: 10.1210/clinem/dgac463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Indexed: 12/05/2022]
Abstract
CONTEXT Circulating branched-chain amino acids (BCAAs) are associated with the risk of type 2 diabetes (T2D). OBJECTIVE We examined to what extent lifestyle intervention aiming to prevent T2D interacts with this association and how BCAA concentrations change during the intervention. METHODS We computed trajectory clusters by k-means clustering of serum fasting BCAAs analyzed annually by mass spectrometry during a 4-year intervention. We investigated whether baseline BCAAs, BCAA trajectories, and BCAA change trajectories predicted T2D and whether BCAAs predicted T2D differently in the intervention (n = 198) and control group (n = 196). RESULTS Elevated baseline BCAAs predicted the incidence of T2D in the control group (hazard ratio [HR] 1.05 per 10 μmol/L, P = 0.01), but not in the intervention group. BCAA concentration decreased during the first year in the whole cohort (mean -14.9 μmol/L, P < 0.001), with no significant difference between the groups. We identified 5 BCAA trajectory clusters and 5 trajectory clusters for the change in BCAAs. Trajectories with high mean BCAA levels were associated with an increased HR for T2D compared with the trajectory with low BCAA levels (trajectory with highest vs lowest BCAA, HR 4.0; P = 0.01). A trajectory with increasing BCAA levels had a higher HR for T2D compared with decreasing trajectory in the intervention group only (HR 25.4, P < 0.001). CONCLUSION Lifestyle intervention modified the association of the baseline BCAA concentration and BCAA trajectories with the incidence of T2D. Our study adds to the accumulating evidence on the mechanisms behind the effect of lifestyle changes on the risk of T2D.
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Affiliation(s)
- Jemina Kivelä
- Correspondence: Jemina Kivelä, MSc, Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PO Box 30, FI-00271 Helsinki, Finland.
| | - Jelena Meinilä
- Department of Food and Nutrition, University of Helsinki, 00014 Helsinki, Finland
| | - Matti Uusitupa
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland
| | - Jaakko Tuomilehto
- Population Health Unit, Finnish Institute of Health and Welfare, 00271 Helsinki, Finland
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
- Saudi Diabetes Research Group, King Abdulaziz University, 80200 Jeddah, Saudi Arabia
- Department of International Health, National School of Public Health, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jaana Lindström
- Population Health Unit, Finnish Institute of Health and Welfare, 00271 Helsinki, Finland
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29
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García-Gavilán JF, Connelly MA, Babio N, Matzoros CS, Ros E, Salas-Salvadó J. Nut consumption is associated with a shift of the NMR lipoprotein subfraction profile to a less atherogenic pattern among older individuals at high CVD risk. Cardiovasc Diabetol 2022; 21:189. [PMID: 36127725 PMCID: PMC9487141 DOI: 10.1186/s12933-022-01624-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 09/08/2022] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Scientific evidence has accumulated on the beneficial effects of nut consumption on cardiovascular risk and cholesterol reduction, but few studies have examined the effects of nuts on advanced measures of lipoprotein atherogenicity determined by nuclear magnetic resonance (NMR) spectroscopy. We analyzed associations between the amount and type of of nuts consumed and advanced measures of lipoprotein atherogenity and insulin resistance in older individuals at high cardiovascular risk. METHODS The present observational study was carried out within the framework of the Prevención con Dieta Mediterránea (PREDIMED) trial. Cross-sectional and longitudinal analyses after 1-year of follow-up were conducted in 196 men and women recruited in the PREDIMED-Reus (Spain) center. Dietary intake was assessed using a validated semi-quantitative food questionnaire. Baseline and 1-year fasting plasma lipoprotein and metabolite profiling were performed in plasma using NMR spectra Vantera® Clinical Analyzer. Associations by tertiles of nut consumption between baseline and 1-year changes and advanced measures of lipoprotein atherogenicity, branched chain amminoacids, and measures of insulin resistance were tested by multivariable-adjusted ANCOVA models. RESULTS Compared to paticipants in the bottom tertile, those in the top tertile of total nut consumption showed higher levels of large HDL particles and HDL-cholesterol, lower levels of branched-chain amino acids (BCAA) and GlycA, and reduced lipoprotein insulin resistance and diabetes risk index. Participants in the top tertile of walnut consumption disclosed lower levels of very large VLDL, total LDL particles, LDL-cholesterol, and GlycA. Participants in the top tertile of non-walnut nut consumption displayed higher levels of total HDL particles, HDL-cholesterol and apoliporotein A1, lower BCAA and GlycA, and reduced lipoprotein insulin resistance. Participants in the top tertile of 1-year changes in walnut consumption showed increases in medium-sized HDL particles in comparison to the bottom tertile. CONCLUSIONS In older individuals at high cardiovascular risk, increasing nut consumption was associated with a shift of the NMR lipoprotein subfraction profile to a less atherogenic pattern, as well as lower circulating concentrations of BCAA and decreased insulin resistance. These results provide novel mechanistic insight into the cardiovascular benefit of nut consumption. Trial registration ISRCTN35739639; registration date: 05/10/2005; recruitment start date 01/10/2003.
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Affiliation(s)
- Jesús F García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, 43201, Reus, Tarragona, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.,Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Margery A Connelly
- Laboratory Corporation of America® Holdings (Labcorp), Morrisville, Raleigh, NC, USA
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, 43201, Reus, Tarragona, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.,Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Christos S Matzoros
- Department of Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, 02215, USA.,Section of Endocrinology, VA Boston Healthcare System, Jamaica Plain, Boston, MA, 02130, USA
| | - Emilio Ros
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.,Lipid Clinic, Department of Endocrinology and Nutrition, Agust Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, 43201, Reus, Tarragona, Spain. .,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. .,Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
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30
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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: 7.5] [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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31
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Ruiz-Canela M, Guasch-Ferré M, Razquin C, Toledo E, Hernández-Alonso P, Clish CB, Li J, Wittenbecher C, Dennis C, Alonso-Gómez Á, Almanza-Aguilera E, Liang L, Corella D, Gómez-Gracia E, Estruch R, Fiol M, Lapetra J, Serra-Majem L, Ros E, Arós F, Salas-Salvadó J, Hu FB, Martínez-González MÁ. Plasma acylcarnitines and risk of incident heart failure and atrial fibrillation: the Prevención con dieta mediterránea study. REVISTA ESPAÑOLA DE CARDIOLOGÍA (ENGLISH EDITION) 2022; 75:649-658. [PMID: 34866031 PMCID: PMC9160218 DOI: 10.1016/j.rec.2021.10.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 10/07/2021] [Indexed: 11/29/2022]
Abstract
INTRODUCTION AND OBJECTIVES Fatty acid metabolic dysregulation in mitochondria is a common mechanism involved in the development of heart failure (HF) and atrial fibrillation (AF). We evaluated the association between plasma acylcarnitine levels and the incidence of HF or AF, and whether the mediterranean diet (MedDiet) may attenuate the association between acylcarnitines and HF or AF risk. METHODS Two case-control studies nested within the Prevención con dieta mediterránea (PREDIMED) trial. High cardiovascular risk participants were recruited in Spain: 326 incident HF and 509 AF cases individually matched to 1 to 3 controls. Plasma acylcarnitines were measured with high-throughput liquid chromatography-tandem mass spectrometry. Conditional logistic regression models were fitted to estimate multivariable OR and 95%CI. Additive and multiplicative interactions were assessed by intervention group, obesity (body mass index ≥ 30 kg/m2), and type 2 diabetes. RESULTS Elevated levels of medium- and long-chain acylcarnitines were associated with increased HF risk (adjusted ORperDE, 1.28; 95%CI, 1.09-1.51 and adjusted ORperDE, 1.21; 95%CI, 1.04-1.42, respectively). A significant association was observed for AF risk with long-chain acylcarnitines: 1.20 (1.06-1.36). Additive interaction of the association between long-chain acylcarnitines and AF by the MediDiet supplemented with extra virgin olive oil (P for additive interaction=.036) and by obesity (P=.022) was observed in an inverse and direct manner, respectively. CONCLUSIONS Among individuals at high cardiovascular risk, elevated long-chain acylcarnitines were associated with a higher risk of incident HF and AF. An intervention with MedDiet+extra-virgin olive oil may reduce AF risk associated with long-chain acylcarnitines. This trial was registered at controlled-trials.com (Identifier: ISRCTN35739639).
