Novel biomarkers for pre-diabetes identified by metabolomics
Open accessAbstract
Type 2 diabetes (T2D) can be prevented in pre-diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre-diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre-diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4×10(-4) to 2.1×10(-13). Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. Using metabolite-protein network analysis, we identified seven T2D-related genes that are associated with these three IGT-specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D.
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An independent inverse association of glycine with diabetes risk was previously described by us and others.
“described by us and others (12,41).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [41]
Heme biosynthesis is an important glycine-using pathway triggered by high iron availability.
“Interestingly, heme biosynthesis, which is triggered by high iron availability, is an important glycine-using pathway, and high expression of heme-synthesizing enzymes was associated with low circulating glycine concentrations in humans (41).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [41]
High expression of heme-synthesizing enzymes is associated with low circulating glycine concentrations in humans.
“Interestingly, heme biosynthesis, which is triggered by high iron availability, is an important glycine-using pathway, and high expression of heme-synthesizing enzymes was associated with low circulating glycine concentrations in humans (41).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [41]
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Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538 · see citing works
Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin
(2002) · New England Journal of Medicine · doi:10.1056/nejmoa012512 · Cited by 19,011 · see citing works
Diagnosis and Classification of Diabetes Mellitus
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc11-s062 · Cited by 14,019 · see citing works
Tuomilehto, J., Lindström, J., Eriksson, J. G., Valle, T. T., Hämäläinen, H., Ilanne-Parikka, P., Keinänen-Kiukaanniemi, S., Laakso, M., Louheranta, A., Rastas, M., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200105033441801 · Cited by 10,873 · see citing works
Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,185 · see citing works
Szklarczyk, D., Franceschini, A., Kuhn, M., Simonovic, M., Roth, A. C., Mínguez, P., Doerks, T., Stark, M., Muller, J., Bork, P., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq973 · Cited by 3,469 · see citing works
Newgard, C. B., An, J., Bain, J. R., Muehlbauer, M. J., Stevens, R. D., Lien, L. F., Haqq, A. M., Shah, S. H., Arlotto, M., Slentz, C. A., et al. (2009) · Cell Metabolism · doi:10.1016/j.cmet.2009.02.002 · Cited by 3,165 · see citing works
Metabolite profiles and the risk of developing diabetes
Wang, T. J., Larson, M. G., Vasan, R. S., Cheng, S., Rhee, E. P., McCabe, E., Lewis, G. D., Fox, C. S., Jacques, P. F., Fernandez, C., et al. (2011) · Nature Medicine · doi:10.1038/nm.2307 · Cited by 3,143 · see citing works
Prediabetes: a high-risk state for diabetes development
Tabák, A. G., Herder, C., Rathmann, W., Brunner, E. J., & Kivimäki, M. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60283-9 · Cited by 2,958 · see citing works
Self-citationType 2 diabetes: principles of pathogenesis and therapy
Stumvoll, M., Goldstein, B. J., & van Haeften, T. W. (2005) · The Lancet · doi:10.1016/s0140-6736(05)61032-x · Cited by 2,662 · see citing works
Koves, T. R., Ussher, J. R., Noland, R. C., Slentz, D., Mosedale, M., Ilkayeva, O., Bain, J., Stevens, R., Dyck, J. R. B., Newgard, C. B., et al. (2008) · Cell Metabolism · doi:10.1016/j.cmet.2007.10.013 · Cited by 1,990 · see citing works
HMDB: a knowledgebase for the human metabolome
Wishart, D. S., Knox, C., Guo, A. C., Eisner, R., Young, N., Gautam, B., Hau, D., Psychogios, N., Dong, E., Bouatra, S., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn810 · Cited by 1,874 · see citing works
Riboli, E., Hunt, K., Slimani, N., Ferrari, P., Norat, T., Fahey, M., Charrondière, U., Hémon, B., Casagrande, C., Vignat, J., et al. (2002) · Public Health Nutrition · doi:10.1079/phn2002394 · Cited by 1,866 · see citing works
Self-citationMcGarry, J. D. (2002) · Diabetes · doi:10.2337/diabetes.51.1.7 · Cited by 1,435 · see citing works
Molecular and metabolic mechanisms of insulin resistance and β-cell failure in type 2 diabetes
Muoio, D. M., & Newgard, C. B. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2327 · Cited by 1,177 · see citing works
Tabák, A. G., Jokela, M., Akbaraly, T. N., Brunner, E. J., Kivimäki, M., & Witte, D. R. (2009) · The Lancet · doi:10.1016/s0140-6736(09)60619-x · Cited by 898 · see citing works
Morino, K. (2005) · Journal of Clinical Investigation · doi:10.1172/jci25151 · Cited by 811 · see citing works
KORA - A Research Platform for Population Based Health Research
Holle, R., Happich, M., Löwel, H., & Wichmann, H. ‐. (2005) · Das Gesundheitswesen · doi:10.1055/s-2005-858235 · Cited by 753 · see citing works
