Lupus & antiphospholipid syndrome
Multiple polygenic risk scores can improve the prediction of systemic lupus erythematosus in Taiwan
Authors' conclusion
The use of PRSs to predict SLE enables the identification of high-risk patients before abnormal laboratory data were obtained or symptoms were manifested.
Study context
- Population
- Patients with SLE and controls from China Medical University Hospital in Taiwan
- Participants
- 2,429 vs 48,580
- Comparison
- SLE vs controls
- SLEn = 2,429
- Controlsn = 48,580reference
- Outcome
- Diagnostic accuracy of polygenic risk score (PRS) models for SLE
Methodological detailssingle-centre, polygenic risk score analysis, Youden Index cut-off points
- Single-centre
- Polygenic risk score analysis
- Youden Index cut-off points
Main finding
As reported in the abstract
Combined PRSs for SLE, ANA, dsDNA and Sm, prediction of SLE
AUC at optimal cut-off points
0.64
Observational data: associations, not effects.
Further findings
Novel genes associated with SLE in Taiwan (genome-wide association study (GWAS))
- Some novel genes, e.g. RCC1L and EGLN3, associated with SLE in Taiwan
Human leucocyte antigen (HLA) haplotypes in SLE
- HLA-DQA1*01:01 and HLA-DQB1*05:01 carriers at higher risk of being classified into the SLE group
Original publication
Multiple polygenic risk scores can improve the prediction of systemic lupus erythematosus in Taiwan. Lupus Sci Med. Published 9 May 2024. doi:10.
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