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Affiliation(s)
- Miguel Ruiz-Canela
- Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain.
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, United States
| | - Cristina Razquin
- Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
| | - Estefanía Toledo
- Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
| | - Pablo Hernández-Alonso
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Unitat de Nutrició Humana, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Reus, Tarragona, Spain; Institut d'Investigació Sanitària Pere iVirgili, Hospital Universitari Sant Joan de Reus, Reus, Tarragona, Spain
| | - Clary B Clish
- Broad 13Broad Institute and MIT, Harvard University, Cambridge, MA, United States
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Clemens Wittenbecher
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Courtney Dennis
- Broad 13Broad Institute and MIT, Harvard University, Cambridge, MA, United States
| | - Ángel Alonso-Gómez
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Instituto Sanitario de Investigación de Bioaraba, Servicio Vasco de Salud-Osakidetza, Hospital Universitario de Araba; Universidad del País Vasco UPV/EHU; Vitoria-Gasteiz, Spain
| | - Enrique Almanza-Aguilera
- Unidad de Riesgo Cardiovascular y Nutrición, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain; Centro de Investigación Biomédica en Red Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain; Instituto de Nutrición y Seguridad Alimentaria (INSA-UB), Universidad de Barcelona, Santa Coloma de Gramanet, Barcelona, Spain
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Dolores Corella
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Medicina Preventiva, Universidad de Valencia, Valencia, Spain
| | - Enrique Gómez-Gracia
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Medicina Preventiva, Universidad de Málaga, Málaga, Spain
| | - Ramón Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Medicina Interna, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Universidad de Barcelona, Barcelona, Spain
| | - Miguel Fiol
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Plataforma de Ensayos Clínicos, Instituto de Investigación Sanitaria Illes Balears (IdISBa), Hospital Universitario Son Espases, Palma de Mallorca, Balearic Islands, Spain
| | - José Lapetra
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Medicina de familia, Unidad de Investigación, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Lluis Serra-Majem
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Grupo de Investigación de Nutrición, Instituto de Investigación Biomédica y Ciencias de la Salud (IUIBS), Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
| | - Emilio Ros
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Unidad Clínica de Lípidos, Departamento de Nutrición y Endocrinología, Institut d'Investigacions Biomèdiques Agust Pi i Sunyer (IDIBAPS), Hospital Clínic, Universidad de Barcelona, Barcelona, Spain
| | - Fernando Arós
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Instituto Sanitario de Investigación de Bioaraba, Servicio Vasco de Salud-Osakidetza, Hospital Universitario de Araba; Universidad del País Vasco UPV/EHU; Vitoria-Gasteiz, Spain
| | - Jordi Salas-Salvadó
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Unitat de Nutrició Humana, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Reus, Tarragona, Spain; Institut d'Investigació Sanitària Pere iVirgili, Hospital Universitari Sant Joan de Reus, Reus, Tarragona, Spain
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, United States
| | - Miguel Ángel Martínez-González
- Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
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Portero V, Nicol T, Podliesna S, Marchal GA, Baartscheer A, Casini S, Tadros R, Treur JL, Tanck MWT, Cox IJ, Probert F, Hough TA, Falcone S, Beekman L, Müller-Nurasyid M, Kastenmüller G, Gieger C, Peters A, Kääb S, Sinner MF, Blease A, Verkerk AO, Bezzina CR, Potter PK, Remme CA. Chronically elevated branched chain amino acid levels are pro-arrhythmic. Cardiovasc Res 2022; 118:1742-1757. [PMID: 34142125 PMCID: PMC9215196 DOI: 10.1093/cvr/cvab207] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 06/16/2021] [Indexed: 01/03/2023] Open
Abstract
AIMS Cardiac arrhythmias comprise a major health and economic burden and are associated with significant morbidity and mortality, including cardiac failure, stroke, and sudden cardiac death (SCD). Development of efficient preventive and therapeutic strategies is hampered by incomplete knowledge of disease mechanisms and pathways. Our aim is to identify novel mechanisms underlying cardiac arrhythmia and SCD using an unbiased approach. METHODS AND RESULTS We employed a phenotype-driven N-ethyl-N-nitrosourea mutagenesis screen and identified a mouse line with a high incidence of sudden death at young age (6-9 weeks) in the absence of prior symptoms. Affected mice were found to be homozygous for the nonsense mutation Bcat2p.Q300*/p.Q300* in the Bcat2 gene encoding branched chain amino acid transaminase 2. At the age of 4-5 weeks, Bcat2p.Q300*/p.Q300* mice displayed drastic increase of plasma levels of branch chain amino acids (BCAAs-leucine, isoleucine, valine) due to the incomplete catabolism of BCAAs, in addition to inducible arrhythmias ex vivo as well as cardiac conduction and repolarization disturbances. In line with these findings, plasma BCAA levels were positively correlated to electrocardiogram indices of conduction and repolarization in the German community-based KORA F4 Study. Isolated cardiomyocytes from Bcat2p.Q300*/p.Q300* mice revealed action potential (AP) prolongation, pro-arrhythmic events (early and late afterdepolarizations, triggered APs), and dysregulated calcium homeostasis. Incubation of human pluripotent stem cell-derived cardiomyocytes with elevated concentration of BCAAs induced similar calcium dysregulation and pro-arrhythmic events which were prevented by rapamycin, demonstrating the crucial involvement of mTOR pathway activation. CONCLUSIONS Our findings identify for the first time a causative link between elevated BCAAs and arrhythmia, which has implications for arrhythmogenesis in conditions associated with BCAA metabolism dysregulation such as diabetes, metabolic syndrome, and heart failure.
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Affiliation(s)
- Vincent Portero
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
| | - Thomas Nicol
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell, Oxfordshire, UK
| | - Svitlana Podliesna
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
| | - Gerard A Marchal
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
| | - Antonius Baartscheer
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
| | - Simona Casini
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
| | - Rafik Tadros
- Cardiovascular Genetics Center, Montreal Heart Institute and Faculty of Medicine, Université de Montréal, Montreal, Canada
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| | - Michael W T Tanck
- Amsterdam UMC, University of Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health (APH), The Netherlands
| | - I Jane Cox
- Institute of Hepatology London, Foundation for Liver Research, London, UK
- Faculty of Life Sciences & Medicine, Kings College, London, UK
| | - Fay Probert
- Department of Chemistry, University of Oxford, Oxford, UK
| | - Tertius A Hough
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell, Oxfordshire, UK
| | - Sara Falcone
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell, Oxfordshire, UK
| | - Leander Beekman
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
| | - Martina Müller-Nurasyid
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- IBE, Faculty of Medicine, Ludwig Maximilian’s University (LMU) Munich, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site: Munich Heart Alliance, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site: Munich Heart Alliance, Munich, Germany
| | - Stefan Kääb
- German Centre for Cardiovascular Research (DZHK), Partner Site: Munich Heart Alliance, Munich, Germany
- Department of Medicine I (Cardiology), University Hospital, LMU Munich, Munich, Germany
| | - Moritz F Sinner
- German Centre for Cardiovascular Research (DZHK), Partner Site: Munich Heart Alliance, Munich, Germany
- Department of Medicine I (Cardiology), University Hospital, LMU Munich, Munich, Germany
| | - Andrew Blease
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell, Oxfordshire, UK
| | - Arie O Verkerk
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
| | - Connie R Bezzina
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
| | - Paul K Potter
- Department of Biological and Medical Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK
| | - Carol Ann Remme
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam UMC, Location AMC, Room K2-104.2, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, The Netherlands
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Yu L, Song P, Zhu Q, Li Y, Jia S, Zhang S, Wang Z, Zhang J. The Dietary Branched-Chain Amino Acids Transition and Risk of Type 2 Diabetes Among Chinese Adults From 1997 to 2015: Based on Seven Cross-Sectional Studies and a Prospective Cohort Study. Front Nutr 2022; 9:881847. [PMID: 35677550 PMCID: PMC9168595 DOI: 10.3389/fnut.2022.881847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 04/25/2022] [Indexed: 11/13/2022] Open
Abstract
Background The situation is grim for the prevention and control of type 2 diabetes (T2D) and prediabetes in China. Serum and dietary branched-chain amino acids (BCAAs) were risk factors for T2D. However, there is a lack of information on trends in consumption of BCAAs and the risk of T2D associated with BCAAs intake, based on nationally representative data in China. Thus, we aimed to comprehensively describe the dietary BCAAs transition and risk of T2D, at a national level among Chinese adults from 1997 to 2015. Methods The data sources were the China Health and Nutrition Survey (CHNS) and China Nutrition and Health Survey (CNHS). Cross-sectional data on intake were obtained from CHNS (1997, n = 9,404), CHNS (2000, n = 10,291), CHNS (2004, n = 9,682), CHNS (2006, n = 9,553), CHNS (2009, n = 9,811), CHNS (2011, n = 12,686) and CNHS (2015, n = 71,695). Prospective cohort data were obtained CHNS (1997-2015, n = 15,508). Results From 1997 to 2015, there was a significant decreasing trend in the BCAAs intake of Chinese adults in all subgroups (P < 0.0001) except for Leu in 80 or older, and a decreasing trend in the consumption of BCAAs after 40 years old (P < 0.05). The mean intake of BCAAs in the population of cohort study was 11.83 ± 3.77g/day. The 95% CI was above the HR of 1.0, when the consumptions were higher than 14.01, 3.75, 6.07, 4.21 g/day in BCAAs, Ile, Leu and Val, based on RCS curves. According to the Cox proportional hazards models, Compared with individuals with BCAAs consumption of 10.65-12.37 g/day, the multivariable-adjusted HR for diabetes was 2.26 (95% CI 1.45 to 3.51) for individuals with consumption of BCAAs more than 18.52 g/day. A statistically significant positive association between BCAAs intake and risk of T2D was observed in males or participants aged 45 years and older, but not in females or participants younger than 45 years. Conclusion Our results reveal a trend toward decreased BCAAs intake in Chinese from 1997 to 2015. After 40 years of age, consumption of BCAAs declined with increasing age. Higher BCAAs intake was associated with higher risk of T2D. This relationship is more stable among men and middle-aged and elderly people.
