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Metabonomic analysis of potential biomarkers and drug targets involved in diabetic nephropathy mice.

Wei T, Zhao L, Jia J, Xia H, Du Y, Lin Q, Lin X, Ye X, Yan Z, Gao H - Sci Rep (2015)

Bottom Line: Age-dependent and correlated metabolite analysis identified that cis-aconitate and allantoin could serve as biomarkers for the diagnosis of DN.Further correlative analysis revealed that the enzymes dimethylarginine dimethylaminohydrolase (DDAH), guanosine triphosphate cyclohydrolase I (GTPCH I), and 3-hydroxy-3-methylglutaryl-CoA lyase (HMG-CoA lyase) were involved in dimethylamine metabolism, ketogenesis and GTP metabolism pathways, respectively, and could be potential therapeutic targets for DN.Our results highlight that metabonomic analysis can be used as a tool to identify potential biomarkers and novel therapeutic targets to gain a better understanding of the mechanisms underlying the initiation and progression of diseases.

View Article: PubMed Central - PubMed

Affiliation: School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035 China.

ABSTRACT
Diabetic nephropathy (DN) is one of the lethal manifestations of diabetic systemic microvascular disease. Elucidation of characteristic metabolic alterations during diabetic progression is critical to understand its pathogenesis and identify potential biomarkers and drug targets involved in the disease. In this study, (1)H nuclear magnetic resonance ((1)H NMR)-based metabonomics with correlative analysis was performed to study the characteristic metabolites, as well as the related pathways in urine and kidney samples of db/db diabetic mice, compared with age-matched wildtype mice. The time trajectory plot of db/db mice revealed alterations, in an age-dependent manner, in urinary metabolic profiles along with progression of renal damage and dysfunction. Age-dependent and correlated metabolite analysis identified that cis-aconitate and allantoin could serve as biomarkers for the diagnosis of DN. Further correlative analysis revealed that the enzymes dimethylarginine dimethylaminohydrolase (DDAH), guanosine triphosphate cyclohydrolase I (GTPCH I), and 3-hydroxy-3-methylglutaryl-CoA lyase (HMG-CoA lyase) were involved in dimethylamine metabolism, ketogenesis and GTP metabolism pathways, respectively, and could be potential therapeutic targets for DN. Our results highlight that metabonomic analysis can be used as a tool to identify potential biomarkers and novel therapeutic targets to gain a better understanding of the mechanisms underlying the initiation and progression of diseases.

No MeSH data available.


Related in: MedlinePlus

Correlation analysis of urinary and renal metabolites.Pearson’s correlations of UACR and quantities of the metabolites determined from 17-week-old mice urine samples (A, wildtype mice; B, db/db mice) and kidney samples (C, wildtype mice; D, db/db mice). Red and blue represent positive and negative correlations, respectively, the colour scale represents Pearson’s correlation coefficients. Keys: UACR, urinary albumin to creatinine ratio; LAC, lactate; PYR, pyruvate; SUCC, succinate; 2-OX, 2-oxoglutarate; CIT, citrate; C-AC, cis-aconitate; FUM, fumarate; Ma, methylamine; DMA, dimethylamine; TMA, trimethylamine; ACE, acetate; 3-HB, 3-hydroxybutyrate; AC, acetone; ACA, acetoacetate; CRE, creatine; CRT, creatinine; ALLA, allantion; HIP, hippurate; MNA, 1-methylnicotinamide; 3-IS, 3-indoxylsulfate; FOR, formate; ALA, alanine; PHE, phenylalanine; CHO, choline; M-INS, myo-inositol; GLU, glutamate; GLY, glycine; TYR, tyrosine; TAU, taurine; ASP, aspartate; VAL, valine; LEU, leucine; ILE, isoleucine; URA, uracil; URI, uridine; GTP, guanosine triphosphate; NIA, niacinamide.
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f7: Correlation analysis of urinary and renal metabolites.Pearson’s correlations of UACR and quantities of the metabolites determined from 17-week-old mice urine samples (A, wildtype mice; B, db/db mice) and kidney samples (C, wildtype mice; D, db/db mice). Red and blue represent positive and negative correlations, respectively, the colour scale represents Pearson’s correlation coefficients. Keys: UACR, urinary albumin to creatinine ratio; LAC, lactate; PYR, pyruvate; SUCC, succinate; 2-OX, 2-oxoglutarate; CIT, citrate; C-AC, cis-aconitate; FUM, fumarate; Ma, methylamine; DMA, dimethylamine; TMA, trimethylamine; ACE, acetate; 3-HB, 3-hydroxybutyrate; AC, acetone; ACA, acetoacetate; CRE, creatine; CRT, creatinine; ALLA, allantion; HIP, hippurate; MNA, 1-methylnicotinamide; 3-IS, 3-indoxylsulfate; FOR, formate; ALA, alanine; PHE, phenylalanine; CHO, choline; M-INS, myo-inositol; GLU, glutamate; GLY, glycine; TYR, tyrosine; TAU, taurine; ASP, aspartate; VAL, valine; LEU, leucine; ILE, isoleucine; URA, uracil; URI, uridine; GTP, guanosine triphosphate; NIA, niacinamide.

