← BioTransfer GEO Dataset Finder
GEO series

Integrative Molecular Analyses of Inflammatory and Autoimmune Signals in Cardiac Sarcoidosis [snRNA-Seq]

GSE319770 Homo sapiens (human) Single-nucleus RNA-seq 41 samples Submitted 2026/05/24 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 41 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Homo sapiens (human)
Samples
41 samples: 33 distinct titles, 6 of them repeatedGroups 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
Integrative Molecular Analyses of Inflammatory and Autoimmune Signals in Cardiac SarcoidosisCirculation · 2026
Summary (written by the submitters)
BACKGROUND:Cardiac sarcoidosis (CS) is an enigmatic disorder characterized by unexplained patchy, sterile granulomas intermixed with preserved myocardium and fibrotic regions without granuloma. CS causes arrhythmias, sudden cardiac death, and heart failure. The mechanisms producing this remarkable histopathology and disease progression remain unexplained.
Read the full summary ↓
METHODS:Using comprehensive single-cell and spatial transcriptomic analyses, we characterized the cellular composition and gene expression in preserved, granulomatous, and fibrotic regions of human CS hearts. From unexpectedly identified clonally expanded cardiac B cells with rearranged immunoglobulin sequences, we reconstructed antibodies and screened libraries comprising the human peptidome or microbial and allergen peptides to define reactive epitopes in CS hearts. RESULTS:Cellular composition and gene expression differed substantially in CS tissues with preserved, granulomatous, or fibrotic histopathology. Cardiomyocytes upregulated arrhythmogenic and inflammasome transcripts associated with pyroptosis. Cardiomyocytes and fibroblasts activated chemoattractant cytokines that sustained myeloid and lymphoid infiltration. Granulomas contained abundant macrophages expressing modulators of cell–cell fusion, along with Th17-skewed T cells that upregulated B-cell–activating factor, thereby promoting antibody production. Fibrotic regions, without active granulomas, exhibited tertiary lymphoid structures, with clonal expansion of mature B and plasma cells. Reconstructed antibodies derived from expanded B-cell clones were inert to microbial and allergen peptides, but reacted to PPL (periplakin), a desmosome protein, and other peptides expressed on cardiac cells. CONCLUSIONS:Progressive inflammatory signals in CS are mediated by chemoattractant genes in cardiomyocytes and fibroblasts within preserved myocardium, cell–cell fusion modulators in activated macrophages within granulomatous regions, and tertiary lymphoid structures in fibrotic regions that produce patient-specific autoimmune antibodies. Identification of PPL as a CS autoantigen may account for shared clinical manifestations in CS and arrhythmic desmosomal cardiomyopathies. CS autoantigens may underlie enigmatic histopathologic findings, perpetuate disease, and contribute to adverse outcomes. Uncovering an intracardiac humoral autoimmune axis in CS provides specific therapeutic opportunities to limit granuloma formation and B-cell activation, which may reduce arrhythmogenicity and progressive dysfunction. Parallel analytic strategies have potential to define autoantigens in other enigmatic cardiac immune disorders.
Published in
Integrative Molecular Analyses of Inflammatory and Autoimmune Signals in Cardiac Sarcoidosis
Neyazi M, Venturini G, Brown KJ et al. · Circulation 2026 · PMID 42206386 · doi:10.1161/CIRCULATIONAHA.126.079304
This dataset
Open GSE319770 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 GSE319770_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 PRJNA1425070 and SRA study SRP677859. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42206386) ↗
Study design
33 distinct titles, 6 of them repeated
A0090_LV ×3 A0239_LV ×3 A0069_LV ×2 A0282_RV ×2 SS-1003_LV ×2 SS-1013_LV ×2

How we read this: Read from 41 sample titles: 33 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

+ 1 more — browse all 41 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.