Abstract TP222: The Impact Of Il-6 Level On Visit-to-visit Blood Pressure Variability And Incidence Of Stroke: A Post-hoc Analysis Of Mesa

Abstract

Background: Increased blood pressure variability (BPV) has been associated with stroke risk, but no serum inflammatory markers have been identified associated with increased BPV, despite preclinical data suggesting a role. Methods: This is a post-hoc analysis of the Multi-Ethnic Study of Atherosclerosis (MESA) study. The study exposure was tertiles of serum level of interleukin-6 (IL-6) at the baseline study visit. The primary outcome was visit-to-visit BPV measured as the residual standard deviation (rSD) of at least 4 subsequent study visits (1999-2018). Two logistic regression models were fit to the top tertile (i.e. most variability) of rSD during follow-up: in Model 1, we adjusted for covariates chosen with restricted Least Absolute Shrinkage and Selection Operator (LASSO) and in Model 2, for all covariates. Results: Our analysis included 5,483 patients, of mean (SD) age 61.4 (10.0) years and with 52.9% female. Mean (SD) of IL-6 was 1.7 (1.2) (pg/mL) in the top tertile BPV rSD and 1.4 (1.1) in the bottom tertiles. The incidence of ischemic stroke and all major adverse cardiovascular event was higher in top tertile of BPV (Table 1). Elevated serum IL-6, but not other serum biomarkers of inflammation and clotting (see comment below), was associated with the highest tertile of BPV, independent of potential confounders (Table 2). Conclusion: Higher levels of serum IL-6 were associated with increased subsequent BPV in a large multiracial cohort. Further investigation is needed to better understand the relationship between chronic inflammation and BPV. Table 1. Baseline demographics, serum biomarkers, and clinical outcomes during follow-up (how long was follow-up on average?) in the full cohort, and stratified by the top versus lower tertiles of BPV. Table 2. Association of serum biomarkers at baseline with the highest tertile of blood pressure variability.*Model 1 adjusted for patient age categories (<55, 55-64, 65-69, ≥70), sex, and hypertension. **Model 2 (n=5,447) adjusted for patient age categories (<55, 55-64, 65-69, ≥70), sex, race/ethnicity, education, hypertension, diabetes, smoking, drinking, body mass index, lipid lowering medication, and mean systolic blood pressure