Untargeted Profiling of Concordant/Discordant Phenotypes of High Insulin Resistance and Obesity To Predict the Risk of Developing Diabetes.
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Raul Gonzalez-Dominguez | Cristina Andres-Lacueva | Anna Marco-Ramell | Magali Palau-Rodriguez | Alex Sanchez-Pla | F. Tinahones | Alex Sánchez-Pla | M. Macías-González | C. Andrés-Lacueva | O. Jáuregui | S. Tulipani | F. Cardona | A. Miñarro | A. Marco-Ramell | R. González-Domínguez | Fernando Cardona | Olga Jauregui | Sara Tulipani | Francisco J Tinahones | M. Palau-Rodriguez | Antonio Miñarro | Manuel Macias-Gonzalez | Álex Sánchez-Pla | Anna Marco-Ramell
[1] F. Tinahones,et al. Metabolomic insights into the intricate gut microbial–host interaction in the development of obesity and type 2 diabetes , 2015, Front. Microbiol..
[2] Jasper Engel,et al. Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling , 2016, Metabolomics.
[3] M. Patti,et al. Bile acids, obesity, and the metabolic syndrome. , 2014, Best practice & research. Clinical gastroenterology.
[4] Nigel W. Hardy,et al. Proposed minimum reporting standards for chemical analysis , 2007, Metabolomics.
[5] M. Tomita,et al. Serum metabolomics reveals γ-glutamyl dipeptides as biomarkers for discrimination among different forms of liver disease. , 2011, Journal of hepatology.
[6] Julian L Griffin,et al. Metabolomics as a functional genomic tool for understanding lipid dysfunction in diabetes, obesity and related disorders. , 2006, Pharmacogenomics.
[7] F. Tinahones,et al. New and vintage solutions to enhance the plasma metabolome coverage by LC-ESI-MS untargeted metabolomics: the not-so-simple process of method performance evaluation. , 2015, Analytical chemistry.
[8] M. Puig-Domingo,et al. Prevención, diagnóstico y tratamiento de la obesidad. Posicionamiento de la Sociedad Española para el Estudio de la Obesidad de 2016 , 2016 .
[9] David R. Gilbert,et al. MetaNetter: inference and visualization of high-resolution metabolomic networks , 2008, Bioinform..
[10] Ian D. Wilson,et al. Metabolic Phenotyping in Health and Disease , 2008, Cell.
[11] Andreas Krämer,et al. Causal analysis approaches in Ingenuity Pathway Analysis , 2013, Bioinform..
[12] K. Petersen,et al. Lipid-induced insulin resistance: unravelling the mechanism , 2010, The Lancet.
[13] David S. Wishart,et al. Current Progress in computational metabolomics , 2007, Briefings Bioinform..
[14] R. Holman,et al. Normal weight individuals who develop type 2 diabetes: the personal fat threshold. , 2015, Clinical science.
[15] Oliver Fiehn,et al. Chemical Similarity Enrichment Analysis (ChemRICH) as alternative to biochemical pathway mapping for metabolomic datasets , 2017, Scientific Reports.
[16] Hae-Young Kim,et al. Statistical notes for clinical researchers: Chi-squared test and Fisher's exact test , 2017, Restorative dentistry & endodontics.
[17] F. Tinahones,et al. The obese healthy paradox: is inflammation the answer? , 2010, The Biochemical journal.
[18] G. Shulman,et al. Diacylglycerol-mediated insulin resistance , 2010, Nature Medicine.
[19] D. Levy,et al. Glycemic status and development of kidney disease: the Framingham Heart Study. , 2005, Diabetes care.
[20] G. Boden. Insulin Resistance and Free Fatty Acids , 2011 .
[21] Tim D. Spector,et al. Mixing omics: combining genetics and metabolomics to study rheumatic diseases , 2017, Nature Reviews Rheumatology.
[22] Bhawna Singh,et al. Surrogate markers of insulin resistance: A review. , 2010, World journal of diabetes.
[23] R. A. van den Berg,et al. Centering, scaling, and transformations: improving the biological information content of metabolomics data , 2006, BMC Genomics.
[24] J. Cabral,et al. Hyporeninemic hypoaldosteronism and diabetes mellitus: Pathophysiology assumptions, clinical aspects and implications for management. , 2016, World journal of diabetes.
[25] Y. Tsai,et al. The metabolome profiling and pathway analysis in metabolic healthy and abnormal obesity , 2015, International Journal of Obesity.
[26] M. Urpi-Sardà,et al. Comparative analysis of sample preparation methods to handle the complexity of the blood fluid metabolome: when less is more. , 2013, Analytical chemistry.
[27] V. Mootha,et al. Metabolite profiles and the risk of developing diabetes , 2011, Nature Medicine.
[28] O. Monte,et al. Cholesterol oxides as biomarkers of oxidative stress in type 1 and type 2 diabetes mellitus , 2007, Diabetes/metabolism research and reviews.
[29] F. Karpe,et al. Fatty Acids, Obesity, and Insulin Resistance: Time for a Reevaluation , 2011, Diabetes.
[30] J. Gómez-Ariza,et al. Iberian ham typification by direct infusion electrospray and photospray ionization mass spectrometry fingerprinting. , 2012, Rapid communications in mass spectrometry : RCM.
[31] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[32] F. Tinahones,et al. Metabolomics‐guided insights on bariatric surgery versus behavioral interventions for weight loss , 2016, Obesity.
[33] Satoru Kodama,et al. Association Between Serum Uric Acid and Development of Type 2 Diabetes , 2009, Diabetes Care.
[34] T. Azuma,et al. Adrenic acid as an inflammation enhancer in non-alcoholic fatty liver disease. , 2017, Archives of biochemistry and biophysics.
[35] V. Mootha,et al. Metabolite profiles and the risk of developing diabetes , 2011, Nature Network Boston.
[36] I. Bondia-Pons,et al. Oxidative stress and inflammation interactions in human obesity , 2012, Journal of Physiology and Biochemistry.
[37] Alexandre Perera-Lluna,et al. An R package to analyse LC/MS metabolomic data: MAIT (Metabolite Automatic Identification Toolkit) , 2014, Bioinform..
[38] Jean-François Hocquette,et al. Assessment of hierarchical clustering methodologies for proteomic data mining. , 2007, Journal of proteome research.
[39] 2. Classification and Diagnosis of Diabetes , 2014, Diabetes Care.
[40] F. Tinahones,et al. Biomarkers of Morbid Obesity and Prediabetes by Metabolomic Profiling of Human Discordant Phenotypes. , 2016, Clinica chimica acta; international journal of clinical chemistry.
[41] F. Tinahones,et al. Adipose tissue infiltration in normal-weight subjects and its impact on metabolic function. , 2016, Translational research : the journal of laboratory and clinical medicine.
[42] D. Fairlie,et al. Inflammatory lipid mediators in adipocyte function and obesity , 2010, Nature Reviews Endocrinology.
[43] Cristina Andres-Lacueva,et al. Plasma metabolomic biomarkers of mixed nuts exposure inversely correlate with severity of metabolic syndrome. , 2015, Molecular nutrition & food research.
[44] M. Lanaspa,et al. Uric acid in metabolic syndrome: From an innocent bystander to a central player. , 2016, European journal of internal medicine.