The Predictive Value of Tumor Necrosis Factor Receptor-Associated Factor-Interacting Protein With Forkhead-Associated Domain (TIFA) and Interleukin-1 Beta in Sepsis-Associated Acute Kidney Injury: Bioinformatics Analysis and Experimental Validation DOI Open Access

Zuyi Zhao,

Wen Guo,

Bohui Zhao

et al.

Cureus, Journal Year: 2025, Volume and Issue: unknown

Published: May 18, 2025

Background and objective Sepsis is a systemic inflammatory response syndrome caused by severe infection. Sepsis-associated acute kidney injury (SA-AKI) one of the most common complications sepsis. Early prediction subsequent treatment SA-AKI can improve patient outcomes; hence, accurate its occurrence paramount importance. This study aimed to investigate predictive value potential biomarkers interleukin-1 beta (IL-1β) tumor necrosis factor receptor‑associated (TRAF)‑interacting protein with forkhead‑associated domain (TIFA) related development SA-AKI. Methods We identified relevant GSE datasets (225192) from Gene Expression Omnibus (GEO) database conducted secondary analyses, revealing increased expression TIFA IL-1β in renal tissues. Building on our preliminary findings, we performed prospective observational (March 2024 December 2024) among patients sepsis who were admitted Department Critical Care Medicine at First Affiliated Hospital Xinjiang Medical University. Patients stratified based AKI. Plasma samples collected within 24 hours ICU admission analyzed using enzyme-linked immunosorbent assay (ELISA) measure plasma levels IL-1β. Results The analysis revealed that length hospital stay, albumin/globulin ratio, white blood cell count did not show any significant differences between groups. However, significantly higher AKI compared those without area under receiver operating characteristic (ROC) curve (AUC) was 0.912, indicating possess high discriminatory power calibration accuracy. These findings suggest are closely associated respect patients. Conclusions Bioinformatics experimental validation upregulated may serve as for predicting

Language: Английский

Correction: Metabolomics- and proteomics-based multi-omics integration reveals early metabolite alterations in sepsis-associated acute kidney injury DOI Creative Commons
Pengfei Huang, Yanqi Liu, Yue Li

et al.

BMC Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: March 8, 2025

Language: Английский

Citations

0
SAA1 as a Potential Early Diagnostic Biomarker for Sepsis Through Integrated Proteomics and Metabolomics DOI
Mengyao Yuan, Pengfei Huang, Yuhan Liu

et al.

Immunology, Journal Year: 2025, Volume and Issue: unknown

Published: April 10, 2025

ABSTRACT Sepsis is characterised by fatal organ dysfunction resulting from a dysfunctional host response to infection, imposing substantial economic burden on families and society. Therefore, identifying biomarkers for early sepsis diagnosis improving patient prognosis are critical. This study recruited 59 patients 35 healthy volunteers the Department of Critical Care Medicine at Harbin Medical University Affiliated First Hospital between March December 2021. Through combination non‐targeted targeted proteomics metabolomics sequencing, along with various analytical methods, we initially identified validated serum amyloid A1 (SAA1) as diagnostic biomarker sepsis. Our found that SAA1 was significantly elevated in group, demonstrating its value ( AUC : 0.95, 95% CI 0.88–1). Additionally, positive correlation observed disease severity, indicated Sequential Organ Failure Assessment SOFA ) score R = 0.51, p 0.004) Acute Physiology Chronic Health Evaluation II APACHE 0.52, 0.003). suggests potentially effective reliable marker diagnosing predicting severity.

Language: Английский

Citations

0
The Predictive Value of Tumor Necrosis Factor Receptor-Associated Factor-Interacting Protein With Forkhead-Associated Domain (TIFA) and Interleukin-1 Beta in Sepsis-Associated Acute Kidney Injury: Bioinformatics Analysis and Experimental Validation DOI Open Access

Zuyi Zhao,

Wen Guo,

Bohui Zhao

et al.

Cureus, Journal Year: 2025, Volume and Issue: unknown

Published: May 18, 2025

Background and objective Sepsis is a systemic inflammatory response syndrome caused by severe infection. Sepsis-associated acute kidney injury (SA-AKI) one of the most common complications sepsis. Early prediction subsequent treatment SA-AKI can improve patient outcomes; hence, accurate its occurrence paramount importance. This study aimed to investigate predictive value potential biomarkers interleukin-1 beta (IL-1β) tumor necrosis factor receptor‑associated (TRAF)‑interacting protein with forkhead‑associated domain (TIFA) related development SA-AKI. Methods We identified relevant GSE datasets (225192) from Gene Expression Omnibus (GEO) database conducted secondary analyses, revealing increased expression TIFA IL-1β in renal tissues. Building on our preliminary findings, we performed prospective observational (March 2024 December 2024) among patients sepsis who were admitted Department Critical Care Medicine at First Affiliated Hospital Xinjiang Medical University. Patients stratified based AKI. Plasma samples collected within 24 hours ICU admission analyzed using enzyme-linked immunosorbent assay (ELISA) measure plasma levels IL-1β. Results The analysis revealed that length hospital stay, albumin/globulin ratio, white blood cell count did not show any significant differences between groups. However, significantly higher AKI compared those without area under receiver operating characteristic (ROC) curve (AUC) was 0.912, indicating possess high discriminatory power calibration accuracy. These findings suggest are closely associated respect patients. Conclusions Bioinformatics experimental validation upregulated may serve as for predicting

Language: Английский

Citations

0