Purpose <p>Owing to insufficient understanding of the molecular basis of arteriovenous fistula (AVF) failure, strategies to facilitate maturation and prevent access loss remain limited. This study aimed to identify potential biomarkers for AVF nonmaturation.</p> Methods <p>We enrolled 123 patients with end-stage renal disease who underwent AVF surgery. Finally, 86 were classified into AVF matured (AM; <i>n</i> = 52) and AVF nonmatured (ANM; <i>n</i> = 34) groups following exclusion. Four cephalic vein tissue samples from each group were used for data-independent acquisition–mass spectrometry (DIA–MS) proteomic analysis to identify differently expressed genes. All 86 vein tissue samples were used for histological analysis, and all serum samples were used for ELISA.</p> Results <p>DIA–MS proteomic analysis identified 17 upregulated and 363 downregulated proteins in the ANM group compared with the AM group. Fibrinogen α (FGA), fibrinogen β (FGB), and fibrinogen γ (FGG) were the most activated proteins. Univariate logistic regression analysis revealed collagen volume fraction (CVF) (odds ratio [OR] = 1.278, 95% confidence interval [CI] 1.133–1.440, <i>P</i> &lt; 0.001), FGA (OR = 1.005, 95% CI 1.003–1.007, <i>P</i> &lt; 0.001), FGB (OR = 1.269, 95% CI 1.147–1.403, <i>P</i> &lt; 0.001), and FGG (OR = 1.010, 95% CI 1.007–1.014, <i>P</i> &lt; 0.001) as potential independent predictors of AVF nonmaturation. Multivariable logistic regression models further confirmed that FGA, FGB, and FGG could predict AVF outcomes.</p> Conclusion <p>This study suggested high FGA, FGB, and FGG levels are risk factors for AVF nonmaturation and could be potential biomarkers.</p>

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Data-independent acquisition–mass spectrometry proteomic analysis reveals fibrinogen α, β, and γ chains as candidate biomarkers for the nonmaturation of autogenous arteriovenous fistula

  • Bin Zhao,
  • Shen Zhan,
  • Xue Zhou,
  • Pei Yu,
  • YuZhu Wang

摘要

Purpose

Owing to insufficient understanding of the molecular basis of arteriovenous fistula (AVF) failure, strategies to facilitate maturation and prevent access loss remain limited. This study aimed to identify potential biomarkers for AVF nonmaturation.

Methods

We enrolled 123 patients with end-stage renal disease who underwent AVF surgery. Finally, 86 were classified into AVF matured (AM; n = 52) and AVF nonmatured (ANM; n = 34) groups following exclusion. Four cephalic vein tissue samples from each group were used for data-independent acquisition–mass spectrometry (DIA–MS) proteomic analysis to identify differently expressed genes. All 86 vein tissue samples were used for histological analysis, and all serum samples were used for ELISA.

Results

DIA–MS proteomic analysis identified 17 upregulated and 363 downregulated proteins in the ANM group compared with the AM group. Fibrinogen α (FGA), fibrinogen β (FGB), and fibrinogen γ (FGG) were the most activated proteins. Univariate logistic regression analysis revealed collagen volume fraction (CVF) (odds ratio [OR] = 1.278, 95% confidence interval [CI] 1.133–1.440, P < 0.001), FGA (OR = 1.005, 95% CI 1.003–1.007, P < 0.001), FGB (OR = 1.269, 95% CI 1.147–1.403, P < 0.001), and FGG (OR = 1.010, 95% CI 1.007–1.014, P < 0.001) as potential independent predictors of AVF nonmaturation. Multivariable logistic regression models further confirmed that FGA, FGB, and FGG could predict AVF outcomes.

Conclusion

This study suggested high FGA, FGB, and FGG levels are risk factors for AVF nonmaturation and could be potential biomarkers.