Self-citationA genome-wide perspective of genetic variation in human metabolism
Illig, T., Gieger, C., Zhai, G., Römisch-Margl, W., Wang-Sattler, R., Prehn, C., Altmaier, E., Kastenmüller, G., Kato, B. S., Mewes, H.-W., et al. (2010) · Nature Genetics · doi:10.1038/ng.507 · Cited by 653 · see citing works
Self-citationRhee, E. P., Cheng, S., Larson, M. G., Walford, G. A., Lewis, G. D., McCabe, E., Yang, E., Farrell, L., Fox, C. S., O’Donnell, C. J., et al. (2011) · Journal of Clinical Investigation · doi:10.1172/jci44442 · Cited by 647 · see citing works
Adams, S. H., Hoppel, C. L., Lok, K. H., Zhao, L., Wong, S. W., Minkler, P. E., Hwang, D. H., Newman, J. W., & Garvey, W. T. (2009) · The Journal of Nutrition · doi:10.3945/jn.108.103754 · Cited by 598 · see citing works
Metabolite Profiling Identifies Pathways Associated With Metabolic Risk in Humans
Cheng, S. C., Rhee, E. P., Larson, M. G., Lewis, G. D., McCabe, E. L., Shen, D., Palma, M. J., Roberts, L. D., Dejam, A., Souza, A. L., et al. (2012) · Circulation · doi:10.1161/circulationaha.111.067827 · Cited by 588 · see citing works
KORA-gen - Resource for Population Genetics, Controls and a Broad Spectrum of Disease Phenotypes
Wichmann, H. ‐., Gieger, C., & Illig, T. (2005) · Das Gesundheitswesen · doi:10.1055/s-2005-858226 · Cited by 417 · see citing works
Self-citationShaham, O., Wei, R., Wang, T. J., Ricciardi, C., Lewis, G. D., Vasan, R. S., Carr, S. A., Thadhani, R., Gerszten, R. E., & Mootha, V. K. (2008) · Molecular Systems Biology · doi:10.1038/msb.2008.50 · Cited by 399 · see citing works
Mechanism of Amino Acid-Induced Skeletal Muscle Insulin Resistance in Humans
Krebs, M., Krssak, M., Bernroider, E., Anderwald, C., Brehm, A., Meyerspeer, M., Nowotny, P., Roth, E., Waldhäusl, W., & Roden, M. (2002) · Diabetes · doi:10.2337/diabetes.51.3.599 · Cited by 392 · see citing works
Self-citationDiscovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers
Mittelstraß, K., Ried, J. S., Yu, Z., Krumsiek, J., Gieger, C., Prehn, C. P., Roemisch‐Margl, W., Polonikov, A., Peters, A., Theis, F. J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002215 · Cited by 385 · see citing works
Self-citationHuman serum metabolic profiles are age dependent
Yu, Z., Zhai, G., Singmann, P., He, Y., Xu, T., Prehn, C., Römisch‐Margl, W., Lattka, E., Gieger, C., Soranzo, N., et al. (2012) · Aging Cell · doi:10.1111/j.1474-9726.2012.00865.x · Cited by 340 · see citing works
Self-citationNoland, R. C., Koves, T. R., Seiler, S. E., Lum, H., Lust, R. M., Ilkayeva, O., Stevens, R. D., Hegardt, F. G., & Muoio, D. M. (2009) · Journal of Biological Chemistry · doi:10.1074/jbc.m109.032888 · Cited by 317 · see citing works
Römisch‐Margl, W., Prehn, C. P., Bogumil, R., Röhring, C., Suhre, K., & Adamski, J. (2011) · Metabolomics · doi:10.1007/s11306-011-0293-4 · Cited by 292 · see citing works
Self-citationExecutive Summary: Standards of Medical Care in Diabetes—2010
(2009) · Diabetes Care · doi:10.2337/dc10-s004 · Cited by 286 · see citing works
Chen, H., Ju, H., Wu, T.-T., Liu, Y., Lee, C., Chang, C., Chung, Y., & Shieh, C. (2010) · BioMed Research International · doi:10.1155/2011/950725 · Cited by 262 · see citing works
EPIC-Germany – A Source for Studies into Diet and Risk of Chronic Diseases
Boeing, H., Wahrendorf, J., & Becker, N. (1999) · Annals of Nutrition and Metabolism · doi:10.1159/000012786 · Cited by 256 · see citing works
Self-citationMuscle Mitochondrial ATP Synthesis and Glucose Transport/Phosphorylation in Type 2 Diabetes
Szendroedi, J., Schmid, A. I., Chmelik, M., Toth, C., Brehm, A., Krssak, M., Nowotny, P., Wolzt, M., Waldhausl, W., & Roden, M. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040154 · Cited by 243 · see citing works
Self-citationAssociation of Lipidome Remodeling in the Adipocyte Membrane with Acquired Obesity in Humans
Pietiläinen, K. H., Róg, T., Seppänen‐Laakso, T., Virtue, S., Gopalacharyulu, P. V., Tang, J. P., Rodríguez‐Cuenca, S., Maciejewski, A., Naukkarinen, J., Ruskeepää, A., et al. (2011) · PLoS Biology · doi:10.1371/journal.pbio.1000623 · Cited by 238 · see citing works
Færch, K., Vaag, A. A., Holst, J. J., Hansen, T. F., Jørgensen, T., & Borch‐Johnsen, K. (2008) · Diabetes Care · doi:10.2337/dc08-1195 · Cited by 207 · see citing works
Metabonomic fingerprints of fasting plasma and spot urine reveal human pre-diabetic metabolic traits
Zhao, X., Fritsche, J., Wang, J., Chen, J., Rittig, K., Schmitt‐Kopplin, P., Fritsche, A., Häring, H., Schleicher, E. D., Xu, G., et al. (2010) · Metabolomics · doi:10.1007/s11306-010-0203-1 · Cited by 207 · see citing works
Rathmann, W., Straßburger, K., Heier, M., Holle, R., Thorand, B., Giani, G., & Meisinger, C. (2009) · Diabetic Medicine · doi:10.1111/j.1464-5491.2009.02863.x · Cited by 181 · see citing works
Self-citationChanges in Peroxisomal Fatty Acid Oxidation in the Diabetic Rat Liver
Horie, S., Ishii, H., & Suga, T. (1981) · The Journal of Biochemistry · doi:10.1093/oxfordjournals.jbchem.a133645 · Cited by 172 · see citing works
Follow-Up Procedures in EPIC-Germany – Data Quality Aspects
