Metabolomics insights into early type 2 diabetes pathogenesis and detection in individuals with normal fasting glucose
暂无分享,去创建一个
Thomas J. Wang | J. Flannick | J. Florez | J. Meigs | J. Dupuis | R. Gerszten | Ching‐Ti Liu | B. Porneala | G. Walford | J. Merino | A. Leong | M. V. Grotthuss | Bianca C. Porneala | D. Levy | M. Grotthuss
[1] Tero Aittokallio,et al. Early metabolic markers identify potential targets for the prevention of type 2 diabetes , 2017, Diabetologia.
[2] T. Hansen,et al. Genetic evidence of a causal effect of insulin resistance on branched-chain amino acid levels , 2017, Diabetologia.
[3] Ashutosh Kumar Singh,et al. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015 , 2016, Lancet.
[4] Stephen C. J. Parker,et al. The genetic architecture of type 2 diabetes , 2016, Nature.
[5] L. Liang,et al. Early Prediction of Developing Type 2 Diabetes by Plasma Acylcarnitines: A Population-Based Study , 2016, Diabetes Care.
[6] Frank B Hu,et al. Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis , 2016, Diabetes Care.
[7] M. M. Rahman,et al. Worldwide trends in diabetes since 1980 : pooled analysis of 751 population-based measurement studies with over 4 . 4 million participants , 2016 .
[8] M. Pirinen,et al. Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA , 2016, Nature Communications.
[9] Thomas J. Wang,et al. Metabolite Profiles of Diabetes Incidence and Intervention Response in the Diabetes Prevention Program , 2016, Diabetes.
[10] E. Barrett-Connor,et al. Long-term Effects of Lifestyle Intervention or Metformin on Diabetes Development and Microvascular Complications: the DPP Outcomes Study , 2015, The lancet. Diabetes & endocrinology.
[11] V. Mohan,et al. Incidence of Diabetes and Prediabetes and Predictors of Progression Among Asian Indians: 10-Year Follow-up of the Chennai Urban Rural Epidemiology Study (CURES) , 2015, Diabetes Care.
[12] David S. Wishart,et al. MetaboAnalyst 3.0—making metabolomics more meaningful , 2015, Nucleic Acids Res..
[13] G. Davey Smith,et al. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression , 2015, International journal of epidemiology.
[14] Wanchang Lin,et al. Untargeted metabolic profiling identifies altered serum metabolites of type 2 diabetes mellitus in a prospective, nested case control study. , 2015, Clinical chemistry.
[15] Thomas J. Wang,et al. Metabolite Traits and Genetic Risk Provide Complementary Information for the Prediction of Future Type 2 Diabetes , 2014, Diabetes Care.
[16] R. Vasan,et al. 2-Aminoadipic acid is a biomarker for diabetes risk. , 2013, The Journal of clinical investigation.
[17] A. Butterworth,et al. Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data , 2013, Genetic epidemiology.
[18] Jussi Paananen,et al. Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes , 2013, Diabetes.
[19] A. Peters,et al. Identification of Serum Metabolites Associated With Risk of Type 2 Diabetes Using a Targeted Metabolomic Approach , 2013, Diabetes.
[20] Wolfgang Rathmann,et al. Prediabetes: a high-risk state for diabetes development , 2012, The Lancet.
[21] C. Newgard. Interplay between lipids and branched-chain amino acids in development of insulin resistance. , 2012, Cell metabolism.
[22] R. Tibshirani,et al. Regression shrinkage and selection via the lasso: a retrospective , 2011 .
[23] V. Mootha,et al. Metabolite profiles and the risk of developing diabetes , 2011, Nature Medicine.
[24] K. Park,et al. Hemoglobin A1c as a Diagnostic Tool for Diabetes Screening and New-Onset Diabetes Prediction , 2011, Diabetes Care.
[25] P. Toth. Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans , 2011 .
[26] Svati H Shah,et al. A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. , 2009, Cell metabolism.
[27] Ru Wei,et al. Metabolic profiling of the human response to a glucose challenge reveals distinct axes of insulin sensitivity , 2008, Molecular systems biology.
[28] Ralph B D'Agostino,et al. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. , 2007, Archives of internal medicine.
[29] D. Pereg,et al. Normal fasting plasma glucose levels and type 2 diabetes in young men. , 2005, The New England journal of medicine.
[30] G. Kikuchi. The glycine cleavage system: Composition, reaction mechanism, and physiological significance , 1973, Molecular and Cellular Biochemistry.
[31] R. Turner,et al. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man , 1985, Diabetologia.
[32] S. Fowler,et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. , 2002 .
[33] J M Dekker,et al. Relation of impaired fasting and postload glucose with incident type 2 diabetes in a Dutch population: The Hoorn Study. , 2001, JAMA.
[34] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[35] E. DeLong,et al. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. , 1988, Biometrics.
[36] W. Kannel,et al. An investigation of coronary heart disease in families. The Framingham offspring study. , 1979, American journal of epidemiology.
[37] R. Levy,et al. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. , 1972, Clinical chemistry.