Systemic inflammation as a predictor of clinical outcomes after lower extremity angioplasty/stenting  Kenneth DeSart, MD, Kerri O'Malley, PhD, Bradley Schmit, MD, Maria-Cecilia Lopez, PhD, Lyle Moldawer, PhD, Henry Baker, PhD, Scott Berceli, MD, PhD, Peter Nelson, MD, MS  Journal of Vascular Surgery  Volume 64, Issue 3, Pages 766-778.e5 (September 2016) DOI: 10.1016/j.jvs.2015.04.399 Copyright © 2016 Terms and Conditions

Fig 1 Supervised hierarchal clustering analysis of plasma inflammatory protein concentrations. Each patient sample at each time point is displayed across the x-axis, with each patient represented by the letters A through L. Each patient appears to have a unique inflammatory protein profile that remains relatively constant after endovascular intervention. Red represents upregulation, and blue represents downregulation. GMCSF, Granulocyte-macrophage colony-stimulating factor; IFN-γ, interferon-γ; IL, interleukin; IP-10, interferon γ-inducible protein 10; MCP-1, monocyte chemoattractant protein-1; MIP-1a, macrophage inflammatory protein 1 α; sCD40L, soluble CD40 ligand; TNF-α, tumor necrosis factor-α; VEGF, vascular endothelial growth factor. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 2 Circulating monocyte phenotypes after lower extremity endovascular revascularization. A, Classic monocytes, identified by expression of cluster of differentiation (CD)14 only (CD14+/CD16−), remained stable over time. Proinflammatory monocytes, identified by coexpression of CD14 and CD16, also remained stable over time, although the presence of this subtype appeared to demonstrate a downward trend after revascularization. B and C, Integrin surface expression (CD18, CD11a, and CD11b) was similar between the two monocyte phenotypes. CD14+/CD16– cells demonstrated a greater percentage of human leukocyte antigen-DR1 (HLA-DR)+ cells across all time points compared with CD14+/CD16+ cells (P = .021). Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 3 Canonical pathways representing the 31 genes demonstrating a significant change in the initial 1 month after the intervention. Multiple-testing corrected P values were used to control the rate of false discoveries. The first three pathways are considered significantly enriched for this gene set (calculated using the Benjamini-Hochberg [B-H] method, false discovery rate [FDR]-corrected P < .05). The black boxes represent the fraction of the predictive genes in each pathway. FAK, Focal adhesion kinase; HER-2, human epidermal growth factor receptor 2. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 4 Supervised hierarchal clustering analysis of 31 genes demonstrating a significant change in expression after revascularization. Mean expression data at each time point are presented across the x-axis. The vertical dendrogram reveals two distinct gene clusters with differential expression. Cluster A consists of nine genes that exhibit early upregulation (preoperatively, 0.08 days, and 1 day), and cluster B consists of 22 genes that exhibit late upregulation (7 days and 28 days). Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 5 Ingenuity Pathway Analysis of 31 genes demonstrates a significant change in expression after revascularization. The network encompassing this gene set is presented at four time points after intervention. Red indicates upregulation and blue indicates downregulation (relative to preoperative expression levels). Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 6 Unsupervised hierarchal clustering analysis of mean plasma inflammatory protein concentrations at each time point for both outcome groups are displayed across the x-axis. The horizontal dendrogram reveals a tight clustering of the two outcome groups, demonstrating two divergent patterns of protein expression. Red represents upregulation and blue represents downregulation. GMCSF, Granulocyte-macrophage colony-stimulating factor; IFN-γ, interferon-γ; IL, interleukin; IP-10, interferon γ-inducible protein 10; MCP-1, monocyte chemoattractant protein-1; MIP-1a, macrophage inflammatory protein 1 α; sCD40L, soluble CD40 ligand; TNF-α, tumor necrosis factor-α; VEGF, vascular endothelial growth factor. