Marta Guasch-Ferré1, Adela Hruby2, Estefanía Toledo3, Clary B Clish4, Miguel A Martínez-González3, Jordi Salas-Salvadó5, Frank B Hu6. 1. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA Human Nutrition Unit, Faculty of Medicine and Health Sciences, Pere Virgili Institute for Health Research, Rovira i Virgili University, Reus, Spain CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain. 2. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA. 3. CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain Department of Preventive Medicine and Public Health, University of Navarra, Health Research Institute of Navarra, Pamplona, Spain. 4. Broad Institute, Cambridge, MA. 5. Human Nutrition Unit, Faculty of Medicine and Health Sciences, Pere Virgili Institute for Health Research, Rovira i Virgili University, Reus, Spain CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain. 6. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA nhbfh@channing.harvard.edu.
Abstract
OBJECTIVE: To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes. RESEARCH DESIGN AND METHODS: We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite. RESULTS: We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24-1.48]; I(2) = 9.5%), 36% for leucine (1.36 [1.17-1.58]; I(2) = 37.4%), 35% for valine (1.35 [1.19-1.53]; I(2) = 45.8%), 36% for tyrosine (1.36 [1.19-1.55]; I(2) = 51.6%), and 26% for phenylalanine (1.26 [1.10-1.44]; I(2) = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81-0.96] and 0.85 [0.82-0.89], respectively; both I(2) = 0.0%). CONCLUSIONS: In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.
OBJECTIVE: To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes. RESEARCH DESIGN AND METHODS: We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite. RESULTS: We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24-1.48]; I(2) = 9.5%), 36% for leucine (1.36 [1.17-1.58]; I(2) = 37.4%), 35% for valine (1.35 [1.19-1.53]; I(2) = 45.8%), 36% for tyrosine (1.36 [1.19-1.55]; I(2) = 51.6%), and 26% for phenylalanine (1.26 [1.10-1.44]; I(2) = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81-0.96] and 0.85 [0.82-0.89], respectively; both I(2) = 0.0%). CONCLUSIONS: In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.
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