Arterial stiffness association with chronic inflammatory disorders in the UK Biobank study

OBJECTIVE: The present study tested the hypothesis that arterial stiffness will be elevated across overall and specific inflammatory disorders compared with an inflammation-free comparison group. METHODS: Adults (n=171 125) aged 40-70 years from the UK Biobank who were cardiovascular disease (CVD) free and who had their arterial stiffness assessed at the time of study recruitment between 2006 and 2010 were included. The main exposure was represented by a global measure of chronic inflammatory disorders. Two inflammatory biomarker measures (eg, leucocytes count, granulocytes count) were included as markers of inflammation severity. The arterial stiffness index assessed by a non-invasive technique represented the study primary outcome measure. RESULTS: A total of 5976 (3%) participants diagnosed with inflammatory disorders and 165 149 participants without an inflammatory disorder had data on arterial stiffness. Adjusted linear regression analyses revealed a 14% increment in mean arterial stiffness for chronic inflammatory disorders (beta coefficient (β) 1.14, 95% CI 1.05 to 1.24, P=0.002) compared with no chronic inflammatory disorder. Arterial stiffness tended to increase (P value=0.031) with tertiles of leucocytes and granulocytes count. For instance, mean arterial stiffness values increased from 1.11 (95% CI 0.96 to 1.29) in the first tertile to 1.17 (95% CI 1.02 to 1.34) in the second tertile, and 1.21 (95% CI 1.05 to 1.39) in the third tertile of leucocytes count. There was evidence for similar associations with some of the most common individual inflammatory disorders, including psoriasis and rheumatoid arthritis. CONCLUSION: Arterial stiffness was associated with multiple chronic inflammatory disorders. An increasing trend in mean arterial stiffness was also documented with increasing tertiles of different inflammatory biomarkers. Future studies are needed to investigate the discriminant value of arterial stiffness to predict major CVD events within various inflammatory disorders.