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Temporal changes in metabolism guide oligodendrocyte precursor cell dynamics in aging and multiple sclerosis [BulkRNAseq]

GSE330029 Homo sapiens (human) RNA-seq (gene expression) 108 samples Submitted 2026/08/07 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 108 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
108 samples: 36 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
Impaired oligodendrocyte precursor cell (OPC) differentiation limits myelin renewal in aging and contributes to multiple sclerosis (MS) progression. How aging drives OPC deficits remains incompletely understood. We find dysregulation of genes associated with the circadian clock, including Bmal1, and metabolism in aged compared with young OPCs.
Read the full summary ↓
Targeted loss of Bmal1 in OPCs drives metabolic dysfunction, leading to cellular senescence and impaired dynamics. OPC proliferation and differentiation occur at different rates throughout the day in young adult mice and become disrupted with aging. Chronotherapeutic targeting of BMAL1-controlled sirtuin signaling restores Bmal1-disrupted OPC dynamics after demyelination via sirtuin 2 (Sirt2)-dependent mechanisms. Induced pluripotent stem cell (iPSC)-derived OPCs from MS patients and MS lesion oligodendroglia recapitulate BMAL1 and SIRT2 disruptions. These findings establish BMAL1 as a key regulator of OPC energy metabolism, sirtuin homeostasis, and senescence. We anticipate that this work will provide a foundation for future studies investigating the interconnected roles of aging, circadian disruption, and myelin biology.
This dataset
Open GSE330029 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 GSE330029_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 PRJNA1462594 and SRA study SRP697879. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
36 conditions, mostly in triplicate
iPSC-derived OPCs, control_2, CT24, differtia… ×3 iPSC-derived OPCs, control_3, CT24, differtia… ×3 iPSC-derived OPCs, RRMS_1, CT24, differtiation ×3 iPSC-derived OPCs, RRMS_3, CT24, differtiation ×3 iPSC-derived OPCs, SPMS_1, CT24, differtiation ×3 iPSC-derived OPCs, SPMS_2, CT24, differtiation ×3 iPSC-derived OPCs, SPMS_3, CT24, differtiation ×3 iPSC-derived OPCs, control_2, CT30, differtia… ×3 +37 more

Supports a between-group comparison across 99 samples.

How we read this: 36 replicated groups read from 108 sample titles; they account for 99 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

+ 68 more — browse all 108 samples with per-sample file links →

Datasets on a similar topic

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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.