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Identification of Aging-Related Signature Genes in Temporomandibular Joint Degeneration Based on Bioinformatics

GSE315467 Mus musculus (mouse) RNA-seq (gene expression) 13 samples Submitted 2026/04/26 Platform GPL23479
At a glance

RNA-seq (gene expression) · mouse · 13 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
13 samples: 7 × mandibular condylar cartilage, young mice(2 months) vs 6 × mandibular condylar cartilage, aged mice(18 months)Groups 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)
Background: Temporomandibular joint (TMJ) degenerative diseases are increasingly affecting elderly populations, with aging being a significant risk factor driving the TMJ changes. This study aims to explore the shared characteristics between aging and TMJ degenerative diseases at the tissue level, and to identify aging-related signature genes in TMJ degenerations using bioinformatics approaches.
Read the full summary ↓
Methods: Young (2 months of age, n=7) and aged (18 months of age, n=6) mice’s condyles were used to construct an aging dataset. Overlapping genes were selected from differentially expressed genes in the TMJOA dataset, aging dataset and mechanical stimulation dataset. Temporomandibular joint osteoarthritis-associated and aging-related differentially expressed genes (TMJOA-ARDEGs) were identified through Weighted gene co-expression network analysis. Functional enrichment analysis and Protein-Protein Interaction networks were employed. Machine learning was applied to select Hub temporomandibular joint osteoarthritis-associated and aging-related differentially expressed genes (Hub TMJOA-ARDEGs). An age-related TMJOA mouse model (18 months of age) was established and grouped based on the micro-CT and the modified Mankin scores. The expression changes of key Hub TMJOA-ARDEGs were verified by immunohistochemical staining. The Mann-Whitney U test was used in non-normally distributed data, presented as [median (interquartile range)]. Results: Fifty-two TMJOA-ARDEGs were identified, with functional enrichment analysis revealed that these genes participate in circadian rhythm and apoptosis. Eight Hub TMJOA-ARDEGs were identified, ANK1, MELTF, FERMT3, MDFI, CXCL14, EPHA3, SMOC2 and NR1D1. Based on the micro-CT, 12 TMJs of aged mice were divided into the TMJOA group (n=6) and the healthy group (n=6). Micro-CT revealed bone resorption in the TMJOA group compared to the healthy group, with a decrease in BV/TV (p<0.05) and an increase in Tb.Sp (p<0.05). The modified Mankin scores showed that the TMJOA group had a score of 5.61 (2.28), higher than the healthy group's score of 0.83 (1.28), p<0.01. These results confirm the validity of the model grouping. Among the Hub TMJOA-ARDEGs, NR1D1 is a key gene involved in regulating circadian rhythm. In immunohistochemical staining, the expression level of NR1D1 showed significantly elevated expression in osteoarthritis mice (p<0.01). Conclusion: NR1D1, a negative feedback regulator in the circadian rhythm loop, is a characteristic gene associated with both aging and TMJ degenerative diseases.
This dataset
Open GSE315467 in finder → Find more mouse 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 GSE315467_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 PRJNA1397197 and SRA study SRP659382. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 × mandibular condylar cartilage, young mice(2 months) vs 6 × mandibular condylar cartilage, aged mice(18 months)

Supports a between-group comparison across 13 samples.

How we read this: 2 replicated groups read from 13 sample titles; they account for 13 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
Datasets on a similar topic

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