Skip to main content
SpringerLink
Log in

Metabolomics in human type 2 diabetes research

  • Review
  • Published:
Frontiers of Medicine Aims and scope Submit manuscript

Abstract

The high prevalence of diabetes and diabetic complications has caused a huge burden on the modern society. Although scientific advances have led to effective strategies for preventing and treating diabetes over the past several decades, little progress has been made toward curing the disease or even getting it under control, from a public health and overall societal standpoint. There is still a lack of reliable biomarkers indicative of metabolic alterations associated with diabetes and different drug responses, highlighting the need for the development of early diagnostic and prognostic markers for diabetes and diabetic complications. The emergence of metabolomics has allowed researchers to systemically measure the small molecule metabolites, which are sensitive to the changes of both environmental and genetic factors and therefore, could be regarded as the link between genotypes and phenotypes. During the last decade, the progression made in metabolomics has provided insightful information on disease development and disease onset prediction. Recent studies using metabolomics approach coupled with statistical tools to predict incident diabetes revealed a number of metabolites that are significantly altered, including branched-chain and aromatic amino acids, such as isoleucine, leucine, valine, tyrosine and phenylalanine, as diagnostic or highly-significant predictors of future diabetes. This review summarizes the current findings of metabolomic studies in human investigations with the most common form of diabetes, type 2 diabetes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. World Health Organization. Diabetes: Fact sheet N°312. 2011

    Google Scholar 

  2. National Diabetes Information Clearinghouse (NDIC). Complications of Diabetes. 2012

    Google Scholar 

  3. Friedrich N. Metabolomics in diabetes research. J Endocrinol 2012; 215(1): 29–42

    Article  PubMed  CAS  Google Scholar 

  4. Pal A, McCarthy M. The genetics of type 2 diabetes and its clinical relevance. Clin Genet 2012 Nov 20. [Epub ahead of print] doi: 10.1111/cge.12055

  5. Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Langenberg C, Hofmann OM, Dupuis J, Qi L, Segrè AV, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R, Boerwinkle E, Bonnycastle LL, Bengtsson Boström K, Bravenboer B, Bumpstead S, Burtt NP, Charpentier G, Chines PS, Cornelis M, Couper DJ, Crawford G, Doney AS, Elliott KS, Elliott AL, Erdos MR, Fox CS, Franklin CS, Ganser M, Gieger C, Grarup N, Green T, Griffin S, Groves CJ, Guiducci C, Hadjadj S, Hassanali N, Herder C, Isomaa B, Jackson AU, Johnson PR, Jørgensen T, Kao WH, Klopp N, Kong A, Kraft P, Kuusisto J, Lauritzen T, Li M, Lieverse A, Lindgren CM, Lyssenko V, Marre M, Meitinger T, Midthjell K, Morken MA, Narisu N, Nilsson P, Owen KR, Payne F, Perry JR, Petersen AK, Platou C, Proença C, Prokopenko I, Rathmann W, Rayner NW, Robertson NR, Rocheleau G, Roden M, Sampson MJ, Saxena R, Shields BM, Shrader P, Sigurdsson G, Sparsø T, Strassburger K, Stringham HM, Sun Q, Swift AJ, Thorand B, Tichet J, Tuomi T, van Dam RM, van Haeften TW, van Herpt T, van Vliet-Ostaptchouk JV, Walters GB, Weedon MN, Wijmenga C, Witteman J, Bergman RN, Cauchi S, Collins FS, Gloyn AL, Gyllensten U, Hansen T, Hide WA, Hitman GA, Hofman A, Hunter DJ, Hveem K, Laakso M, Mohlke KL, Morris AD, Palmer CN, Pramstaller PP, Rudan I, Sijbrands E, Stein LD, Tuomilehto J, Uitterlinden A, Walker M, Wareham NJ, Watanabe RM, Abecasis GR, Boehm BO, Campbell H, Daly MJ, Hattersley AT, Hu FB, Meigs JB, Pankow JS, Pedersen O, Wichmann HE, Barroso I, Florez JC, Frayling TM, Groop L, Sladek R, Thorsteinsdottir U, Wilson JF, Illig T, Froguel P, van Duijn CM, Stefansson K, Altshuler D, Boehnke M, McCarthy MI; MAGIC investigators; GIANT Consortium. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet 2010; 42(7): 579–589

