Hemodynamics and plasma biomarkers in individuals with mild-to-moderate ascending aortic dilatation and tricuspid aortic valves

Abstract

Abstract Background Ascending aortic (AA) dilatation is a silent disease that requires frequent follow-up measurements of the AA diameter. Unfortunately, the AA diameter is an insufficient predictor of future growth and complications. Hemodynamic and circulating biomarkers represent promising ways of improving the risk stratification in AA dilatation. Most patients with AA dilatation have tricuspid aortic valves (TAV). However, previous studies have mainly focused on AA dilation in individuals with bicuspid aortic valves (BAV) using either hemodynamic or circulating biomarkers separately. Purpose To assess the relationship between hemodynamics in the AA and circulating biomarkers in individuals with mild-to-moderate AA dilatation and age-and-sex matched controls with TAV. Methods The study cohort of individuals with mild-to-moderate AA dilatation were identified based on AA diameter on coronary CT angiography in the population-based Swedish CardioPulmonary BioImage Study (SCAPIS) in Linköping. 54 cases with AA diameter >= 40 mm and 50 controls with AA diameter <40 mm (mean age 59, 19% female) underwent 4D Flow cardiovascular magnetic resonance imaging (CMR). The 4D Flow CMR images were processed to compute mean and maximum velocities, wall shear stress (WSS), flow displacement (FD) at peak systole, and oscillatory shear index (OSI) in the AA. Markers of collagen synthesis and degradation; type I collagen α1 chain (COL1α1), matrix metalloproteinase (MMP)-1,-2,-3,-9,-12) and their inhibitors (TIMP-1,-2,-3,-4), were quantified in plasma (n=104). High sensitivity C-reactive protein and interleukin(IL)-6 were used to assess systemic inflammation. Results FD at the location of maximum dilatation, mean FD and mean OSI were higher in cases compared to controls. Mean velocity, mean WSS and maximum WSS were lower in cases compared to controls. None of the circulating biomarkers differed significantly between cases and controls. Interestingly, several circulating biomarkers correlated with hemodynamics markers in the whole cohort. COL1α1, MMP-2 and TIMP-2 correlated inversely with max OSI (r=-0.342, p=0.001; r=-0.277, p=0.006; r=-0.238, p=0.018, respectively) while MMP-3 correlated positively with mean velocity (r=0.274, p=0.006), mean WSS (r=0.270, p=0.007), max WSS (r=0.220, p=0.029), and inversely with FD at the location of maximum dilatation (r=-0.218, p=0.031). TIMP-4 correlated with mean OSI (r=-0.284, p=0.005). Conclusions Several hemodynamic markers obtained with 4D Flow CMR were altered in mild-to-moderate AA dilatation with TAV, while circulating biomarkers did not differ from controls. However, significant correlations were identified between several biomarkers and hemodynamic markers. We therefore speculate that the levels of circulating biomarkers may be altered as the disease progresses. Future studies should examine the implications of these novel findings along the trajectory of AA dilation and its association with complication risk.Methods figureHemodynamics markers table