Bergmann, M. M., Bussas, U., & Boeing, H. (1999) · Annals of Nutrition and Metabolism · doi:10.1159/000012789 · Cited by 141 · see citing works
Self-citationFloegel, A., Drogan, D., Wang-Sattler, R., Prehn, C., Illig, T., Adamski, J., Joost, H.-G., Boeing, H., & Pischon, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021103 · Cited by 135 · see citing works
Self-citationComputational detection of cis -regulatory modules
Aerts, S., Loo, P. V., Thijs, G., Moreau, Y., & Moor, B. D. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg1052 · Cited by 126 · see citing works
Wopereis, S., Rubingh, C. M., van Erk, M. J., Verheij, E. R., van Vliet, T., Cnubben, N. H. P., Smilde, A. K., van der Greef, J., van Ommen, B., & Hendriks, H. F. J. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004525 · Cited by 123 · see citing works
Serum Metabolite Concentrations and Decreased GFR in the General Population
Goek, O.-N., Döring, A., Gieger, C., Heier, M., Koenig, W., Prehn, C., Römisch-Margl, W., Wang-Sattler, R., Illig, T., Suhre, K., et al. (2012) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2012.01.014 · Cited by 121 · see citing works
Self-citationBody Fat Free Mass Is Associated with the Serum Metabolite Profile in a Population-Based Study
Jourdan, C., Petersen, A.-K., Gieger, C., Döring, A., Illig, T., Wang‐Sattler, R., Meisinger, C., Peters, A., Adamski, J., Prehn, C. P., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040009 · Cited by 107 · see citing works
Self-citationMeisinger, C., Straßburger, K., Heier, M., Thorand, B., Baumeister, S., Giani, G., & Rathmann, W. (2009) · Diabetic Medicine · doi:10.1111/j.1464-5491.2009.02905.x · Cited by 94 · see citing works
Self-citationAltmaier, E., Kastenmüller, G., Römisch-Margl, W., Thorand, B., Weinberger, K. M., Illig, T., Adamski, J., Döring, A., & Suhre, K. (2011) · European Journal of Epidemiology · doi:10.1007/s10654-010-9524-7 · Cited by 84 · see citing works
Self-citationmetaP‐Server: A Web‐Based Metabolomics Data Analysis Tool
Kastenmüller, G., Römisch‐Margl, W., Wägele, B., Altmaier, E., & Suhre, K. (2010) · BioMed Research International · doi:10.1155/2011/839862 · Cited by 77 · see citing works
Self-citationRathmann, W., Kowall, B., Heier, M., Herder, C., Holle, R., Thorand, B., Strassburger, K., Peters, A., Wichmann, H. ‐., Giani, G., et al. (2010) · Diabetic Medicine · doi:10.1111/j.1464-5491.2010.03065.x · Cited by 74 · see citing works
Self-citationBishop, D. F. (1990) · Nucleic Acids Research · doi:10.1093/nar/18.23.7187 · Cited by 64 · see citing works
Obscurin Depletion Impairs Organization of Skeletal Muscle in Developing Zebrafish Embryos
Raeker, M. Ö., & Russell, M. W. W. (2011) · BioMed Research International · doi:10.1155/2011/479135 · Cited by 63 · see citing works
Metabolomics and human nutrition
Primrose, S. B., Draper, J., Elsom, R. L., Kirkpatrick, V., Mathers, J. C., Seal, C. J., Beckmann, M., Haldar, S., Beattie, J. H., Lodge, J. K., et al. (2011) · British Journal Of Nutrition · doi:10.1017/s0007114510004812 · Cited by 63 · see citing works
Effect of Somatostatin on Meal-stimulated Pancreatic Exocrine Secretions in Dogs
Wilson, R. M., Boden, G. H., Shore, L. S., & Essa-Koumar, N. (1977) · Diabetes · doi:10.2337/diab.26.1.7 · Cited by 43 · see citing works
Pontiroli, A. E., Pizzocri, P., Caumo, A., Perseghin, G., & Luzi, L. (2004) · Acta Diabetologica · doi:10.1007/s00592-004-0147-x · Cited by 29 · see citing works
Phillips, J. D., & Kushner, J. P. (2005) · Nature Medicine · doi:10.1038/nm1005-1049 · Cited by 22 · see citing works
Hypoglycaemia: a therapeutic concern in type 2 diabetes
Garber, A. J. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60947-7 · Cited by 16 · see citing works
Arachidonic acid and glucose uptake by freshly isolated human adipocytes
Malipa, A. C. A., Meintjes, R. A., & Haag, M. (2007) · Cell Biochemistry and Function · doi:10.1002/cbf.1439 · Cited by 4 · see citing works
Sridharan, S., Gunathilake, W., Fernando, D., & Idris, I. (2010) · Diabetic Medicine · doi:10.1111/j.1464-5491.2010.03077.x · Cited by 4 · see citing works
Alberti (1998) · doi:10.1002/(sici)1096-9136(199807)15:7
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The role of microbial amino acid metabolism in host metabolism
Neis, E., Dejong, C., & Rensen, S. (2015) · Nutrients · doi:10.3390/nu7042930 · Cited by 920 · see citing works
Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis
Guasch‐Ferré, M., Hruby, A., Toledo, E., Clish, C. B., Martínez‐González, M. Á., Salas‐Salvadó, J., & Hu, F. B. (2016) · Diabetes Care · doi:10.2337/dc15-2251 · Cited by 908 · see citing works
An Updated Review of Lysophosphatidylcholine Metabolism in Human Diseases
Law, S.-H., Chan, M.-L., Marathe, G. K., Parveen, F., Chen, C.-H., & Ke, L.-Y. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20051149 · Cited by 817 · see citing works
Linking Gut Microbiota and Inflammation to Obesity and Insulin Resistance
Saad, M. J. A., Santos, A., & Prada, P. O. (2016) · Physiology · doi:10.1152/physiol.00041.2015 · Cited by 818 · see citing works
