Review
Copyright ©The Author(s) 2016.
World J Diabetes. Jul 25, 2016; 7(14): 290-301
Published online Jul 25, 2016. doi: 10.4239/wjd.v7.i14.290
Table 4 Applications of metabolomics in the diagnosis of diabetic kidney disease
SpecimenPanelApplicationRef.
PlasmaFatty acids C10:0, C12:0, C14:0, C16:1n-9, C16:0, C18:2, C18:1n-9, C18:1n-11, C18:0, C20:4, C20:5, C20:3, C20:2, C20:0, C22:6Diverse profiles in different stages of DKD[122]
PlasmaPhospholipids C18:2-LPC, C16:0/18:1-PE, pC18:0/20:4-PE, C18:0/22:6-PI, C18:0/18:0-PS, dC18:0/20:2-SMDiagnosis of DKD[123]
Serumγ-butyrobetaine, SDMA, azelaic acid, MID 114, MID 127Diagnosis of DKD[124]
Urine3-hydroxy isovalerate, aconitic acid, citric acid, 2-ethyl 3-OH propionate, glycolic acid, homovanillic acid, 3-hydroxy isobutyrate, 2-methyl acetoacetate, 3-methyl adipic acid, 3-methyl crotonyl glycine, 3-hydroxy propionate, tiglylglycine, uracilReduced expression in DKD patients[125]
Plasma and urinePlasma: Histidine, butenoylcarnitine Urine: Hexose, glutamine, tyrosineAddition to the original predictive model improved risk estimation for albuminuria progression[126]
PlasmaP-cresol sulfate, phenylacetylglutamine, myoinositol, pseudouridine, uratePredicting progression toward ESRD[127]