Integrative single-cell analysis of epigenomic and transcriptomic states in patients with systemic sclerosis-associated interstitial lung disease

Abstract

Interstitial lung disease is the primary cause of death in individuals who have systemic sclerosis, one of the autoimmune connective tissue diseases. Understanding the pathophysiology of the disease is crucial to developing treatment options. Here, we performed a single-cell multi-omic analysis on lung tissue samples from patients with systemic sclerosis-associated interstitial lung disease (SSC-ILD), profiling chromatin accessibility and gene expression in the same samples and discovering significant cellular heterogeneity. Systemic-venous endothelial cells (ECs) have been shown to be pro-inflammatory and highly active. In addition, it was shown that the transcription factor FOSL2 targets the genes involved in response to unfolded proteins in systemic-venous ECs. Furthermore, we prioritized functional risk variants for systemic sclerosis using a genome-wide association study. Ligand-receptor analysis revealed that ECs significantly increased interaction with B cells via CXCL10-CXCR3 in patients with SSC-ILD. Overall, our analysis emphasizes epigenetic and transcriptional patterns in systemic-venous ECs, which might be beneficial in understanding the pathogenesis of SSC-ILD.

Integrative proteogenomics study identifies the indirect effect of circulating proteins on 8 diseases via telomere length

“…GSE138266 includes 12 scRNA-seq datasets from cerebrospinal fluid (CSF) in 6 multiple sclerosis patients and 6 control groups. The raw data of the gene expression matrix was taken from GEO and turned into a Seurat object for downstream processing, as previously indicated [30]. In brief, doublets were detected using the “scrub.scrub_doublets()” function in Scrublet package (v2.0.2) [31] and further removed.…”

“…The copyright holder for this this version posted December 8, 2023. ; https://doi.org/10.1101/2023.12.06.23299603 doi: medRxiv preprint matrix was taken from GEO and turned into a Seurat object for downstream processing, as previously indicated [30]. In brief, doublets were detected using the "scrub.scrub_doublets()" function in Scrublet package (v2.0.2) [31] and further removed.…”