GEO series

Single Cell Landscape of Left Atria Reveals Amphiregulin and Insulin-like Growth Factor 1 as Surrogate Markers in Patients with Atrial Fibrillation.

GSE261170 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2024/06/01 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 15 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: 15 samples: 15 samples, each with a distinct title — no replicated groupsGroups 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: Left atrial single-cell transcriptomics reveals amphiregulin as a surrogate marker for atrial fibrillationCommunications biology · 2024

Summary (written by the submitters)

Atrial fibrillation (AF) is strongly associated with strokes, heart failure, and increased mortality. Inflammation plays a role in the pathophysiology of AF; however, how inflammation in AF is sustained and induces fibrosis is unclear. Therefore, this study aimed to identify the characteristic monocyte–macrophage heterogeneity and the cell–cell interactions between immune and non-immune cells at a single cell level in the left atrial (LA) tissues of patients with AF who underwent LA appendectomies.

Read the full summary ↓

Myeloid cells were divided into five macrophage clusters, TNF+, two IL1B+, TREM2+, LYVE1+ resident macrophages, three monocyte clusters, five dendritic cell clusters, neutrophils, and mast cells. The CellChat analysis revealed that IL1B+ macrophages send epidermal growth factor (EGF) signalling to fibroblasts and resident macrophages send IGF1 singalling to cardiomyocytes. When compared to openly published control samples, Amphiregulin (AREG) was the most upregulated gene in monocytes and monocyte-derived IL1B+ macrophages in the AF group. We also found that AREG levels in serum were higher in patients with AF than controls. EGF signalling from IL1B+ macrophages could be therapeutic targets for AF, and AREG could be a functional biomarker for AF.

Published in

Left atrial single-cell transcriptomics reveals amphiregulin as a surrogate marker for atrial fibrillation

Suzuki Y, Emoto T, Sato S et al. · Communications biology 2024 · PMID 39622943 · doi:10.1038/s42003-024-07308-w

This dataset

Open GSE261170 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 GSE261170_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 PRJNA1085681 and SRA study SRP494138. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39622943) ↗

Study design

15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 distinct titles with little repetition. 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

GSM8136885 sample1and2 early atrial fibrillation
GSM8136886 sample3and4 permanent atrial fibrillation
GSM8136887 sample5 permanent atrial fibrillation
GSM8136888 sample6 early atrial fibrillation
GSM8136889 sample7 early atrial fibrillation
GSM8136890 sample8 early atrial fibrillation
GSM8136891 sample9blood
GSM8136892 sample9endocardium
GSM8136893 sample9epicardium
GSM8136894 sample10blood
GSM8136895 sample10endocardium
GSM8136896 sample10epicardium
GSM8136897 sample11 permanent atrial fibrillation
GSM8136898 sample12 permanent atrial fibrillation
GSM8136899 sample13 permanent atrial fibrillation

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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.