Correlation of urinary peptides with kidney function.

<p>a) Heatmap of the signal of the 88 peptides of the CKD273 model showing monotone variations. Each line represents a single peptide, and the four columns correspond to the four groups of patients separated according to their eGFR value (90–61, 60–31, 30–16 and 15–0 mL/min/1.73 m²). The mean signal per peptide and per group is represented following the color key included in the figure. <b>b)</b> and <b>c)</b>: the median scoring and interquartile range for 2 of the 88 peptides is presented in logarithmic scale. The upper panel shows the distribution of LLSPYSYSTTAVVTNPKE, a peptide derived from Transthyretin (AA 130–147). The lower panel depicts the distribution of SGSVIDQSRVL, a peptide derived from Uromodulin (AA 589–599). The abundance of these peptides changes significantly with decreasing MDRD-estimated GFR.</p

CKD273 scoring and eGFR values in the patients included in the study.

<p>The patients treated by dialysis are not included in the figure as their eGFR could not be calculated by the serum creatinine level. Linear Regression equation, y = −0.019x +1.12; R² = 0.40; p<0.001.</p

The full urinary proteome/peptidome analysed by CE-MS of selected patients.

<p>Patient number 58 (A) and the diabetic patient 27 (B) are shown in the upper panels. These patients had eGFR of 64.3 and 15.7 ml/mn/1.73 m², respectively. The molecular mass (0.8–20 kDa, on a logarithmic scale) is plotted against normalized migration time (18–45 min). Signal intensity is encoded by peak height and color. The two lower panels show only the peptides that are addressed in the CKD273 model. Differences already visible in the entire proteome become evident when examining the specific biomarkers of the CKD273 classifier.</p

Cluster analysis.

<p>Clustering of the 53 patients was performed according to their CKD273 pattern using an average linkage clustering and standard Euclidean distances to assign the patients to clusters.</p

Correlation analysis of metabolomic and proteomic based classifier scores with baseline eGFR.

<p>The correlation analysis is performed by using the support vector machine classification scores obtained for the test set with baseline. A. Classifier MetaboP (plasma metabolites) ρ = −0.8031 and p<0.0001. B. Classifier MetaboU (urinary metabolites) ρ = −0.6557 and p = 0.0001. C. Classifier Pept (urinary peptides) ρ = −0.7752 and p<0.0001.</p

Regulation of metabolites and peptides.

<p>The fold changes of metabolites and peptides “mild CKD” vs. “advanced CKD”. A. Plasma metabolites. B. Urinary metabolites. C. Urinary peptides. C19∶0: Nonadecanoic acid. SM C26∶1: Sphingomyelin with acyl residue sum C26∶1. PC aa C42∶4: Phosphatidylcholine with acyl-alkyl residue sum C42∶4. C14∶2: Tetradecadienoylcarnitine. cis-C20∶1w9: cis-11-Eicosenoic acid. PC aa C42∶4: Phosphatidylcholine with acyl-alkyl residue sum C42∶4. C17∶0: Heptadecanoic acid. PC aa C42∶5: Phosphatidylcholine with acyl-alkyl residue sum C42∶5. C4: Nonanoylcarnitine. C5: Isovalerylcarnitine. ADMA: Asymmetric dimethylarginine. Total DMA: Total dimethylarginine. C9: Nonanoylcarnitine. C4∶1: Butenoylcarnitine. C5-DC(C6-OH): Acylcarnitine. C14∶1-OH: 3-Hydroxytetradecenoylcarnitine. dH: Deoxyhexose. HNAc(S2): (N-acetylhexosamine)-disulfate. C3∶1: Propenoylcarnitine. C7-DC: Pimelylcarnitine. H2-dH2: Dihexose-dideoxyhexose. Asn: Asparagine. Leu: Leucine. H1: Hexose. Pro: Proline. Cit: Citrulline.</p

Correlation analysis of metabolomic and proteomic based classifier scores with follow-up eGFR.

<p>The correlation analysis is performed by using the support vector machine classification scores obtained for the test set with follow-up eGFR. A. Classifier MetaboP (plasma metabolites) ρ = −0.6009 and p = 0.0019. B. Classifier MetaboU (urinary metabolites) ρ = −0.6574 and p = 0.0005. C. Classifier Pept (urinary peptides) ρ = −0.8400 and p<0.0001.</p