Mentions: To investigate the relationship among the metabolites, their levels in the urine and kidney samples from 17-week-old wildtype and db/db mice were correlated separately using the Pearson’s correlation (Fig. 7). UACR is a well-known marker of kidney damage and dysfunction. Analysis of the correlation between UACR and identified metabolites can be used to screen for specific biomarkers. Remarkably, the UACR showed a negative correlation with cis-aconitate, dimethylamine (DMA), 3-HB, acetoacetate, creatinine, allantoin, and a positive correlation with fumarate in the urine samples of db/db mice. In addition, lactate levels were positively correlated with UACR in the urine samples of db/db mice, whereas a negative correlation was observed in the wildtype mice (Fig. 7A,B). In the kidney tissue samples of db/db mice, UACR was positively correlated with phenylalanine, fumarate, acetate, glutamate, glycine, uridine, and GTP, and negatively correlated with lactate. No such correlation was evident in the wildtype mice (Fig. 7C,D). These metabolites, which showed significant correlation with UACR in the db/db mice, could serve as potential biomarkers for assessing the progression of DN.


Metabonomic analysis of potential biomarkers and drug targets involved in diabetic nephropathy mice.

Wei T, Zhao L, Jia J, Xia H, Du Y, Lin Q, Lin X, Ye X, Yan Z, Gao H - Sci Rep (2015)

Correlation analysis of urinary and renal metabolites.Pearson’s correlations of UACR and quantities of the metabolites determined from 17-week-old mice urine samples (A, wildtype mice; B, db/db mice) and kidney samples (C, wildtype mice; D, db/db mice). Red and blue represent positive and negative correlations, respectively, the colour scale represents Pearson’s correlation coefficients. Keys: UACR, urinary albumin to creatinine ratio; LAC, lactate; PYR, pyruvate; SUCC, succinate; 2-OX, 2-oxoglutarate; CIT, citrate; C-AC, cis-aconitate; FUM, fumarate; Ma, methylamine; DMA, dimethylamine; TMA, trimethylamine; ACE, acetate; 3-HB, 3-hydroxybutyrate; AC, acetone; ACA, acetoacetate; CRE, creatine; CRT, creatinine; ALLA, allantion; HIP, hippurate; MNA, 1-methylnicotinamide; 3-IS, 3-indoxylsulfate; FOR, formate; ALA, alanine; PHE, phenylalanine; CHO, choline; M-INS, myo-inositol; GLU, glutamate; GLY, glycine; TYR, tyrosine; TAU, taurine; ASP, aspartate; VAL, valine; LEU, leucine; ILE, isoleucine; URA, uracil; URI, uridine; GTP, guanosine triphosphate; NIA, niacinamide.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493693&req=5

