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Does Adding Single-Nucleotide Polymorphisms to Risk Algorithms Improve Cardiovascular Disease Risk Prediction in

Rabia Agca1, Calin D Popa2, Martijn W Heymans3

  • 1Amsterdam Rheumatology and Immunology Center, Amsterdam, the Netherlands.

Arthritis Care & Research
|June 26, 2024
PubMed
Summary
This summary is machine-generated.

Single-nucleotide polymorphisms (SNPs) show association with cardiovascular disease (CVD) in rheumatoid arthritis (RA) patients. While adding SNPs slightly improved risk prediction models, their clinical relevance requires further investigation in larger studies.

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Area of Science:

  • Rheumatology
  • Cardiovascular Medicine
  • Genetics

Background:

  • Current cardiovascular disease (CVD) risk algorithms lack accuracy for rheumatoid arthritis (RA) patients.
  • Single-nucleotide polymorphisms (SNPs) are implicated in CVD in the general population.
  • Investigating SNPs' role in RA-associated CVD is crucial.

Purpose of the Study:

  • To determine if specific SNPs associated with CVD in the general population are also linked to CVD in RA patients.
  • To assess if incorporating these SNPs can enhance CVD risk prediction models for RA.

Main Methods:

  • Genotyping of 60 SNPs in 353 RA patients.
  • Logistic and Cox regression analyses to identify SNPs associated with new CVD events.
  • Development and validation of clinical and SNP-inclusive risk prediction models.

Main Results:

  • Four SNPs (rs3184504, rs4773144, rs12190287, rs445925) were significantly associated with new CVD.
  • A clinical model achieved an AUC of 0.74 (internal validation 0.76).
  • An SNP-inclusive model showed a marginal improvement (AUC 0.77), but lacked external validation fit.

Conclusions:

  • Several SNPs demonstrate association with CVD in RA.
  • The addition of SNPs offers a slight improvement in risk prediction, but clinical utility remains uncertain.
  • Larger studies are necessary to definitively establish the value of SNPs in RA CVD risk algorithms.