Serum Uric Acid and Cardiometabolic Disease
Another Brick in the Wall?
This article requires a subscription to view the full text. If you have a subscription you may use the login form below to view the article. Access to this article can also be purchased.
See related article, pp 1036–1044
Several epidemiological and experimental studies have demonstrated a significant relationship between hyperuricemia and hypertension, metabolic syndrome, chronic kidney disease, and cardiovascular events.1,2 This is confirmed in patients with gout,3 as well as in those with asymptomatic hyperuricemia,4 and may significantly contribute to the overall cardiovascular risk beyond the role of traditional risk factors. However, most of the studies assessing the role of elevated serum uric acid (SUA) in cardiovascular disease have been performed in patients with ≥1 interfering comorbidities. In the present issue of Hypertension, Kuwabara et al5 have provided an interesting demonstration that hyperuricemia, per se, can be associated with an independent increase in the risk of cardiometabolic diseases in a large Japanese population. Specifically, after exclusion of all the patients with overt cardiometabolic disease at baseline, hyperuricemia was still associated with an increased incidence of hypertension, dyslipidemia, chronic kidney disease, and overweight/obesity. These results agree with those of the MRFIT (Multiple Risk Factor Intervention Trial)6 and the PAMELA (Pressioni Arteriose Monitorate E Loro Associazioni)7 studies, showing a significant increase in the new onset of hypertension and metabolic syndrome in healthy subjects with elevated SUA levels after the adjustment for confounding risk factors associated with hyperuricemia.
The findings of Kuwabara et al5 partially overcome one of the main obstacles in the evaluation of the pathogenetic role of elevated SUA levels in cardiovascular disease, namely the possible interference of other risk factors currently associated with hyperuricemia. This problem has usually been resolved with the application of multiple statistical adjustments, leading to a …