The development of new therapies for chronic diseases, such as diabetic kidney disease (DKD), will continue to be hampered by lack of sufficient biomarkers that will provide insights and will be responsive to treatment interventions. The recent application of metabolomic technologies, such as nuclear magnetic resonance and mass spectroscopy, has allowed large-scale analysis of small molecules to be interrogated in a targeted or untargeted manner. Recent advances from both human and animal studies that have arisen from metabolomic analysis have recognized that mitochondrial function and fatty acid oxidation play key roles in the development and progression of DKD. Although many challenges in the technology for clinical chronic kidney disease (CKD) are yet to be validated, there will very likely be ongoing major contributions of metabolomics to develop new biochemical understanding for diabetic and CKD. The clinical application of metabolomics and accompanying bioinformatic tools will likely be a cornerstone of personalized medicine triumphs for CKD.

Keywords:
Metabolomics, Diabetic kidney disease, Chronic kidney disease, GC-MS, Mitochondria
1.
Jha V, Garcia-Garcia G, Iseki K, Li Z, Naicker S, Plattner B, Saran R, Wang AY, Yang CW: Chronic kidney disease: global dimension and perspectives. Lancet 2013;382:260-272.
2.
Centers for Disease Control and Prevention (CDC): National Chronic Kidney Disease Fact Sheet: General Information and National Estimates on Chronic Kidney Disease in the United States. Atlanta, US Department of Health and Human Services, Centers for Disease Control and Prevention, 2014.
3.
Afkarian M, Sachs MC, Kestenbaum B, Hirsch IB, Tuttle KR, Himmelfarb J, de Boer IH: Kidney disease and increased mortality risk in type 2 diabetes. J Am Soc Nephrol 2013;24:302-308.
4.
King H, Aubert RE, Herman WH: Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections. Diabetes Care 1998;21:1414-1431.
5.
Statistics About Diabetes: National Diabetes Statistics Report. American Diabetes Association, 2014.
6.
Gross JL, de Azevedo MJ, Silveiro SP, Canani LH, Caramori ML, Zelmanovitz T: Diabetic nephropathy: diagnosis, prevention, and treatment. Diabetes Care 2005;28:164-176.
7.
Rheinberger M, Böger CA: [Diabetic nephropathy: new insights into diagnosis, prevention and treatment]. Dtsch Med Wochenschr 2014;139:704-706.
8.
Krolewski AS, Niewczas MA, Skupien J, Gohda T, Smiles A, Eckfeldt JH, Doria A, Warram JH: Early progressive renal decline precedes the onset of microalbuminuria and its progression to macroalbuminuria. Diabetes Care 2014;37:226-234.
9.
Tabaei BP, Al-Kassab AS, Ilag LL, Zawacki CM, Herman WH: Does microalbuminuria predict diabetic nephropathy? Diabetes Care 2001;24:1560-1566.
10.
Dumas ME: Metabolome 2.0: quantitative genetics and network biology of metabolic phenotypes. Mol Biosyst 2012;8:2494-2502.
11.
Du F, Virtue A, Wang H, Yang XF: Metabolomic analyses for atherosclerosis, diabetes, and obesity. Biomark Res 2013;1:17.
12.
Breit M, Weinberger KM: Metabolic biomarkers for chronic kidney disease. Arch Biochem Biophys 2016;589:62-80.
13.
Gao R, Cheng J, Fan C, Shi X, Cao Y, Sun B, Ding H, Hu C, Dong F, Yan X: Serum metabolomics to identify the liver disease-specific biomarkers for the progression of hepatitis to hepatocellular carcinoma. Sci Rep 2015;5:18175.
14.
Cajka T, Fiehn O: Toward merging untargeted and targeted methods in mass spectrometry-based metabolomics and lipidomics. Anal Chem 2016;88:524-545.
15.
Sims JK, Manteiga S, Lee K: Towards high resolution analysis of metabolic flux in cells and tissues. Curr Opin Biotechnol 2013;24:933-939.
16.
Vacanti NM, Divakaruni AS, Green CR, Parker SJ, Henry RR, Ciaraldi TP, Murphy AN, Metallo CM: Regulation of substrate utilization by the mitochondrial pyruvate carrier. Mol Cell 2014;56:425-435.
17.
Chouchani ET, Pell VR, Gaude E, Aksentijević D, Sundier SY, Robb EL, Logan A, Nadtochiy SM, Ord EN, Smith AC, Eyassu F, Shirley R, Hu CH, Dare AJ, James AM, Rogatti S, Hartley RC, Eaton S, Costa AS, Brookes PS, Davidson SM, Duchen MR, Saeb-Parsy K, Shattock MJ, Robinson AJ, Work LM, Frezza C, Krieg T, Murphy MP: Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature 2014;515:431-435.
18.
Dieterle F, Riefke B, Schlotterbeck G, Ross A, Senn H, Amberg A: NMR and MS methods for metabonomics. Methods Mol Biol 2011;691:385-415.
19.
Emwas AH: The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research. Methods Mol Biol 2015;1277:161-193.
20.
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;2:2692-2703.
21.
