Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study
暂无分享,去创建一个
C. Gieger | W. Rathmann | A. Peters | M. McCarthy | S. Brunak | M. Schulze | A. Ziegler | G. Willemsen | T. Pischon | D. Boomsma | E. D. de Geus | M. Beekman | J. Deelen | H. Grallert | P. Slagboom | K. Suhre | M. Roden | R. Wang-Sattler | C. Herder | L. T. ’t Hart | Ramneek Gupta | A. Jonsson | B. Thorand | H. Boeing | D. van Heemst | E. D. Geus | S. Wahl | J. Adamski | R. Pool | C. Prehn | V. Gudmundsdottir | H. Draisma | M. Kramer | S. Hummel | A. Floegel | E. Pearson | H. Pedersen | D. Heemst | W. Bernigau | N. van Leeuwen | D. Much | Michaela Breier | E. Eekhoff | N. Leeuwen | L. Hart | A. Simonis-Bik | Mark Haid | S. Molnos | L. '. ’t Hart | P. Slagboom | D. Boomsma | M. McCarthy | A. Peters | Anna Floegel | M. McCarthy | A. Peters
[1] Scott B. Crown,et al. Catabolism of Branched Chain Amino Acids Contributes Significantly to Synthesis of Odd-Chain and Even-Chain Fatty Acids in 3T3-L1 Adipocytes , 2015, PloS one.
[2] Christian Gieger,et al. Novel biomarkers for pre-diabetes identified by metabolomics , 2012, Molecular systems biology.
[3] Nele Friedrich,et al. Metabolomics in diabetes research. , 2012, The Journal of endocrinology.
[4] R. Holle,et al. Incidence of Type 2 diabetes in the elderly German population and the effect of clinical and lifestyle risk factors: KORA S4/F4 cohort study , 2009, Diabetic medicine : a journal of the British Diabetic Association.
[5] Jerzy Adamski,et al. Procedure for tissue sample preparation and metabolite extraction for high-throughput targeted metabolomics , 2011, Metabolomics.
[6] M. Beekman,et al. Nonagenarian Siblings and Their Offspring Display Lower Risk of Mortality and Morbidity than Sporadic Nonagenarians: The Leiden Longevity Study , 2009, Journal of the American Geriatrics Society.
[7] K. Suhre. Metabolic profiling in diabetes. , 2014, The Journal of endocrinology.
[8] E. Benjamin,et al. Plasma Asymmetric Dimethylarginine and Incidence of Cardiovascular Disease and Death in the Community , 2009, Circulation.
[9] H. Boeing,et al. Recruitment Procedures of EPIC-Germany , 1999, Annals of Nutrition and Metabolism.
[10] A. Beyerlein,et al. Postpartum outcomes in women with gestational diabetes and their offspring: POGO study design and first-year results. , 2013, The review of diabetic studies : RDS.
[11] H. Finner,et al. Specific Metabolic Profiles and Their Relationship to Insulin Resistance in Recent-Onset Type 1 and Type 2 Diabetes. , 2016, The Journal of clinical endocrinology and metabolism.
[12] J. Hartung,et al. On tests of the overall treatment effect in meta‐analysis with normally distributed responses , 2001, Statistics in medicine.
[13] R. Lehmann,et al. Metabolic profiles during an oral glucose tolerance test in pregnant women with and without gestational diabetes. , 2015, Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association.
[14] Inês Barroso,et al. Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis , 2016, PLoS medicine.
[15] David S. Wishart,et al. HMDB: a knowledgebase for the human metabolome , 2008, Nucleic Acids Res..
[16] Kurt Hoffmann,et al. An Accurate Risk Score Based on Anthropometric, Dietary, and Lifestyle Factors to Predict the Development of Type 2 Diabetes , 2007, Diabetes Care.
[17] H. Boeing,et al. Recruitment procedures of EPIC-Germany. European Investigation into Cancer and Nutrition. , 1999, Annals of nutrition & metabolism.
[18] M. Kleber,et al. Childhood Obesity Is Associated with Changes in the Serum Metabolite Profile , 2012, Obesity Facts.
[19] Christian Gieger,et al. Metabolic Footprint of Diabetes: A Multiplatform Metabolomics Study in an Epidemiological Setting , 2010, PloS one.
