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Inhibition of discoidin domain receptor (DDR)-1 with nilotinib alters CSF miRNAs and is associated with reduced inflammation and vascular fibrosis in Alzheimer's Disease

GSE279869 Homo sapiens (human) RNA-seq (gene expression) 67 samples Submitted 2024/10/24 Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 67 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
67 samples: 22 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
Inhibition of discoidin domain receptor (DDR)-1 with nilotinib alters CSF miRNAs and is associated with reduced inflammation and vascular fibrosis in Alzheimer's diseaseJournal of neuroinflammation · 2023
Summary (written by the submitters)
Discoidin Domain Receptor (DDR)-1 is activated by collagen. Nilotinib is a tyrosine kinase inhibitor that is FDAapproved for leukemia and potently inhibits DDR-1. Individuals diagnosed with mild–moderate Alzheimer’s disease (AD) treated with nilotinib (versus placebo) for 12 months showed reduction of amyloid plaque and cerebrospinal fluid (CSF) amyloid, and attenuation of hippocampal volume loss. However, the mechanisms are unclear. Here, we explored unbiased next generation whole genome miRNA sequencing from AD patients CSF
Published in
Inhibition of discoidin domain receptor (DDR)-1 with nilotinib alters CSF miRNAs and is associated with reduced inflammation and vascular fibrosis in Alzheimer's disease
Stevenson M, Varghese R, Hebron ML et al. · Journal of neuroinflammation 2023 · PMID 37194065 · doi:10.1186/s12974-023-02802-0
This dataset
Open GSE279869 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 GSE279869_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 PRJNA1174807 and SRA study SRP539439. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 37194065) ↗
Study design
22 conditions, mostly in duplicate
6 ×2 7 ×2 8 ×2 9 ×2 10 ×2 11 ×2 13 ×2 14 ×2 +37 more

Supports a between-group comparison across 44 samples.

How we read this: 22 replicated groups read from 67 sample titles; they account for 44 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

+ 27 more — browse all 67 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.