← BioTransfer GEO Dataset Finder
GEO series

Age-related Increase of CD38 Directs Osteoclastogenic Potential of Monocytic Myeloid-Derived Suppressor Cells through Mitochondrial Dysfunction

GSE252129 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/09/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
Mus musculus (mouse)
Samples
12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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
Age-related increase of CD38 directs osteoclastogenic potential of monocytic myeloid-derived suppressor cells through mitochondrial dysfunction in male miceAging cell · 2024
Summary (written by the submitters)
An aged immune system undergoes substantial changes where myelopoiesis dominates within the bone marrow. Monocytic-MDSCs (M-MDSCs) have been found to play an important role in osteoclastogenesis and bone resorption. In this study, we sought to provide a more comprehensive understanding of the osteoclastogenic potential of bone marrow M-MDSCs during normal aging through transcriptomic and metabolic changes.
Read the full summary ↓
Using young mature and aged mice, detailed immunophenotypic analyses of myeloid cells revealed that the M-MDSCs were not increased in bone marrow, however M-MDSCS were significantly expanded in peripheral tissues. Although aged mice exhibited a similar number of M-MDSCs in bone marrow, these M-MDSCs had significantly higher osteoclastogenic potential and greater bone resorption capacity. Intriguingly, osteoclast progenitors from aged bone marrow M-MDSCs exhibited greater mitochondrial respiration rate and glucose metabolism. Further, transcriptomic analyses revealed the upregulation of mitochondrial oxidative phosphorylation and glucose metabolism genes. Interestingly, there was a 3-fold increase in Cd38 mRNA gene expression, consistent with the Mouse Aging Cell Atlas transcriptomic database. CD38 regulates NAD+ availability, and 78c, a small molecule inhibitor of CD38, reduced the mitochondrial oxygen consumption rate and glucose metabolism and inhibited the osteoclastogenic potential of aged mice bone marrow-derived M-MDSCs. These results indicate that the age-related increase in Cd38 expression in M-MDSCs bias the transcriptome of M-MDSCs towards osteoclastogenesis. This enhanced understanding of the mechanistic underpinnings of M-MDSCs and their osteoclastogenesis during aging could lead to new therapeutic approaches for age-related bone loss and promote healthy aging.
Published in
Age-related increase of CD38 directs osteoclastogenic potential of monocytic myeloid-derived suppressor cells through mitochondrial dysfunction in male mice
Thiyagarajan R, Zhang L, Glover OD et al. · Aging cell 2024 · PMID 39180173 · doi:10.1111/acel.14298
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 GSE252129_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 PRJNA1057839 and SRA study SRP480335. Searching any of these in the dataset finder brings you back here.

Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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
Datasets on a similar topic

Search all mouse 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.