[20] D. Boomsma,et al. Genetic influences on the insulin response of the beta cell to different secretagogues , 2009, Diabetologia.
[21] Karel G M Moons,et al. Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct): a validation of existing models. , 2014, The lancet. Diabetes & endocrinology.
[22] J. Adamski,et al. Targeted Metabolomics of Dried Blood Spot Extracts , 2013, Chromatographia.
[23] Terho Lehtimäki,et al. Branched-Chain and Aromatic Amino Acids Are Predictors of Insulin Resistance in Young Adults , 2013, Diabetes Care.
[24] Gabi Kastenmüller,et al. Biochemical insights from population studies with genetics and metabolomics. , 2016, Archives of biochemistry and biophysics.
[25] D. Altshuler,et al. Branched chain and aromatic amino acids change acutely following two medical therapies for type 2 diabetes mellitus. , 2013, Metabolism: clinical and experimental.
[26] Søren Højsgaard,et al. The R Package geepack for Generalized Estimating Equations , 2005 .
[27] Hans L. Hillege,et al. External validation of the KORA S4/F4 prediction models for the risk of developing type 2 diabetes in older adults: the PREVEND study , 2011, European Journal of Epidemiology.
[28] E. Hardt,et al. A novel hyperglycaemic clamp for characterization of islet function in humans: assessment of three different secretagogues, maximal insulin response and reproducibility , 2000, European journal of clinical investigation.
[29] T. Lehner,et al. The Netherlands Twin Register Biobank: A Resource for Genetic Epidemiological Studies , 2010, Twin Research and Human Genetics.
[30] M. Beekman,et al. Favorable Glucose Tolerance and Lower Prevalence of Metabolic Syndrome in Offspring without Diabetes Mellitus of Nonagenarian Siblings: The Leiden Longevity Study , 2010, Journal of the American Geriatrics Society.
[31] Christian Gieger,et al. On the hypothesis-free testing of metabolite ratios in genome-wide and metabolome-wide association studies , 2012, BMC Bioinformatics.
[32] R. DeFronzo,et al. Glucose clamp technique: a method for quantifying insulin secretion and resistance. , 1979, The American journal of physiology.
[33] R Holle,et al. KORA - A Research Platform for Population Based Health Research , 2005, Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)).
[34] A. Peters,et al. Identification of Serum Metabolites Associated With Risk of Type 2 Diabetes Using a Targeted Metabolomic Approach , 2013, Diabetes.
[35] K. V. van Dijk,et al. Reanalysis of mGWAS results and in vitro validation show that lactate dehydrogenase interacts with branched-chain amino acid metabolism , 2015, European Journal of Human Genetics.
[36] Christian M. Metallo,et al. Branched chain amino acid catabolism fuels adipocyte differentiation and lipogenesis , 2015, Nature chemical biology.
[37] K. Suhre,et al. Metabolic switch during adipogenesis: From branched chain amino acid catabolism to lipid synthesis. , 2016, Archives of biochemistry and biophysics.
[38] Tuija Tammelin,et al. Metabolic Signatures of Insulin Resistance in 7,098 Young Adults , 2012, Diabetes.
[39] Frank B Hu,et al. Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis , 2016, Diabetes Care.
[40] Christian Gieger,et al. A genome-wide perspective of genetic variation in human metabolism , 2010, Nature Genetics.
[41] Alla Karnovsky,et al. Metabolomics and Diabetes: Analytical and Computational Approaches , 2015, Diabetes.
[42] Christian Gieger,et al. Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels , 2015, Nature Communications.
[43] C. Gieger,et al. Comparative analysis of plasma metabolomics response to metabolic challenge tests in healthy subjects and influence of the FTO obesity risk allele , 2013, Metabolomics.
[44] D. Boomsma,et al. The impact of genetic variation in the G6PC2 gene on insulin secretion depends on glycemia. , 2010, The Journal of clinical endocrinology and metabolism.
[45] J. Griffin,et al. Towards metabolic biomarkers of insulin resistance and type 2 diabetes: progress from the metabolome. , 2014, The lancet. Diabetes & endocrinology.