Cargando…
Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis
Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condition with high morbidity and mortality among emergency patients, and it poses a significant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnosti...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10526551/ https://www.ncbi.nlm.nih.gov/pubmed/37759729 http://dx.doi.org/10.3390/biom13091329 |
_version_ | 1785111045805703168 |
---|---|
author | Xu, Jiatong Li, Jiaying Li, Yan Shi, Xiaoxiao Zhu, Huadong Chen, Limeng |
author_facet | Xu, Jiatong Li, Jiaying Li, Yan Shi, Xiaoxiao Zhu, Huadong Chen, Limeng |
author_sort | Xu, Jiatong |
collection | PubMed |
description | Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condition with high morbidity and mortality among emergency patients, and it poses a significant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnostic biomarkers or treatment targets. In this study, we established an SA-AKI mouse model using lipopolysaccharide (LPS) and performed proteomics and metabolomics analyses. A variety of bioinformatic analyses, including gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein and protein interactions (PPI), and MetaboAnalyst analysis, were conducted to investigate the key molecules of SA-AKI. Integrated proteomics and metabolomics analysis revealed that sepsis led to impaired renal mitochondrial function and metabolic disorders. Immune-related pathways were found to be activated in kidneys upon septic infection. The catabolic products of polyamines accumulated in septic kidneys. Overall, our integrated analysis provides a multidimensional understanding of SA-AKI and identifies potential pathways for this condition. |
format | Online Article Text |
id | pubmed-10526551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105265512023-09-28 Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis Xu, Jiatong Li, Jiaying Li, Yan Shi, Xiaoxiao Zhu, Huadong Chen, Limeng Biomolecules Article Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condition with high morbidity and mortality among emergency patients, and it poses a significant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnostic biomarkers or treatment targets. In this study, we established an SA-AKI mouse model using lipopolysaccharide (LPS) and performed proteomics and metabolomics analyses. A variety of bioinformatic analyses, including gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein and protein interactions (PPI), and MetaboAnalyst analysis, were conducted to investigate the key molecules of SA-AKI. Integrated proteomics and metabolomics analysis revealed that sepsis led to impaired renal mitochondrial function and metabolic disorders. Immune-related pathways were found to be activated in kidneys upon septic infection. The catabolic products of polyamines accumulated in septic kidneys. Overall, our integrated analysis provides a multidimensional understanding of SA-AKI and identifies potential pathways for this condition. MDPI 2023-08-30 /pmc/articles/PMC10526551/ /pubmed/37759729 http://dx.doi.org/10.3390/biom13091329 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xu, Jiatong Li, Jiaying Li, Yan Shi, Xiaoxiao Zhu, Huadong Chen, Limeng Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis |
title | Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis |
title_full | Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis |
title_fullStr | Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis |
title_full_unstemmed | Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis |
title_short | Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis |
title_sort | multidimensional landscape of sa-aki revealed by integrated proteomics and metabolomics analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10526551/ https://www.ncbi.nlm.nih.gov/pubmed/37759729 http://dx.doi.org/10.3390/biom13091329 |
work_keys_str_mv | AT xujiatong multidimensionallandscapeofsaakirevealedbyintegratedproteomicsandmetabolomicsanalysis AT lijiaying multidimensionallandscapeofsaakirevealedbyintegratedproteomicsandmetabolomicsanalysis AT liyan multidimensionallandscapeofsaakirevealedbyintegratedproteomicsandmetabolomicsanalysis AT shixiaoxiao multidimensionallandscapeofsaakirevealedbyintegratedproteomicsandmetabolomicsanalysis AT zhuhuadong multidimensionallandscapeofsaakirevealedbyintegratedproteomicsandmetabolomicsanalysis AT chenlimeng multidimensionallandscapeofsaakirevealedbyintegratedproteomicsandmetabolomicsanalysis |