Clinical correlates of change in inflammatory biomarkers: The Framingham Heart Study

Abstract

Objectives: Traditional clinical risk factors are associated with inflammation cross-sectionally, but associations of longitudinal variation in inflammatory biomarkers with corresponding changes in clinical risk factors are incompletely described. We sought to analyze clinical factors associated with change in inflammation in the community.

Methods: We studied 3013 Framingham Offspring (n = 2735) and Omni Cohort (n = 278) participants (mean age 59 years, 55% women, 9% ethnic/racial minority) who attended two consecutive examination cycles (mean 6.7 years apart). We selected ten inflammatory biomarkers representing distinctive biological functions: C-reactive protein (CRP), intercellular adhesion molecule-1, interleukin-6, isoprostanes, lipoprotein-associated phospholipase-2 (Lp-PLA2) activity, Lp-PLA2-mass, monocyte chemoattractant protein-1, osteoprotegerin, P-selectin, and tumor necrosis factor receptor II (TNFRII). We constructed multivariable-adjusted regression models to assess the relations of baseline, follow-up and change in clinical risk factors with change in biomarker concentrations over time.

Results: Baseline, follow-up and change in clinical risk factors explain a moderate amount of the variation in biomarker concentrations across 2 consecutive examinations (ranging from r(2) = 0.28 [TNFRII] up to 0.52 [Lp-PLA2-mass]). In multivariable models, increasing body-mass index, smoking initiation, worsening lipid profile, and increasing waist size were associated with increasing concentrations of several biomarkers. Conversely, hypercholesterolemia therapy and hormone replacement cessation were associated with decreasing concentrations of biomarkers such as CRP, Lp-PLA2-mass and activity.

Conclusion: Cardiovascular risk factors have different patterns of association with longitudinal change in inflammatory biomarkers and explain modest amounts of variability in biomarker concentrations. Nevertheless, a substantial proportion of longitudinal change in inflammatory markers is not explained by traditional risk factors.

Fig. 1

Histogram for changes in log biomarkers.