Applications of Metabolomics for Kidney Disease Research

Figures & data

Figure 1. Metabolites are most closely related to phenotype. Metabolomics is most closely related to phenotype. In addition, there are many fewer extant metabolites than genes, proteins, and transcripts which considerably simplify data acquisition and analysis.

Figure 2. Comprehensive small molecule biomarker detection in urine. Algorithm describing the metabolomic approaches for biomarker identification using complementary analytical techniques covering the whole metabolome or small molecule space. GC-MS: gas chromatography–mass spectrometry, LC-MS: liquid chromatography–mass spectrometry, NMR: nuclear magnetic resonance

Table 1. Kidney diseases to which metabolomics have been applied

Kidney disease	Potential biomarkers and targets	References
ADPKD	Urinary adenosine and allantoin	Taylor et al. (2010)^14
RCC	Tissue α-tocopherol, hippuric acid, myoinositol, fructose-1-phosphate and glucose- 1-phosphate	Catchpole et al. (2011)^30
	Urinary quinolinate, 4‐hydroxybenzoate, and gentisate	Kim et al. (2011)^16
	Urinary acylcarnitines	Ganti et al. (2011)^18
	Serum and tissue cinnamoylglycine and nicotinamide	Ganti et al. (2012)^17
	Tissue cysteine–glutathione
AKI	Urinary amino acids and polyamines	Boudonck et al. (2009)^20
	Urinary amino acids; glycolysis and citric acid cycle intermediates	Xu et al. (2008)^21
	Urinary glucose, lactate, amino acids, citric acid cycle intermediates	Melnick et al. (1994)^19
Diabetes mellitus nephropathy	Serum 3‐indoxyl sulfate, glycerophospholipids, free fatty acids	Suhre et al. (2010)^22
	Metabolism of fatty acids, tryptophan, uric acid, bile acid and lysophosphatidylcholine, citric acid cycle intermediates	Zhao et al. (2010)^23
	Amino acid degradation, amino group metabolism and the urea cycle	Connor et al. (2010)^24
Diabetes insipidus	Urinary acetate, lactate, allantoin and trimethylamine	Mahadevan et al. (2008)^25
Uremic syndrome	Serum indoxyl sulfate, phenyl sulfate, hippuric acid, and p‐cresyl sulfate	Kikuchi et al. (2010)^26
	52 metabolites increased as eGFR declined	Toyohara et al. (2010)^27
LN	Urine citrate, taurine, hippurate	Romick-Rosendale et al. (2011)^28
IgA nephropathy	Increased serum phenylalanine, myo-Inositol, lactate, L6, L5, and L3 lipids	Sui et al. (2012)^29
	Decreased serum β-glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolpho- sphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine

ADPKD, autosomal dominant polycystic kidney disease; RCC, renal cell carcinoma; AKI, acute kidney injury; LN, lupus nephritis

Figure 3. Our strategy for metabolomics-based biomarker discovery strategy.

Taylor SL, Ganti S, Bukanov NO, Chapman A, Fiehn O, Osier M, et al. A metabolomics approach using juvenile cystic mice to identify urinary biomarkers and altered pathways in polycystic kidney disease. Am J Physiol Renal Physiol 2010; 298:F909 - 22; http://dx.doi.org/10.1152/ajprenal.00722.2009; PMID: 20130118

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Kikuchi K, Itoh Y, Tateoka R, Ezawa A, Murakami K, Niwa T. Metabolomic analysis of uremic toxins by liquid chromatography/electrospray ionization-tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2010; 878:1662 - 8; http://dx.doi.org/10.1016/j.jchromb.2009.11.040; PMID: 20036201

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Romick-Rosendale LE, Brunner HI, Bennett MR, Mina R, Nelson S, Petri M, et al. Identification of urinary metabolites that distinguish membranous lupus nephritis from proliferative lupus nephritis and focal segmental glomerulosclerosis. Arthritis Res Ther 2011; 13:R199; http://dx.doi.org/10.1186/ar3530; PMID: 22152586

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Sui W, Li L, Che W, Guimai Z, Chen J, Li W, et al. A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy. Clinics (Sao Paulo) 2012; 67:363 - 73; http://dx.doi.org/10.6061/clinics/2012(04)10; PMID: 22522762

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