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Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease

Urinary proteomics studies have primarily focused on identifying markers of chronic kidney disease (CKD) progression. Here, we aimed to determine urinary markers of CKD renal parenchymal injury through proteomics analysis in animal kidney tissues and cells and in the urine of patients with CKD. Labe...

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Autores principales: Kim, Ji Eun, Han, Dohyun, Jeong, Jin Seon, Moon, Jong Joo, Moon, Hyun Kyung, Lee, Sunhwa, Kim, Yong Chul, Yoo, Kyung Don, Lee, Jae Wook, Kim, Dong Ki, Kwon, Young Joo, Kim, Yon Su, Yang, Seung Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Biochemistry and Molecular Biology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7950200/
https://www.ncbi.nlm.nih.gov/pubmed/33453410
http://dx.doi.org/10.1074/mcp.RA120.002159
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author Kim, Ji Eun
Han, Dohyun
Jeong, Jin Seon
Moon, Jong Joo
Moon, Hyun Kyung
Lee, Sunhwa
Kim, Yong Chul
Yoo, Kyung Don
Lee, Jae Wook
Kim, Dong Ki
Kwon, Young Joo
Kim, Yon Su
Yang, Seung Hee
author_facet Kim, Ji Eun
Han, Dohyun
Jeong, Jin Seon
Moon, Jong Joo
Moon, Hyun Kyung
Lee, Sunhwa
Kim, Yong Chul
Yoo, Kyung Don
Lee, Jae Wook
Kim, Dong Ki
Kwon, Young Joo
Kim, Yon Su
Yang, Seung Hee
author_sort Kim, Ji Eun
collection PubMed
description Urinary proteomics studies have primarily focused on identifying markers of chronic kidney disease (CKD) progression. Here, we aimed to determine urinary markers of CKD renal parenchymal injury through proteomics analysis in animal kidney tissues and cells and in the urine of patients with CKD. Label-free quantitative proteomics analysis based on liquid chromatography–tandem mass spectrometry was performed on urine samples obtained from 6 normal controls and 9, 11, and 10 patients with CKD stages 1, 3, and 5, respectively, and on kidney tissue samples from a rat CKD model by 5/6 nephrectomy. Tandem mass tag-based quantitative proteomics analysis was performed for glomerular endothelial cells (GECs) and proximal tubular epithelial cells (PTECs) before and after inducing 24-h hypoxia injury. Upon hierarchical clustering, out of 858 differentially expressed proteins (DEPs) in the urine of CKD patients, the levels of 416 decreased and 403 increased sequentially according to the disease stage, respectively. Among 2965 DEPs across 5/6 nephrectomized and sham-operated rat kidney tissues, 86 DEPs showed same expression patterns in the urine and kidney tissue. After cross-validation with two external animal proteome data sets, 38 DEPs were organized; only ten DEPs, including serotransferrin, gelsolin, poly ADP-ribose polymerase 1, neuroblast differentiation-associated protein AHNAK, microtubule-associated protein 4, galectin-1, protein S, thymosin beta-4, myristoylated alanine-rich C-kinase substrate, and vimentin, were finalized by screening human GECs and PTECs data. Among these ten potential candidates for universal CKD marker, validation analyses for protein S and galectin-1 were conducted. Galectin-1 was observed to have a significant inverse correlation with renal function as well as higher expression in glomerulus with chronic injury than protein S. This constitutes the first multisample proteomics study for identifying key renal-expressed proteins associated with CKD progression. The discovered proteins represent potential markers of chronic renal cell and tissue damage and candidate contributors to CKD pathophysiology.
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spelling pubmed-79502002021-03-19 Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease Kim, Ji Eun Han, Dohyun Jeong, Jin Seon Moon, Jong Joo Moon, Hyun Kyung Lee, Sunhwa Kim, Yong Chul Yoo, Kyung Don Lee, Jae Wook Kim, Dong Ki Kwon, Young Joo Kim, Yon Su Yang, Seung Hee Mol Cell Proteomics Research Urinary proteomics studies have primarily focused on identifying markers of chronic kidney disease (CKD) progression. Here, we aimed to determine urinary markers of CKD renal parenchymal injury through proteomics analysis in animal kidney tissues and cells and in the urine of patients with CKD. Label-free quantitative proteomics analysis based on liquid chromatography–tandem mass spectrometry was performed on urine samples obtained from 6 normal controls and 9, 11, and 10 patients with CKD stages 1, 3, and 5, respectively, and on kidney tissue samples from a rat CKD model by 5/6 nephrectomy. Tandem mass tag-based quantitative proteomics analysis was performed for glomerular endothelial cells (GECs) and proximal tubular epithelial cells (PTECs) before and after inducing 24-h hypoxia injury. Upon hierarchical clustering, out of 858 differentially expressed proteins (DEPs) in the urine of CKD patients, the levels of 416 decreased and 403 increased sequentially according to the disease stage, respectively. Among 2965 DEPs across 5/6 nephrectomized and sham-operated rat kidney tissues, 86 DEPs showed same expression patterns in the urine and kidney tissue. After cross-validation with two external animal proteome data sets, 38 DEPs were organized; only ten DEPs, including serotransferrin, gelsolin, poly ADP-ribose polymerase 1, neuroblast differentiation-associated protein AHNAK, microtubule-associated protein 4, galectin-1, protein S, thymosin beta-4, myristoylated alanine-rich C-kinase substrate, and vimentin, were finalized by screening human GECs and PTECs data. Among these ten potential candidates for universal CKD marker, validation analyses for protein S and galectin-1 were conducted. Galectin-1 was observed to have a significant inverse correlation with renal function as well as higher expression in glomerulus with chronic injury than protein S. This constitutes the first multisample proteomics study for identifying key renal-expressed proteins associated with CKD progression. The discovered proteins represent potential markers of chronic renal cell and tissue damage and candidate contributors to CKD pathophysiology. American Society for Biochemistry and Molecular Biology 2021-01-13 /pmc/articles/PMC7950200/ /pubmed/33453410 http://dx.doi.org/10.1074/mcp.RA120.002159 Text en © 2021 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research
Kim, Ji Eun
Han, Dohyun
Jeong, Jin Seon
Moon, Jong Joo
Moon, Hyun Kyung
Lee, Sunhwa
Kim, Yong Chul
Yoo, Kyung Don
Lee, Jae Wook
Kim, Dong Ki
Kwon, Young Joo
Kim, Yon Su
Yang, Seung Hee
Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease
title Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease
title_full Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease
title_fullStr Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease
title_full_unstemmed Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease
title_short Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease
title_sort multisample mass spectrometry-based approach for discovering injury markers in chronic kidney disease
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7950200/
https://www.ncbi.nlm.nih.gov/pubmed/33453410
http://dx.doi.org/10.1074/mcp.RA120.002159
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