Metabolomics in prediabetes and diabetes: A systematic review and meta-analysis

Diabetes Care

Volumn 39, Issue 5, 2016, Pages 833-846

  Guasch Ferré, Marta ^a,b,c   Hruby, Adela ^a   Toledo, Estefanía ^c,d   Clish, Clary B ^e   Martínez González, Miguel A ^c,d   Salas Salvadó, Jordi ^b,c   Hu, Frank B ^a,f  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b INSTITUT D INVESTIGACIÓ SANITÀRIA PERE VIRGILI IISPV   (Spain)

^c Instituto de Salud Carlos III   (Spain)

^d UNIVERSITY OF NAVARRA   (Spain)

^e BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^f HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AROMATIC AMINO ACID; BIOLOGICAL MARKER; BRANCHED CHAIN AMINO ACID; FRUCTOSE; GLUCOSE; GLUTAMINE; GLYCINE; LEUCINE; PHENYLALANINE; PHOSPHOLIPID; SPHINGOMYELIN; TRIACYLGLYCEROL; VALINE;

AMINO ACID BLOOD LEVEL; CROSS-SECTIONAL STUDY; DIABETES MELLITUS; DISEASE ASSOCIATION; HIGH THROUGHPUT SCREENING; HUMAN; IMPAIRED GLUCOSE TOLERANCE; METABOLOMICS; NON INSULIN DEPENDENT DIABETES MELLITUS; PHOSPHOLIPID BLOOD LEVEL; PROSPECTIVE STUDY; PUBLICATION; REVIEW; RISK FACTOR; SYSTEMATIC REVIEW; TRIACYLGLYCEROL BLOOD LEVEL; BLOOD; DIABETES MELLITUS, TYPE 2; FEMALE; INCIDENCE; META ANALYSIS; METABOLISM; MIDDLE AGED; PREDIABETIC STATE; PROCEDURES;

BIOMARKERS; CROSS-SECTIONAL STUDIES; DIABETES MELLITUS, TYPE 2; FEMALE; HUMANS; INCIDENCE; METABOLOMICS; MIDDLE AGED; PREDIABETIC STATE; PROSPECTIVE STUDIES;

EID: 84964746576     PISSN: 01495992     EISSN: 19355548     Source Type: Journal    
DOI: 10.2337/dc15-2251     Document Type: Review

References (65)

