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Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s disease

GSE268599 Homo sapiens (human) Single-nucleus RNA-seq 146 samples Submitted 2024/07/22 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 146 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
146 samples: 59 conditions, mostly in duplicateGroups 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
Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer's diseaseNature neuroscience · 2024
Summary (written by the submitters)
Astrocytes are crucial to brain homeostasis, yet their changes along the spatiotemporal progression of Alzheimer’s disease (AD) neuropathology remain largely unexplored. Here, we performed single- nucleus RNA-sequencing of 628,943 astrocytes from five brain regions representing the stereotypical progression of AD pathology, across 32 donors spanning the entire normal aging-to-severe AD continuum.
Read the full summary ↓
We discovered astrocyte gene expression trajectories that are differentially activated or suppressed at various regions and disease stages. We mapped out several unique astrocyte subclusters that exhibited varying responses to neuropathology across the AD-vulnerable neural network (spatial axis) or AD pathology stage (temporal axis). The proportion of homeostatic, intermediate, and reactive astrocytes changed solely along the spatial axis, whereas two other unique subclusters changed along the temporal axis. One of these, a trophic factor-rich subcluster, declined along pathology stage, whereas the other, defined by proteostasis and metabolic genes, increased in late-stage but unexpectedly returned to baseline levels in end-stage, suggesting exhaustion of response with chronic exposure to neuropathology. Our study underscores the complex and dynamic nature of astrocytic responses in AD and our findings are available at https://ad-progression-atlas.partners.org
Published in
Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer's disease
Serrano-Pozo A, Li H, Li Z et al. · Nature neuroscience 2024 · PMID 39528672 · doi:10.1038/s41593-024-01791-4
This dataset
Open GSE268599 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 GSE268599_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 PRJNA916657 and SRA study SRP415133. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39528672) ↗
Study design
59 conditions, mostly in duplicate
1906_V ×2 2021_BA ×2 2021_V ×2 2018_BA ×2 2018_V ×2 2057_V ×2 2132_V ×2 2132_BA ×2 +79 more

Supports a between-group comparison across 118 samples.

How we read this: 59 replicated groups read from 146 sample titles; they account for 118 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

+ 106 more — browse all 146 samples with per-sample file links →

Datasets on a similar topic

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