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Loss of age-associated increase in m6A-modified RNA contributes to GABAergic dysregulation in Alzheimer’s disease

GSE297551 Homo sapiens (human) RNA-seq (gene expression) 60 samples Submitted 2025/05/20 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 60 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
60 samples
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)
Dysregulated RNA metabolism is a significant feature of Alzheimer’s disease (AD), yet how post-transcriptional RNA modifications like N6-methyladenosine (m6A) are altered in AD is unknown. Here, we performed deamination adjacent to RNA modification targets (DART-seq) on human dorsolateral prefrontal cortices to assess changes in m6A with nucleotide resolution.
Read the full summary ↓
In non-AD brains, m6A sites increased with age, predominantly within the 3′UTR of transcripts encoding tripartite synapse proteins. In contrast, AD brains lost the age-associated m6A site increase and exhibited global hypomethylation of transcripts, including MAPT and APP. Hypomethylated genes involved with GABAergic signaling, glutamate transport, and ubiquitin-mediated proteolysis exhibited reduced expression, connecting m6A to synaptic excitotoxicity and disrupted proteostasis in AD. Site-specific m6A levels were linked with GABRA1 expression and protein levels, but this relationship was abolished in AD. Our findings provide insight into post-transcriptional mechanisms of dysregulated RNA metabolism in AD that are related to aging and GABAergic regulation.
This dataset
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.

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 GSE297551_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1265180 and SRA study SRP586355. Searching any of these in the dataset finder brings you back here.

Samples in this study

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