GEO series

Monocytes defined by platelet interactions and oxidative stress signaling underlie HIV-associated atherosclerosis [scRNA-seq]

GSE319710 Homo sapiens (human) Single-cell RNA-seq 48 samples Submitted 2026/02/20 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 48 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 48 samples: 24 × Seq_GEX vs 24 × Seq_HTOGroups 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: Monocytes Defined by Platelet Interactions and Oxidative Stress Signaling Underlie HIV-Associated AtherosclerosisJournal of the American Heart Association · 2026

Summary (written by the submitters)

Background: Monocytes contribute to atherosclerosis (AS) by migrating into inflamed endothelium and differentiating into foam cells. In people living with HIV (PLWH), chronic inflammation increases AS risk, yet the role of specific monocyte clusters remains unclear. We investigated how distinct monocyte populations contribute to vascular pathology in early HIV-associated AS.

Read the full summary ↓

Methods: We profiled 123,965 circulating monocytes using single-cell RNA-seq and integrated plasma microparticle proteomics in 32 individuals stratified by HIV and AS status. Supervised learning identified cluster- and disease-specific signatures, validated by platelet-monocyte co-cultures, RT-qPCR, bulk RNA-seq, flow cytometry and ELISA. Results: Seven monocyte clusters were identified, including a subset characterized by platelet–monocyte complexes (PMCs). Bulk RNA-seq of platelet–monocyte co-cultures revealed platelet-driven upregulation of genes involved in inflammation, lipid metabolism, oxidative stress, and endothelial adhesion. PMC-derived macrophages secreted higher levels of TGF-β and IL-10, displayed decreased CD14 and increased CD80/CD86 while retaining CD36, and promoted endothelial-to-mesenchymal transition (decreased CDH5, PECAM1; increased S100A4) and vascular inflammation (increased ICAM1, VCAM and IL-6, CCL2 secretion). Additionally, CD14+ monocytes from HIV+AS- and HIV+AS+ groups showed enhanced ROS-NRF2 pathway activities, supported by increased basal and H2O2-induced p90RSK phosphorylation, indicating oxidative stress priming. Conclusions: Two monocyte clusters contribute independently to vascular immune dysregulation in PLWH. PMC-derived macrophages promote endothelial dysfunction while adopting a profibrotic cytokine profile. CD14+ monocytes show heightened oxidative signaling and stress responses, consistent with vascular activation. Together, these mechanisms may accelerate AS development in HIV, even in the absence of traditional cardiovascular risk factors.

Published in

Monocytes Defined by Platelet Interactions and Oxidative Stress Signaling Underlie HIV-Associated Atherosclerosis

Wang RH, Boodoo ZD, Sutton KR et al. · Journal of the American Heart Association 2026 · PMID 41823228 · doi:10.1161/JAHA.125.046482

This dataset

Open GSE319710 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 GSE319710_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1424988 and SRA study SRP677834. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41823228) ↗

Study design

24 × Seq_GEX vs 24 × Seq_HTO

Supports a between-group comparison across 48 samples.

How we read this: 2 replicated groups read from 48 sample titles; they account for 48 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

GSM9524194 Seq_GEX_1 Seq_GEX
GSM9524195 Seq_GEX_2 Seq_GEX
GSM9524196 Seq_GEX_3 Seq_GEX
GSM9524197 Seq_GEX_4 Seq_GEX
GSM9524198 Seq_GEX_5 Seq_GEX
GSM9524199 Seq_GEX_6 Seq_GEX
GSM9524200 Seq_GEX_7 Seq_GEX
GSM9524201 Seq_GEX_8 Seq_GEX
GSM9524202 Seq_GEX_9 Seq_GEX
GSM9524203 Seq_GEX_10 Seq_GEX
GSM9524204 Seq_GEX_11 Seq_GEX
GSM9524205 Seq_GEX_12 Seq_GEX
GSM9524206 Seq_GEX_13 Seq_GEX
GSM9524207 Seq_GEX_14 Seq_GEX
GSM9524208 Seq_GEX_15 Seq_GEX
GSM9524209 Seq_GEX_16 Seq_GEX
GSM9524210 Seq_GEX_17 Seq_GEX
GSM9524211 Seq_GEX_18 Seq_GEX
GSM9524212 Seq_GEX_19 Seq_GEX
GSM9524213 Seq_GEX_20 Seq_GEX
GSM9524214 Seq_GEX_21 Seq_GEX
GSM9524215 Seq_GEX_22 Seq_GEX
GSM9524216 Seq_GEX_23 Seq_GEX
GSM9524217 Seq_GEX_24 Seq_GEX
GSM9524218 Seq_HTO_1 Seq_HTO
GSM9524219 Seq_HTO_2 Seq_HTO
GSM9524220 Seq_HTO_3 Seq_HTO
GSM9524221 Seq_HTO_4 Seq_HTO
GSM9524223 Seq_HTO_5 Seq_HTO
GSM9524225 Seq_HTO_6 Seq_HTO
GSM9524227 Seq_HTO_7 Seq_HTO
GSM9524229 Seq_HTO_8 Seq_HTO
GSM9524232 Seq_HTO_9 Seq_HTO
GSM9524234 Seq_HTO_10 Seq_HTO
GSM9524236 Seq_HTO_11 Seq_HTO
GSM9524238 Seq_HTO_12 Seq_HTO
GSM9524240 Seq_HTO_13 Seq_HTO
GSM9524242 Seq_HTO_14 Seq_HTO
GSM9524245 Seq_HTO_15 Seq_HTO
GSM9524247 Seq_HTO_16 Seq_HTO

+ 8 more — browse all 48 samples with per-sample file links →

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GSE253903 High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis [scRNA-seq] 12 samples shares atherosclerosis, scrna-seq
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