ArticleBiomolecules2023
Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis.
Article in Biomolecules, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 13 citations in OpenAlex.
- Integrating metabolomics and machine learning with in silico analysis to identify early biomarkers and molecular interactions in sepsis-associated acute kidney injury.Scientific reports · 2026Article
- Mitochondrial dysfunction in sepsis-associated acute kidney injury: mechanisms and therapeutic potential.Frontiers in immunology · 2026Review
- Research advances on the gut-kidney axis theory in sepsis-associated acute kidney injury.Frontiers in pharmacology · 2026Review
- Biomarker-driven risk stratification and early intervention in acute kidney injury: a comprehensive review from early warning to clinical response.Frontiers in medicine · 2026Review
- Research Progress on Signalling Pathways Related to Sepsis-Associated Acute Kidney Injury in Children.Current issues in molecular biology · 2025Review
- Norepinephrine ameliorates sepsis-associated acute kidney injury through inhibiting damage of renal tubular epithelium induced by macrophage inflammatory response.BMC nephrology · 2025Article
- Fibro-NPC: a pathogenic subtype identified at single-cell resolution with secreted SFRP4 as a biomarker in intervertebral disc degeneration.Journal of translational medicine · 2025Article
- DPP8 and DPP9 promote tubular epithelial cell ferroptosis in acute kidney injury.European journal of medical research · 2025Article
- Exploring the molecular mechanisms of lactylation-related biological functions and immune regulation in sepsis-associated acute kidney injury.Clinical and experimental medicine · 2025Article
- Novel insights into the molecular mechanisms of sepsis-associated acute kidney injury: an integrative study of GBP2, PSMB8, PSMB9 genes and immune microenvironment characteristics.BMC nephrology · 2025Article
- Metabolomics- and proteomics-based multi-omics integration reveals early metabolite alterations in sepsis-associated acute kidney injury.BMC medicine · 2025Article
- Acute kidney injury through a metabolic lens: pathological reprogramming mechanisms and clinical translation potential.Frontiers in physiology · 2025Review
- Review of research progress in sepsis-associated acute kidney injury.Frontiers in molecular biosciences · 2025Review
- Sepsis-Associated Acute Kidney Injury: Where Are We Now?Medicina (Kaunas, Lithuania) · 2024Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.