    Article  PubMed  CAS  Google Scholar 

  6. Fiehn O. Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp Funct Genomics 2001; 2(3): 155–168

    Article  PubMed  CAS  Google Scholar 

  7. Nicholson JK, Lindon JC, Holmes E. “Metabonomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 1999; 29(11): 1181–1189

    Article  PubMed  CAS  Google Scholar 

  8. Lucio M, Fekete A, Weigert C, Wägele B, Zhao X, Chen J, Fritsche A, Häring HU, Schleicher ED, Xu G, Schmitt-Kopplin P, Lehmann R. Insulin sensitivity is reflected by characteristic metabolic fingerprints-a Fourier transform mass spectrometric non-targeted metabolomics approach. PLoS ONE 2010; 5(10): e13317

    Article  PubMed  Google Scholar 

  9. Newgard CB, An J, Bain JR, Muehlbauer MJ, Stevens RD, Lien LF, Haqq AM, Shah SH, Arlotto M, Slentz CA, Rochon J, Gallup D, Ilkayeva O, Wenner BR, Yancy WS Jr, Eisenson H, Musante G, Surwit RS, Millington DS, Butler MD, Svetkey LP. A branchedchain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab 2009; 9(4): 311–326

    Article  PubMed  CAS  Google Scholar 

  10. Qiu Y, Cai G, Su M, Chen T, Zheng X, Xu Y, Ni Y, Zhao A, Xu LX, Cai S, Jia W. Serum metabolite profiling of human colorectal cancer using GC-TOFMS and UPLC-QTOFMS. J Proteome Res 2009; 8(10): 4844–4850

    Article  PubMed  CAS  Google Scholar 

  11. Lanza IR, Zhang S, Ward LE, Karakelides H, Raftery D, Nair KS. Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes. PLoS ONE 2010; 5(5): e10538

    Article  PubMed  Google Scholar 

  12. Bernini P, Bertini I, Luchinat C, Tenori L, Tognaccini A. The cardiovascular risk of healthy individuals studied by NMR metabonomics of plasma samples. J Proteome Res 2011; 10(11): 4983–4992

    Article  PubMed  CAS  Google Scholar 

  13. Xie G, Zheng X, Qi X, Cao Y, Chi Y, Su M, Ni Y, Qiu Y, Liu Y, Li H, Zhao A, Jia W. Metabonomic evaluation of melamine-induced acute renal toxicity in rats. J Proteome Res 2010; 9(1): 125–133

    Article  PubMed  CAS  Google Scholar 

  14. Chen T, Xie G, Wang X, Fan J, Qiu Y, Zheng X, Qi X, Cao Y, Su M, Xu LX, Yen Y, Liu P, Jia W. Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma. Mol Cell Proteomics 2011;10(7):M110.004945

    Article  PubMed  Google Scholar 

  15. Lenz EM, Wilson ID. Analytical strategies in metabonomics. J Proteome Res 2007; 6(2): 443–458

    Article  PubMed  CAS  Google Scholar 

  16. Beckonert O, Keun HC, Ebbels TM, Bundy J, Holmes E, Lindon JC, Nicholson JK. Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat Protoc 2007; 2(11): 2692–2703

    Article  PubMed  CAS  Google Scholar 

  17. Bictash M, Ebbels TM, Chan Q, Loo RL, Yap IK, Brown IJ, de Iorio M, Daviglus ML, Holmes E, Stamler J, Nicholson JK, Elliott P. Opening up the “Black Box”: metabolic phenotyping and metabolome-wide association studies in epidemiology. J Clin Epidemiol 2010; 63(9): 970–979

    Article  PubMed  Google Scholar 

  18. Büscher JM, Czernik D, Ewald JC, Sauer U, Zamboni N. Crossplatform comparison of methods for quantitative metabolomics of primary metabolism. Anal Chem 2009; 81(6): 2135–2143

    Article  PubMed  Google Scholar 

  19. Kim HK, Choi YH, Verpoorte R. NMR-based plant metabolomics: where do we stand, where do we go? Trends Biotechnol 2011; 29(6): 267–275