The Subtle Balance between Lipolysis and Lipogenesis: A Critical Point in Metabolic Homeostasis
Saponaro, C., Gaggini, M., Carli, F., & Gastaldelli, A. (2015) · Nutrients · doi:10.3390/nu7115475 · Cited by 531 · see citing works
Acylcarnitines: Nomenclature, Biomarkers, Therapeutic Potential, Drug Targets, and Clinical Trials
Dambrova, M., Makrecka‐Kuka, M., Kuka, J., Vilšķe̅rsts, R., Nordberg, D. O. T., Attwood, M. M., Smesny, S., Şen, Z. D., Guo, A. C., Oler, E., et al. (2022) · Pharmacological Reviews · doi:10.1124/pharmrev.121.000408 · Cited by 528 · see citing works
Altered amino acid concentrations in NAFLD: Impact of obesity and insulin resistance
Gaggini, M., Carli, F., Rosso, C., Buzzigoli, E., Marietti, M., Latta, V. D., Ciociaro, D., Abate, M. L., Gambino, R., Cassader, M., et al. (2017) · Hepatology · doi:10.1002/hep.29465 · Cited by 467 · see citing works
Lotta, L. A., Scott, R. A., Sharp, S. J., Burgess, S., Luan, J., Tillin, T., Schmidt, A. F., Imamura, F., Stewart, I. D., Perry, J. R. B., et al. (2016) · PLOS Medicine · doi:10.1371/journal.pmed.1002179 · Cited by 417 · see citing works
Osteocalcin Signaling in Myofibers Is Necessary and Sufficient for Optimum Adaptation to Exercise
Mera, P., Laue, K., Ferron, M., Confavreux, C. B., Wei, J., Galán-Díez, M., Lacampagne, A., Mitchell, S. J., Mattison, J. A., Chen, Y., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.05.004 · Cited by 429 · see citing works
Menni, C., Fauman, E., Erte, I., Perry, J. R. B., Kastenmüller, G., Shin, S.-Y., Petersen, A.-K., Hyde, C., Psatha, M., Ward, K. J., et al. (2013) · Diabetes · doi:10.2337/db13-0570 · Cited by 416 · see citing works
Self-citationMetabolomics toward personalized medicine
Jacob, M., Lopata, A. L., Dasouki, M., & Rahman, A. M. A. (2017) · Mass Spectrometry Reviews · doi:10.1002/mas.21548 · Cited by 405 · see citing works
de Mello, V. D., Paananen, J., Lindström, J., Lankinen, M. A., Shi, L. S., Kuusisto, J., Pihlajamäki, J., Auriola, S. O. K., Lehtonen, M., Rolandsson, O., et al. (2017) · Scientific Reports · doi:10.1038/srep46337 · Cited by 383 · see citing works
Livestock metabolomics and the livestock metabolome: A systematic review
Goldansaz, S. A., Guo, A. C., Sajed, T., Steele, M. A., Plastow, G. S., & Wishart, D. S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177675 · Cited by 379 · see citing works
Glycine Metabolism and Its Alterations in Obesity and Metabolic Diseases
Alves, A., Bassot, A., Bulteau, A., Pirola, L., & Morio, B. (2019) · Nutrients · doi:10.3390/nu11061356 · Cited by 371 · see citing works
Metabolomics for clinical use and research in chronic kidney disease
Hocher, B., & Adamski, J. (2017) · Nature Reviews Nephrology · doi:10.1038/nrneph.2017.30 · Cited by 335 · see citing works
Self-citationMansur, R. B., Brietzke, E. M., & McIntyre, R. S. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.12.017 · Cited by 325 · see citing works
Morze, J., Wittenbecher, C., Schwingshackl, L., Danielewicz, A., Rynkiewicz, A., Hu, F. B., & Guasch‐Ferré, M. (2022) · Diabetes Care · doi:10.2337/dc21-1705 · Cited by 303 · see citing works
Large-scale Metabolomic Profiling Identifies Novel Biomarkers for Incident Coronary Heart Disease
Ganna, A., Salihović, S., Sundström, J., Broeckling, C. D., Hedman, Å. K., Magnusson, P. K. E., Pedersen, N. L., Larsson, A. O., Siegbahn, A. G., Zilmer, M., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004801 · Cited by 283 · see citing works
Metabolomics of type 1 and type 2 diabetes
Arneth, B., Arneth, R., & Shams, M. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20102467 · Cited by 262 · see citing works
Umeno, A., Biju, V., & Yoshida, Y. (2017) · Free Radical Research · doi:10.1080/10715762.2017.1315114 · Cited by 268 · see citing works
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Metwaly, A., Reitmeier, S., & Haller, D. (2022) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-022-00581-2 · Cited by 263 · see citing works
Siskos, A. P., Jain, P., Römisch-Margl, W., Bennett, M., Achaintre, D., Asad, Y., Marney, L., Richardson, L., Koulman, A., Griffin, J. L., et al. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.6b02930 · Cited by 269 · see citing works
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Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies
Jin, Q., & Ma, R. C. W. (2021) · Cells · doi:10.3390/cells10112832 · Cited by 252 · see citing works
Cui, X., Qian, D., Jiang, S., Shang, E., Zhu, Z., & Duan, J. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19113634 · Cited by 245 · see citing works
Novel biomarkers for prediabetes, diabetes, and associated complications
Dorcely, B., Katz, K., Jagannathan, R., Chiang, S. S., Oluwadare, B., Goldberg, I. J., & Bergman, M. (2017) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s100074 · Cited by 227 · see citing works
Environmental risk factors of type 2 diabetes—an exposome approach
Beulens, J. W. J., de Pinho, M. G. M., Abreu, T. C., den Braver, N. R., Lam, T. M., Huss, A., Vlaanderen, J. J., Sonnenschein, T., Siddiqui, N. Z., Yuan, Z., et al. (2021) · Diabetologia · doi:10.1007/s00125-021-05618-w · Cited by 223 · see citing works