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Affiliation(s)
- Lianlong Yu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Pengkun Song
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.,NHC Key Laboratory of Trace Element Nutrition, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qianrang Zhu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuqian Li
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shanshan Jia
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shixiu Zhang
- Department of Nutrition and Food Hygiene, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Zhihong Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jian Zhang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
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Hamaya R, Mora S, Lawler PR, Cook NR, Buring JE, Lee IM, Manson JE, Tobias DK. Association of Modifiable Lifestyle Factors with Plasma Branched-Chain Amino Acid Metabolites in Women. J Nutr 2022; 152:1515-1524. [PMID: 35259270 PMCID: PMC9178956 DOI: 10.1093/jn/nxac056] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 02/04/2022] [Accepted: 03/04/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Circulating branched-chain amino acids (BCAAs-isoleucine, leucine, and valine) are strongly associated with higher risk of incident type 2 diabetes (T2D); however, determinants of elevated fasting BCAA concentrations are largely unknown. OBJECTIVES We aimed to characterize the modifiable lifestyle factors related to plasma BCAAs. METHODS We performed a cross-sectional analysis among n = 18,897 women (mean ± SD age: 54.9 ± 7.2 y) in the Women's Health Study, free of T2D and cardiovascular disease at baseline blood draw. Lifestyle factors, weight, and height were self-reported via questionnaire, including smoking status, alcohol, leisure-time physical activity (LTPA), diet quality scores [2010 Alternative Healthy Eating Index (without alcohol) (aHEI); alternate Mediterranean Diet (aMED)], and dietary sources of BCAAs. Plasma BCAAs were quantified via NMR spectroscopy. We calculated multivariable-adjusted percentage mean differences (95% CIs) and P values for linear trend of BCAAs stratified by categoric lifestyle factors. We estimated R2 from univariate cubic spline regression models to estimate the variability in BCAAs explained. RESULTS Compared with women with BMI (in kg/m2) <25.0, BCAAs were 8.6% (95% CI: 8.0%, 9.3%), 15.3% (95% CI: 14.4%, 16.3%), and 21.0% (95% CI: 18.2%, 23.9%) higher for the BMI strata 25.0-29.9, 30.0-39.9, and ≥40.0, respectively (P-trend < 0.0001). Women with higher LTPA and higher alcohol intake compared with lower had modestly (∼1%) lower plasma BCAAs (P-trend = 0.014 and 0.0003, respectively). Differences in smoking status, aHEI, and aMED score were not related to plasma BCAAs. Women with higher dietary BCAAs had dose-response higher plasma BCAA concentrations, 3.4% (95% CI: 2.5%, 4.4%) higher when comparing the highest with the lowest quintile (P-trend < 0.0001). BMI explained 11.6% of the variability of BCAAs, whereas other factors explained between 0.1% and 1%. CONCLUSIONS Our findings among a large cohort of US women indicate that BMI, but less so diet, physical activity, and other lifestyle factors, is related to plasma BCAAs.This trial was registered at clinicaltrials.gov as NCT00000479.
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Affiliation(s)
- Rikuta Hamaya
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Samia Mora
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Lipid Metabolomics and Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Patrick R Lawler
- Peter Munk Cardiac Centre, University Health Network, and Heart and Stroke/Richard Lewar Centre of Excellence in Cardiovascular Research, University of Toronto, Toronto, Ontario, Canada
| | - Nancy R Cook
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Julie E Buring
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - I-Min Lee
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - JoAnn E Manson
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Mary Horrigan Connors Center for Women's Health and Gender Biology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - 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 TH Chan School of Public Health, Boston, MA, USA
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35
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Zhang F, Li DX, Lu DY, Lu YF, Zhang R, Zhao LL, Ji S, Guo MZ, Du Y, Tang DQ. Analysis of plasma free amino acids in diabetic rat and the intervention of Ginkgo biloba leaves extract using hydrophilic interaction liquid chromatography coupled with tandem mass-spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2022; 1196:123230. [PMID: 35349934 DOI: 10.1016/j.jchromb.2022.123230] [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: 10/18/2021] [Revised: 02/10/2022] [Accepted: 03/15/2022] [Indexed: 11/18/2022]
Abstract
Amino acids (AAs) are important metabolites that are related with diabetes. However, their roles in the initiation and development of diabetes mellitus (DM), especially in the treatment of Ginkgo biloba leaves extract (GBE) have not been fully explored. Thus, we investigated the roles that AAs played in the progression and GBE supplementation of DM rat induced by streptozotocin. The rats were randomly divided into a normal control group treated with drug-free solution, a normal control group treated with GBE, a DM group treated with drug-free solution, and DM group treated with GBE; and maintained on this protocol for 9 weeks. Rat plasma was collected from the sixth week to the ninth week and then analyzed with the optimized hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry method. A total of 17 AAs with differential levels were monitored to indicate dysfunction of AAs metabolism to confirm the occurrence and development of DM. Treatment with GBE partially reversed the changes seen in seven AAs including leucine, isoleucine, tyrosine, glutamic acid, asparagines, lysine and alanine in DM rats, indicating that GBE could prevent the occurrence and development of DM by acting on AAs metabolism. The improvement of those AAs metabolism disorders may play a considerable role in the treatment of GBE on the occurrence and development of DM. Those findings potentially promote the understanding of the pathogenic progression of DM and reveal the therapeutic mechanism of GBE against DM.
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Affiliation(s)
- Fan Zhang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Ding-Xiang Li
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Dong-Yu Lu
- Department of Pharmacy, Suining People's Hospital, Suining, China
| | - Yi-Fan Lu
- The Second Clinical College, Xuzhou Medical University, Xuzhou, China
| | - Ran Zhang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Lin-Lin Zhao
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Shuai Ji
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China; Department of Pharmaceutical Analysis, Xuzhou Medical University, Xuzhou, China
| | - Meng-Zhe Guo
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China; Department of Pharmaceutical Analysis, Xuzhou Medical University, Xuzhou, China
| | - Yan Du
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Dao-Quan Tang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China; Department of Pharmacy, Suining People's Hospital, Suining, China; Department of Pharmaceutical Analysis, Xuzhou Medical University, Xuzhou, China.
