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Differential Roles of Astrocytic CSF1 in Alzheimer's Disease and Cerebral Amyloid Angiopathy: Insights from Transcriptomic Analysis

GSE278723 Homo sapiens (human) RNA-seq (gene expression) 248 samples Submitted 2024/12/15 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 248 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
248 samples: 50 conditions, mostly with about 4 replicates eachGroups 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
Differential Roles of Astrocytic CSF1 in Alzheimer's Disease and Cerebral Amyloid Angiopathy: Insights from Transcriptomic AnalysisAging and disease · 2024
Summary (written by the submitters)
Alzheimer's disease (AD) and cerebral amyloid angiopathy (CAA) are neurodegenerative disorders characterized by the pathological deposition of amyloid-beta (Aβ) in the brain. Although both conditions share common pathogenic pathways, they exhibit distinct cellular manifestations and disease progression. Our study focused on the differential expression and role of astrocytic colony-stimulating factor 1 (CSF1) in these diseases.
Read the full summary ↓
Using transcriptomic analysis of 248 brain tissue samples from the hippocampal-entorhinal system of 50 individuals, we identified a significant increase in CSF1 expression in the CA4 subfield of AD patients compared to a marked decrease in CAA. Functional investigations revealed that astrocytes with elevated CSF1 levels displayed neurotoxicity associated with AD-like pathology, whereas reduced CSF1 expression in astrocytes was linked to vascular damage typical of CAA. These findings suggest that CSF1 plays divergent roles in AD and CAA, contributing to their distinct pathological profiles. Our study highlights the potential of targeting astrocytic CSF1 expression as a differential diagnostic marker and therapeutic approach in managing these overlapping yet distinct neurological conditions.
Published in
Differential Roles of Astrocytic CSF1 in Alzheimer's Disease and Cerebral Amyloid Angiopathy: Insights from Transcriptomic Analysis
Li C, Chen Y, Luo S et al. · Aging and disease 2024 · PMID 39571157 · doi:10.14336/AD.2024.10530
This dataset
Open GSE278723 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 GSE278723_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 PRJNA1168520 and SRA study SRP536444. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39571157) ↗
Study design
50 conditions, mostly with about 4 replicates each
01CA ×4 02CA ×4 04CA ×4 05CA ×4 06CA ×4 07CA ×4 08CA ×4 09CA ×4 +92 more

Supports a between-group comparison across 198 samples.

How we read this: 50 replicated groups read from 248 sample titles; they account for 198 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

+ 208 more — browse all 248 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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