Abstract 2114: Differences In The Circulating Transcriptome Between Peripheral Artery Disease And Coronary Artery Disease - Ni, Richard; Muller, Matthew; Ruggles, Kelly; Barrett, Tessa; Berger, Jeffrey (Arteriosclerosis, thrombosis, and vascular biology, 2024)
Introduction: Despite common risk factors, peripheral artery disease (PAD) and coronary artery disease (CAD) exhibit distinct pathological presentations. Previous gene expression profiling of blood from CAD and PAD patients shows alterations in inflammatory and immune related transcripts relative to controls. Studies have not directly compared gene expression in PAD versus CAD. Here, we aimed to use whole-blood RNA sequencing to investigate transcriptomic differences between PAD and CAD. Methods: Whole blood from subjects age 40-65 years with symptomatic PAD (n=20, mean age 59, 75% male, 35% white) and CAD (n=51, mean age 52, 82% male, 78% white) was collected into PAXgene tubes. Patients with concomitant CAD and PAD were excluded. RNA was isolated, sequenced and analyzed to investigate differential circulating gene expression between PAD and CAD subjects adjusting for age, sex, and race/ethnicity. Cell type deconvolution method dtangle was applied to characterize cell type proportions in the whole blood transcriptome. Results: Between PAD and CAD subjects, 106 transcripts were differentially expressed (adjP < 0.1), of which 38 were enriched in PAD and 68 were enriched in CAD. Gene set enrichment analysis (GSEA) revealed 29 pathways differentially expressed (FDR 0.05) between PAD and CAD, of which 8 were enriched in PAD and 21 enriched in CAD. The top enriched pathways in PAD were "specific granule" (Normalized enrichment score [NES] = 2.1, q value = 2.5 x 10-5) and "secretory granule membrane" (NES = 1.9, q = 1.0 x 10-4). Top enriched pathways in CAD were "T cell receptor complex" (NES = 3.1, q = 2.2 x 10-7) and "response to interferon-alpha" (NES = 3.1, q = 2.2 x 10-9). Cellular deconvolution using dtangle showed increased CD8 T-cells (p=0.01) and CD4 Naïve T-cells (p=0.007) in subjects with CAD versus PAD. Conclusion: Whole blood transcriptomics revealed significant differences in the circulating transcriptome between patients presenting with PAD and CAD. Our data suggest upregulation of pathways related to secretory granules in PAD, and enrichment of CD8 and CD4 Naïve T-cells and pathways related to T-cell signaling in CAD. Differences in the circulating transcriptome may help explain pathological and clinical differences between PAD and CAD.