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Plasma multi-omics identify early pathogenesis and biomarkers of SCD post-AMI

GSE221740 Homo sapiens (human) RNA-seq (gene expression) 106 samples Submitted 2024/12/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 106 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
106 samples: 53 × SCD post AMI, D vs 53 × Survivor post AMI, SGroups 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
S100a9 lactylation triggers neutrophil trafficking and cardiac inflammation in myocardial ischemia/reperfusion injuryThe Journal of clinical investigation · 2025
Summary (written by the submitters)
Early identification and treatment of Sudden Cardiac Death (SCD) post-myocardial infarction (MI) are currently limited by unclear warning indicators and elusive pathogenesis. Here, we constructed a comprehensive multi-omics blood atlas in the acute phase of AMI from 55 pairs of SCD patients and matched survivors, confirmed immune dysregulation and metabolic disorders as the biological hubs leading to post-MI SCD.
Read the full summary ↓
Targeted proteome quantification identified a TOP4 protein-based biomarker panel, which were validated by internal and external cohorts, and confirmed a superior early prediction power of SCD to traditional clinical risk models. Further interventions targeting complement factor D (CFD) suggested a potential therapeutic strategy for high-risk MI. Our study provided valuable knowledge about the molecular changes and pathogenesis of SCD, shed light on accurate risk stratification and potential therapeutic targets in high SCD-risk MI.
Published in
S100a9 lactylation triggers neutrophil trafficking and cardiac inflammation in myocardial ischemia/reperfusion injury
Wang X, Yan X, Mang G et al. · The Journal of clinical investigation 2025 · PMID 41066195 · doi:10.1172/JCI194664
This dataset
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.

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 GSE221740_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA915943 and SRA study SRP414823. Searching any of these in the dataset finder brings you back here.

Study design
53 × SCD post AMI, D vs 53 × Survivor post AMI, S

Supports a between-group comparison across 106 samples.

How we read this: 2 replicated groups read from 106 sample titles; they account for 106 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

+ 66 more — browse all 106 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.