Significance of l ‐carnitine for human health
Adeva‐Andany, M. M., Calvo‐Castro, I., Fernández‐Fernández, C., Donapetry, C., & Pedre‐Piñeiro, A. M. (2017) · IUBMB Life · doi:10.1002/iub.1646 · Cited by 214 · see citing works
A metabolomic study of biomarkers of meat and fish intake
Cheung, W., Keski-Rahkonen, P., Assi, N., Ferrari, P., Freisling, H., Rinaldi, S., Slimani, N., Zamora-Ros, R., Rundle, M., Frost, G., et al. (2017) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.146639 · Cited by 206 · see citing works
Self-citationMetabolomics and Proteomics in Type 2 Diabetes
Chen, Z., & Gerszten, R. E. (2020) · Circulation Research · doi:10.1161/circresaha.120.315898 · Cited by 207 · see citing works
A computationally fast variable importance test for random forests for high-dimensional data
Janitza, S., Celik, E., & Boulesteix, A. (2016) · Advances in Data Analysis and Classification · doi:10.1007/s11634-016-0276-4 · Cited by 203 · see citing works
Review of methods for detecting glycemic disorders
Bergman, M., Abdul‐Ghani, M. A., DeFronzo, R. A., Manco, M., Sesti, G., Fiorentino, T. V., Ceriello, A., Rhee, M. K., Phillips, L. S., Chung, S. T., et al. (2020) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2020.108233 · Cited by 202 · see citing works
Interorgan Metabolic Crosstalk in Human Insulin Resistance
Gancheva, S., Jeleník, T., Álvarez-Hernández, E., & Roden, M. (2018) · Physiological Reviews · doi:10.1152/physrev.00015.2017 · Cited by 192 · see citing works
Self-citationIshikawa, M., Maekawa, K., Saito, K., Senoo, Y., Urata, M., Murayama, M., Tajima, Y., Kumagai, Y., & Saito, Y. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091806 · Cited by 187 · see citing works
Dumas, M., Kinross, J. K., & Nicholson, J. K. (2013) · Gastroenterology · doi:10.1053/j.gastro.2013.11.001 · Cited by 186 · see citing works
Ho, J. E., Larson, M. G., Ghorbani, A., Cheng, S. C., Chen, M., Keyes, M. J., Rhee, E. P., Clish, C. B., Vasan, R. S., Gerszten, R. E., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0148361 · Cited by 188 · see citing works
Vangipurapu, J., Stančáková, A., Smith, U., Kuusisto, J., & Laakso, M. (2019) · Diabetes · doi:10.2337/db18-1076 · Cited by 185 · see citing works
Tzoulaki, I., Ebbels, T. M. D., Valdes, A. M., Elliott, P., & Ioannidis, J. P. A. (2014) · American Journal of Epidemiology · doi:10.1093/aje/kwu143 · Cited by 183 · see citing works
Serum Levels of Acylcarnitines Are Altered in Prediabetic Conditions
Mai, M., Tönjes, A., Kovacs, P. L., Stümvoll, M., Fiedler, M., & Leichtle, A. B. (2013) · PLoS ONE · doi:10.1371/journal.pone.0082459 · Cited by 178 · see citing works
Skene, D. J., Skornyakov, E., Chowdhury, N. R., Gajula, R. P., Middleton, B., Satterfield, B. C., Porter, K. I., Van Dongen, H. P. A., & Gaddameedhi, S. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1801183115 · Cited by 176 · see citing works
A Metabolomic Approach to Understanding the Metabolic Link between Obesity and Diabetes
Park, S., Sadanala, K. C., & Kim, E. K. (2015) · Molecules and Cells · doi:10.14348/molcells.2015.0126 · Cited by 168 · see citing works
Metabolomics and Diabetes: Analytical and Computational Approaches
Sas, K. M., Karnovsky, A., Michailidis, G. C., & Pennathur, S. (2015) · Diabetes · doi:10.2337/db14-0509 · Cited by 169 · see citing works
Metabolomics as a tool for the early diagnosis and prognosis of diabetic kidney disease
Pereira, P., Carrageta, D. F., Oliveira, P. F., Rodrigues, A. S., Alves, M. G., & Monteiro, M. P. (2022) · Medicinal Research Reviews · doi:10.1002/med.21883 · Cited by 167 · see citing works
Giesbertz, P., Padberg, I., Rein, D., Ecker, J., Hoefle, A. S., Spanier, B., & Daniel, H. (2015) · Diabetologia · doi:10.1007/s00125-015-3656-y · Cited by 164 · see citing works
Early Prediction of Developing Type 2 Diabetes by Plasma Acylcarnitines: A Population-Based Study
Sun, L. D., Liang, L., Gao, X., Zhang, H., Yao, P., Hu, Y., Ma, Y., Wang, F., Jin, Q., Li, H., et al. (2016) · Diabetes Care · doi:10.2337/dc16-0232 · Cited by 166 · see citing works
Self-citationInsulin resistance and glycine metabolism in humans
Adeva‐Andany, M. M., Souto-Adeva, G., Ameneiros-Rodríguez, E., Fernández-Fernández, C., Donapetry, C., & Domínguez-Montero, A. (2017) · Amino Acids · doi:10.1007/s00726-017-2508-0 · Cited by 163 · see citing works
Wigger, L., Barovic, M., Brunner, A., Marzetta, F., Schöniger, E., Mehl, F., Kipke, N., Friedland, D., Burdet, F., Kessler, C., et al. (2021) · Nature Metabolism · doi:10.1038/s42255-021-00420-9 · Cited by 158 · see citing works
Prediabetes and associated disorders
Buysschaert, M., Medina, J. L., Bergman, M., Shah, A., & Lonier, J. (2014) · Endocrine · doi:10.1007/s12020-014-0436-2 · Cited by 159 · see citing works
Allalou, A., Nalla, A., Prentice, K. J., Liu, Y., Zhang, M., Dai, F. F., Ning, X., Osborne, L. R., Cox, B., Gunderson, E. P., et al. (2016) · Diabetes · doi:10.2337/db15-1720 · Cited by 159 · see citing works
Metabolic fingerprint of Gestational Diabetes Mellitus