    Article  PubMed  CAS  Google Scholar 

  20. Blumich B. Essential NMR: For Scientists and Engineers. Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2005

    Google Scholar 

  21. Lu J, Zhou J, Bao Y, Chen T, Zhang Y, Zhao A, Qiu Y, Xie G, Wang C, Jia W, Jia W. Serum metabolic signatures of fulminant type 1 diabetes. J Proteome Res 2012; 11(9): 4705–4711

    Article  PubMed  CAS  Google Scholar 

  22. Messana I, Forni F, Ferrari F, Rossi C, Giardina B, Zuppi C. Proton nuclear magnetic resonance spectral profiles of urine in type II diabetic patients. Clin Chem 1998; 44(7): 1529–1534

    PubMed  CAS  Google Scholar 

  23. Salek RM, Maguire ML, Bentley E, Rubtsov DV, Hough T, Cheeseman M, Nunez D, Sweatman BC, Haselden JN, Cox RD, Connor SC, Griffin JL. A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human. Physiol Genomics 2007; 29(2): 99–108

    PubMed  CAS  Google Scholar 

  24. Yamanouchi T, Tachibana Y, Akanuma H, Minoda S, Shinohara T, Moromizato H, Miyashita H, Akaoka I. Origin and disposal of 1,5-anhydroglucitol, a major polyol in the human body. Am J Physiol 1992; 263(2 Pt 1): E268–E273

    PubMed  CAS  Google Scholar 

  25. Yamanouchi T, Akanuma H, Asano T, Konishi C, Akaoka I, Akanuma Y. Reduction and recovery of plasma 1,5-anhydro-Dglucitol level in diabetes mellitus. Diabetes 1987; 36(6): 709–715

    Article  PubMed  CAS  Google Scholar 

  26. Dungan KM, Buse JB, Largay J, Kelly MM, Button EA, Kato S, Wittlin S. 1,5-anhydroglucitol and postprandial hyperglycemia as measured by continuous glucose monitoring system in moderately controlled patients with diabetes. Diabetes Care 2006; 29(6): 1214–1219

    Article  PubMed  CAS  Google Scholar 

  27. Yamanouchi T, Inoue T, Ogata E, Kashiwabara A, Ogata N, Sekino N, Yoshimura T, Ichiyanagi K, Kawasaki T. Post-load glucose measurements in oral glucose tolerance tests correlate well with 1,5-anhydroglucitol, an indicator of overall glycaemic state, in subjects with impaired glucose tolerance. Clin Sci (Lond) 2001; 101(3): 227–233

    Article  CAS  Google Scholar 

  28. Yamanouchi T, Ogata N, Tagaya T, Kawasaki T, Sekino N, Funato H, Akaoka L, Miyashita H. Clinical usefulness of serum 1,5-anhydroglucitol in monitoring glycaemic control. Lancet 1996; 347(9014): 1514–1518

    Article  PubMed  CAS  Google Scholar 

  29. Hanefeld M, Fischer S, Julius U, Schulze J, Schwanebeck U, Schmechel H, Ziegelasch HJ, Lindner J. Risk factors for myocardial infarction and death in newly detected NIDDM: the Diabetes Intervention Study, 11-year follow-up. Diabetologia 1996; 39(12): 1577–1583

    Article  PubMed  CAS  Google Scholar 

  30. Muggeo M, Zoppini G, Bonora E, Brun E, Bonadonna RC, Moghetti P, Verlato G. Fasting plasma glucose variability predicts 10-year survival of type 2 diabetic patients: the Verona Diabetes Study. Diabetes Care 2000; 23(1): 45–50

    Article  PubMed  CAS  Google Scholar 

  31. Temelkova-Kurktschiev TS, Koehler C, Henkel E, Leonhardt W, Fuecker K, Hanefeld M. Postchallenge plasma glucose and glycemic spikes are more strongly associated with atherosclerosis than fasting glucose or HbA1c level. Diabetes Care 2000; 23(12): 1830–1834

    Article  PubMed  CAS  Google Scholar 

  32. Erlinger TP, Brancati FL. Postchallenge hyperglycemia in a national sample of U.S. adults with type 2 diabetes. Diabetes Care 2001; 24(10): 1734–1738

    Article  PubMed  CAS  Google Scholar 

  33. Kannel WB. Lipids, diabetes, and coronary heart disease: insights from the Framingham Study. Am Heart J 1985; 110(5): 1100–1107

