← BioTransfer GEO Dataset Finder
GEO series

Exploring the biological basis for the identification of different syndromes in ischemic heart failure based on joint multi-omics analysis

GSE303117 Homo sapiens (human) RNA-seq (gene expression) 129 samples Submitted 2025/08/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 129 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
129 samples: 44 × QDBS vs 33 × YDBSF vs 30 × YDBS vs 22 × HPGroups 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.
Summary (written by the submitters)
IHF is a major chronic disease that seriously threatens human health. Qi deficiency and blood stasis syndrome (QDBS), Yang deficiency with blood stasis syndrome (YDBS) and Yang deficiency and blood stasis with fluid retention syndrome (YDBSFR) are the basic syndromes of IHF in Chinese medicine. This study aims to explore the biological basis of the three IHF syndromes through integrated multi-omics research.
Read the full summary ↓
We analyzed and integrated transcriptomic, proteomic, and targeted metabolomic data from IHF patients and healthy persons to obtain the key biomarkers and enriched pathways of QDBS, YDBS and YDBSFR(Registration No.: ChiCTR2200058314). These biomarkers were combined with clinical indicators to construct the "Disease-Syndromes-Clinical phenotypes-Biomarkers-Pathways" network, and the obtained differential genes and proteins were externally validated. The potential biomarkers for QDBS included SDHD, IL10, ACTG1, VWF, MDH2, COX5A, Valeric acid, Succinic Acid and L-Histidine, which were predominantly enriched in TCA cycle, oxidative phosphorylation, platelet activation, and neutrophil extracellular trap formation pathways, demonstrating associations with energy metabolism, coagulation system, and immune-inflammatory responses.YDBS potential biomarkers included TSHR, PRKG1, ATP1A2, GNAI2, APOA2, PLTP, 3-Hydroxybutyrate, Hexadecanoic acid and Palmitelaidic acid, and the combined pathways were mainly enriched in thyroid hormone synthesis, regulation of lipolysis in adipocytes, cholesterol metabolism and PPAR signaling pathways, correlating with hormonal regulation and lipid metabolism. The potential biomarkers of YDBSFR were CNGB1, KCNMA1, PIK3R2, HSPA8, C3, FH, Oxamic acid, N-Acetyl-L-alanine, 4-Hydroxyhippuric acid, and the combined pathways were mainly enriched in aldosterone-regulated sodium reabsorption, cGMP-PKG signaling pathway, neutrophil extracellular trap formation and TCA cycle signaling pathways, which are related to hormone regulation, signal transduction, immune-inflammatory response and energy metabolism. Platelet activation was involved in the whole process of IHF. External validation demonstrated the above core targets. This study investigated the biological basis of QDBS, YDBS and YDBSFR in IHF from a modern biomedical perspective, providing references for the objective research of TCM syndrome differentiation.
This dataset
Open GSE303117 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 GSE303117_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: 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 PRJNA1294199 and SRA study SRP602560. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
44 × QDBS vs 33 × YDBSF vs 30 × YDBS vs 22 × HP

Supports a between-group comparison across 129 samples.

How we read this: 4 replicated groups read from 129 sample titles; they account for 129 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

+ 89 more — browse all 129 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.