Dudzik, D., Żórawski, M., Skotnicki, M., Zarzycki, W., Kozłowska, G., Bibik-Malinowska, K., Vallejo, M., Garcı́a, A., Barbas, C., & Ramos, P. (2014) · Journal of Proteomics · doi:10.1016/j.jprot.2014.03.025 · Cited by 154 · see citing works
Pietzner, M., Kaul, A., Henning, A., Kastenmüller, G., Artati, A., Lerch, M. M., Adamski, J., Nauck, M. A., & Friedrich, N. (2017) · BMC Medicine · doi:10.1186/s12916-017-0974-6 · Cited by 152 · see citing works
Self-citationDefects in muscle branched-chain amino acid oxidation contribute to impaired lipid metabolism
Lerín, C., Goldfine, A. B., Boes, T., Liu, M., Kasif, S., Dreyfuss, J. M., Sousa‐Coelho, A. L. D., Daher, G., Manoli, I., Sysol, J. R., et al. (2016) · Molecular Metabolism · doi:10.1016/j.molmet.2016.08.001 · Cited by 150 · see citing works
Metabolomics Signatures in Type 2 Diabetes: A Systematic Review and Integrative Analysis
Sun, Y., Gao, H., Fan, Z., He, Y., & Yan, Y. (2019) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgz240 · Cited by 149 · see citing works
Self-citationPerakakis, N., Yazdani, A. Z. K., Karniadakis, G. E., & Mantzoros, C. S. (2018) · Metabolism · doi:10.1016/j.metabol.2018.08.002 · Cited by 148 · see citing works
Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men
Suvitaival, T., Bondia‐Pons, I., Yetukuri, L., Pöhö, P., Nolan, J. J., Hyötyläinen, T., Kuusisto, J., & Orešič, M. (2017) · Metabolism · doi:10.1016/j.metabol.2017.08.014 · Cited by 147 · see citing works
Lu, J., Lam, S. M., Wan, Q., Shi, L., Huo, Y., Chen, L., Tang, X., Li, B., Wu, X., Peng, K., et al. (2019) · Diabetes Care · doi:10.2337/dc19-0100 · Cited by 147 · see citing works
Drogan, D., Dunn, W. B., Lin, W., Buijsse, B., Schulze, M. B., Langenberg, C., Brown, M., Floegel, A., Dietrich, S., Rolandsson, O., et al. (2014) · Clinical Chemistry · doi:10.1373/clinchem.2014.228965 · Cited by 145 · see citing works
Self-citationMetabolomics and Type 2 Diabetes: Translating Basic Research into Clinical Application
Klein, M. S., & Shearer, J. (2015) · Journal of Diabetes Research · doi:10.1155/2016/3898502 · Cited by 139 · see citing works
Xu, T., Holzapfel, C., Dong, X., Bader, E., Yu, Z., Prehn, C. P., Perstorfer, K., Jaremek, M., Roemisch‐Margl, W., Rathmann, W., et al. (2013) · BMC Medicine · doi:10.1186/1741-7015-11-60 · Cited by 140 · see citing works
Self-citationSerum and plasma amino acids as markers of prediabetes, insulin resistance, and incident diabetes
Gar, C., Rottenkolber, M., Prehn, C. P., Adamski, J., Seißler, J., & Lechner, A. (2017) · Critical Reviews in Clinical Laboratory Sciences · doi:10.1080/10408363.2017.1414143 · Cited by 140 · see citing works
Self-citationEffects of Metformin on Metabolite Profiles and LDL Cholesterol in Patients With Type 2 Diabetes
Xu, T., Brandmaier, S., Messias, A. C., Herder, C., Draisma, H. H. M., Demirkan, A., Yu, Z., Ried, J. S., Haller, T., Heier, M., et al. (2015) · Diabetes Care · doi:10.2337/dc15-0658 · Cited by 137 · see citing works
Self-citationEarly metabolic markers identify potential targets for the prevention of type 2 diabetes
Gopalacharyulu, P. V., Cobb, J. E., Yengo, L., Froguel, P., Kravić, J., Balkau, B., Tuomilehto, J., Aittokallio, T. A., & Groop, L. (2017) · Diabetologia · doi:10.1007/s00125-017-4325-0 · Cited by 138 · see citing works
The relationship between phospholipids and insulin resistance: From clinical to experimental studies
Chang, W., Hatch, G. M., Wang, Y., Yu, F., & Wang, M. (2018) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.13984 · Cited by 142 · see citing works
Analytical Metabolomics and Applications in Health, Environmental and Food Science
Fraga‐Corral, M., Carpena, M., Garcia‐Oliveira, P., Pereira, A. G., Prieto, M. A., & Simal‐Gándara, J. (2020) · Critical Reviews in Analytical Chemistry · doi:10.1080/10408347.2020.1823811 · Cited by 138 · see citing works
Libert, D. M., Nowacki, A. S., & Natowicz, M. R. (2018) · PeerJ · doi:10.7717/peerj.5410 · Cited by 135 · see citing works
α-Hydroxybutyric Acid Is a Selective Metabolite Biomarker of Impaired Glucose Tolerance
Cobb, J. E., Eckhart, A. D., Motsinger‐Reif, A. A., Carr, B., Groop, L., & Ferrannini, E. (2016) · Diabetes Care · doi:10.2337/dc15-2752 · Cited by 135 · see citing works
Assessing the causal association of glycine with risk of cardio-metabolic diseases
Wittemans, L. B. L., Lotta, L. A., Oliver‐Williams, C., Stewart, I. D., Surendran, P., Karthikeyan, S., Day, F. R., Koulman, A., Imamura, F., Zeng, L., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08936-1 · Cited by 134 · see citing works
Floegel, A., von Ruesten, A., Drogan, D., Schulze, M. B., Prehn, C. P., Adamski, J., Pischon, T., & Boeing, H. (2013) · European Journal of Clinical Nutrition · doi:10.1038/ejcn.2013.147 · Cited by 132 · see citing works
Self-citationUrine metabolome profiling of immune-mediated inflammatory diseases
Alonso, A., Julià, A., Vinaixa, M., Domènech, E., Fernández‐Nebro, A., Cañete, J. D. D., Ferrándiz, C., Tornero, J., Gisbert, J. P., Nos, P., et al. (2016) · BMC Medicine · doi:10.1186/s12916-016-0681-8 · Cited by 131 · see citing works
