Identification of a novel transcriptome signature for predicting the response to anti-TNF-α treatment in patients with rheumatoid arthritis
Authors' conclusion
We identified a transcriptomic signature that aids the prediction of the response to TNFi treatment in patients with RA.
Study context
- Population
- Patients with rheumatoid arthritis (RA) before initiation of tumour necrosis factor inhibitors (TNFi) therapy
- Participants
- 279 external validations
- Outcome
- Prediction of response to TNFi treatment (responders vs nonresponders)
Methodological detailsretrospective transcriptomic analysis, 2 public datasets (GSE138746 RNA-seq PBMC; GSE33377 whole-blood microarray), leave-one-out cross-validation, internal and external validation
- Retrospective transcriptomic analysis
- 2 public datasets (GSE138746 RNA-seq PBMC; GSE33377 whole-blood microarray)
- Leave-one-out cross-validation
- Internal and external validation
Performance
As reported in the abstract
Prediction of response to TNFi treatment
| Test or model | AUC (GSE33377) | AUC (internal validation, GSE138746) | AUC (external validation) |
|---|---|---|---|
| 7-gene signature | 0.84 | 0.89 | ≥ 0.85 |
7-gene signature
AUC (GSE33377)0.84
AUC (internal validation, GSE138746)0.89
AUC (external validation)≥ 0.85
Further findings
Differentially expressed genes, responders vs nonresponders (RNA-seq, GSE138746)
- Genes differentially expressed; none significant after Benjamini-Hochberg adjustment
- 53
18-gene signature, leave-one-out cross-validation predictive accuracy
- Predictive accuracy
- 88.75%
Original publication
Identification of a novel transcriptome signature for predicting the response to anti-TNF-α treatment in patients with rheumatoid arthritis. Ann Rheum Dis. Published 3 September 2025. doi:10.
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