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The nephrotic syndrome (NS) is defined as the presence of proteinuria (>3 g/24 h or a protein/creatinine ratio >3 mg), hypoalbuminemia (<2.5 g/dL), and peripheral edema. The associated metabolic alterations include a procoagulant state, susceptibility to infections, increased vascular risk, and/or acute kidney injury that can progress to chronic kidney disease. It represents the primary indication for percutaneous renal biopsy (PRB) with all the inherent risks. The causes of NS are divided into primary glomerular disease (PGN) and secondary conditions (SGN), determined by PRB. Several studies have been conducted in search of biomarkers associated with different etiologies to either avoid the need for PRB or reduce the study time, utilizing new analytical methods. Recently, approximately 3000 metabolites have been detected in urine, positioning it as a potential biofluid for early diagnosis. Fourier-transform infrared spectroscopy (FTIR) provides information about biomolecules (lipids, proteins, carbohydrates, and nucleic acids) by identifying mid-infrared bands associated with functional groups. When combined with computational techniques, it becomes relevant for clinical diagnosis. The aim of this study was to characterize the FTIR spectrum of urine from patients with NS, categorizing them as those with primary or secondary causes versus healthy individuals, determining the bands that allow differentiation between these groups.
The methodology used urine samples from patients diagnosed with NS (n=13) and from healthy individuals (n=13) with similar demographic characteristics at the Central Military Hospital. The samples were refrigerated at 4°C and immediately analyzed using a Jasco FT/IR-6600 spectrometer in attenuated total reflectance mode with parameters ranging from 4000 to 400 cm-1, a resolution of 4 cm-1, 120 scans, and triplicate analysis. 3 µL of urine were placed and allowed to dry for 15 minutes. The spectra were normalized and averaged. Area under the curve calculations, second derivative, and principal component analysis (PCA) were performed, along with normality tests and statistical analysis using OriginPro 8 and GraphPad Prism software
The biomolecular composition of urine from patients with NS compared to healthy individuals using FTIR spectroscopy revealed statistically significant differences in the bands related to albumin (3390-3240 cm-1), cholesterol (3000-2800 cm-1), amide I (1640-1575 cm-1) and II (1480-1408 cm-1), urea (1200-1090 cm-1), sulfate (1090-1059 cm-1), and phosphates (949-913 cm-1).
The PGN group displayed higher absorbance in the albumin band, which correlated with increased albuminuria.
The PCA analysis of the albumin band (3390-3240 cm-1) demonstrated the most significant relationship in data clustering and group discrimination, explaining 95% of the variables in the two principal components. This was associated with symmetric O-H stretching, possibly attributed to the hydrogen bonds formed in albumin (Usoltsev, D. et al., 2019), which has not been extensively reported in the literature, as most studies typically focus only on the biological fingerprint.
The biomolecular components characterizing the urine of patients with NS using FTIR spectroscopy are the spectral bands of albumin, cholesterol, amides I and II, urea, sulfate, and phosphate.