Prospective analysis of circulating metabolites and breast cancer in EPIC
His, M., Viallon, V., Dossus, L., Gicquiau, A., Achaintre, D., Scalbert, A., Ferrari, P., Romieu, I., Onland‐Moret, N. C., Weiderpass, E., et al. (2019) · BMC Medicine · doi:10.1186/s12916-019-1408-4 · Cited by 130 · see citing works
Self-citationSerum and Adipose Tissue Amino Acid Homeostasis in the Metabolically Healthy Obese
Badoud, F., Lam, K. P., DiBattista, A., Perreault, M., Zulyniak, M. A., Cattrysse, B., Stephenson, S., Britz‐McKibbin, P., & Mutch, D. M. (2014) · Journal of Proteome Research · doi:10.1021/pr500416v · Cited by 129 · see citing works
Insulin resistance and the metabolism of branched-chain amino acids
Lu, J., Xie, G., Jia, W., & Jia, W. P. (2013) · Frontiers of Medicine · doi:10.1007/s11684-013-0255-5 · Cited by 126 · see citing works
Serum metabolomic profile of incident diabetes
Rebholz, C. M., Yu, B., Zheng, Z., Chang, P., Tin, A., Köttgen, A., Wagenknecht, L. E., Coresh, J., Boerwinkle, E., & Selvin, E. (2018) · Diabetologia · doi:10.1007/s00125-018-4573-7 · Cited by 125 · see citing works
Wittenbecher, C., Mühlenbruch, K., Kröger, J., Jacobs, S., Kuxhaus, O., Floegel, A., Fritsche, A., Pischon, T., Prehn, C., Adamski, J., et al. (2015) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.099150 · Cited by 120 · see citing works
Self-citationPathophysiology of type 2 diabetes and the impact of altered metabolic interorgan crosstalk
Sanches, J. M., Zhao, L. N., Salehi, A. A., Wollheim, C. B., & Kaldis, P. (2021) · FEBS Journal · doi:10.1111/febs.16306 · Cited by 125 · see citing works
Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes
Bakar, M. H. A., Sarmidi, M. R., Cheng, K., Khan, A. A., Suan, C. L., Huri, H. Z., & Yaakob, H. (2015) · Molecular BioSystems · doi:10.1039/c5mb00158g · Cited by 117 · see citing works
Taneera, J., Fadista, J., Ahlqvist, E., Atac, D., Ottosson-Laakso, E., Wollheim, C. B., & Groop, L. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu610 · Cited by 115 · see citing works
Dietrich, S., Floegel, A., Troll, M., Kuhn, T. E., Rathmann, W., Peters, A., Sookthai, D., von Bergen�, M., Kaaks, R., Adamski, J., et al. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw145 · Cited by 116 · see citing works
Self-citationBragg, F., Trichia, E., Aguilar-Ramirez, D. J., Bešević, J., Lewington, S., & Emberson, J. (2022) · BMC Medicine · doi:10.1186/s12916-022-02354-9 · Cited by 116 · see citing works
Ding, Y., Svingen, G. F. T., Pedersen, E. R., Gregory, J. F., Ueland, P. M., Tell, G. S., & Nygard, O. K. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.115.002621 · Cited by 115 · see citing works
Long, J., Yang, Z., Wang, L., Han, Y., Peng, C. Y., Yan, C., & Yan, D. (2020) · BMC Endocrine Disorders · doi:10.1186/s12902-020-00653-x · Cited by 115 · see citing works
Anton, G., Wilson, R., Yu, Z., Prehn, C. P., Zukunft, S., Adamski, J., Heier, M., Meisinger, C., Römisch‐Margl, W., Wang‐Sattler, R., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0121495 · Cited by 113 · see citing works
Self-citationA Review of Emerging Technologies for the Management of Diabetes Mellitus
Zarkogianni, K., Litsa, E. E., Mitsis, K., Wu, P.-Y., Kaddi, C. D., Cheng, C., Wang, M. D., & Nikita, K. S. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2470521 · Cited by 112 · see citing works
Giesbertz, P., Ecker, J., Haag, A., Spanier, B., & Daniel, H. (2015) · Journal of Lipid Research · doi:10.1194/jlr.d061721 · Cited by 111 · see citing works
Monnerie, S., Comte, B., Ziegler, D., Morais, J. A., Pujos‐Guillot, E., & Gaudreau, P. (2020) · Scientific Reports · doi:10.1038/s41598-019-56909-7 · Cited by 109 · see citing works
Fall, T., Salihović, S., Brandmaier, S., Nowak, C., Ganna, A., Gustafsson, S., Broeckling, C. D., Prenni, J. E., Kastenmüller, G., Peters, A., et al. (2016) · Diabetologia · doi:10.1007/s00125-016-4041-1 · Cited by 109 · see citing works
Self-citationMetabolic signatures across the full spectrum of non-alcoholic fatty liver disease
McGlinchey, A. J., Govaere, O., Geng, D., Ratziu, V., Allison, M., Bousier, J., Petta, S., de Oliviera, C., Bugianesi, E., Schattenberg, J. M., et al. (2022) · JHEP Reports · doi:10.1016/j.jhepr.2022.100477 · Cited by 107 · see citing works
Pharmacometabonomics in Humans: A New Tool for Personalized Medicine
Everett, J. R. (2015) · Pharmacogenomics · doi:10.2217/pgs.15.20 · Cited by 106 · see citing works
Plasma-free amino acid profiles are predictors of cancer and diabetes development
Bi, X., & Henry, C. J. (2017) · Nutrition and Diabetes · doi:10.1038/nutd.2016.55 · Cited by 106 · see citing works
Chen, S., Akter, S., Kuwahara, K., Matsushita, Y., Nakagawa, T., Konishi, M., Honda, T., Yamamoto, S., Hayashi, T., Noda, M., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-43431-z · Cited by 102 · see citing works
Alcohol-induced metabolomic differences in humans
Jaremek, M., Yu, Z., Mangino, M., Mittelstraß, K., Prehn, C. P., Singmann, P., Xu, T., Dahmen, N., Weinberger, K. M., Suhre, K., et al. (2013) · Translational Psychiatry · doi:10.1038/tp.2013.55 · Cited by 100 · see citing works
