← BioTransfer GEO Dataset Finder
GEO series

Circulating monocytes from patients promote calcific aortic valve disease development

GSE290104 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2025/02/24 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 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
15 samples
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.
Summary (written by the submitters)
Calcific Aortic Valve Disease (CAVD) is the most frequent valvular heart disease in developed countries. It is characterized by a progressive calcification of aortic valve leaflets mediated by myeloid cells, such as monocytes and macrophages. However, the molecular mechanisms involved in their recruitment and activity are still poorly understood and limit the development of a pharmacological treatments.
Read the full summary ↓
Previous studies have already demonstrated the role of macrophages in CAVD development. However, little is known about the implication of their precursors, monocytes. Thus, we hypothesized that circulating monocytes from CAVD patients have higher pro-calcific and pro-inflammatory capacities. We aimed first to assess the pro-calcifying potential of circulating monocytes from patients with CAVD and second to better understand the molecular mechanisms of this pro-calcific effect through a whole transcriptomic study. Methods : We first characterized monocytes sub-population, from PBMCs isolated from peripheral blood of healthy volunteers (Vol) and patients with CAVD or without CAVD (NCAVD), with flow cytometry. Then we analyzed the whole transcriptome of these monocytes by RNA sequencing (RNAseq) to identify dysregulated genes expression, further confirmed by RT-qPCR. Finally, after evaluation of monocytes secretome with multiplex analysis, we evaluated CAVD monocytes capacities to induce myofibroblastic transdifferenciation and osteoblastic differencitation of human valvular interstitial cells (hVIC) with immunocytochemistry (ICC) and O-cresolphtalein assay. Results : In CAVD (calcific aortic valve disease) monocytes, we observe a shift in their sub-populations, with an increased frequency of classical monocytes (CD14+CD16-) and a decreased frequency of non-classical monocytes (CD14+CD16++). Interestingly, we found specific upregulation of genes linked to both inflammation (PDK4) and calcification (ATP2B1), alongside the downregulation of immunomodulatory genes (DDR1, IKBKE) in monocytes from CAVD patients. Additionally, CAVD monocytes produce lower levels of immunomodulatory and anti-osteoblastogenic cytokines (IL3, CCL3), which promote myofibroblastic transdifferentiation (TIMP1, TNC) and osteoblastic differentiation (ALPL, OPG). This correlates with an increase in αsma+ and opn+ cells and a doubling of hVIC calcifications. Conclusions : We demonstrated for the first time that circulating monocytes from CAVD patients have higher pro-inflammatory and pro-calcific capacities that might promote CAVD development. Likewise, we identify dysregulated genes, which could be used as new therapeutic targets.
This dataset
Open GSE290104 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 GSE290104_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 PRJNA1226216 and SRA study SRP565306. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 15 more — browse all 15 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.