1. International Diabetes Federation. IDF Diabetes Atlas, 6th ed. Brussels, Belgium, International Diabetes Federation, 2013
2. Hu FB, Satija A, Manson JE. Curbing the diabetes pandemic: the need for global policy solutions. JAMA 2015;313:2319-2320
3. Roberts LD, Koulman A, Griffin JL. Towards metabolic biomarkers of insulin resistance and type 2 diabetes: progress from the metabolome. Lancet Diabetes Endocrinol 2014;2:65-75
4. Nicholson JK, Lindon JC. Systems biology: Metabonomics. Nature 2008;455:1054-1056
5. Wang TJ, Larson MG, Vasan RS, et al. Metabolite profiles and the risk of developing diabetes. Nat Med 2011;17:448-453
6. Floegel A, Stefan N, Yu Z, et al. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes 2013;62:639-648
7. Padberg I, Peter E, González-Maldonado S, et al. A new metabolomic signature in type-2 diabetes mellitus and its pathophysiology. PLoS One 2014;9:e85082
8. Würtz P, Tiainen M, Mäkinen V-P, et al. Circulating metabolite predictors of glycemia in middle-aged men and women. Diabetes Care 2012;35:1749-1756
9. Rhee EP, Cheng S, Larson MG, et al. Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans. J Clin Invest 2011;121:1402-1411
10. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2011;34(Suppl. 1):S62-S69
11. Hayden JA, Côté P, Bombardier C. Evaluation of the quality of prognosis studies in systematic reviews. Ann Intern Med 2006;144:427-437
12. Stancáková A, Civelek M, Saleem NK, et al. Hyperglycemia and a common variant of GCKR are associated with the levels of eight amino acids in 9, 369 Finnish men. Diabetes 2012;61:1895-1902
13. Ferrannini E, Natali A, Camastra S, et al. Early metabolic markers of the development of dysglycemia and type 2 diabetes and their physiological significance. Diabetes 2013;62:1730-1737
14. Hasselblad V, Hedges LV. Meta-analysis of screening and diagnostic tests. Psychol Bull 1995;117:167-178
15. da Costa BR, Rutjes AWS, Johnston BC, et al. Methods to convert continuous outcomes into odds ratios of treatment response and numbers needed to treat: meta-epidemiological study. Int J Epidemiol 2012;41:1445-1459
16. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629-634
17. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics 1994;50:1088-1101
18. Tai ES, Tan MLS, Stevens RD, et al. Insulin resistance is associated with a metabolic profile of altered protein metabolism in Chinese and Asian-Indian men. Diabetologia 2010;53:757-767
19. Newgard CB, An J, Bain JR, et al. A branchedchain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab 2009;9:311-326
20. Lucio M, Fekete A, Weigert C, et al. Insulin sensitivity is reflected by characteristic metabolic fingerprints - A Fourier transform mass spectrometric non-targeted metabolomics approach. PLoS One 2010;5:e13317
21. Gall WE, Beebe K, Lawton KA, et al.; RISC Study Group. Alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population. PLoS One 2010;5:e10883
22. Würtz P, Mäkinen V-P, Soininen P, et al. Metabolic signatures of insulin resistance in 7, 098 young adults. Diabetes 2012;61:1372-1380
23. Ho JE, Larson MG, Vasan RS, et al. Metabolite profiles during oral glucose challenge. Diabetes 2013;62:2689-2698
24. Geidenstam N, Spégel P, Mulder H, Filipsson K, Ridderstråle M, Danielsson APH. Metabolite profile deviations in an oral glucose tolerance test - A comparison between lean and obese individuals. Obesity (Silver Spring) 2014;22:2388-2395
25. Haus JM, Kashyap SR, Kasumov T, et al. Plasma ceramides are elevated in obese subjects with type 2 diabetes and correlate with the severity of insulin resistance. Diabetes 2009;58:337-343
26. Zhang X, Wang Y, Hao F, et al. Human serum metabonomic analysis reveals progression axes for glucose intolerance and insulin resistance statuses. J Proteome Res 2009;8:5188-5195
27. Mihalik SJ, Goodpaster BH, Kelley DE, et al. Increased levels of plasma acylcarnitines in obesity and type 2 diabetes and identification of a marker of glucolipotoxicity. Obesity (Silver Spring) 2010;18:1695-1700
28. 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:e15234
29. Zhou Y, Qiu L, Xiao Q, et al. Obesity and diabetes related plasma amino acid alterations. Clin Biochem 2013;46:1447-1452
30. Menni C, Fauman E, Erte I, et al. Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach. Diabetes 2013;62:4270-4276
31. Xu F, Tavintharan S, Sum CF, Woon K, Lim SC, Ong CN. Metabolic signature shift in type 2 diabetes mellitus revealedby mass spectrometrybased metabolomics. J Clin Endocrinol Metab 2013;98:E1060-E1065
32. Meikle PJ, Wong G, Barlow CK, et al. Plasma lipid profiling shows similar associations with prediabetes and type 2 diabetes. PLoS One 2013;8:e74341
33. Thalacker-Mercer AE, Ingram KH, Guo F, Ilkayeva O, Newgard CB, Garvey WT. BMI, RQ, diabetes, and sex affect the relationships between amino acids and clamp measures of insulin action in humans. Diabetes 2014;63:791-800
34. 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;44:1529-1534
35. Wang C, Kong H, Guan Y, et al. Plasma phospholipid metabolic profiling and biomarkers of type 2 diabetes mellitus based on high-performance liquid chromatography/electrospray mass spectrometry and multivariate statistical analysis. Anal Chem 2005;77:4108-4116
