Defining left ventricular remodeling using lean body mass allometry: a UK Biobank study

Abstract

Purpose:The geometric patterns of ventricular remodeling are determined using indexed left ventricular mass (LVM), end-diastolic volume (LVEDV) and concentricity, most often measured using the mass to volume ratio (MVR). The aims of this study were to validate lean body mass (LBM) based allometric coefficients for scaling and to determine an index of concentricity that is independent of both volume and LBM.Methods: Participants from the UK Biobank who underwent both CMR and dual-energy x-ray absorptiometry (DXA) during 2014-2015 were considered (n=5064). We excluded participants aged ≥70 years or those with cardiometabolic risk factors. We determined allometric coefficients for scaling using linear regression of the logarithmically transformed ventricular remodeling parameters. We further defined a multiplicative allometric relationship for LV concentricity (LVC) adjusting for both LVEDV and LBM.Results: A total of 1638 individuals (1057 female) were included. In subjects with lower body fat percentage (<25% in males, <35% in females, n= 644), the LBM allometric coefficients for scaling LVM and LVEDV were 0.85±0.06 and 0.85±0.03 respectively (R 2 = 0.61 and 0.57, P<0.001) with no evidence of sex-allometry interaction. While the MVR was independent of LBM, it demonstrated a negative association with LVEDV in (females: r= -0.44, P<0.001; males: -0.38, P< 0.001). In contrast, LVC was independent of both LVEDV and LBM [LVC = LVM / (LVEDV 0.40 × LBM 0.50 )] leading to increased overlap between LV hypertrophy and higher concentricity.Conclusions. We validated allometric coefficients for LBM based scaling for CMR indexed parameters relevant for classifying geometric patterns of ventricular remodeling.

Quantifying assumptions underlying peak oxygen consumption equations across the body mass spectrum

“…It is recognized that VO 2 is more directly associated with FFM than total body weight, as fat mass has a minimal contribution to peak oxygen consumption 15,22 . As Jackson et al demonstrated and we replicated in our simulation, the BMI versus fat mass percentage relationship is mostly linear for populations with a BMI < 30 kg/m 2 and becomes non‐linear at higher BMIs 16 .…”

“…Comparing pVO 2 indexed to FFM allows for a better evaluation of the fitness assumptions of the different predictive equations as pVO 2 is more influenced by FFM and less by an individual's percentage fat composition 21 . To derive FFM, data from 1057 and 581 apparently healthy female and male subjects participating in the UK Biobank project, respectively, who underwent dual‐energy x‐ray absorptiometry (DEXA) imagining between August 2014 and 2015 were used (project: 22282 genetic and environmental determinants of exercise capacity and fitness) 22 . Importantly, this FFM estimate considered the non‐linear relationship between total body weight and percent body fat which allowed for a more accurate model of FFM in those with high BMI.…”

“…21 To derive FFM, data from 1057 and 581 apparently healthy female and male subjects participating in the UK Biobank project, respectively, who underwent dual-energy x-ray absorptiometry (DEXA) imagining between August 2014 and 2015 were used (project: 22282 genetic and environmental determinants of exercise capacity and fitness). 22 Importantly, this FFM estimate considered the nonlinear relationship between total body weight and percent body fat which allowed for a more accurate model of FFM in those with high BMI. Detailed methodology of the inclusion/exclusion criteria for the UK Biobank cohort, as well as baseline characteristics of included subjects, are included in Supplementary Information under "UK Biobank.…”