    Article  PubMed  CAS  Google Scholar 

  34. Krauss RM, Siri PW. Dyslipidemia in type 2 diabetes. Med Clin North Am 2004; 88(4): 897–909, x

    Article  PubMed  CAS  Google Scholar 

  35. Taskinen MR. Diabetic dyslipidaemia: from basic research to clinical practice. Diabetologia 2003; 46(6): 733–749

    Article  PubMed  Google Scholar 

  36. Fiehn O, Garvey WT, Newman JW, Lok KH, Hoppel CL, Adams SH. Plasma metabolomic profiles reflective of glucose homeostasis in non-diabetic and type 2 diabetic obese African-American women. PLoS ONE 2010; 5(12): e15234

    Article  PubMed  Google Scholar 

  37. Balasse EO, Féry F. Ketone body production and disposal: effects of fasting, diabetes, and exercise. Diabetes Metab Rev 1989; 5(3): 247–270

    Article  PubMed  CAS  Google Scholar 

  38. Suhre K, Meisinger C, Döring A, Altmaier E, Belcredi P, Gieger C, Chang D, Milburn MV, Gall WE, Weinberger KM, Mewes HW, Hrabé de Angelis M, Wichmann HE, Kronenberg F, Adamski J, Illig T. Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting. PLoS ONE 2010; 5(11): e13953

    Article  PubMed  Google Scholar 

  39. Blaak EE, van Aggel-Leijssen DP, Wagenmakers AJ, Saris WH, van Baak MA. Impaired oxidation of plasma-derived fatty acids in type 2 diabetic subjects during moderate-intensity exercise. Diabetes 2000; 49(12): 2102–2107

    Article  PubMed  CAS  Google Scholar 

  40. Kelley DE. Skeletal muscle fat oxidation: timing and flexibility are everything. J Clin Invest 2005; 115(7): 1699–1702

    Article  PubMed  CAS  Google Scholar 

  41. Kelley DE, Goodpaster B, Wing RR, Simoneau JA. Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. Am J Physiol 1999; 277(6 Pt 1): E1130–E1141

    PubMed  CAS  Google Scholar 

  42. Adams SH, Hoppel CL, Lok KH, Zhao L, Wong SW, Minkler PE, Hwang DH, Newman JW, Garvey WT. Plasma acylcarnitine profiles suggest incomplete long-chain fatty acid beta-oxidation and altered tricarboxylic acid cycle activity in type 2 diabetic African-American women. J Nutr 2009; 139(6): 1073–1081

    Article  PubMed  CAS  Google Scholar 

  43. Kramer HF, Goodyear LJ. Exercise, MAPK, and NF-kappaB signaling in skeletal muscle. J Appl Physiol 2007; 103(1): 388–395

    Article  PubMed  CAS  Google Scholar 

  44. Tilg H, Moschen AR. Inflammatory mechanisms in the regulation of insulin resistance. Mol Med 2008; 14(3–4): 222–231

    PubMed  CAS  Google Scholar 

  45. Mihalik SJ, Goodpaster BH, Kelley DE, Chace DH, Vockley J, Toledo FG, DeLany JP. Increased levels of plasma acylcarnitines in obesity and type 2 diabetes and identification of a marker of glucolipotoxicity. Obesity (Silver Spring) 2010; 18(9): 1695–1700

    Article  CAS  Google Scholar 

  46. Ha CY, Kim JY, Paik JK, Kim OY, Paik YH, Lee EJ, Lee JH. The association of specific metabolites of lipid metabolism with markers of oxidative stress, inflammation and arterial stiffness in men with newly diagnosed type 2 diabetes. Clin Endocrinol (Oxf) 2012; 76(5): 674–682

    Article  CAS  Google Scholar 

  47. Mihalik SJ, Michaliszyn SF, de las Heras J, Bacha F, Lee S, Chace DH, DeJesus VR, Vockley J, Arslanian SA. Metabolomic profiling of fatty acid and amino acid metabolism in youth with obesity and type 2 diabetes: evidence for enhanced mitochondrial oxidation. Diabetes Care 2012; 35(3): 605–611

    Article  PubMed  CAS  Google Scholar 

  48. Cole LK, Vance JE, Vance DE. Phosphatidylcholine biosynthesis and lipoprotein metabolism. Biochim Biophys Acta 2012; 1821(5): 754–761

