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Mapping Endothelial-Macrophage Interactions in Diabetic Vasculature: Role of TREM2 in Vascular Inflammation and Ischemic Response [scRNA-Seq]

GSE293428 Homo sapiens (human) Single-cell RNA-seq 18 samples Submitted 2026/03/20 Platform GPL16791Platform GPL24676Platform GPL20795
At a glance

Single-cell RNA-seq · human · 18 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
18 samples: 7 conditions, mostly in duplicateGroups 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
Diabetes-induced TREM2-endothelial cell signaling impairs ischemic vascular repairScience translational medicine · 2026
Summary (written by the submitters)
Diabetes mellitus (DM) significantly accelerates vascular diseases like peripheral arterial disease (PAD). Endothelial cells (ECs) and macrophages (MΦs) singularly and synergistically are important contributors to DM-associated vascular dysfunction. Single-cell (sc) profiling technologies are revealing the true heterogeneity of ECs and MΦs, but how this cellular diversity translates to cell-cell interactions, and consequentially vascular function, remains unknown.
Read the full summary ↓
We leveraged scRNA sequencing and spatial transcriptome (ST) profiling to analyze human mesenteric arteries from non-diabetic (ND) and type 2 diabetic (T2D) donors. We generated a transcriptome and interactome map encompassing the major arterial cells and highlighted Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) as a top T2D-induced gene in mononuclear phagocytes (MPs), with concomitant increases of TREM2 ligands in ECs. We verified DM-associated TREM2 induction in cell and mouse models, and found that TREM2 inhibition decreases pro-inflammatory responses in MPs and ECs, as well as increases EC migration in vitro. Furthermore, TREM2 inhibition using a neutralizing antibody enhanced ischemic recovery and flow reperfusion in DM mice subjected to hindlimb ischemia, suggesting that TREM2 promotes ischemic injury in DM. Finally, in human PAD, co-existing DM was associated with greater expression of TREM2 and its interaction with ECs, with a further increase in ischemic tissue compared to patient-matched non-ischemic tissue. Collectively, our study presents the first atlas of human diabetic vessels with single cell and spatial resolution, and identifies TREM2-EC interaction as a key driver of diabetic vasculopathies, the targeting of which may offer an opportunity to ameliorate vascular dysfunction associated with DM-PAD.
Published in
Diabetes-induced TREM2-endothelial cell signaling impairs ischemic vascular repair
Malhi NK, Luo Y, Chen M et al. · Science translational medicine 2026 · PMID 42018669 · doi:10.1126/scitranslmed.adu3761
This dataset
Open GSE293428 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 GSE293428_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 PRJNA1244414 and SRA study SRP575493. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42018669) ↗
Study design
7 conditions, mostly in duplicate
Non-Diabetic mesenteric artery intima ×4 Diabetic mesenteric artery intima 4 ×3 Non-Diabetic mesenteric artery intima 1 ×2 Diabetic mesenteric artery intima 1 ×2 Diabetic mesenteric artery intima 2 ×2 Diabetic mesenteric artery intima ×2 Non-Diabetic mesenteric artery ×2 Diabetic mesenteric artery ×1

Supports a between-group comparison across 17 samples.

How we read this: 7 replicated groups read from 18 sample titles; they account for 17 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
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