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A Twin Study Approach Towards Understanding Genetic Contributions to Body Size and Metabolic Rate

Published online by Cambridge University Press:  01 August 2014

J.K. Hewitt*
Affiliation:
Department of Human Genetics, Medical College of Virginia, Richmond, USA Department of Psychology, University of Birmingham, UK
A.J. Stunkard
Affiliation:
Department of Psychiatry, University of Pennsylvania, Philadelphia, USA
D. Carroll
Affiliation:
Department of Psychology, University of Birmingham, UK
J. Sims
Affiliation:
Department of Occupational Health, University of Birmingham, UK
J.R. Turner
Affiliation:
Department of Psychology, University of Birmingham, UK Department of Psychiatry, University of North Carolina, Chapel Hill, USA
*
Department of Human Genetics, Medical College of Virginia, Richmond, VA 23298-0003, USA

Abstract

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The genetic and environmental determinants of a brief assessment of metabolic rate at rest and under psychological stress were studied in 40 pairs of monozygotic and 40 pairs of dizygotic young adult male twins. Height, weight and age were employed as covariates. Univariate analyses showed a high heritability for height and weight and moderate heritability for metabolic rate. Classical twin analyses and multivariate genetic modeling indicated that genetic influences on resting metabolic rate were entirely explained by body weight: there was no independent genetic contribution to resting metabolic rate. Metabolic rate under psychological stress, on the other hand, showed a significant genetic effect. The exponent (3/4) in the power function relating body weight to resting metabolic rate was the same as that found in a wide variety of animal species, a value that has been proposed as defining a body weight set point. We speculate that an adult body weight set point is genetically transmitted. Independent genetic effects on resting metabolic rate would be observed only when the normal equilibrium between body weight and metabolic rate is unbalanced during development, aging or disease. The study illustrates the use of multivariate genetic analyses of twin data which may be readily applied to widely used metabolic rate assessments.

Type
Research Article
Copyright
Copyright © The International Society for Twin Studies 1991

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