Abstract P107: Serum Urate Trajectories in Young Adulthood and Incident Cardiovascular Disease Events By Middle Age; The Coronary Artery Risk Development in Young Adults (cardia) Study

Introduction: Higher levels of serum urate (UA) obtained on a single occasion have been shown to be associated with a higher risk of cardiovascular disease (CVD) events among middle-aged or older adults. However, little is known regarding UA trajectory patterns during young adulthood and their associations with CVD outcomes by middle age. Hypothesis: We hypothesize that higher UA trajectory is associated with a higher risk for CVD events compared to lower UA trajectories. Methods: We included data from 4845 CARDIA Study participants (mean age at the Year 20 exam 44.8±3.7 (37-55) years; 50.8% African American; 55.6% female). Sex-specific UA trajectories were assessed using group-based trajectory modeling (PROC TRAJ in SAS version 9.4) based on UA levels obtained at baseline (Year 0) and 10, 15, 20 years later. Covariates included age, sex, race, and clinical characteristics at Year 20 (body mass index, diabetes and creatinine). We estimated hazard ratios (HR) for CVD events (coronary heart disease, heart failure, and stroke) from Year 20 (2005-06) through 2017. Results: We identified 3 UA trajectories in men and 3 similar but lower UA trajectories in women, characterized by low-increasing (men: 30%; n=652, mean UA 5.1; women 43%, n=1191, mean UA 3.9), moderate-increasing (men: 52%; n=1290, mean UA 6.4; women 45%, n=1284, mean UA 5.0), and high-increasing UA (men: 17%; n=377, mean UA 8.0; women 12%, n=305, mean UA 6.4) (Figure 1). Sex-specific trajectories were pooled. Over a median follow-up of 10.9 years, 203 incident CVD events occurred. The adjusted HRs for CVD events were 0.98 (95%CI, 0.66-1.45) for the pooled moderate-increasing group and 1.77 (95%CI, 1.10-2.84) for the pooled high-increasing group compared to the pooled low-increasing group. Conclusions: High-increasing UA trajectory during young adulthood was associated with an greater risk of CVD events by middle age. Modeling UA trajectories may help identify young adults at higher risk for CVD events.