Transcriptomic Profiling of Scleroderma Monocytes Reveals Links with Cardiovascular Complications, Implicating Notch and Interferon Pathways

Objectives: Recent research has highlighted the critical role of monocytes and macrophages in driving both inflammatory and fibrotic processes in systemic sclerosis (SSc). This study seeks to elucidate the gene expression profiles of SSc monocytes and their potential links to disease complications, with the ultimate goal of uncovering novel therapeutic targets. Methods: 48 SSc patients and 15 controls were recruited and monocytes were isolated using CD14+ magnetic beads. Total RNA was extracted and bulk RNA-seq analysis was performed. Differential gene expression followed by unsupervised hierarchical clustering and pathway analysis were conducted and correlations with clinical features were analyzed. Interferon signature score (IFN6) was calculated using the log transformed values of 6 genes (IFIT3, IFIT2, MX1, IFIH1, STAT2, and NCF1). Results: We identified four distinct patient subgroups, relative to normal, two with inflammatory and two with non-inflammatory gene profiles. The inflammatory subgroups exhibited high expression of interferon-related genes and included all SSc patients with pulmonary hypertension and most with cardiac involvement. In these patients, IFN6 was markedly elevated and showed a significant correlation with global longitudinal strain - GLS (r=-0.5, p=0.006), a key indicator of cardiac function. Furthermore, pathway analysis identified an enrichment of the Notch signaling pathway among genes whose overexpression correlated with impaired GLS. Conclusion: These findings unveil a potential new mechanistic link between interferon activity, Notch signaling, and cardiac complications in SSc, offering new insights into disease pathogenesis and potential therapeutic targets. Peripheral blood samples were obtained from 48 patients with systemic sclerosis (SSc) who met the 2013 ACR revised classification criteria and 15 healthy controls (HCs). Monocytes were isolated using CD14+ magnetic beads. Total RNA was extracted and bulk RNA-seq analysis was performed. RNA libraries were generated with the Library Prep Kit (Illumina) and sequenced (paired-end, 2 × 50 bp) on an Illumina NextSeq 2000. Quality control was performed using FastQC; reads were aligned to the hg38 human reference genome with STAR, and gene-level counts were generated using featureCounts. Differential expression was assessed using DESeq2 with age as a covariate. Functional enrichment analysis was performed using clusterProfiler. Unsupervised hierarchical clustering was performed using Euclidean distance and complete linkage, with feature selection using elastic net regularization.