f7: Correlation analysis of urinary and renal metabolites.Pearson’s correlations of UACR and quantities of the metabolites determined from 17-week-old mice urine samples (A, wildtype mice; B, db/db mice) and kidney samples (C, wildtype mice; D, db/db mice). Red and blue represent positive and negative correlations, respectively, the colour scale represents Pearson’s correlation coefficients. Keys: UACR, urinary albumin to creatinine ratio; LAC, lactate; PYR, pyruvate; SUCC, succinate; 2-OX, 2-oxoglutarate; CIT, citrate; C-AC, cis-aconitate; FUM, fumarate; Ma, methylamine; DMA, dimethylamine; TMA, trimethylamine; ACE, acetate; 3-HB, 3-hydroxybutyrate; AC, acetone; ACA, acetoacetate; CRE, creatine; CRT, creatinine; ALLA, allantion; HIP, hippurate; MNA, 1-methylnicotinamide; 3-IS, 3-indoxylsulfate; FOR, formate; ALA, alanine; PHE, phenylalanine; CHO, choline; M-INS, myo-inositol; GLU, glutamate; GLY, glycine; TYR, tyrosine; TAU, taurine; ASP, aspartate; VAL, valine; LEU, leucine; ILE, isoleucine; URA, uracil; URI, uridine; GTP, guanosine triphosphate; NIA, niacinamide.
Mentions: To investigate the relationship among the metabolites, their levels in the urine and kidney samples from 17-week-old wildtype and db/db mice were correlated separately using the Pearson’s correlation (Fig. 7). UACR is a well-known marker of kidney damage and dysfunction. Analysis of the correlation between UACR and identified metabolites can be used to screen for specific biomarkers. Remarkably, the UACR showed a negative correlation with cis-aconitate, dimethylamine (DMA), 3-HB, acetoacetate, creatinine, allantoin, and a positive correlation with fumarate in the urine samples of db/db mice. In addition, lactate levels were positively correlated with UACR in the urine samples of db/db mice, whereas a negative correlation was observed in the wildtype mice (Fig. 7A,B). In the kidney tissue samples of db/db mice, UACR was positively correlated with phenylalanine, fumarate, acetate, glutamate, glycine, uridine, and GTP, and negatively correlated with lactate. No such correlation was evident in the wildtype mice (Fig. 7C,D). These metabolites, which showed significant correlation with UACR in the db/db mice, could serve as potential biomarkers for assessing the progression of DN.

Bottom Line: Age-dependent and correlated metabolite analysis identified that cis-aconitate and allantoin could serve as biomarkers for the diagnosis of DN.Further correlative analysis revealed that the enzymes dimethylarginine dimethylaminohydrolase (DDAH), guanosine triphosphate cyclohydrolase I (GTPCH I), and 3-hydroxy-3-methylglutaryl-CoA lyase (HMG-CoA lyase) were involved in dimethylamine metabolism, ketogenesis and GTP metabolism pathways, respectively, and could be potential therapeutic targets for DN.Our results highlight that metabonomic analysis can be used as a tool to identify potential biomarkers and novel therapeutic targets to gain a better understanding of the mechanisms underlying the initiation and progression of diseases.

View Article: PubMed Central - PubMed

Affiliation: School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035 China.

ABSTRACT
Diabetic nephropathy (DN) is one of the lethal manifestations of diabetic systemic microvascular disease. Elucidation of characteristic metabolic alterations during diabetic progression is critical to understand its pathogenesis and identify potential biomarkers and drug targets involved in the disease. In this study, (1)H nuclear magnetic resonance ((1)H NMR)-based metabonomics with correlative analysis was performed to study the characteristic metabolites, as well as the related pathways in urine and kidney samples of db/db diabetic mice, compared with age-matched wildtype mice. The time trajectory plot of db/db mice revealed alterations, in an age-dependent manner, in urinary metabolic profiles along with progression of renal damage and dysfunction. Age-dependent and correlated metabolite analysis identified that cis-aconitate and allantoin could serve as biomarkers for the diagnosis of DN. Further correlative analysis revealed that the enzymes dimethylarginine dimethylaminohydrolase (DDAH), guanosine triphosphate cyclohydrolase I (GTPCH I), and 3-hydroxy-3-methylglutaryl-CoA lyase (HMG-CoA lyase) were involved in dimethylamine metabolism, ketogenesis and GTP metabolism pathways, respectively, and could be potential therapeutic targets for DN. Our results highlight that metabonomic analysis can be used as a tool to identify potential biomarkers and novel therapeutic targets to gain a better understanding of the mechanisms underlying the initiation and progression of diseases.

No MeSH data available.


Related in: MedlinePlus