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Remme CA. Sudden cardiac death in diabetes and obesity: mechanisms and therapeutic strategies. Can J Cardiol 2022; 38:418-426. [PMID: 35017043 DOI: 10.1016/j.cjca.2022.01.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 01/05/2022] [Accepted: 01/05/2022] [Indexed: 02/07/2023] Open
Abstract
Ventricular arrhythmias and sudden cardiac death (SCD) occur most frequently in the setting of coronary artery disease, cardiomyopathy and heart failure, but are also increasingly observed in individuals suffering from diabetes mellitus and obesity. The incidence of these metabolic disorders is rising in Western countries, but adequate prevention and treatment of arrhythmias and SCD in affected patients is limited due to our incomplete knowledge of the underlying disease mechanisms. Here, an overview is presented of the prevalence of electrophysiological disturbances, ventricular arrhythmias and SCD in the clinical setting of diabetes and obesity. Experimental studies are reviewed, which have identified disease pathways and associated modulatory factors, in addition to pro-arrhythmic mechanisms. Key processes are discussed, including mitochondrial dysfunction, oxidative stress, cardiac structural derangements, abnormal cardiac conduction, ion channel dysfunction, prolonged repolarization and dysregulation of intracellular sodium and calcium homeostasis. In addition, the recently identified pro-arrhythmic effects of dysregulated branched chain amino acid metabolism, a common feature in patients with metabolic disorders, are addressed. Finally, current management options are discussed, in addition to the potential development of novel preventive and therapeutic strategies based on recent insight gained from translational studies.
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Affiliation(s)
- Carol Ann Remme
- Department of Experimental Cardiology, Amsterdam UMC, location AMC, Amsterdam, The Netherlands.
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37
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He Q, Dong H, Guo Y, Gong M, Xia Q, Lu F, Wang D. Multi-target regulation of intestinal microbiota by berberine to improve type 2 diabetes mellitus. Front Endocrinol (Lausanne) 2022; 13:1074348. [PMID: 36465656 PMCID: PMC9715767 DOI: 10.3389/fendo.2022.1074348] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 11/07/2022] [Indexed: 11/21/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) and its complications are major public health problems that seriously affect the quality of human life. The modification of intestinal microbiota has been widely recognized for the management of diabetes. The relationship between T2DM, intestinal microbiota, and active ingredient berberine (BBR) in intestinal microbiota was reviewed in this paper. First of all, the richness and functional changes of intestinal microbiota disrupt the intestinal environment through the destruction of the intestinal barrier and fermentation/degradation of pathogenic/protective metabolites, targeting the liver, pancreas, visceral adipose tissue (VAT), etc., to affect intestinal health, blood glucose, and lipids, insulin resistance and inflammation. Then, we focus on BBR, which protects the composition of intestinal microbiota, the changes of intestinal metabolites, and immune regulation disorder of the intestinal environment as the therapeutic mechanism as well as its current clinical trials. Further research can analyze the mechanism network of BBR to exert its therapeutic effect according to its multi-target compound action, to provide a theoretical basis for the use of different phytochemical components alone or in combination to prevent and treat T2DM or other metabolic diseases by regulating intestinal microbiota.
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Affiliation(s)
- Qiongyao He
- Institute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hui Dong
- Institute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yujin Guo
- Institute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Minmin Gong
- Institute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qingsong Xia
- Institute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Fuer Lu
- Department of Integrated Traditional Chinese and Western Medicine, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
- *Correspondence: Fuer Lu, ; Dingkun Wang,
| | - Dingkun Wang
- Department of Integrated Traditional Chinese and Western Medicine, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
- *Correspondence: Fuer Lu, ; Dingkun Wang,
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Ma H, Hu Y, Zhang B, Shao Z, Roura E, Wang S. Tea polyphenol – gut microbiota interactions: hints on improving the metabolic syndrome in a multi-element and multi-target manner. FOOD SCIENCE AND HUMAN WELLNESS 2022. [DOI: 10.1016/j.fshw.2021.07.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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39
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Ruiz-Canela M, Guasch-Ferré M, Razquin C, Toledo E, Hernández-Alonso P, Clish CB, Li J, Wittenbecher C, Dennis C, Alonso-Gómez Á, Almanza-Aguilera E, Liang L, Corella D, Gómez-Gracia E, Estruch R, Fiol M, Lapetra J, Serra-Majem L, Ros E, Arós F, Salas-Salvadó J, Hu FB, Martínez-González MÁ. Acilcarnitinas en plasma y riesgo de insuficiencia cardiaca y fibrilación auricular: el estudio Prevención con dieta mediterránea. Rev Esp Cardiol 2022. [PMID: 34866031 DOI: 10.1016/j.recesp.2021.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Miguel Ruiz-Canela
- Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain.
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, United States
| | - Cristina Razquin
- Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
| | - Estefanía Toledo
- Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
| | - Pablo Hernández-Alonso
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Unitat de Nutrició Humana, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Reus, Tarragona, Spain; Institut d'Investigació Sanitària Pere iVirgili, Hospital Universitari Sant Joan de Reus, Reus, Tarragona, Spain
| | - Clary B Clish
- Broad 13Broad Institute and MIT, Harvard University, Cambridge, MA, United States
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Clemens Wittenbecher
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Courtney Dennis
- Broad 13Broad Institute and MIT, Harvard University, Cambridge, MA, United States
| | - Ángel Alonso-Gómez
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Instituto Sanitario de Investigación de Bioaraba, Servicio Vasco de Salud-Osakidetza, Hospital Universitario de Araba; Universidad del País Vasco UPV/EHU; Vitoria-Gasteiz, Spain
| | - Enrique Almanza-Aguilera
- Unidad de Riesgo Cardiovascular y Nutrición, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain; Centro de Investigación Biomédica en Red Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain; Instituto de Nutrición y Seguridad Alimentaria (INSA-UB), Universidad de Barcelona, Santa Coloma de Gramanet, Barcelona, Spain
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Dolores Corella
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Medicina Preventiva, Universidad de Valencia, Valencia, Spain
| | - Enrique Gómez-Gracia
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Medicina Preventiva, Universidad de Málaga, Málaga, Spain
| | - Ramón Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Medicina Interna, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Universidad de Barcelona, Barcelona, Spain
| | - Miguel Fiol
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Plataforma de Ensayos Clínicos, Instituto de Investigación Sanitaria Illes Balears (IdISBa), Hospital Universitario Son Espases, Palma de Mallorca, Balearic Islands, Spain
| | - José Lapetra
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Medicina de familia, Unidad de Investigación, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Lluis Serra-Majem
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Grupo de Investigación de Nutrición, Instituto de Investigación Biomédica y Ciencias de la Salud (IUIBS), Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
| | - Emilio Ros
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Unidad Clínica de Lípidos, Departamento de Nutrición y Endocrinología, Institut d'Investigacions Biomèdiques Agust Pi i Sunyer (IDIBAPS), Hospital Clínic, Universidad de Barcelona, Barcelona, Spain
| | - Fernando Arós
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Instituto Sanitario de Investigación de Bioaraba, Servicio Vasco de Salud-Osakidetza, Hospital Universitario de Araba; Universidad del País Vasco UPV/EHU; Vitoria-Gasteiz, Spain
| | - Jordi Salas-Salvadó
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Unitat de Nutrició Humana, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Reus, Tarragona, Spain; Institut d'Investigació Sanitària Pere iVirgili, Hospital Universitari Sant Joan de Reus, Reus, Tarragona, Spain
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, United States
| | - Miguel Ángel Martínez-González
- Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
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Wittenbecher C, Guasch-Ferré M, Haslam DE, Dennis C, Li J, Bhupathiraju SN, Lee CH, Qi Q, Liang L, Eliassen AH, Clish C, Sun Q, Hu FB. Changes in metabolomics profiles over ten years and subsequent risk of developing type 2 diabetes: Results from the Nurses' Health Study. EBioMedicine 2021; 75:103799. [PMID: 34979341 PMCID: PMC8733263 DOI: 10.1016/j.ebiom.2021.103799] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 12/19/2021] [Accepted: 12/20/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Metabolomics profiles were consistently associated with type 2 diabetes (T2D) risk, but evidence on long-term metabolite changes and T2D incidence is lacking. We examined the associations of 10-year plasma metabolite changes with subsequent T2D risk. METHODS We conducted a nested T2D case-control study (n=244 cases, n=244 matched controls) within the Nurses' Health Study. Repeated metabolomics profiling (170 targeted metabolites) was conducted in participant blood specimens from 1989/1990 and 2000/2001, and T2D occurred between 2002 and 2008. We related 10-year metabolite changes (Δ-values) to subsequent T2D risk using conditional logistic models, adjusting for baseline metabolite levels and baseline levels and concurrent changes of BMI, diet quality, physical activity, and smoking status. FINDINGS The 10-year changes of thirty-one metabolites were associated with subsequent T2D risk (false discovery rate-adjusted p-values [FDR]<0.05). The top three high T2D risk-associated 10-year changes were (odds ratio [OR] per standard deviation [SD], 95%CI): Δisoleucine (2.72, 1.97-3.79), Δleucine (2.53, 1.86-3.47), and Δvaline (1.93, 1.52-2.44); other high-risk-associated metabolite changes included alanine, tri-/diacylglycerol-fragments, short-chain acylcarnitines, phosphatidylethanolamines, some vitamins, and bile acids (ORs per SD between 1.31and 1.82). The top three low T2D risk-associated 10-year metabolite changes were (OR per SD, 95% CI): ΔN-acetylaspartic acid (0.54, 0.42-0.70), ΔC20:0 lysophosphatidylethanolamine (0.68, 0.56-0.82), and ΔC16:1 sphingomyelin (0.68, 0.56-0.83); 10-year changes of other sphingomyelins, plasmalogens, glutamine, and glycine were also associated with lower subsequent T2D risk (ORs per SD between 0.66 and 0.78). INTERPRETATION Repeated metabolomics profiles reflecting the long-term deterioration of amino acid and lipid metabolism are associated with subsequent risk of T2D.