Pan Z, Raftery D: Comparing and combining NMR spectroscopy and mass spectrometry in metabolomics. Anal Bioanal Chem 2007;387:525-527.
22.
Want EJ, Wilson ID, Gika H, Theodoridis G, Plumb RS, Shockcor J, Holmes E, Nicholson JK: Global metabolic profiling procedures for urine using UPLC-MS. Nat Protoc 2010;5:1005-1018.
23.
Bruce SJ, Tavazzi I, Parisod V, Rezzi S, Kochhar S, Guy PA: Investigation of human blood plasma sample preparation for performing metabolomics using ultrahigh performance liquid chromatography/mass spectrometry. Anal Chem 2009;81:3285-3296.
24.
Saccenti E, Hoefsloot HCJ, Smilde AK, Westerhuis JA, Hendriks MMWB: Reflections on univariate and multivariate analysis of metabolomics data. Metabolomics 2014;10:361-374.
25.
Broadhurst DI, Kell DB: Statistical strategies for avoiding false discoveries in metabolomics and related experiments. Metabolomics 2006;2:171-196.
26.
Benjamini Y, Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc B Met 1995;57:289-300.
27.
Hirayama A, Nakashima E, Sugimoto M, Akiyama S, Sato W, Maruyama S, Matsuo S, Tomita M, Yuzawa Y, Soga T: Metabolic profiling reveals new serum biomarkers for differentiating diabetic nephropathy. Anal Bioanal Chem 2012;404:3101-3109.
28.
Ng DP, Salim A, Liu Y, Zou L, Xu FG, Huang S, Leong H, Ong CN: A metabolomic study of low estimated GFR in non-proteinuric type 2 diabetes mellitus. Diabetologia 2012;55:499-508.
29.
van der Kloet FM, Tempels FW, Ismail N, van der Heijden R, Kasper PT, Rojas-Cherto M, van Doorn R, Spijksma G, Koek M, van der Greef J, Mäkinen VP, Forsblom C, Holthöfer H, Groop PH, Reijmers TH, Hankemeier T: Discovery of early-stage biomarkers for diabetic kidney disease using MS-based metabolomics (FinnDiane study). Metabolomics 2012;8:109-119.
30.
Duranton F, Lundin U, Gayrard N, Mischak H, Aparicio M, Mourad G, Daurès JP, Weinberger KM, Argilés A: Plasma and urinary amino acid metabolomic profiling in patients with different levels of kidney function. Clin J Am Soc Nephrol 2014;9:37-45.
31.
Benito S, Sánchez A, Unceta N, Andrade F, Aldámiz-Echevarria L, Goicolea MA, Barrio RJ: LC-QTOF-MS-based targeted metabolomics of arginine-creatine metabolic pathway-related compounds in plasma: application to identify potential biomarkers in pediatric chronic kidney disease. Anal Bioanal Chem 2016;408:747-760.
32.
Han LD, Xia JF, Liang QL, Wang Y, Wang YM, Hu P, Li P, Luo GA: 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.
33.
Niewczas MA, Sirich TL, Mathew AV, Skupien J, Mohney RP, Warram JH, Smiles A, Huang X, Walker W, Byun J, Karoly ED, Kensicki EM, Berry GT, Bonventre JV, Pennathur S, Meyer TW, Krolewski AS: Uremic solutes and risk of end-stage renal disease in type 2 diabetes: metabolomic study. Kidney Int 2014;85:1214-1224.
34.
Pena MJ, de Zeeuw D, Mischak H, Jankowski J, Oberbauer R, Woloszczuk W, Benner J, Dallmann G, Mayer B, Mayer G, Rossing P, Lambers Heerspink HJ: Prognostic clinical and molecular biomarkers of renal disease in type 2 diabetes. Nephrol Dial Transplant 2015;30(suppl 4):iv86-iv95.
35.
Posada-Ayala M, Zubiri I, Martin-Lorenzo M, Sanz-Maroto A, Molero D, Gonzalez-Calero L, Fernandez-Fernandez B, de la Cuesta F, Laborde CM, Barderas MG, Ortiz A, Vivanco F, Alvarez-Llamas G: Identification of a urine metabolomic signature in patients with advanced-stage chronic kidney disease. Kidney Int 2014;85:103-111.
36.
Sharma K, Karl B, Mathew AV, Gangoiti JA, Wassel CL, Saito R, Pu M, Sharma S, You YH, Wang L, Diamond-Stanic M, Lindenmeyer MT, Forsblom C, Wu W, Ix JH, Ideker T, Kopp JB, Nigam SK, Cohen CD, Groop PH, Barshop BA, Natarajan L, Nyhan WL, Naviaux RK: Metabolomics reveals signature of mitochondrial dysfunction in diabetic kidney disease. J Am Soc Nephrol 2013;24:1901-1912.
37.
Fleck C, Janz A, Schweitzer F, Karge E, Schwertfeger M, Stein G: Serum concentrations of asymmetric (ADMA) and symmetric (SDMA) dimethylarginine in renal failure patients. Kidney Int Suppl 2001;78:S14-S18.
38.
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;17:448-453.
39.
