Fibrosis Distinguishes Critical Limb Ischemia Patients from Claudicants in a Transcriptomic and Histologic Analysis

Abstract

Most patients with critical limb ischemia (CLI) from peripheral arterial disease (PAD) do not have antecedent intermittent claudication (IC). We hypothesized that transcriptomic analysis would identify CLI-specific pathways, particularly in regards to fibrosis. Derivation cohort data from muscle biopsies in PAD and non-PAD (controls) was obtained from the Gene Expression Omnibus (GSE120642). Transcriptomic analysis indicated CLI patients (N = 16) had a unique gene expression profile, when compared with non-PAD controls (N = 15) and IC (N = 20). Ninety-eight genes differed between controls and IC, 2489 genes differed between CLI and controls, and 2783 genes differed between CLI and IC patients. Pathway enrichment analysis showed that pathways associated with TGFβ, collagen deposition, and VEGF signaling were enriched in CLI but not IC. Receiver operating curve (ROC) analysis of nine fibrosis core gene expression revealed the areas under the ROC (AUC) were all >0.75 for CLI. Furthermore, the fibrosis area (AUC = 0.81) and % fibrosis (AUC = 0.87) in validation cohort validated the fibrosis discrimination CLI from IC and control (all n = 12). In conclusion, transcriptomic analysis identified fibrosis pathways, including those involving TGFβ, as a novel gene expression feature for CLI but not IC. Fibrosis is an important characteristic of CLI, which we confirmed histologically, and may be a target for novel therapies in PAD.

Keywords: claudication; critical limb ischemia (CLI); fibrosis pathway; peripheral artery disease (PAD); transcriptomics.

Figure 1

Flow Diagram of Study design and data processing. RNA sequence data of 51 skeleton muscle biopsies in peripheral arterial disease (PAD) (16 of critical limb ischemia (CLI) and 20 of intermittent claudication (IC)) and non-PAD controls (N = 15) were retrieved from the Gene Expression Omnibus (GEO) database (GSE120642). After principal component analysis, Uniform Manifold Approximation and Projection (UMAP), differential expression analysis, hierarchical cluster analysis, and pathway enrichment analysis were completed using Ingenuity Pathway Analysis (http://www.ingenuity.com). The ability of fibrosis modular gene signatures to discriminate CLI from IC was assessed by ANOVA and receiver operating curve (ROC). For validation, we evaluated fibrosis in 36 muscle biopsies from non-PAD controls, IC, and CLI patients using Masson’s trichrome staining. After the measurement of fibrosis area and percentage, we conducted ROC analysis. PCA, principal component analysis.

Figure 2

Unique gene expression profile presenting in CLI patients. (A) Principal component analysis (PCA) of the samples. Each dot represents one subject. (B) (UMAP) of the samples. Each dot represents one subject. (C) Heatmap of all differentially expressed genes among groups. Samples are on columns, genes are on columns, and the heat map is based on standardized gene expression values. (D) Volcano plot representing differential gene expression among groups. Each dot on the plot is a single gene. Horizontal axis: fold change; vertical axis: false discovery rate (FDR) p-value (in log10 scale) by Wald test. Color coding is based on the fold change. Thick vertical lines highlight fold changes of −2 and +2, while a thick horizontal line represents a FDR p-value of 0.05. N = 15 for non-PAD controls, N = 20 for IC, N = 16 for CLI. PC1, principal component; CLI, critical limb ischemia; IC, intermittent claudication.

Figure 3

IPA of genes differentially expressed between CLI and IC and Con. Differentially expressed genes calculated using DeSeq2 (FC > 2, FDR < 0.05) were merged and submitted for IPA analysis. (A,D) A selection of highly significant functions and their activation z-scores are shown in the bar graphs (orange for positive Z score, blue for negative Z score, and gray for no activation pattern available). The x-axis corresponds to the –log of the p-value (Fisher’s exact test); (B,E) a selection of highly significant functions and their activation percentage are shown in the stack bar graphs (red for activation, green for inhibition. Number for each bar for the total molecular in this pathway.) (C,F) Overlaying pathways. (C) CLI vs. Con; (F) CLI vs. IC; (A–C) for CLI vs. Con; (D–F) for CLI vs. IC. (G) Bar and stacked bar graph of first five function and their activation when IC vs. Con. (H) Canonical pathway heatmap of three comparisons. 3.4 Fibrosis pathways are enriched in CLI patients compared to IC and controls. TCA, Tricarboxylic Acid Cycle; FC, Fold Change; ILK, Integrin Linked Kinase; IPA, Ingenuity Pathway Analysis.

Figure 4

Network overview of modular expression patterns of fibrosis pathway. (A) CLI vs. Con; (B) CLI vs. IC; (C) IC vs Con. Ingenuity Pathway Analysis of the differentially regulated genes when CLI vs. control and CLI vs IC. The network is displayed graphically as nodes (genes/gene products) and edges (biological relationship between nodes). The node color intensity indicates the fold change expression of genes, with red representing activation, green representing down-regulation of genes, orange representing prediction activation, and blue representing prediction inhibition; the lines indicate the type of interaction.

Figure 5

Fibrosis pathway core genes distinguish CLI from IC and control. (A) Representative gene expression of fibrosis pathway by transcriptomic by box and whiskers, violins, and points plot; each dot is a sample. The plot title is the gene symbol of the selected gene. Expression levels are log (total counts) on the vertical axis. * p < 0.05, compared with non-PAD controls by wald test, ^# p < 0.05, compared with IC by wald test. (B) Receiver operating curve (ROC) (spell out ROC) for the diagnosis of CLI of TGF β signaling, collagen deposition signaling, and vascular endothelial growth factor (VEGF) signaling. All area under curve (AUC) > 0.75. N = 15 for non-PAD control, N = 20 for IC, and N = 16 for CLI.

Figure 6

Validation of fibrosis pathway to distinguish CLI from IC and control. Masson trichrome staining of gastrocnemius muscle biopsies. (A) Representative fibrosis staining image (×20 magnification). (B) Assessment of fibrosis by area and percentage. Each dot is a sample. Comparison between HA, IC, and CLI group using single one-way analysis of variance (ANOVA) followed by Bonferroni t-test; ** p < 0.01, *** p < 0.001, **** p < 0.0001. (C) ROC for the diagnosis of CLI. Fibrosis area (AUC area = 0.81) and fibrosis percentage (AUC area = 0.87). N = 12 for non-PAD control, IC, and CLI. NS, not significant.

Figure 7

Derivation cohort included 15 non-PAD controls, 20 IC, and 16 CLI patients. Validation cohort included 12 non-PAD controls, 12 IC, and 12 CLI patients. Both fibrosis pathway identified by transcriptomics and fibrosis quantification by Masson trichrome of skeletal muscle demonstrated an area under the curve (AUC) over 0.75. This indicates that fibrosis distinguishes CLI patients from IC in a transcriptomic and histologic analysis.