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Affiliation(s)
- Clemens Wittenbecher
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany,German Center for Diabetes Research (DZD), Neuherberg, Germany,Corresponding authors at: Department of Nutrition, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA
| | - Danielle E. Haslam
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA
| | | | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Shilpa N. Bhupathiraju
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA
| | - Chih-Hao Lee
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Qibin Qi
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - A. Heather Eliassen
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Clary Clish
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Qi Sun
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,Corresponding authors at: Department of Nutrition, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
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41
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Cardelo MP, Alcala-Diaz JF, Gutierrez-Mariscal FM, Lopez-Moreno J, Villasanta-Gonzalez A, de Larriva APA, Cruz-Ares SDL, Delgado-Lista J, Rodriguez-Cantalejo F, Luque RM, Ordovas JM, Perez-Martinez P, Camargo A, Lopez-Miranda J. Diabetes remission is modulated by branched chain amino acids according to the diet consumed: from the CORDIOPREV study. Mol Nutr Food Res 2021; 66:e2100652. [PMID: 34863046 DOI: 10.1002/mnfr.202100652] [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: 07/07/2021] [Revised: 11/24/2021] [Indexed: 11/08/2022]
Abstract
SCOPE BCAA plasma levels may be differentially associated with type 2 diabetes mellitus (T2DM) remission through the consumption of the Mediterranean diet (Med) and a low-fat (LF) diet. METHODS 183 newly-diagnosed T2DM patients within the CORDIOPREV study were randomized to consume the Med or a LF diet. BCAA plasma levels (isoleucine, leucine and valine) were measured at fasting and after 120 min of an oral glucose tolerance test (OGTT) at the baseline of the study and after 5 y of the dietary intervention. RESULTS Isoleucine, leucine and valine plasma levels after 120 min of an OGTT in the Med diet (N = 80) were associated by COX analysis with T2DM remission: HR per SD (95%CI): 0.53 (0.37-0.77), 0.75 (0.52-1.08) and 0.61 (0.45-0.82), respectively; no association was found in patients who consumed a LF diet (N = 103). BCAA plasma levels combined in a score showed a HR of 3.33 (1.55-7.19) of T2DM remission for patients with a high score values in the Med diet, while in those with a LF diet no association was found. CONCLUSION Our study suggests that BCAA measurements potentially be used as a tool to select the most suitable diet to induce T2DM remission by nutritional strategies. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Magdalena P Cardelo
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
| | - Juan F Alcala-Diaz
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
| | - Francisco M Gutierrez-Mariscal
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
| | - Javier Lopez-Moreno
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
| | - Alejandro Villasanta-Gonzalez
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
| | - Antonio P Arenas- de Larriva
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC)
| | - Silvia de la Cruz-Ares
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
| | - Javier Delgado-Lista
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC)
| | - Fernando Rodriguez-Cantalejo
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC)
| | - Raul M Luque
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,Biochemical Laboratory, Reina Sofia University Hospital, Córdoba, Spain.,Department of Cell Biology, Physiology, and Immunology, University of Córdoba, Reina Sofía University Hospital, Maimonides Biomedical Research Institute of Córdoba (IMIBIC), Córdoba, Spain
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, J.M.-US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts, USA.,IMDEA Alimentación, Madrid, Spain, CNIC, Madrid, Spain
| | - Pablo Perez-Martinez
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
| | - Antonio Camargo
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
| | - Jose Lopez-Miranda
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University, Hospital, Cordoba, 14004, Spain.,Department of Medicine (Medicine, Dermatology and Otorhinolaryngology), University of Cordoba, 4004, Cordoba, Spain.,Maimonides Biomedical Research Institute of Cordoba (IMIBIC).,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Spain
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Galié S, Papandreou C, Arcelin P, Garcia D, Palau-Galindo A, Gutiérrez-Tordera L, Folch À, Bulló M. Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome. Nutrients 2021; 13:nu13124318. [PMID: 34959869 PMCID: PMC8706982 DOI: 10.3390/nu13124318] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 11/20/2021] [Accepted: 11/28/2021] [Indexed: 12/05/2022] Open
Abstract
(1) Background: The microbiota-host cross-talk has been previously investigated, while its role in health is not yet clear. This study aimed to unravel the network of microbial-host interactions and correlate it with cardiometabolic risk factors. (2) Methods: A total of 47 adults with overweight/obesity and metabolic syndrome from the METADIET study were included in this cross-sectional analysis. Microbiota composition (151 genera) was assessed by 16S rRNA sequencing, fecal (m = 203) and plasma (m = 373) metabolites were profiled. An unsupervised sparse generalized canonical correlation analysis was used to construct a network of microbiota-metabolite interactions. A multi-omics score was derived for each cluster of the network and associated with cardiometabolic risk factors. (3) Results: Five multi-omics clusters were identified. Thirty-one fecal metabolites formed these clusters and were correlated with plasma sphingomyelins, lysophospholipids and medium to long-chain acylcarnitines. Seven genera from Ruminococcaceae and a member from the Desulfovibrionaceae family were correlated with fecal and plasma metabolites. Positive correlations were found between the multi-omics scores from two clusters with cholesterol and triglycerides levels. (4) Conclusions: We identified a correlated network between specific microbial genera and fecal/plasma metabolites in an adult population with metabolic syndrome, suggesting an interplay between gut microbiota and host lipid metabolism on cardiometabolic health.
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Affiliation(s)
- Serena Galié
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University RoviraiVirgili (URV), 43201 Reus, Spain; (S.G.); (A.P.-G.); (L.G.-T.); (À.F.)
- Institute of Health Pere Virgili—IISPV, University Hospital Sant Joan, 43202 Reus, Spain;
| | - Christopher Papandreou
- Institute of Health Pere Virgili—IISPV, University Hospital Sant Joan, 43202 Reus, Spain;
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Correspondence: (C.P.); (M.B.); Tel.: +34-977-759388 (M.B.)
| | - Pierre Arcelin
- Institute of Health Pere Virgili—IISPV, University Hospital Sant Joan, 43202 Reus, Spain;
- Atención Basica de Salut (ABS) Reus V. Centre d’Assistència Primària Marià Fortuny, SAGESSA, 43204 Reus, Spain
| | - David Garcia
- ABS Alt Camp Oest, Centre d’Atenció Primària, 43460 Alcover, Spain;
| | - Antoni Palau-Galindo
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University RoviraiVirgili (URV), 43201 Reus, Spain; (S.G.); (A.P.-G.); (L.G.-T.); (À.F.)
