Identification of biomarkers on kidney failure by Raman spectroscopy

Abstract

Chronic kidney disease (CKD) is a global health problem. Our study employed Raman spectroscopy for the first time to analyze potential biomarker such as tryptophan (Trp) on kidney failure and show the difference between normal and CKD groups. Adenine model of CKD characterized most of the physiological changes observed in human CKD. For that, 6‐week‐old Wistar male rats were assigned to the two groups: the control group, 0.5% carboxymethyl cellulose (CMC) was administered; the CKD group, adenine was administered to rats at a dose 600 mg/kg for 10 days. The Raman spectra were obtained in the spectral range of 100–2500 cm−1. The excitation source was 532 nm, the laser power was ~40 mW, and the analyzed tissue area was 10.02 × 82.12 μm2. The results showed a significant reduction in the case of Raman peak intensities at 748, 1359, 1554, and 1636 cm−1, which can be assigned as Trp. Moreover, it was shown that tyrosine at 1169 cm−1 and phenylalanine at 1001 cm−1 decreased in the CKD group. Trp and kynurenine (Kyn) levels in kidney tissue and plasma were analyzed by using the high‐performance liquid chromatography (HPLC). The Trp concentrations in plasma and kidney tissue significantly decreased in CKD 7.4 μg/ml and 0.1 μg/mg, respectively. However, Kyn level was not a statistically significant change in kidney tissue. In this work, we showed that Raman spectroscopy usage in CKD model and Raman spectroscopy can be considered a promising technique for semi‐quantitative analysis of potential biomarkers such as phenylalanine, tyrosine, and Trp of renal function because of the little or no need for sample preparation, and it is easily observing several biomarkers at the same time. The utilization of multivariate analysis method, such as partial least square analysis can be considered as a promising tool for the discrimination of control and CKD groups.

RaMALDI: Enabling simultaneous Raman and MALDI imaging of the same tissue section

“…Raman peaks for component 2 included 1366, 1372, 1437, and 1445 cm -1 , which mainly arose from lipids [7] . The identified Raman peaks are consistent with those reported in previous studies of the kidney under various conditions [52][53][54][55] . While the MCR-ALS analysis of RSI images provides an important starting point for understanding the classes of compositional contributors and their spatial distribution, it does not offer definitive confirmation of the specific molecules in the tissue sample, making the integration with MALDI MSI particularly significant and insightful.…”

SERS for Detection of Proteinuria: A Comparison of Gold, Silver, Al Tape, and Silicon Substrates for Identification of Elevated Protein Concentration in Urine

“…The strongest peak in urine is 1005 cm −1 which corresponds to the N-C-N stretching in urea [ 46 ]. Certain peaks at 1359, 1554, and 1636 cm −1 can be attributed to specific amino acids [ 47 ]. For instance, the peaks at 1355, 1551, and 1610 cm −1 are attributed to tryptophan [ 48 ].…”

Analysis of urine Raman spectra differences from patients with diabetes mellitus and renal pathologies

“…Raman spectroscopy and surface enhanced Raman scattering (SERS) have been used in the analysis of biological fluids, including blood ( Berger et al, 1999 ; Enejder et al, 2002 ), urine ( Premasiri, Clarke & Womble, 2001 ; Moreira et al, 2017 ), saliva ( Virkler & Lednev, 2010 ; Hardy et al, 2022 ), and others with clinical applications ( Panikar et al, 2021 ). Recently, Raman spectroscopy was used to analyze the spectral differences of urine composition from healthy subjects and from patients with advanced kidney disease, including CKD 4/5 and ESRD ( Senger et al, 2020 ; Chen et al, 2020b , 2020a ; Gulyamov et al, 2021 ; Kamińska et al, 2022 ). These studies found that chemometric analysis of urine Raman spectral data detected molecular ‘fingerprints’ associated with advanced kidney disease ( Senger et al, 2019 , 2020 ; Chen et al, 2020b ).…”