Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study
IntroductionChronic kidney disease (CKD) is a global public health problem, and the absence of reliable and accurate diagnostic and monitoring tools contributes to delayed treatment, impacting patients’ quality of life and increasing treatment costs in public health. Proteomics using saliva is a key...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2024.1302637/full |
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| author | Bianca Uliana Picolo Nathália Rabello Silva Mário Machado Martins Hebréia Oliveira Almeida-Souza Letícia Cristina Machado de Sousa Richard Costa Polveiro Luiz Ricardo Goulart Filho Robinson Sabino-Silva Vivian Alonso-Goulart Luciana Saraiva da Silva |
| author_facet | Bianca Uliana Picolo Nathália Rabello Silva Mário Machado Martins Hebréia Oliveira Almeida-Souza Letícia Cristina Machado de Sousa Richard Costa Polveiro Luiz Ricardo Goulart Filho Robinson Sabino-Silva Vivian Alonso-Goulart Luciana Saraiva da Silva |
| author_sort | Bianca Uliana Picolo |
| collection | DOAJ |
| description | IntroductionChronic kidney disease (CKD) is a global public health problem, and the absence of reliable and accurate diagnostic and monitoring tools contributes to delayed treatment, impacting patients’ quality of life and increasing treatment costs in public health. Proteomics using saliva is a key strategy for identifying potential disease biomarkers.MethodsWe analyzed the untargeted proteomic profiles of saliva samples from 20 individuals with end-stage kidney disease (ESKD) (n = 10) and healthy individuals (n = 10) using liquid chromatography–tandem mass spectrometry (LC–MS/MS) to identify potential biomarkers for CKD. A volcano plot was generated using a p-value of ≤0.05 and a fold change (FC) ≥ 2.0. Multivariate analysis was performed to generate the orthogonal partial least squares discriminant analysis (OPLS-DA) model and the variable importance in projection (VIP) scores. The accuracy of candidate biomarker proteins was evaluated using receiver operating characteristic (ROC) curves.ResultsIn total, 431 proteins were identified in the salivary proteomic profile, and 3 proteins were significantly different between the groups: apoptosis inhibitor 5 (API5), phosphoinositide phospholipase C (PI-PLC), and small G protein signaling modulator 2 (Sgsm2). These proteins showed good accuracy based on the ROC curve and a VIP score of >2.0. During pathway enrichment, PI-PLC participates in the synthesis of IP3 and IP4 in the cytosol. Gene ontology (GO) analysis revealed data on molecular functions, biological processes, cellular components, and protein classes.ConclusionWe can conclude that the salivary API5, PI-PLC, and Sgsm2 can be potential biomarker candidates for CKD detection. These proteins may participate in pathways related to renal fibrosis and other associated diseases, such as mineral and bone disorders. |
| format | Article |
| id | doaj-art-c827b17cceba44798829e41f7c9b2891 |
| institution | Kabale University |
| issn | 2296-858X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Medicine |
| spelling | doaj-art-c827b17cceba44798829e41f7c9b28912025-01-17T15:54:56ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-01-011110.3389/fmed.2024.13026371302637Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot studyBianca Uliana Picolo0Nathália Rabello Silva1Mário Machado Martins2Hebréia Oliveira Almeida-Souza3Letícia Cristina Machado de Sousa4Richard Costa Polveiro5Luiz Ricardo Goulart Filho6Robinson Sabino-Silva7Vivian Alonso-Goulart8Luciana Saraiva da Silva9Laboratory of Nanobiotechnology Prof. Dr. Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlândia, Uberlândia, BrazilFaculty of Medicine, Federal University of Uberlândia, Uberlândia, BrazilLaboratory of Nanobiotechnology Prof. Dr. Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlândia, Uberlândia, BrazilLaboratory of Nanobiotechnology Prof. Dr. Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlândia, Uberlândia, BrazilFaculty of Medicine, Federal University of Uberlândia, Uberlândia, BrazilFaculty of Veterinary Medicine and Animal Science, Federal University of Uberlândia, Uberlândia, BrazilLaboratory of Nanobiotechnology Prof. Dr. Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlândia, Uberlândia, BrazilInnovation Center in Salivary Diagnostic and Nanobiotechnology, Institute of Biomedical Sciences, Federal University of Uberlândia, Uberlândia, BrazilLaboratory of Nanobiotechnology Prof. Dr. Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlândia, Uberlândia, BrazilFaculty of Medicine, Federal University of Uberlândia, Uberlândia, BrazilIntroductionChronic kidney disease (CKD) is a global public health problem, and the absence of reliable and accurate diagnostic and monitoring tools contributes to delayed treatment, impacting patients’ quality of life and increasing treatment costs in public health. Proteomics using saliva is a key strategy for identifying potential disease biomarkers.MethodsWe analyzed the untargeted proteomic profiles of saliva samples from 20 individuals with end-stage kidney disease (ESKD) (n = 10) and healthy individuals (n = 10) using liquid chromatography–tandem mass spectrometry (LC–MS/MS) to identify potential biomarkers for CKD. A volcano plot was generated using a p-value of ≤0.05 and a fold change (FC) ≥ 2.0. Multivariate analysis was performed to generate the orthogonal partial least squares discriminant analysis (OPLS-DA) model and the variable importance in projection (VIP) scores. The accuracy of candidate biomarker proteins was evaluated using receiver operating characteristic (ROC) curves.ResultsIn total, 431 proteins were identified in the salivary proteomic profile, and 3 proteins were significantly different between the groups: apoptosis inhibitor 5 (API5), phosphoinositide phospholipase C (PI-PLC), and small G protein signaling modulator 2 (Sgsm2). These proteins showed good accuracy based on the ROC curve and a VIP score of >2.0. During pathway enrichment, PI-PLC participates in the synthesis of IP3 and IP4 in the cytosol. Gene ontology (GO) analysis revealed data on molecular functions, biological processes, cellular components, and protein classes.ConclusionWe can conclude that the salivary API5, PI-PLC, and Sgsm2 can be potential biomarker candidates for CKD detection. These proteins may participate in pathways related to renal fibrosis and other associated diseases, such as mineral and bone disorders.https://www.frontiersin.org/articles/10.3389/fmed.2024.1302637/fullchronic kidney diseaseLC–MS/MSsalivary proteomicbiomarkerPI-PLCSgsm2 |
| spellingShingle | Bianca Uliana Picolo Nathália Rabello Silva Mário Machado Martins Hebréia Oliveira Almeida-Souza Letícia Cristina Machado de Sousa Richard Costa Polveiro Luiz Ricardo Goulart Filho Robinson Sabino-Silva Vivian Alonso-Goulart Luciana Saraiva da Silva Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study Frontiers in Medicine chronic kidney disease LC–MS/MS salivary proteomic biomarker PI-PLC Sgsm2 |
| title | Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study |
| title_full | Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study |
| title_fullStr | Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study |
| title_full_unstemmed | Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study |
| title_short | Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study |
| title_sort | salivary proteomics profiling reveals potential biomarkers for chronic kidney disease a pilot study |
| topic | chronic kidney disease LC–MS/MS salivary proteomic biomarker PI-PLC Sgsm2 |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2024.1302637/full |
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