Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset
2011

Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset

Sample size: 1093 publication 10 minutes Evidence: moderate

Author Information

Author(s): Chibnik Lori B., Keenan Brendan T., Cui Jing, Liao Katherine P., Costenbader Karen H., Plenge Robert M., Karlson Elizabeth W.

Primary Institution: Brigham and Women's Hospital, Boston, Massachusetts, United States of America

Hypothesis

Can a genetic risk score predict the risk of different rheumatoid arthritis phenotypes and the age of symptom onset?

Conclusion

The study suggests that seronegative and seropositive/erosive rheumatoid arthritis have different genetic architectures.

Supporting Evidence

  • 58% of RA cases were seropositive.
  • 30% of RA cases had erosions.
  • 19% of RA cases were seropositive with erosions.
  • The highest genetic risk score group had a 7.6 times increased odds of seropositive, erosive RA.
  • Logistic regression was used to assess the relationship between genetic risk score and RA phenotypes.

Takeaway

Scientists looked at genes to see if they can tell who might get rheumatoid arthritis and when symptoms might start. They found that different types of the disease are linked to different genes.

Methodology

The study evaluated single nucleotide polymorphisms at 31 validated RA risk loci and 8 Human Leukocyte Antigen alleles among 542 Caucasian RA cases and 551 Caucasian controls using logistic regression.

Potential Biases

Potential misclassification bias due to the lack of systematic collection of outcome data after diagnosis.

Limitations

The study only tested anti-CCP status at one time point, which may lead to misclassification bias.

Participant Demographics

Participants were Caucasian women from the Nurses' Health Study and Nurses' Health Study II.

Statistical Information

P-Value

1.7×10−12

Confidence Interval

95% CI 1.9–4.7 for seropositive RA

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1371/journal.pone.0024380

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