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Characterization of DNA methylation changes associated with lung and right ventricle dysfunction in pulmonary hypertension

GSE208592 Homo sapiens (human) DNA methylation 33 samples Submitted 2024/12/01 Platform GPL24676
At a glance

DNA methylation · human · 33 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
33 samples: 18 × Control_Lung vs 15 × PAH_LungGroups 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)
Pulmonary arterial hypertension (PAH) is a lethal vasculopathy associated with pulmonary arteries remodeling and right ventricle (RV) dysfunction. Epigenetic dysregulation, including altered DNA methylation, promotes PAH. However, the DNA methylation changes associated with PAH and their functional consequences on transcriptomic reprogramming remain unexplored in human PAH RV and lungs.
Read the full summary ↓
We conducted an exploratory study in human lung and RV samples to characterize the DNA methylome and transcriptomic changes associated with PAH in both organs. Impaired DNA methylation landscape observed in PAH lungs and RV correlates with adverse pulmonary vascular remodeling, RV fibrosis, and markers of disease severity (e.g. NT-proBNP). PAH differentially methylated genes and differentially expressed transcripts regulate biological functions related to inflammation, fibrosis, heart contraction, blood vessel development. Moreover, we observed substantial lung/RV transcriptomic and methylomic changes overlap in PAH. Thus, PAH is associated with specific DNA methylation changes associated with the disease severity.
This dataset
Open GSE208592 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 GSE208592_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA860188 and SRA study SRP387136. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 × Control_Lung vs 15 × PAH_Lung

Supports a between-group comparison across 33 samples.

How we read this: 2 replicated groups read from 33 sample titles; they account for 33 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
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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.