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LPS stimulation reveals male and female dimorphism in human iPSC-derived macrophages

GSE328566 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/08/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 3 × Control Male vs 3 × LPS Male vs 3 × Control Female vs 3 × LPS FemaleGroups 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)
Clinical disparities in the inflammatory responses between males and females have been reported for decades, revealing sex-biased disease severity and patient outcomes. However, the underlying mechanisms driving these differences are understudied and poorly understood, despite the growing potential for improved diagnoses and treatment strategies.
Read the full summary ↓
In this study, we used male and female iPSC-derived macrophages to identify transcriptomic changes in response to the common bacterial antigen lipopolysaccharide (LPS). Bulk RNA sequencing identified 67 genes differentially expressed between male and female macrophages in the absence of inflammation, the majority of which mapped to the sex chromosomes. This sexual dimorphism was amplified by LPS stimulation, with genes predominantly located on autosomes, leading to divergent patterns in secreted protein production that were consistent with clinical findings following LPS exposure. Although future validation with a larger patient cohort is needed, these data collectively suggest that iPSC-derived macrophages can serve as a meaningful tool for understanding and improving treatment of sex-biased pathophysiological conditions.
This dataset
Open GSE328566 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 GSE328566_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 PRJNA1455650 and SRA study SRP693354. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Control Male vs 3 × LPS Male vs 3 × Control Female vs 3 × LPS Female

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 24 sample titles; they account for 12 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
Datasets on a similar topic

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