Comparison of SERS Substrates in Direct Analysis of Urine Samples for Detection of Albuminuria: Relatively Large Gold Nano-Spheroids Outperform Gold Nanorods on Gold Film
- 1Department of Chemistry, School of Sciences and Humanities (SSH), Nazarbayev University, Astana 010000, Kazakhstan
- 2Department of Medicine, Nazarbayev University School of Medicine, Astana 010000, Kazakhstan
Abstract
Proteins found in human urine can be used as a source of information on kidney function and as possible biomarkers for diseases such as chronic kidney disease (CKD). Focusing on differentiating between high and low albumin concentrations in urine samples, this study examines the roles of various substrates in detecting albuminuria as a specific form of proteinuria using surface-enhanced Raman spectroscopy (SERS). Using gold nanorods (AuNRs) and gold spheroidal nanoparticles (AuNPs) on various substrates to optimize the identification of albuminuria, we studied urine samples from 77 and 124 patients with albumin concentrations above and below 0.3 g/L. SERS spectra were analyzed using principal component analysis—linear discriminant analysis (PCA-LDA), partial least squares with linear discriminant analysis (PLS-LDA), and support vector machine (PLS-SVM)—to differentiate between high- and low-urinary-albumin groups. PLS-LDA was the best-performing method among the three methods. The largest of all tested nanoparticles, 200 nm diameter (D200 nm) AuNPs on gold substrates, performed best in distinguishing between high and low concentrations of albumin in urine, with a maximum average area under the curve (AUC) of 0.97, 100% sensitivity, 92% specificity, and 96% accuracy and a higher enhancement factor of 5.4 × 107 in comparison to the same parameters obtained with λ650 nm and λ750 nm AuNRs on gold, which demonstrated average AUC values of 0.86 and 0.77 and EFs of 11 and 3 × 106, respectively. These larger NPs create hot spots in nanogaps between nanoparticles, which may have better accessibility to protein molecules compared to hot spots created in gaps between smaller nanorods and nanoparticles. This study highlights the role of nanoparticle size and shape in determining optimal SERS substrate parameters, thereby yielding more accurate results in the detection of high concentrations of albumin in urine by direct SERS.
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BibTeX
@article{boranova2026comparison,
title = {{Comparison of SERS Substrates in Direct Analysis of Urine Samples for Detection of Albuminuria: Relatively Large Gold Nano-Spheroids Outperform Gold Nanorods on Gold Film}},
author = {Aigerim Boranova and Almat Kabyl and Bagdat Tuleuov and Madiyar Kassymaly and Zhalaliddin Makhammajanov and Abduzhappar Gaipov and Rostislav Bukasov},
journal = {International journal of molecular sciences},
year = {2026},
month = oct,
doi = {10.3390/ijms27198833},
url = {https://europepmc.org/article/PMC/PMC13665429},
note = {CC BY},
}
RIS
TY - JOUR
TI - Comparison of SERS Substrates in Direct Analysis of Urine Samples for Detection of Albuminuria: Relatively Large Gold Nano-Spheroids Outperform Gold Nanorods on Gold Film
AU - Aigerim Boranova
AU - Almat Kabyl
AU - Bagdat Tuleuov
AU - Madiyar Kassymaly
AU - Zhalaliddin Makhammajanov
AU - Abduzhappar Gaipov
AU - Rostislav Bukasov
PY - 2026
DA - 2026/10/01
JO - International journal of molecular sciences
DO - 10.3390/ijms27198833
UR - https://europepmc.org/article/PMC/PMC13665429
AB - Proteins found in human urine can be used as a source of information on kidney function and as possible biomarkers for diseases such as chronic kidney disease (CKD). Focusing on differentiating between high and low albumin concentrations in urine samples, this study examines the roles of various substrates in detecting albuminuria as a specific form of proteinuria using surface-enhanced Raman spectroscopy (SERS). Using gold nanorods (AuNRs) and gold spheroidal nanoparticles (AuNPs) on various substrates to optimize the identification of albuminuria, we studied urine samples from 77 and 124 patients with albumin concentrations above and below 0.3 g/L. SERS spectra were analyzed using principal component analysis—linear discriminant analysis (PCA-LDA), partial least squares with linear discriminant analysis (PLS-LDA), and support vector machine (PLS-SVM)—to differentiate between high- and low-urinary-albumin groups. PLS-LDA was the best-performing method among the three methods. The largest of all tested nanoparticles, 200 nm diameter (D200 nm) AuNPs on gold substrates, performed best in distinguishing between high and low concentrations of albumin in urine, with a maximum average area under the curve (AUC) of 0.97, 100% sensitivity, 92% specificity, and 96% accuracy and a higher enhancement factor of 5.4 × 107 in comparison to the same parameters obtained with λ650 nm and λ750 nm AuNRs on gold, which demonstrated average AUC values of 0.86 and 0.77 and EFs of 11 and 3 × 106, respectively. These larger NPs create hot spots in nanogaps between nanoparticles, which may have better accessibility to protein molecules compared to hot spots created in gaps between smaller nanorods and nanoparticles. This study highlights the role of nanoparticle size and shape in determining optimal SERS substrate parameters, thereby yielding more accurate results in the detection of high concentrations of albumin in urine by direct SERS.
SN - 1422-0067
ER -