- Atención Basica de Salut (ABS) Reus V. Centre d’Assistència Primària Marià Fortuny, SAGESSA, 43204 Reus, Spain
| | - Laia Gutiérrez-Tordera
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University RoviraiVirgili (URV), 43201 Reus, Spain; (S.G.); (A.P.-G.); (L.G.-T.); (À.F.)
- Institute of Health Pere Virgili—IISPV, University Hospital Sant Joan, 43202 Reus, Spain;
| | - Àlex Folch
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University RoviraiVirgili (URV), 43201 Reus, Spain; (S.G.); (A.P.-G.); (L.G.-T.); (À.F.)
- Institute of Health Pere Virgili—IISPV, University Hospital Sant Joan, 43202 Reus, Spain;
| | - Mònica Bulló
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University RoviraiVirgili (URV), 43201 Reus, Spain; (S.G.); (A.P.-G.); (L.G.-T.); (À.F.)
- Institute of Health Pere Virgili—IISPV, University Hospital Sant Joan, 43202 Reus, Spain;
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Correspondence: (C.P.); (M.B.); Tel.: +34-977-759388 (M.B.)
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Macías-Acosta MP, Valerdi-Contreras L, Bustos-Angel ED, García-Reyes RA, Alvarez-Zavala M, González-Ávila M. Involvement of the fecal amino acid profile in a clinical and anthropometric study of Mexican patients with insulin resistance and type 2 diabetes mellitus. Amino Acids 2021; 54:47-55. [PMID: 34821993 DOI: 10.1007/s00726-021-03107-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 11/15/2021] [Indexed: 12/25/2022]
Abstract
The amino acids synthesized by the intestinal microbiota have been correlated with metabolic diseases, such as type 2 diabetes mellitus and insulin resistance; both are high incidence conditions in Mexico. However, the knowledge of the relationship of fecal amino acids with the development of both diseases in the Mexican population is scarce. The clinical study was descriptive; the study was carried out in the Antiguo Civil Hospital of Guadalajara. Samples were taken from a total of 48 participants with insulin resistance, diabetes, and a control group (n = 16 each). Anthropometric and biochemical measures were evaluated. HPLC carried out the quantification of fecal amino acids. A strong correlation between alanine and HOMA-IR (r = 0.5416) was found and between phenylalanine and HOMA-IR (r = 0.4258). Other interesting correlations were between alanine and glucose (r = 0.5854) and isoleucine and glucose (r = 0.5008). The diabetic group and the insulin-resistant group had increased fecal values of valine and isoleucine (branched-chain amino acids), which were positively correlated with the progression of both conditions. Likewise, alanine and phenylalanine can help predict the development of the disease in the Mexican population. Registry number: 037/19.
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Affiliation(s)
- Mayra Paloma Macías-Acosta
- Department Medical and Pharmaceutical Biotechnology, Center for Research and Assistance in Technology and Design of the State of Jalisco (CIATEJ), A.C., 44270, Guadalajara, JAL, Mexico
| | - Lorena Valerdi-Contreras
- Head of the Medical Division and Assigned to Internal Medicine Department of Antiguo Civil Hospital of Guadalajara "Fray Antonio Alcalde", 44280, Guadalajara, JAL, Mexico
| | - Ericka Denise Bustos-Angel
- Assigned to the Internal Medicine Department of Antiguo Civil Hospital of Guadalajara "Fray Antonio Alcalde", 44280, Guadalajara, JAL, Mexico
| | - Rudy Antonio García-Reyes
- Department Medical and Pharmaceutical Biotechnology, Center for Research and Assistance in Technology and Design of the State of Jalisco (CIATEJ), A.C., 44270, Guadalajara, JAL, Mexico
| | - Monserrat Alvarez-Zavala
- Clinical Medicine Department, University Center of Health Sciences-University of Guadalajara, 44340, Guadalajara, JAL, Mexico
| | - Marisela González-Ávila
- Department Medical and Pharmaceutical Biotechnology, Center for Research and Assistance in Technology and Design of the State of Jalisco (CIATEJ), A.C., 44270, Guadalajara, JAL, Mexico.
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44
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Luís C, Baylina P, Soares R, Fernandes R. Metabolic Dysfunction Biomarkers as Predictors of Early Diabetes. Biomolecules 2021; 11:1589. [PMID: 34827587 PMCID: PMC8615896 DOI: 10.3390/biom11111589] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 10/26/2021] [Accepted: 10/26/2021] [Indexed: 12/23/2022] Open
Abstract
During the pathophysiological course of type 2 diabetes (T2D), several metabolic imbalances occur. There is increasing evidence that metabolic dysfunction far precedes clinical manifestations. Thus, knowing and understanding metabolic imbalances is crucial to unraveling new strategies and molecules (biomarkers) for the early-stage prediction of the disease's non-clinical phase. Lifestyle interventions must be made with considerable involvement of clinicians, and it should be considered that not all patients will respond in the same manner. Individuals with a high risk of diabetic progression will present compensatory metabolic mechanisms, translated into metabolic biomarkers that will therefore show potential predictive value to differentiate between progressors/non-progressors in T2D. Specific novel biomarkers are being proposed to entrap prediabetes and target progressors to achieve better outcomes. This study provides a review of the latest relevant biomarkers in prediabetes. A search for articles published between 2011 and 2021 was conducted; duplicates were removed, and inclusion criteria were applied. From the 29 studies considered, a survey of the most cited (relevant) biomarkers was conducted and further discussed in the two main identified fields: metabolomics, and miRNA studies.
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Affiliation(s)
- Carla Luís
- FMUP–Departamento de Biomedicina, Faculdade de Medicina da Universidade do Porto, 4200-319 Porto, Portugal;
- i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal;
- LABMI-PORTIC, Laboratory of Medical & Industrial Biotechnology, Porto Research, Technology and Innovation Center, Porto Polytechnic, 4200-375 Porto, Portugal;
| | - Pilar Baylina
- LABMI-PORTIC, Laboratory of Medical & Industrial Biotechnology, Porto Research, Technology and Innovation Center, Porto Polytechnic, 4200-375 Porto, Portugal;
- IPP–Escola Superior de Saúde, Instituto Politécnico do Porto, 4200-072 Porto, Portugal
| | - Raquel Soares
- FMUP–Departamento de Biomedicina, Faculdade de Medicina da Universidade do Porto, 4200-319 Porto, Portugal;
- i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal;
- Biochemistry Unit, Department of Biochemistry, FMUP, Faculty of Medicine, University of Porto, Al Prof Hernani Monteiro, 4200-319 Porto, Portugal
| | - Rúben Fernandes
- i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal;
- LABMI-PORTIC, Laboratory of Medical & Industrial Biotechnology, Porto Research, Technology and Innovation Center, Porto Polytechnic, 4200-375 Porto, Portugal;
- IPP–Escola Superior de Saúde, Instituto Politécnico do Porto, 4200-072 Porto, Portugal
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Ning Z, Song Z, Wang C, Peng S, Wan X, Liu Z, Lu A. How Perturbated Metabolites in Diabetes Mellitus Affect the Pathogenesis of Hypertension? Front Physiol 2021; 12:705588. [PMID: 34483960 PMCID: PMC8416465 DOI: 10.3389/fphys.2021.705588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 07/26/2021] [Indexed: 11/17/2022] Open
Abstract
The presence of hypertension (HTN) in type 2 diabetes mellitus (DM) is a common phenomenon in more than half of the diabetic patients. Since HTN constitutes a predictor of vascular complications and cardiovascular disease in type 2 DM patients, it is of significance to understand the molecular and cellular mechanisms of type 2 DM binding to HTN. This review attempts to understand the mechanism via the perspective of the metabolites. It reviewed the metabolic perturbations, the biological function of perturbated metabolites in two diseases, and the mechanism underlying metabolic perturbation that contributed to the connection of type 2 DM and HTN. DM-associated metabolic perturbations may be involved in the pathogenesis of HTN potentially in insulin, angiotensin II, sympathetic nervous system, and the energy reprogramming to address how perturbated metabolites in type 2 DM affect the pathogenesis of HTN. The recent integration of the metabolism field with microbiology and immunology may provide a wider perspective. Metabolism affects immune function and supports immune cell differentiation by the switch of energy. The diverse metabolites produced by bacteria modified the biological process in the inflammatory response of chronic metabolic diseases either. The rapidly evolving metabolomics has enabled to have a better understanding of the process of diseases, which is an important tool for providing some insight into the investigation of diseases mechanism. Metabolites served as direct modulators of biological processes were believed to assess the pathological mechanisms involved in diseases.
