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

GSE303431 Homo sapiens (human) RNA-seq (gene expression) 63 samples Submitted 2025/08/01 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 63 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
63 samples: 6 conditions, mostly with about 8 replicates eachGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Transcriptomic profiling of scleroderma monocytes reveals links with cardiovascular complications, implicating Notch and interferon pathwaysJournal of scleroderma and related disorders · 2025
Summary (written by the submitters)
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.
Read the full summary ↓
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.
Published in
Transcriptomic profiling of scleroderma monocytes reveals links with cardiovascular complications, implicating Notch and interferon pathways
Dinc MT, El-Adili F, Lui JK et al. · Journal of scleroderma and related disorders 2025 · PMID 40735732 · doi:10.1177/23971983251356123
This dataset
Open GSE303431 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE303431_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1295412 and SRA study SRP603780. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40735732) ↗
Study design
6 conditions, mostly with about 8 replicates each
CD14+ monocytes, limited cutaneous systemic s… ×16 CD14+ monocytes, limited cutaneous systemic s… ×14 CD14+ monocytes, diffuse cutaneous systemic s… ×10 CD14+ monocytes, diffuse cutaneous systemic s… ×8 CD14+ monocytes, healthy control, TM_EF_B2 ×8 CD14+ monocytes, healthy control, TM_EF_B1 ×7

Supports a between-group comparison across 63 samples.

How we read this: 6 replicated groups read from 63 sample titles; they account for 63 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 23 more — browse all 63 samples with per-sample file links →

Datasets on a similar topic

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