    Article  PubMed  CAS  Google Scholar 

  49. Floegel A, Stefan N, Yu Z, Mühlenbruch K, Drogan D, Joost HG, Fritsche A, Häring HU, Hrabe de Angelis M, Peters A, Roden M, Prehn C, Wang-Sattler R, Illig T, Schulze MB, Adamski J, Boeing H, Pischon T. Identification of Serum Metabolites Associated With Risk of Type 2 Diabetes Using a Targeted Metabolomic Approach. Diabetes 2012 Oct 4. [Epub ahead of print] doi: 10.2337/db12-0495

  50. Wang-Sattler R, Yu Z, Herder C, Messias AC, 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 HG, de Angelis MH, Rathmann W, Suhre K, Prokisch H, Peters A, Meitinger T, Roden M, Wichmann HE, Pischon T, Adamski J, Illig T. Novel biomarkers for pre-diabetes identified by metabolomics. Mol Syst Biol 2012; 8: 615

    Article  PubMed  CAS  Google Scholar 

  51. Felig P, Marliss E, Cahill GF Jr. Plasma amino acid levels and insulin secretion in obesity. N Engl J Med 1969; 281(15): 811–816

    Article  PubMed  CAS  Google Scholar 

  52. Felig P, Wahren J, Hendler R, Brundin T. Splanchnic glucose and amino acid metabolism in obesity. J Clin Invest 1974; 53(2): 582–590

    Article  PubMed  CAS  Google Scholar 

  53. Luetscher JA Jr. The Metabolism of Amino Acids in Diabetes Mellitus. J Clin Invest 1942; 21(3): 275–279

    Article  PubMed  CAS  Google Scholar 

  54. Huffman KM, Shah SH, Stevens RD, Bain JR, Muehlbauer M, Slentz CA, Tanner CJ, Kuchibhatla M, Houmard JA, Newgard CB, Kraus WE. Relationships between circulating metabolic intermediates and insulin action in overweight to obese, inactive men and women. Diabetes Care 2009; 32(9): 1678–1683

    Article  PubMed  CAS  Google Scholar 

  55. Tai ES, Tan ML, Stevens RD, Low YL, Muehlbauer MJ, Goh DL, Ilkayeva OR, Wenner BR, Bain JR, Lee JJ, Lim SC, Khoo CM, Shah SH, Newgard CB. Insulin resistance is associated with a metabolic profile of altered protein metabolism in Chinese and Asian-Indian men. Diabetologia 2010; 53(4): 757–767

    Article  PubMed  CAS  Google Scholar 

  56. Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E, Lewis GD, Fox CS, Jacques PF, Fernandez C, O’Donnell CJ, Carr SA, Mootha VK, Florez JC, Souza A, Melander O, Clish CB, Gerszten RE. Metabolite profiles and the risk of developing diabetes. Nat Med 2011; 17(4): 448–453

    Article  PubMed  Google Scholar 

  57. Zhang X, Wang Y, Hao F, Zhou X, Han X, Tang H, Ji L. Human serum metabonomic analysis reveals progression axes for glucose intolerance and insulin resistance statuses. J Proteome Res 2009; 8(11): 5188–5195

    Article  PubMed  CAS  Google Scholar 

  58. Bao Y, Zhao T, Wang X, Qiu Y, Su M, Jia W, Jia W. Metabonomic variations in the drug-treated type 2 diabetes mellitus patients and healthy volunteers. J Proteome Res 2009; 8(4): 1623–1630

    Article  PubMed  CAS  Google Scholar 

  59. Mochida T, Tanaka T, Shiraki Y, Tajiri H, Matsumoto S, Shimbo K, Ando T, Nakamura K, Okamoto M, Endo F. Time-dependent changes in the plasma amino acid concentration in diabetes mellitus. Mol Genet Metab 2011; 103(4): 406–409

    Article  PubMed  CAS  Google Scholar 

  60. Phillips JD, Kushner JP. Fast track to the porphyrias. Nat Med 2005; 11(10): 1049–1050

    Article  PubMed  CAS  Google Scholar 

  61. Gall WE, Beebe K, Lawton KA, Adam KP, Mitchell MW, Nakhle PJ, Ryals JA, Milburn MV, Nannipieri M, Camastra S, Natali A, Ferrannini E; RISC Study Group. alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population. PLoS ONE 2010; 5(5): e10883