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Affiliation(s)
- Zhangchi Ning
- Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhiqian Song
- Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Chun Wang
- Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Shitao Peng
- Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiaoying Wan
- Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhenli Liu
- Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Aiping Lu
- School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
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Muralidharan J, Moreno-Indias I, Bulló M, Lopez JV, Corella D, Castañer O, Vidal J, Atzeni A, Fernandez-García JC, Torres-Collado L, Fernández-Carrión R, Fito M, Olbeyra R, Gomez-Perez AM, Galiè S, Bernal-López MR, Martinez-Gonzalez MA, Salas-Salvadó J, Tinahones FJ. Effect on gut microbiota of a 1-y lifestyle intervention with Mediterranean diet compared with energy-reduced Mediterranean diet and physical activity promotion: PREDIMED-Plus Study. Am J Clin Nutr 2021; 114:1148-1158. [PMID: 34020445 PMCID: PMC8408861 DOI: 10.1093/ajcn/nqab150] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 04/09/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The Mediterranean diet is a well-recognized healthy diet that has shown to induce positive changes in gut microbiota. Lifestyle changes such as diet along with physical activity could aid in weight loss and improve cardiovascular risk factors. OBJECTIVES To investigate the effect of an intensive lifestyle weight loss intervention on gut microbiota. METHODS This is a substudy of the PREDIMED-Plus (Prevención con Dieta Mediterránea-Plus), a randomized controlled trial conducted in overweight/obese men and women (aged 55-75 y) with metabolic syndrome. The intervention group (IG) underwent an intensive weight loss lifestyle intervention based on an energy-restricted Mediterranean diet (MedDiet) and physical activity promotion, and the control group (CG) underwent a non-energy-restricted MedDiet for 1 y. Anthropometric, biochemical, and gut microbial 16S rRNA sequencing data were analyzed at baseline (n = 362) and 1-y follow-up (n = 343). RESULTS IG participants had a weight loss of 4.2 (IQR, -6.8, -2.5) kg compared with 0.2 (IQR, -2.1, 1.4) kg in the CG (P < 0.001). Reductions in BMI, fasting glucose, glycated hemoglobin, and triglycerides and an increase in HDL cholesterol were greater in IG than in CG participants (P < 0.05). We observed a decrease in Butyricicoccus, Haemophilus, Ruminiclostridium 5, and Eubacterium hallii in the IG compared with the CG. Many genera shifted in the same direction within both intervention groups, indicating an overall effect of the MedDiet. Decreases in Haemophilus, Coprococcus 3, and few other genera were associated with a decrease in adiposity parameters in both intervention groups. Changes in Lachnospiraceae NK4A136 were positively associated with changes in MedDiet adherence. CONCLUSIONS Weight loss induced by an energy-restricted MedDiet and physical activity induce changes in gut microbiota. The role of MedDiet-induced changes on the host might be via short-chain fatty acid producing bacteria, whereas with energy restriction, these changes might be modulated with other mechanisms, which need to be explored in future studies. This trial was registered at http://www.isrctn.com/ISRCTN89898870 as ISRCT 89898870.
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Affiliation(s)
- Jananee Muralidharan
- Universitat Rovira i Virgili, Department of Biochemistry and Biotechnology, Hospital Universitari de Sant Joan de Reus, Institut d’Investigacions Sanitàries Pere i Virgili, Human Nutrition Unit, Reus, Spain,CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | | | | | - Jesús Vioque Lopez
- Instituto de Investigación Sanitaria y Biomédica de Alicante, ISABIAL-UMH, Alicante, Spain,CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Dolores Corella
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Olga Castañer
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,Cardiovascular Risk and Nutrition (Regicor Study Group), Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - Josep Vidal
- Endocrinology and Nutrition Department, Hospital Clinic Universitari, Barcelona, Spain,August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Alessandro Atzeni
- Universitat Rovira i Virgili, Department of Biochemistry and Biotechnology, Hospital Universitari de Sant Joan de Reus, Institut d’Investigacions Sanitàries Pere i Virgili, Human Nutrition Unit, Reus, Spain,CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Jose Carlos Fernandez-García
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,Unidad de Gestion Clínica de Endocrinología y Nutrición, Laboratorio del Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario de Málaga (Virgen de la Victoria), Universidad de Málaga, Málaga, Spain
| | - Laura Torres-Collado
- Instituto de Investigación Sanitaria y Biomédica de Alicante, ISABIAL-UMH, Alicante, Spain,CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Rebeca Fernández-Carrión
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Monsterrat Fito
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,Cardiovascular Risk and Nutrition (Regicor Study Group), Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - Romina Olbeyra
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Ana Maria Gomez-Perez
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,Unidad de Gestion Clínica de Endocrinología y Nutrición, Laboratorio del Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario de Málaga (Virgen de la Victoria), Universidad de Málaga, Málaga, Spain
| | - Serena Galiè
- Universitat Rovira i Virgili, Department of Biochemistry and Biotechnology, Hospital Universitari de Sant Joan de Reus, Institut d’Investigacions Sanitàries Pere i Virgili, Human Nutrition Unit, Reus, Spain,CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Maria Rosa Bernal-López
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,UGC Medicina Interna, Hospital Regional Universitario de Málaga, Malaga, Spain
| | - Miguel Angel Martinez-Gonzalez
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA, Pamplona, Spain,Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Department of Biochemistry and Biotechnology, Hospital Universitari de Sant Joan de Reus, Institut d’Investigacions Sanitàries Pere i Virgili, Human Nutrition Unit, Reus, Spain,CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Francisco Jose Tinahones
- CIBER de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain,Unidad de Gestion Clínica de Endocrinología y Nutrición, Laboratorio del Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario de Málaga (Virgen de la Victoria), Universidad de Málaga, Málaga, Spain
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Abstract
PURPOSE OF REVIEW An increasing body of evidence suggests that the gut microbiome influences the pathogenesis of insulin resistance and type 2 diabetes (T2D). In this review, we will discuss the latest findings regarding the mechanisms linking the gut microbiome and microbial metabolites with T2D and therapeutic approaches based on the gut microbiota for the prevention and treatment of T2D. RECENT FINDINGS Alterations in the gut microbial composition are associated with the risk of T2D. The gut microbiota can metabolize dietary- and host-derived factors to produce numerous microbial metabolites, which are involved in metabolic processes modulating nutrition and energy harvest, gut barrier function, systemic inflammation, and glucose metabolism. Microbial metabolites are important mediators of microbial-host crosstalk impacting host glucose metabolism. Furthermore, microbiome-based interventions may have beneficial effects on glycemic control. Future research is required to develop personalized T2D therapy based on microbial composition and/or metabolites.
