Transcriptomic Evaluation of Vein Tissue to Identify Risk Factors for Stenosis in Autologous Arteriovenous Fistulas

Background: Diabetes mellitus and hypertension have been reported as risks for shunt failure, but their molecular mechanisms are unknown. We conducted an analysis of the comprehensive gene expression profile of the cephalic vein to identify the set of genes whose expression variations were induced in the venous tissue of patients who required vascular access interventional study (VAIVT) within one year following arterio-venous fistula (AVF) creation. Methods: A transcriptome analysis was conducted on 21 patients with end-stage renal failure who underwent arteriovenous fistula (AVF) creation at our hospital. The analysis utilized the Next Seq 500 platform to examine venous transections collected at the time of anastomosis. The study compared patients who required vascular access intervention within one year post-surgery (10 patients) with those who did not require such intervention (11 patients). Results: There was no difference in the prevalence of hypertension or diabetes mellitus. 282 molecules were defined as variable genes (DEGs) with fold change >1.5 or <0.67, p<0.05. Enrichment analysis showed fluctuations in the expression of inflammation-related molecules, including a group of molecules regulated by STAT2. Network analysis of DEGs identified S100A8, S100A9 and CXCR1 as hub genes. Conclusion: Inflammation-related genes expressed in anastomotic veins may modulate the molecular mechanism of shunt stenosis.

Authors

Institutions

Publication Details

Journal
Journal of the American Society of Nephrology
Published
2025-10-01
DOI
https://doi.org/10.1681/asn.2025tx1wqxjy
Primary Topic
Central Venous Catheters and Hemodialysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Transcriptomic Evaluation of Vein Tissue to Identify Risk Factors for Stenosis in Autologous Arteriovenous Fistulas

Tetsu Miyamoto, Tomohiro Shirouzu
Journal of the American Society of Nephrology
Central Venous Catheters and Hemodialysis
article

Transcriptomic Evaluation of Vein Tissue to Identify Risk Factors for Stenosis in Autologous Arteriovenous Fistulas

Tetsu Miyamoto, Tomohiro Shirouzu
article en

Abstract

Background: Diabetes mellitus and hypertension have been reported as risks for shunt failure, but their molecular mechanisms are unknown. We conducted an analysis of the comprehensive gene expression profile of the cephalic vein to identify the set of genes whose expression variations were induced in the venous tissue of patients who required vascular access interventional study (VAIVT) within one year following arterio-venous fistula (AVF) creation. Methods: A transcriptome analysis was conducted on 21 patients with end-stage renal failure who underwent arteriovenous fistula (AVF) creation at our hospital. The analysis utilized the Next Seq 500 platform to examine venous transections collected at the time of anastomosis. The study compared patients who required vascular access intervention within one year post-surgery (10 patients) with those who did not require such intervention (11 patients). Results: There was no difference in the prevalence of hypertension or diabetes mellitus. 282 molecules were defined as variable genes (DEGs) with fold change >1.5 or <0.67, p<0.05. Enrichment analysis showed fluctuations in the expression of inflammation-related molecules, including a group of molecules regulated by STAT2. Network analysis of DEGs identified S100A8, S100A9 and CXCR1 as hub genes. Conclusion: Inflammation-related genes expressed in anastomotic veins may modulate the molecular mechanism of shunt stenosis.

Journal of the American Society of NephrologyVol. 36(10S)
University of Occupational and Environmental Health Japan (JP)
Openalex Percentile: Top 53%
Central Venous Catheters and Hemodialysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.