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 7 Clustering analysis of plasma inflammatory protein concentrations. A, Mean plasma protein concentrations at each time point for both outcome groups are displayed across the x-axis. The heat map reveals two divergent patterns of protein expression across all time points between the two outcome groups. B-D, A dynamic clustering algorithm identified three distinct patterns of protein expression. The mean fold-change from baseline (preoperative) concentrations of all proteins within each cluster for each outcome group is displayed. All three clusters demonstrated highly significant outcome-dependent differences (analysis of variance). GMCSF, Granulocyte-macrophage colony-stimulating factor; IFN-γ, interferon-γ; IL, interleukin; IP-10, interferon γ-inducible protein 10; MCP-1, monocyte chemoattractant protein-1; MIP-1a, macrophage inflammatory protein 1 α; sCD40L, soluble CD40 ligand; TNF-α, tumor necrosis factor-α; VEGF, vascular endothelial growth factor. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 8 Canonical pathways associated with the subset of day 1 genes that differentiate long-term success or failure of the intervention. The 10 most significant canonical pathways representing these 39 genes are presented. Multiple-testing corrected P values were used to control the rate of false discoveries. The black boxes represent the fraction of predictive genes in each pathway. B-H, Benjamini-Hochberg; ERKs, extracellular-signal-regulated kinases; NRF-2, nuclear factor erythroid 2-related factor 2. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 9 Unsupervised hierarchal clustering analysis of the subset of 39 day 1 genes that differentiate long-term success or failure. Mean expression data for both outcome groups at each time point is presented across the x-axis. Although this gene subset was selected for its ability to predict outcome at 1 day after revascularization, the primary node of clustering separates the outcome groups across all time points. Red represents upregulation and blue represents downregulation. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Fig 10 Ingenuity Pathway Analysis of the subset of day 1 genes that differentiate long-term success or failure, divided into two groups (F and G) after an unsupervised cluster analysis. The network pathway on the left contains 11 of the 25 cluster F genes and is primarily involved in cell death and survival. The pathway on the right contains 10 of the 12 cluster G genes and is primarily associated with cell-cycle regulation. Class prediction genes are represented in gray. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Supplementary Fig 1 (online only) Kaplan-Meier estimations of primary and secondary patency. Cumulative 1-year and 2-year primary patency was 79% and 66%, and 1-year and 2-year secondary patency was 83% and 76%. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Supplementary Fig 2 (online only) Plasma inflammatory protein levels after endovascular revascularization. By 24 hours after the intervention, the increase in the interleukin-6 (IL-6) concentration (16.0 ± 5.0 ng/mL) reached the Bonferroni-adjusted significance level compared with the preoperative levels (7.0 ± 4.7 ng/mL; P = .001). The plasma concentrations of IL-8, monocyte chemoattractant protein-1 (MCP-1), and soluble CD40 ligand (sCD40L) also demonstrated alterations after the intervention; however, these changes did not reach significance. The horizontal line in the middle of each box indicates the median; the top and bottom borders of the box mark the 75th and 25th percentiles, respectively, the whiskers mark the 90th and 10th percentiles, and the black circles indicate outliers. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions

Supplementary Fig 3 (online only) Unsupervised hierarchal clustering analysis of plasma inflammatory protein concentrations. Each patient sample at each time point is displayed across the x-axis, with each patient represented by the letters A through L. The horizontal dendrogram identifies the individual patient's plasma protein signature as the dominant clustering effect. Each patient appears to have a unique inflammatory protein profile that remains relatively constant after endovascular intervention. Red represents upregulation and blue represents downregulation. GMCSF, Granulocyte-macrophage colony-stimulating factor; IFN-γ, interferon-γ; IL, interleukin; IP-10, interferon γ-inducible protein 10; MCP-1, monocyte chemoattractant protein-1; MIP-1a, macrophage inflammatory protein 1 α; sCD40L, soluble CD40 ligand; TNF-α, tumor necrosis factor-α; VEGF, vascular endothelial growth factor. Journal of Vascular Surgery 2016 64, 766-778.e5DOI: (10.1016/j.jvs.2015.04.399) Copyright © 2016 Terms and Conditions