Self-citationRochat, B. (2016) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2016.02.009 · Cited by 100 · see citing works
Methylglyoxal – An emerging biomarker for diabetes mellitus diagnosis and its detection methods
Ramachandra, B. L., Vedantham, S., Krishnan, U. M., & Rayappan, J. B. B. (2019) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2019.03.010 · Cited by 100 · see citing works
Metabolomics in Plants and Humans: Applications in the Prevention and Diagnosis of Diseases
Gomez‐Casati, D. F., Zanor, M. I., & Busi, M. V. (2013) · BioMed Research International · doi:10.1155/2013/792527 · Cited by 97 · see citing works
Biomarkers of Morbid Obesity and Prediabetes by Metabolomic Profiling of Human Discordant Phenotypes
Tulipani, S., Palau‐Rodriguez, M., Miñarro, A., Cardona, F., Marco‐Ramell, A., Žonja, B., de Alda, M. L., Muñoz‐Garach, A., Sánchez‐Pla, Á., Tinahones, F. J., et al. (2016) · Clinica Chimica Acta · doi:10.1016/j.cca.2016.10.005 · Cited by 97 · see citing works
Bergmann, K., & Sypniewska, G. (2012) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2012-0490 · Cited by 96 · see citing works
A New Metabolomic Signature in Type-2 Diabetes Mellitus and Its Pathophysiology
Padberg, I., Peter, E., Gonzalez-Maldonado, S., Witt, H., Mueller, M., Weis, T., Bethan, B., Liebenberg, V., Wiemer, J. C., Katus, H. A., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0085082 · Cited by 96 · see citing works
Flores-Guerrero, J. L., Osté, M. C. J., Kieneker, L. M., Gruppen, E. G., Wolak, J. E., Otvos, J. D., Connelly, M. A., Bakker, S. J. L., & Dullaart, R. P. F. (2018) · Journal of Clinical Medicine · doi:10.3390/jcm7120513 · Cited by 96 · see citing works
Direct Infusion Mass Spectrometry for Metabolomic Phenotyping of Diseases
González‐Domínguez, R., Sayago, A., & Fernández‐Recamales, Á. (2016) · Bioanalysis · doi:10.4155/bio-2016-0202 · Cited by 98 · see citing works
- Authors
- Wang‐Sattler, R., Yu, Z., Herder, C., Messias, A. C., Floegel, A., He, Y., Heim, K., Campillos, M., Holzapfel, C., Thorand, B., Grallert, H., Xu, T., Bader, E., Huth, C., Mittelstrass, K., Döring, A., Meisinger, C., Gieger, C., Prehn, C., Roemisch‐Margl, W., Carstensen, M., Xie, L., Yamanaka‐Okumura, H., Xing, G., Ceglarek, U., Thiery, J., Giani, G., Lickert, H., Lin, X., Li, Y., Boeing, H., Joost, H., de Angelis, M. H., Rathmann, W., Suhre, K., Prokisch, H., Peters, A., Meitinger, T., Roden, M., Wichmann, H., Pischon, T., Adamski, J., & Illig, T.
- Affiliations
- Helmholtz Munich (DE)
- Deutsches Diabetes-Zentrum e.V. (DE)
- German Institute of Human Nutrition (DE)
- Chinese Academy of Sciences (CN)
- TUM Klinikum (DE)
- Shanghai Center For Bioinformation Technology (CN)
- Tokushima University (JP)
- University Hospital Leipzig (DE)
- Max Delbrück Center (DE)
- Corresponding author
- Wang‐Sattler, Rui
- ORCID
- Wang‐Sattler, Rui
- Herder, Christian
- Messias, Ana C
- Floegel, Anna
- He, Ying
- Holzapfel, Christina
- Thorand, Barbara
- Grallert, Harald
- Xu, Tao
- Bader, Erik
- Huth, Cornelia
- Meisinger, Christa
- Gieger, Christian
- Prehn, Cornelia
- Xie, Lu
- Yamanaka‐Okumura, Hisami
- Ceglarek, Uta
- Thiery, Joachim
- Lickert, Heiko
- Lin, Xu
- Li, Yixue
- Boeing, Heiner
- Joost, Hans‐Georg
- Rathmann, Wolfgang
- Suhre, Karsten
- Prokisch, Holger
- Peters, Annette
- Meitinger, Thomas
- Roden, Michael
- Wichmann, H‐Erich
- Pischon, Tobias
- Adamski, Jerzy
- Illig, Thomas
- Venue
- Molecular Systems Biology
- Published
- 2012-09-25
- Volume
- 8
- Issue
- 1
- Pages
- 615-615
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC3472689
- OpenAlex
- W2145665725
- Cited by
- 701
- References
- 58
- Citations by year
- 2026: 11 · 2025: 25 · 2024: 36 · 2023: 55 · 2022: 49 · 2021: 47 · 2020: 72 · 2019: 67 · 2018: 56 · 2017: 55 · 2016: 71 · 2015: 60 · 2014: 52 · 2013: 43 · 2012: 2
- FWCI
- 20.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Molecular Systems Biology (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Institutional Repositories DataBase (IRDB) (submittedVersion, other-oa)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- mediaTUM (Technical University of Munich) (submittedVersion, cc-by)
- Site cant be reached (submittedVersion, cc-by)
- OPUS (Augsburg University) (submittedVersion, cc-by-nc-sa)
- Funders
- Bundesministerium für Bildung und Forschung (01GS0423, 01DO12030, 0315494A)
- Bundesministerium für Gesundheit
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
- Keywords
- type 2 diabetes, prediabetes, impaired glucose tolerance, serum metabolites, biomarkers, glycine, lysophosphatidylcholine, acetyl-L-carnitine, diabetes prevention, KORA cohort, EPIC-Potsdam cohort
- MeSH terms
- Aged, Blood Glucose, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Fasting, Female, Germany, Glucose Tolerance Test, Humans, Male, Middle Aged, Models, Biological, Prediabetic State, Prospective Studies, Risk Factors, Reproducibility of Results, Biomarkers, Odds Ratio, Case-Control Studies, Metabolomics
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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