Abstract

Uric acid (UA) is a biomarker of inflammation that has been linked to obesity, hypertension, metabolic syndrome (MetS) and other factors associated with cardiometabolic risk (CMR). UA levels are often elevated in minority populations and tend to increase in response to poor lifestyle behaviors (i.e diet, inactivity, sleep). Multiple definitions exist for MetS—some of which include UA—but it is really the clustering of CMR factors in adolescence that is crucial for identification of disease risk and prevention. However, little is known about the relation between UA across the CMR spectrum in adolescents. PURPOSE: To investigate the relations between CMR classification, sex, physical activity, and sleep on UA among adolescents. METHODS: At age 16, subjects [Caucasian=45.9%; Male: N=47, BMI=24.6±6.7; Female: N=67, BMI=23.9±9.3] came to the lab for a fasted blood draw, anthropometric measures and assessment of physical activity (PA) and sleep [Godin and Pittsburgh Sleep Quality Index (PSQI), respectively]. CMR biomarkers were assessed using multiplex assays and ELISAs. Serum UA was assessed using a commercial EIA. A linear mixed model was used to investigate UA by CMR profile (low, dyslipidemia, high) and sex, controlling for BMI, PA and sleep. RESULTS: Similar to previous studies in adolescents, the mean UA level was higher for males (7.11±1.19) compared to females (5.59±0.85). While men had a higher mean UA concentration, females had a higher UA after adjusting for BMI, PA, and sleep (p=0.056). More specifically, females in the low (p<0.001) and dyslipidemia risk (p<0.001) groups had higher UA compared to their male counterparts. Also, BMI was significantly associated with UA regardless of group or sex (p=0.047). CONCLUSIONS: These findings suggest that 1) subjects in the dyslipidemia profile had higher UA after controlling for BMI, PA and sleep compared to subjects in either the low or high CMR profiles and 2) while males may have higher mean UA concentrations on average, females have higher UA concentrations after adjusting for BMI, PA, and sleep. Future studies should track UA levels across adolescence and investigate whether or not the relation between CMR profiles and UA levels changes from adolescence in to adulthood. Funded by NIH R01HD78346

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