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MEF2C controls lysosomal and lipid clearance programs linked to Alzheimer’s disease risk in macrophagesm [scRNAseq_WTC11_iMGL_ReN]

GSE323982 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2026/08/06 Platform GPL34281
At a glance

Single-cell RNA-seq · human · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
16 samples: 14 distinct titles, 2 of them repeatedGroups 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
MEF2C controls lysosomal and lipid clearance programs linked to Alzheimer's disease risk in macrophagesResearch square · 2026
Summary (written by the submitters)
Risk alleles for late-onset Alzheimer’s disease (AD) are enriched in myeloid cis-regulatory elements, implicating myeloid gene-regulatory networks in disease susceptibility. A conserved lipid-associated transcriptional signature—spanning disease-associated microglia and peripheral lipid-associated macrophages (DLAM)—emerges across neurodegenerative and metabolic diseases, yet the transcriptional regulators of this gene expression program remain incompletely defined.
Read the full summary ↓
Here, we show that MEF2C—a candidate AD risk gene—is a master DLAM regulator. Using MEF2C knockout and knockdown in human iPSC-derived microglia and macrophages, we found that total or partial MEF2C loss is sufficient to induce DLAM-associated transcriptional, epigenomic, and functional remodeling, including enhanced lysosomal activity and cholesterol efflux. Integration of chromatin accessibility and regulatory epigenetic profiles with functionally informed fine-mapping linked AD causal variants in other loci to MEF2C-regulated regulatory regions and downstream risk genes. In a triculture model of AD, microglial MEF2C loss is associated with an increased DLAM population and a reduced Aβ42/40 ratio, supporting context-dependent reprogramming of microglia as a mechanism to modulate AD-relevant pathology.
Published in
MEF2C controls lysosomal and lipid clearance programs linked to Alzheimer's disease risk in macrophages
Podlesny-Drabiniok A, Kim JJ, Bezemer LJ et al. · Research square 2026 · PMID 42094058 · doi:10.21203/rs.3.rs-9164252/v1
This dataset
Open GSE323982 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 GSE323982_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1432879 and SRA study SRP681353. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42094058) ↗
Study design
14 distinct titles, 2 of them repeated
MEF2C-KO, CTRL ReN, differentiation 1, clone D ×2 MEF2C-KO, AD ReN, differentiation 1, clone D ×2

How we read this: Read from 16 sample titles: 14 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
Datasets on a similar topic

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