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

Pan, Jonathan A.a,*; Michaëlsson, Erikb,*; Shaw, Peter W.c; Kuruvilla, Sujithd; Kramer, Christopher M.a,e,i; Gan, Li-Mingf,g; Keeley, Ellen C.a; Salerno, Michaela,e,h,i

doi: 10.1097/HJH.0000000000001875
ORIGINAL PAPERS: Heart and vessels

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 CVDI 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.

aDepartment of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA

bHeart Failure Bioscience, Cardiovascular, Renal and Metabolism, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Gothenburg, Sweden

cBerkshire Medical Center, Pittsfield, Massachusetts, USA

dDepartment of Medicine, Philadelphia VA Medical Center and University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania

eDepartment of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA

fDepartment of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy at the University of Gothenburg

gEarly Clinical Development, Cardiovascular, Renal and Metabolism, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Gothenburg, Sweden

hDepartment of Biomedical Engineering

iCardiovascular Imaging Center, University of Virginia Health System, Charlottesville, Virginia, USA

Correspondence to Michael Salerno, MD, PhD, MS, Director of Cardiac MRI, Associate Professor of Medicine, Radiology, and Biomedical Engineering, Department of Medicine, Cardiovascular Division, University of Virginia Health System, 1215 Lee Street, Box 800158, Charlottesville, VA 22908, USA Tel: +1 434 982 6135; fax: +1 434 982 1998; e-mail:

Abbreviations: CCL20, macrophage inflammatory protein-3; CD40-L, CD40 ligand; CX3CL1, fractalkine; DENSE, displacement encoding with stimulated echoes-pulse; ECV, extracellular volume; ESM-1, endothelial-specific molecule 1; FABP4, fatty acid binding protein 4; GAL, galanin peptide; Gd-DTPA, gadopentetate dimeglumine; HSP 27, heat shock protein 27; ICTP, telopeptide of type I collage; IL-18, Interleukin 18; IL-6, interleukin 6; IL-6RA, interleukin 6 receptor subunit alpha; LVMI, left ventricular mass indexed by body surface area; MCP-1, monocyte chemotactic protein; MMP1, matrix metalloproteinase 1; MMP7, matrix metalloproteinase 7; MOLLI, modified look-locker inversion recovery; NPX, normalized protein expression; OPG, osteoprotegerin; OPLS, orthogonal projection to latent structures by partial least squares; PAR-1, protease-activated receptor; PICP and PIIICP, C-terminal propeptides type I or III; PINP and PIIINP, N-terminal propeptides type I or III; PLS-DA, partial least squares discriminant analysis; Q2, cross-validation for coefficient of determination; R2, coefficient of determination; TNF-R1, tumour necrosis factor-receptor 1; TNF-R2, tumour necrosis factor-receptor 2; U-PAR, urokinase-type plasminogen

Received 12 June, 2018

Accepted 2 July, 2018

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