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Caballero FF, Struijk EA, Buño A, Vega-Cabello V, Rodríguez-Artalejo F, Lopez-Garcia E. Plasma Amino Acids and Risk of Impaired Lower-Extremity Function and Role of Dietary Intake: A Nested Case-Control Study in Older Adults. Gerontology 2021; 68:181-191. [PMID: 33965943 DOI: 10.1159/000516028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 03/22/2021] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Amino acids are key elements in the regulation of the aging process which entails a progressive loss of muscle mass. The health effects of plasma amino acids can be influenced by dietary intake. This study assessed the prospective association between amino acid species and impaired lower-extremity function (ILEF) in older adults, exploring the role of diet on this association. METHODS This is a case-control design comprising 43 incident cases of ILEF and 85 age- and sex-matched controls. Plasma concentrations of 20 amino acid species were measured at baseline using liquid chromatography-tandem mass spectrometry, and incident cases of ILEF were measured after 2 years by means of the Short Physical Performance Battery. Conditional logistic regression models were used to assess longitudinal relationships. RESULTS After adjusting for potential confounders, higher levels of tryptophan were associated with a decreased 2-year risk of ILEF (OR per 1-SD increase = 0.64, 95% CI = [0.42, 0.97]), while glutamine and total essential amino acids were linked to higher ILEF risk (OR = 1.57, 95% CI = [1.01, 2.45]; OR = 1.89, 95% CI = [1.18, 3.03], respectively). Those with a lower adherence to a Mediterranean diet, a higher BMI, a higher consumption of red meat, and a lower consumption of nuts and legumes had an increased risk of ILEF associated with higher levels of essential amino acids. DISCUSSION/CONCLUSION Some amino acid species could serve as risk markers for physical function decline in older adults, and healthy diet might attenuate the excess risk of ILEF linked to essential amino acids.
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Affiliation(s)
- Francisco Félix Caballero
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid-IdiPaz and CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Ellen A Struijk
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid-IdiPaz and CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Antonio Buño
- Department of Laboratory Medicine, La Paz University Hospital-IdiPaz, Madrid, Spain
| | - Verónica Vega-Cabello
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid-IdiPaz and CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Fernando Rodríguez-Artalejo
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid-IdiPaz and CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain.,IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
| | - Esther Lopez-Garcia
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid-IdiPaz and CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain.,IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
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49
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Drouin-Chartier JP, Hernández-Alonso P, Guasch-Ferré M, Ruiz-Canela M, Li J, Wittenbecher C, Razquin C, Toledo E, Dennis C, Corella D, Estruch R, Fitó M, Eliassen AH, Tobias DK, Ascherio A, Mucci LA, Rexrode KM, Karlson EW, Costenbader KH, Fuchs CS, Liang L, Clish CB, Martínez-González MA, Salas-Salvadó J, Hu FB. Dairy consumption, plasma metabolites, and risk of type 2 diabetes. Am J Clin Nutr 2021; 114:163-174. [PMID: 33742198 PMCID: PMC8246603 DOI: 10.1093/ajcn/nqab047] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 02/08/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Epidemiologic studies have reported a modest inverse association between dairy consumption and the risk of type 2 diabetes (T2D). Whether plasma metabolite profiles associated with dairy consumption reflect this relationship remains unknown. OBJECTIVES We aimed to identify the plasma metabolites associated with total and specific dairy consumption, and to evaluate the association between the identified multi-metabolite profiles and T2D. METHODS The discovery population included 1833 participants from the Prevención con Dieta Mediterránea (PREDIMED) trial. The confirmatory cohorts included 1522 PREDIMED participants at year 1 of the trial and 4932 participants from the Nurses' Health Studies (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-Up Study US-based cohorts. Dairy consumption was assessed using validated FFQs. Plasma metabolites (n = 385) were profiled using LC-MS. We identified the dairy-related metabolite profiles using elastic net regularized regressions with a 10-fold cross-validation procedure. We evaluated the associations between the metabolite profiles and incident T2D in the discovery and the confirmatory cohorts. RESULTS Total dairy intake was associated with 38 metabolites. C14:0 sphingomyelin (positive coefficient), C34:0 phosphatidylethanolamine (positive coefficient), and γ-butyrobetaine (negative coefficient) were associated in a directionally similar fashion with total and specific (milk, yogurt, cheese) dairy consumption. The Pearson correlation coefficients between self-reported total dairy intake and predicted total dairy intake based on the corresponding multi-metabolite profile were 0.37 (95% CI, 0.33-0.40) in the discovery cohort and 0.16 (95% CI, 0.13-0.19) in the US confirmatory cohort. After adjusting for T2D risk factors, a higher total dairy intake-related metabolite profile score was associated with a lower T2D risk [HR per 1 SD; discovery cohort: 0.76 (95% CI, 0.63-0.90); US confirmatory cohort: 0.88 (95% CI, 0.78-0.99)]. CONCLUSIONS Total dairy intake was associated with 38 metabolites, including 3 consistently associated with dairy subtypes (C14:0 sphingomyelin, C34:0 phosphatidylethanolamine, γ-butyrobetaine). A score based on the 38 identified metabolites showed an inverse association with T2D risk in Spanish and US populations.
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Affiliation(s)
| | - Pablo Hernández-Alonso
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Hospital Universitari San Joan de Reus, Reus, Spain,Institut d'Investigació Pere Virgili (IISPV), Reus, Spain,Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Unidad de Gestión Clínica de Endocrinología y Nutrición del Hospital Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, 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
| | - Miguel Ruiz-Canela
- Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain,University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain
| | - Jun Li
- 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
| | - Clemens Wittenbecher
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Cristina Razquin
- Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain,University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain
| | - Estefanía Toledo
- Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain,University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain
| | - Courtney Dennis
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Dolores Corella
- Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramon Estruch
- Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Internal Medicine, Department of Endocrinology and Nutrition Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Montserrat Fitó
- Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Cardiovascular and Nutrition Research Group, Institut de Recerca Hospital del Mar, Barcelona, Spain
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Deirdre K Tobias
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA,Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alberto Ascherio
- Department of Nutrition, 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,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Lorelei A Mucci
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kathryn M Rexrode
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA,Division of Women`s Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth W Karlson
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Karen H Costenbader
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Charles S Fuchs
- Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA
| | - 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
| | - Clary B Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Miguel A Martínez-González
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA,Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain,University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Hospital Universitari San Joan de Reus, Reus, Spain,Institut d'Investigació Pere Virgili (IISPV), Reus, Spain,Consorcio Centro de Investigación Biomedica en Red Fisiopatologia de la Obesidad y Nutricion, Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Frank B Hu
- Department of Nutrition, 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,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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50
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Cheng D, Zhao X, Yang S, Cui H, Wang G. Metabolomic Signature Between Metabolically Healthy Overweight/Obese and Metabolically Unhealthy Overweight/Obese: A Systematic Review. Diabetes Metab Syndr Obes 2021; 14:991-1010. [PMID: 33692630 PMCID: PMC7939496 DOI: 10.2147/dmso.s294894] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 01/28/2021] [Indexed: 12/11/2022] Open
Abstract
The clinical manifestations of overweight/obesity are heterogeneous and complex. In contrast to metabolically unhealthy overweight/obese (MUO), a particular sub-group of obese patients who are considered as metabolically healthy overweight/obese (MHO), display favorable metabolic profiles characterized by high levels of insulin sensitivity, normal blood pressure, as well as favorable lipid, inflammation, hormone, liver enzyme, and immune profiles. While only a few available studies focused on the metabolic files underlying the obese phenotypes, the current review aimed to perform a systematic review of available studies focusing on describing the metabolomic signature between MUO and MHO. We did the systematic search for literature on MEDLINE (PubMed), the Cochrane Library, EMBASE, and searched for the references of relevant manuscripts from inception to 29 May 2020. After critical selection, 20 studies were eligible for this systematic review and evaluated by using QUADOMICS for quality assessment. Eventually, 12 of 20 studies were classified as "high quality". Branched-chain amino acids (isoleucine, leucine, and valine), aromatic amino acids (phenylalanine and tyrosine), lipids (palmitic acid, palmitoleic acid, oleic acid, eicosapentaenoic acid, and docosahexaenoic acid), and acylcarnitines (propionyl carnitine) levels might be elevated in MUO. The current results suggested that MHO showed a favorable trend in the overall metabolic signature. More longitudinal studies are needed to elaborate deeply on the metabolic pathway and the relationship between metabolic patterns and the occurrence of the disease.
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Affiliation(s)
- Dihe Cheng
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, 130021, People’s Republic of China
| | - Xue Zhao
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, 130021, People’s Republic of China
| | - Shuo Yang
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, 130021, People’s Republic of China
| | - Haiying Cui
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, 130021, People’s Republic of China
| | - Guixia Wang
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, 130021, People’s Republic of China
- Correspondence: Guixia Wang Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, 130021, People’s Republic of ChinaTel +15843081103 Email
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