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Chronic alcohol drinking compromises lung immunity by altering immunometabolism in both human and mouse lungs

GSE248233 Mus musculus (mouse) RNA-seq (gene expression) 42 samples Submitted 2024/07/22 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 42 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
Mus musculus (mouse)
Samples
42 samples: 42 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
Chronic Alcohol Intake Compromises Lung Immunity by Altering Immunometabolism in Humans and Mouse ModelsAmerican journal of respiratory cell and molecular biology · 2024
Summary (written by the submitters)
Heavy alcohol drinking dysregulates lung immunity and host defense, which makes individuals with AUD more susceptible to develop inflammatory condition in lungs with poor prognosis. Current study, we focused on exploring the effects of chronic alcohol consumption on lungs using NIAAA alcohol feeding model in mice with 10 days of a Lieber-DeCarli liquid diet containing 5% ethanol followed by a single ethanol binge (5 g/kg) and population based human lung transcriptome data from Genotype-Tissue Expression (GTEx) project consist of 328 alcohol drinkers and 110 non-drinkers.
Read the full summary ↓
Flow cytometry and transcriptomics analysis in mice lungs revealed that alcohol consumption dysregulates cellularity of immune cell levels and lung immunity. Transcriptomics analysis both in lungs and liver at 9-, 24- hours and 14 days post ethanol binge in mice uncovered that the lungs were more sensitive to alcohol effect to down-regulate pathways of immune system regulations than liver. Comparative data analysis of lung transcriptomes between mice and human subjects not only confirmed similar dysregulation on lung immunity but also provided evidence that immunometabolic changes are the central driver of alterations in lung transcriptome with down regulating immune pathways and upregulating metabolic pathways. Since the NIAAA model recapitulates multiple changes in the lung transcriptome that had been observed in human subjects with chronic alcohol drinking, this makes the mouse model suitable for experimental studies exploring role of alcohol drinking in lung health. Chronic alcohol drinking reduced mTOR signaling and cellularity of immune cells, which can be further attenuated by selective inhibition of mTOR. BCAA-mTOR signaling axis can be an upstream regulator of alcohol induced dysregulation in lung immunity
Published in
Chronic Alcohol Intake Compromises Lung Immunity by Altering Immunometabolism in Humans and Mouse Models
Pommerolle L, Arif M, Behee M et al. · American journal of respiratory cell and molecular biology 2024 · PMID 39024537 · doi:10.1165/rcmb.2024-0086OC
This dataset
Open GSE248233 in finder → Find more mouse 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 GSE248233_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 PRJNA1043069 and SRA study SRP472998. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39024537) ↗
Study design
42 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 42 sample titles: 42 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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