36. Yuan K, Kong H, Guan Y, Yang J, Xu G. A GC-based metabonomics investigation of type 2 diabetes by organic acids metabolic profile. J Chromatogr B Analyt Technol Biomed Life Sci 2007;850:236-240
37. Li X, Xu Z, Lu X, et al. Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry for metabonomics: Biomarker discovery for diabetes mellitus. Anal Chim Acta 2009;633:257-262
38. Adams SH, Hoppel CL, Lok KH, et al. Plasma acylcarnitine profiles suggest incomplete longchain fatty acid beta-oxidation and altered tricarboxylic acid cycle activity in type 2 diabetic African-American women. J Nutr 2009;139:1073-1081
39. Zhang J, Yan L, Chen W, et al. Metabonomics research of diabetic nephropathy and type 2 diabetes mellitus based on UPLC-oaTOF-MS system. Anal Chim Acta 2009;650:16-22
40. Suhre K, Meisinger C, Döring A, et al. Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting. PLoS One 2010;5:e13953
41. Han L-D, Xia J-F, Liang Q-L, et al. Plasma esterified and non-esterified fatty acids metabolic profiling using gas chromatography-mass spectrometry and its application in the study of diabetic mellitus and diabetic nephropathy. Anal Chim Acta 2011;689:85-91
42. Ha CY, Kim JY, Paik JK, et al. 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;76:674-682
43. Kaur P, Rizk N, Ibrahim S, et al. Quantitative metabolomic and lipidomic profiling reveals aberrant amino acid metabolism in type 2 diabetes. Mol Biosyst 2013;9:307-317
44. Zhang AH, Sun H, Yan GL, Yuan Y, Han Y, Wang XJ. Metabolomicsstudy of type 2diabetes using ultra-performance LC-ESI/quadrupole-TOF high-definition MS coupled with pattern recognition methods. J Physiol Biochem 2014;70:117-128
45. Wang-Sattler R, Yu Z, Herder C, et al. Novel biomarkers for pre-diabetes identified by metabolomics. Mol Syst Biol 2012;8:615
46. Cheng S, Rhee EP, Larson MG, et al. Metabolite profiling identifies pathways associated with metabolic risk in humans. Circulation 2012;125:2222-2231
47. Mahendran Y, Cederberg H, Vangipurapu J, et al. Glycerol and fatty acids in serum predict the development of hyperglycemia and type 2 diabetes in Finnish men. Diabetes Care 2013;36:3732-3738
48. Mahendran Y, Vangipurapu J, Cederberg H, et al. Association of ketone body levels with hyperglycemia and type 2 diabetes in 9, 398 Finnish men. Diabetes 2013;62:3618-3626
49. Wang TJ, Ngo D, Psychogios N, etal. 2-Aminoadipic acid is a biomarker for diabetes risk. J Clin Invest 2013;123:4309-4317
50. Palmer ND, Stevens RD, Antinozzi PA, et al. Metabolomic profile associated with insulin resistance and conversion to diabetes in the Insulin Resistance Atherosclerosis Study. J Clin Endocrinol Metab 2015;100:E463-E468
51. Drogan D, Dunn WB, Lin W, et al. Untargeted metabolic profiling identifies altered serum metabolites of type 2 diabetes mellitus in a prospective, nested case control study. Clin Chem 2015;61:487-497
52. Zhao J, Zhu Y, Hyun N, et al. Novel metabolic markers for the risk of diabetes development in American Indians. Diabetes Care 2015;38:220-227
53. Fizelova M, Miilunpohja M, Kangas AJ, et al. Associations of multiple lipoprotein and apolipoprotein measures with worsening of glycemia and incident type 2 diabetes in 6607 non-diabetic Finnish men. Atherosclerosis 2015;240:272-277
54. Tillin T, Hughes AD, Wang Q, et al. Diabetes risk and amino acid profiles: cross-sectional and prospective analyses of ethnicity, amino acids and diabetes in a South Asian and European cohort from the SABRE (Southall And Brent REvisited) Study. Diabetologia 2015;58:968-979
55. Shah SH, Crosslin DR, Haynes CS, et al. Branched-chain amino acid levels are associated with improvement in insulin resistance with weight loss. Diabetologia 2012;55:321-330
56. Würtz P, Soininen P, Kangas AJ, et al. Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults. Diabetes Care 2013;36:648-655
57. Cobb J, Gall W, Adam K-P, et al. A novel fasting blood test for insulin resistance and prediabetes. J Diabetes Sci Technol 2013;7:100-110
58. Krebs M, Krssak M, Bernroider E, et al. Mechanism ofamino acid-induced skeletal muscle insulin resistance in humans. Diabetes 2002;51:599-605
59. Yano M, Watanabe K, Yamamoto T, et al. Mitochondrial dysfunction and increased reactive oxygen species impair insulin secretion in sphingomyelin synthase 1-null mice. JBiol Chem 2011;286:3992-4002
60. Horie S, Ishii H, Suga T. Changes in peroxisomal fatty acid oxidation in the diabetic rat liver. J Biochem 1981;90:1691-1696
61. Kahn BB. Type 2 diabetes: when insulin secretion fails to compensate for insulin resistance. Cell 1998;92:593-596
62. McGill JB, Cole TG, Nowatzke W, et al.; U. S. trial of the GlycoMark assay. Circulating 1, 5-anhydroglucitol levels in adult patients with diabetes reflect longitudinal changes of glycemia: a U. S. trial of the GlycoMark assay. Diabetes Care 2004;27:1859-1865
63. Ley SH, Hamdy O, Mohan V, Hu FB. Prevention and management of type 2 diabetes: dietary components and nutritional strategies. Lancet 2014;383:1999-2007
64. Cornelis MC, Hu FB. Systems epidemiology: a new direction in nutrition and metabolic disease research. Curr Nutr Rep 2013;2
65. Tzoulaki I, Ebbels TMD, Valdes A, Elliott P, Ioannidis JPA. Design and analysis of metabolomics studies in epidemiologic research: a primer on -omic technologies. Am J Epidemiol 2014;180:129-139