Pena MJ, Lambers Heerspink HJ, Hellemons ME, Friedrich T, Dallmann G, Lajer M, Bakker SJ, Gansevoort RT, Rossing P, de Zeeuw D, Roscioni SS: Urine and plasma metabolites predict the development of diabetic nephropathy in individuals with type 2 diabetes mellitus. Diabet Med 2014;31:1138-1147.
40.
Kang HM, Ahn SH, Choi P, Ko YA, Han SH, Chinga F, Park AS, Tao J, Sharma K, Pullman J, Bottinger EP, Goldberg IJ, Susztak K: Defective fatty acid oxidation in renal tubular epithelial cells has a key role in kidney fibrosis development. Nat Med 2015;21:37-46.
41.
Duranton F, Cohen G, De Smet R, Rodriguez M, Jankowski J, Vanholder R, Argiles A; European Uremic Toxin Work Group: Normal and pathologic concentrations of uremic toxins. J Am Soc Nephrol 2012;23:1258-1270.
42.
Ramezani A, Raj DS: The gut microbiome, kidney disease, and targeted interventions. J Am Soc Nephrol 2014;25:657-670.
43.
Knip M, Siljander H: The role of the intestinal microbiota in type 1 diabetes mellitus. Nat Rev Endocrinol 2016;12:154-167.
44.
Nigam SK, Bush KT, Martovetsky G, Ahn SY, Liu HC, Richard E, Bhatnagar V, Wu W: The organic anion transporter (OAT) family: a systems biology perspective. Physiol Rev 2015;95:83-123.
45.
Eraly SA, Vallon V, Vaughn DA, Gangoiti JA, Richter K, Nagle M, Monte JC, Rieg T, Truong DM, Long JM, Barshop BA, Kaler G, Nigam SK: Decreased renal organic anion secretion and plasma accumulation of endogenous organic anions in OAT1 knock-out mice. J Biol Chem 2006;281:5072-5083.
46.
den Besten G, van Eunen K, Groen AK, Venema K, Reijngoud DJ, Bakker BM: The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. J Lipid Res 2013;54:2325-2340.
47.
Kasubuchi M, Hasegawa S, Hiramatsu T, Ichimura A, Kimura I: Dietary gut microbial metabolites, short-chain fatty acids, and host metabolic regulation. Nutrients 2015;7:2839-2849.
48.
Canfora EE, Jocken JW, Blaak EE: Short-chain fatty acids in control of body weight and insulin sensitivity. Nat Rev Endocrinol 2015;11:577-591.
49.
Liang H, Ward WF: PGC-1alpha: a key regulator of energy metabolism. Adv Physiol Educ 2006;30:145-151.
50.
LeBleu VS, O'Connell JT, Gonzalez Herrera KN, Wikman H, Pantel K, Haigis MC, de Carvalho FM, Damascena A, Domingos Chinen LT, Rocha RM, Asara JM, Kalluri R: PGC-1α mediates mitochondrial biogenesis and oxidative phosphorylation in cancer cells to promote metastasis. Nat Cell Biol 2014;16:992-1003, 1-15.
51.
You YH, Quach T, Saito R, Pham J, Sharma K: Metabolomics reveals a key role for fumarate in mediating the effects of NADPH oxidase 4 in diabetic kidney disease. J Am Soc Nephrol 2016;27:466-481.
52.
Wei T, Zhao L, Jia J, Xia H, Du Y, Lin Q, Lin X, Ye X, Yan Z, Gao H: Metabonomic analysis of potential biomarkers and drug targets involved in diabetic nephropathy mice. Sci Rep 2015;5:11998.
53.
Liu J, Wang C, Liu F, Lu Y, Cheng J: Metabonomics revealed xanthine oxidase-induced oxidative stress and inflammation in the pathogenesis of diabetic nephropathy. Anal Bioanal Chem 2015;407:2569-2579.
54.
Stec DF, Wang S, Stothers C, Avance J, Denson D, Harris R, Voziyan P: Alterations of urinary metabolite profile in model diabetic nephropathy. Biochem Biophys Res Commun 2015;456:610-614.
55.
Gorin Y, Block K, Hernandez J, Bhandari B, Wagner B, Barnes JL, Abboud HE: Nox4 NAD(P)H oxidase mediates hypertrophy and fibronectin expression in the diabetic kidney. J Biol Chem 2005;280:39616-39626.
56.
Li M, Wang X, Aa J, Qin W, Zha W, Ge Y, Liu L, Zheng T, Cao B, Shi J, Zhao C, Wang X, Yu X, Wang G, Liu Z: GC/TOFMS analysis of metabolites in serum and urine reveals metabolic perturbation of TCA cycle in db/db mice involved in diabetic nephropathy. Am J Physiol Renal Physiol 2013;304:F1317-F1324.
57.
Zhao T, Zhang H, Zhao T, Zhang X, Lu J, Yin T, Liang Q, Wang Y, Luo G, Lan H, Li P: Intrarenal metabolomics reveals the association of local organic toxins with the progression of diabetic kidney disease. J Pharm Biomed Anal 2012;60:32-43.
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2016
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