    Article  PubMed  Google Scholar 

  62. Li X, Xu Z, Lu X, Yang X, Yin P, Kong H, Yu Y, Xu G. Comprehensive two-dimensional gas chromatography/time-offlight mass spectrometry for metabonomics: Biomarker discovery for diabetes mellitus. Anal Chim Acta 2009; 633(2): 257–262

    Article  PubMed  CAS  Google Scholar 

  63. Mosharov E, Cranford MR, Banerjee R. The quantitatively important relationship between homocysteine metabolism and glutathione synthesis by the transsulfuration pathway and its regulation by redox changes. Biochemistry 2000; 39(42): 13005–13011

    Article  PubMed  CAS  Google Scholar 

  64. Persa C, Pierce A, Ma Z, Kabil O, Lou MF. The presence of a transsulfuration pathway in the lens: a new oxidative stress defense system. Exp Eye Res 2004; 79(6): 875–886

    Article  PubMed  CAS  Google Scholar 

  65. Kostolanská J, Jakus V, Barák L. HbA1c and serum levels of advanced glycation and oxidation protein products in poorly and well controlled children and adolescents with type 1 diabetes mellitus. J Pediatr Endocrinol Metab 2009; 22(5): 433–442

    Article  PubMed  Google Scholar 

  66. Bennion LJ, Grundy SM. Effects of diabetes mellitus on cholesterol metabolism in man. N Engl J Med 1977; 296(24): 1365–1371

    Article  PubMed  CAS  Google Scholar 

  67. Schwartz SL, Lai YL, Xu J, Abby SL, Misir S, Jones MR, Nagendran S. The effect of colesevelam hydrochloride on insulin sensitivity and secretion in patients with type 2 diabetes: a pilot study. Metab Syndr Relat Disord 2010; 8(2): 179–188

    Article  PubMed  CAS  Google Scholar 

  68. Wang Z, Klipfell E, Bennett BJ, Koeth R, Levison BS, Dugar B, Feldstein AE, Britt EB, Fu X, Chung YM, Wu Y, Schauer P, Smith JD, Allayee H, Tang WH, DiDonato JA, Lusis AJ, Hazen SL. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 2011; 472(7341): 57–63

    Article  PubMed  CAS  Google Scholar 

  69. McGill HC Jr, McMahan CA. Determinants of atherosclerosis in the young. Am J Cardiol 1998; 82(10B): 30T–36T

    Article  PubMed  Google Scholar 

  70. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation 1998; 97(18): 1837–1847

    Article  PubMed  CAS  Google Scholar 

  71. al-Waiz M, Mikov M, Mitchell SC, Smith RL. The exogenous origin of trimethylamine in the mouse. Metabolism 1992; 41(2): 135–136

    Article  PubMed  CAS  Google Scholar 

  72. Swann JR, Want EJ, Geier FM, Spagou K, Wilson ID, Sidaway JE, Nicholson JK, Holmes E. Systemic gut microbial modulation of bile acid metabolism in host tissue compartments. Proc Natl Acad Sci USA 2011; 108(Suppl 1): 4523–4530

    Article  PubMed  CAS  Google Scholar 

  73. Nicholson JK, Holmes E, Wilson ID. Gut microorganisms, mammalian metabolism and personalized health care. Nat Rev Microbiol 2005; 3(5): 431–438

    Article  PubMed  CAS  Google Scholar 

  74. Fujimura KE, Slusher NA, Cabana MD, Lynch SV. Role of the gut microbiota in defining human health. Expert Rev Anti Infect Ther 2010; 8(4): 435–454

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Shanghai Diabetes Institute; Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital; Shanghai Key Laboratory of Diabetes Mellitus; Shanghai Clinical Center for Diabetes, Shanghai, 200233, China

    Jingyi Lu & Weiping Jia

  2. Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, 200233, China

    Guoxiang Xie & Wei Jia

  3. Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, 28081, USA

    Guoxiang Xie & Wei Jia

Authors
  1. Jingyi Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guoxiang Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weiping Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wei Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wei Jia.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lu, J., Xie, G., Jia, W. et al. Metabolomics in human type 2 diabetes research. Front. Med. 7, 4–13 (2013). https://doi.org/10.1007/s11684-013-0248-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11684-013-0248-4

Keywords

Search

Navigation