GEO series

Dominant intragraft plasma cells targeting bilirubin implicate local heme catabolism in human cardiac allograft vasculopathy

GSE293483 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2025/10/26 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. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
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: Dominant intragraft plasma cells targeting bilirubin implicate local heme catabolism in human cardiac allograft vasculopathyThe Journal of clinical investigation · 2026

Summary (written by the submitters)

Cardiac allograft vasculopathy (CAV) is invariably associated with immune infiltrates around affected coronary arteries, including antibody-producing plasma cells (PC). We used single-cell-RNA-sequencing and IGHV profiling to characterize these infiltrating PC. We then generated 37 recombinant monoclonal antibodies (mAb) using rearranged immunoglobulin gene sequences from dominant intragraft PC clones as well as 24 control mab from peripheral blood PC.

Read the full summary ↓

Unexpectedly, a majority (21/37) of mAb derived from intragraft PC, but none of the control mAb derived from blood PC, reacted to bilirubin, a by-product of heme degradation. Furthermore, we observed the deposition of bilirubin within lymphocytic aggregates of cardiac grafts with CAV but not in healthy heart tissue. Bilirubin also accumulated in the cytoplasm and the nuclei of smooth muscle cells in the tunica media of coronary arteries with CAV lesions. Lastly, expression of heme-oxygenase-1 and biliverdin reductases in graft-infiltrating macrophages as well as presence of Fe2+ ion in the media of arteries with hyperplasia further supported the implication of heme catabolism in CAV. Collectively, our findings suggest a key role for bilirubin in CAV. The enrichment of PC clones reactive to this metabolite within graft infiltrates indicates that it acts as a prominent target of local antibody responses.

Published in

Dominant intragraft plasma cells targeting bilirubin implicate local heme catabolism in human cardiac allograft vasculopathy

See SB, Aguiar T, Dietzel M et al. · The Journal of clinical investigation 2026 · PMID 41289018 · doi:10.1172/JCI194138

This dataset

Open GSE293483 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 GSE293483_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 PRJNA1244783 and SRA study SRP575819. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41289018) ↗

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

GSM8883212 Explant 2
GSM8883213 Explant 2 V(D)J sequencing
GSM8883214 Explant 3 all cells
GSM8883215 Explant 3 all cells for V(D)J sequencing
GSM8883216 Explant 3 CD45+ enriched cells
GSM8883217 Explant 3 CD45+ enriched cells for V(D)J sequencing
GSM8883218 Explant 4 all cells
GSM8883219 Explant 4 CD45+ enriched cells
GSM8883220 Explant 4 CD45+ enriched cells for V(D)J sequencing
GSM8883221 Explant 5 all cells
GSM8883222 Explant 5 CD45+ enriched cells
GSM8883223 Explant 5 CD45+ enriched cells for V(D)J sequencing
GSM8883224 Explant 1 all cells
GSM8883225 Explant 1 CD45+ enriched cells
GSM8883226 Explant 1 CD45+ enriched cells V(D)J sequencing

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