Extracellular volume by cardiac magnetic resonance is associated with biomarkers of inflammation in hypertensive heart disease

• Published in: Journal of hypertension Vol. 37; no. 1; pp. 65 - 72
• Main Authors: Pan, Jonathan A, Michaëlsson, Erik, Shaw, Peter W, Kuruvilla, Sujith, Kramer, Christopher M, Gan, Li-Ming, Keeley, Ellen C, Salerno, Michael
• Format: Journal Article
• Language: English
• Published: England Copyright Wolters Kluwer Health, Inc. All rights reserved 01-01-2019
• Subjects: Biomarkers - blood; Cardiac and Cardiovascular Systems; Heart - diagnostic imaging; Humans; Hypertension - blood; Hypertension - epidemiology; Hypertension - metabolism; Hypertension - pathology; Hypertrophy, Left Ventricular - diagnostic imaging; Hypertrophy, Left Ventricular - pathology; Inflammation; Kardiologi; Magnetic Resonance Imaging; Myocardium - pathology
• ISSN: 0263-6352; 1473-5598; 1473-5598
• DOI: 10.1097/HJH.0000000000001875

OBJECTIVES:Cardiac magnetic resonance (CMR) provides a unique approach to the characterization of hypertensive heart disease (HHD), enabling the measurement of left ventricular mass and expansion of extracellular volume (ECV). Combining plasma biomarkers with CMR could provide potential insights into the pathophysiological mechanisms in ventricular remodelling.
METHODS:In this study, we estimated correlations between plasma biomarkers and CMR parameters of HHD. Patients with a history of hypertension with or without left ventricular hypertrophy (LVH) and healthy volunteers (17 hypertensive non-LVH, 13 hypertensive LVH and 11 controls) underwent CMR on a Siemens 1.5T Avanto. T1 mapping was performed before (native T1) and serially after injection of 0.15 mmol/kg gadolinium-DTPA. Mean ECV and left ventricular mass index (LVMI) were determined. Blood samples were obtained and analysed using the Olink CVD 92-plex biomarker panel.
RESULTS:Individual groups were compared on the basis of 91 plasma biomarkers using partial least squares discriminant analysis (PLS-DA). ECV and LVMI were correlated with the 91 distinct plasma biomarkers via orthogonal projection to latent structures by partial least square (OPLS) analysis. A two-dimensional PLS-DA explained 49% of the differences between the three groups. OPLS analysis showed that four plasma biomarkers were significantly correlated to both ECV and LVMI, eight were significantly correlated with LVMI only and 11 were significantly correlated to ECV only.
CONCLUSION:ECV and LVMI correlate differentially in plasma biomarker patterns. Top predictors of ECV consisted of well established biomarkers of systemic inflammation and metabolic function.