Heritability of somatotype components: a multivariate analysis.
International Journal of Obesity 2007 ; 31: 1295-301.
DOI : 10.1038/sj.ijo.0803575
PubMed ID : 17342076
PMCID : 0
To study the genetic and environmental determination of variation in Heath-Carter somatotype (ST) components (endomorphy, mesomorphy and ectomorphy).
Multivariate path analysis on twin data.
Eight hundred and three members of 424 adult Flemish twin pairs (18-34 years of age).
The results indicate the significance of sex differences and the significance of the covariation between the three ST components. After age-regression, variation of the population in ST components and their covariation is explained by additive genetic sources of variance (A), shared (familial) environment (C) and unique environment (E). In men, additive genetic sources of variance explain 28.0% (CI 8.7-50.8%), 86.3% (71.6-90.2%) and 66.5% (37.4-85.1%) for endomorphy, mesomorphy and ectomorphy, respectively. For women, corresponding values are 32.3% (8.9-55.6%), 82.0% (67.7-87.7%) and 70.1% (48.9-81.8%). For all components in men and women, more than 70% of the total variation was explained by sources of variance shared between the three components, emphasising the importance of analysing the ST in a multivariate way.
The findings suggest that the high heritabilities for mesomorphy and ectomorphy reported in earlier twin studies in adolescence are maintained in adulthood. For endomorphy, which represents a relative measure of subcutaneous adipose tissue, however, the results suggest heritability may be considerably lower than most values reported in earlier studies on adolescent twins. The heritability is also lower than values reported for, for example, body mass index (BMI), which next to the weight of organs and adipose tissue also includes muscle and bone tissue. Considering the differences in heritability between musculoskeletal robustness (mesomorphy) and subcutaneous adipose tissue (endomorphy) it may be questioned whether studying the genetics of BMI will eventually lead to a better understanding of the genetics of fatness, obesity and overweight.