*2.2. Urinary Proteome Analysis for Identification and Label-Free Quantitation*

The workflow of data processes contained identified and quantified urinary proteins indicative of disease status, as well as significant proteins to build the clinical models (Figure 1A). Liquid chromatography–mass spectrometry (LC-MS) analysis of the 54 urine samples identified 1296 proteins (Table S2). Of these proteins, 1244 were quantified, and their quantities were adjusted relative to the concentration of creatinine [9,10]. Sample-to-sample variation was subsequently fixed by the amount of proteins, leading to the selection of six endogenous normalization proteins that showed stable abundance in all LC-MS analyses. A boxplot of protein abundances in the 54 samples, composed of 35 patients in good-prognostic group (GPG) and 19 patients in poor-prognostic group (PPG), is depicted in Figure 1B. The normalized abundance of 68 proteins significantly correlated with their immunoassay [11] determined concentrations in urine, with a Pearson's coefficient of 0.502 (permutation *p*-value < 0.001; Figure 1C).

**Figure 1.** (**A**) Analysis workflow of urinary proteins in the 54 diabetic kidney disease (DKD) patients. The analysis method is written in the upper part, the number of proteins in the middle, and the meaning of the protein in the bottom part. (**B**) Boxplots of normalized urinary protein abundances in the 54 samples (35 patients in good-prognostic group and 19 patients in poor-prognostic group) measured by LC-MS analysis. (**C**) Scatter plot of 68 urine proteins between normalized log2 abundance and log2 immunoassays concentration (Pearson correlation coefficient (ρ): 0.5 and *<sup>p</sup>*-value: 1.9 <sup>×</sup> <sup>10</sup><sup>−</sup>4).
