Identifying the strongest novel gene-respiratory disease interactions for rheumatoid arthritis risk.

OBJECTIVE

We aimed to identify the strongest individual gene-respiratory interactions for rheumatoid arthritis (RA) risk.

METHODS

This case-control study used the Mayo Clinic (MC) and Mass General Brigham (MGB) biobanks for discovery and validation, respectively. We matched criteria-confirmed incident RA cases to four non-RA controls on age, sex, and duration electronic health record (EHR) history. Genetic exposures included known RA risk alleles. We identified respiratory diseases by codes and defined "respiratory burden" as the total number of respiratory codes divided by EHR duration before index date of RA. Using logistic regression models adjusting for potential confounders, we estimated odds ratios (OR) with 95% confidence intervals (CI) for the interactions between genetic and respiratory exposures for RA risk.

RESULTS

We identified 1,125 incident RA cases and 4,495 non-RA controls (mean age 64 years, 70% female in MC; 54 years, 76% female in MGB). In MC, both interstitial lung disease (OR 1.55, 95% CI 1.00-2.40) and overall respiratory burden (OR 1.67, 95% CI 1.30-2.15) were associated with incident RA. Four novel gene-respiratory interactions validated in MGB including CD83/RNF182 (rs12530098)-acute pharyngitis for seronegative RA (OR 4.06 [95% CI 1.61-10.3] MC; 3.68 [95% CI 1.42-9.56] MGB) and JARID2 (rs113532504)-asthma for seropositive RA (OR 2.66 [95% CI 1.30-5.44] MC; 1.93 [95% CI 1.20-3.08] MGB). The CD83/RNF182-acute pharyngitis interaction exhibited the strongest dose-response association (OR 8.54 [95% CI 1.59-45.9] for highest respiratory burden).

CONCLUSION

This study identified novel respiratory risk factors and gene-respiratory endotypes for RA, which may be useful for RA prevention, diagnosis, and treatment.