Quantile-dependent heritability of computed tomography, dual-energy x-ray absorptiometry, anthropometric, and bioelectrical measures of adiposity.
Pubmed ID: 32665611
Pubmed Central ID: PMC7530941
Journal: International journal of obesity (2005)
Publication Date: Oct. 1, 2020
MeSH Terms: Humans, United States, Body Height, Obesity, Anthropometry, Adiposity, Tomography, X-Ray Computed, Electric Impedance, Gene-Environment Interaction, Absorptiometry, Photon, Intra-Abdominal Fat, Subcutaneous Fat
Grants: N01HC25195, HHSN268201500001I, R21 ES020700, HHSN268201500001C, R01 AR041398
Authors: Williams PT
Cite As: Williams PT. Quantile-dependent heritability of computed tomography, dual-energy x-ray absorptiometry, anthropometric, and bioelectrical measures of adiposity. Int J Obes (Lond) 2020 Oct;44(10):2101-2112. Epub 2020 Jul 14.
Studies:
Abstract
BACKGROUND/OBJECTIVES: Quantile-dependent expressivity occurs when a gene's phenotypic expression depends upon whether the trait (e.g., BMI) is high or low relative to its distribution. We have previously shown that the obesity effects of a genetic risk score (GRS<sub>BMI</sub>) increased significantly with increasing quantiles of BMI. However, BMI is an inexact adiposity measure and GRS<sub>BMI</sub> explains <3% of the BMI variance. The purpose of this paper is to test BMI for quantile-dependent expressivity using a more inclusive genetic measure (h<sup>2</sup>, heritability in the narrow sense), extend the result to other adiposity measures, and demonstrate its consistency with purported gene-environment interactions. SUBJECTS/METHODS: Quantile-specific offspring-parent regression slopes (β<sub>OP</sub>) were obtained from quantile regression for height (ht) and computed tomography (CT), dual-energy x-ray absorptiometry (DXA), anthropometric, and bioelectrical impedance (BIA) adiposity measures. Heritability was estimated by 2β<sub>OP</sub>/(1 + r<sub>spouse</sub>) in 6227 offspring-parent pairs from the Framingham Heart Study, where r<sub>spouse</sub> is the spouse correlation. RESULTS: Compared to h<sup>2</sup> at the 10th percentile, genetic heritability was significantly greater at the 90th population percentile for BMI (3.14-fold greater, P < 10<sup>-15</sup>), waist girth/ht (3.27-fold, P < 10<sup>-15</sup>), hip girth/ht (3.12-fold, P = 6.3 × 10<sup>-14</sup>), waist-to-hip ratio (1.75-fold, P = 0.01), sagittal diameter/ht (3.89-fold, P = 3.7 × 10<sup>-7</sup>), DXA total fat/ht<sup>2</sup> (3.62-fold, P = 0.0002), DXA leg fat/ht<sup>2</sup> (3.29-fold, P = 2.0 × 10<sup>-11</sup>), DXA arm fat/ht<sup>2</sup> (4.02-fold, P = 0.001), CT-visceral fat/ht<sup>2</sup> (3.03-fold, P = 0.002), and CT-subcutaneous fat/ht<sup>2</sup> (3.54-fold, P = 0.0004). External validity was suggested by the phenomenon's consistency with numerous published reports. Quantile-dependent expressivity potentially explains precision medicine markers for weight gain from overfeeding or antipsychotic medications, and the modifying effects of physical activity, sleep, diet, polycystic ovary syndrome, socioeconomic status, and depression on gene-BMI relationships. CONCLUSIONS: Genetic heritabilities of anthropometric, CT, and DXA adiposity measures increase with increasing adiposity. Some gene-environment interactions may arise from analyzing subjects by characteristics that distinguish high vs. low adiposity rather than the effects of environmental stimuli on transcriptional and epigenetic processes.