N L Segal1, R Feng, S A McGuire, D B Allison, S Miller. 1. Department of Psychology, California State University, 800 N. State College Blvd., Fullerton, CA 92834, USA. nsegal@fullerton.edu
Abstract
BACKGROUND: Earlier studies have established that a substantial percentage of variance in obesity-related phenotypes is explained by genetic components. However, only one study has used both virtual twins (VTs) and biological twins and was able to simultaneously estimate additive genetic, non-additive genetic, shared environmental and unshared environmental components in body mass index (BMI). Our current goal was to re-estimate four components of variance in BMI, applying a more rigorous model to biological and virtual multiples with additional data. Virtual multiples share the same family environment, offering unique opportunities to estimate common environmental influence on phenotypes that cannot be separated from the non-additive genetic component using only biological multiples. METHODS: Data included 929 individuals from 164 monozygotic twin pairs, 156 dizygotic twin pairs, five triplet sets, one quadruplet set, 128 VT pairs, two virtual triplet sets and two virtual quadruplet sets. Virtual multiples consist of one biological child (or twins or triplets) plus one same-aged adoptee who are all raised together since infancy. We estimated the additive genetic, non-additive genetic, shared environmental and unshared random components in BMI using a linear mixed model. The analysis was adjusted for age, age(2), age(3), height, height(2), height(3), gender and race. RESULTS: Both non-additive genetic and common environmental contributions were significant in our model (P-values<0.0001). No significant additive genetic contribution was found. In all, 63.6% (95% confidence interval (CI) 51.8-75.3%) of the total variance of BMI was explained by a non-additive genetic component, 25.7% (95% CI 13.8-37.5%) by a common environmental component and the remaining 10.7% by an unshared component. CONCLUSION: Our results suggest that genetic components play an essential role in BMI and that common environmental factors such as diet or exercise also affect BMI. This conclusion is consistent with our earlier study using a smaller sample and shows the utility of virtual multiples for separating non-additive genetic variance from common environmental variance.
BACKGROUND: Earlier studies have established that a substantial percentage of variance in obesity-related phenotypes is explained by genetic components. However, only one study has used both virtual twins (VTs) and biological twins and was able to simultaneously estimate additive genetic, non-additive genetic, shared environmental and unshared environmental components in body mass index (BMI). Our current goal was to re-estimate four components of variance in BMI, applying a more rigorous model to biological and virtual multiples with additional data. Virtual multiples share the same family environment, offering unique opportunities to estimate common environmental influence on phenotypes that cannot be separated from the non-additive genetic component using only biological multiples. METHODS: Data included 929 individuals from 164 monozygotic twin pairs, 156 dizygotic twin pairs, five triplet sets, one quadruplet set, 128 VT pairs, two virtual triplet sets and two virtual quadruplet sets. Virtual multiples consist of one biological child (or twins or triplets) plus one same-aged adoptee who are all raised together since infancy. We estimated the additive genetic, non-additive genetic, shared environmental and unshared random components in BMI using a linear mixed model. The analysis was adjusted for age, age(2), age(3), height, height(2), height(3), gender and race. RESULTS: Both non-additive genetic and common environmental contributions were significant in our model (P-values<0.0001). No significant additive genetic contribution was found. In all, 63.6% (95% confidence interval (CI) 51.8-75.3%) of the total variance of BMI was explained by a non-additive genetic component, 25.7% (95% CI 13.8-37.5%) by a common environmental component and the remaining 10.7% by an unshared component. CONCLUSION: Our results suggest that genetic components play an essential role in BMI and that common environmental factors such as diet or exercise also affect BMI. This conclusion is consistent with our earlier study using a smaller sample and shows the utility of virtual multiples for separating non-additive genetic variance from common environmental variance.
Authors: Dino A Giussani; Alison J Forhead; David S Gardner; Andrew J W Fletcher; W R Allen; Abigail L Fowden Journal: J Physiol Date: 2002-11-15 Impact factor: 5.182
Authors: Peter M Visscher; Sarah E Medland; Manuel A R Ferreira; Katherine I Morley; Gu Zhu; Belinda K Cornes; Grant W Montgomery; Nicholas G Martin Journal: PLoS Genet Date: 2006-03-24 Impact factor: 5.917
Authors: Jennifer L Scheid; Katelyn A Carr; Henry Lin; Kelly D Fletcher; Lara Sucheston; Prashant K Singh; Robbert Salis; Richard W Erbe; Myles S Faith; David B Allison; Leonard H Epstein Journal: Physiol Behav Date: 2014-04-24
Authors: James Niels Rosenquist; Steven F Lehrer; A James O'Malley; Alan M Zaslavsky; Jordan W Smoller; Nicholas A Christakis Journal: Proc Natl Acad Sci U S A Date: 2014-12-29 Impact factor: 11.205
Authors: A L Jermendy; M Kolossvary; Z D Drobni; A D Tarnoki; D L Tarnoki; J Karady; S Voros; H J Lamb; B Merkely; G Jermendy; P Maurovich-Horvat Journal: Int J Obes (Lond) Date: 2017-08-30 Impact factor: 5.095
Authors: Georgina A Ankra-Badu; Daniel Shriner; Elisabeth Le Bihan-Duval; Sandrine Mignon-Grasteau; Frédérique Pitel; Catherine Beaumont; Michel J Duclos; Jean Simon; Tom E Porter; Alain Vignal; Larry A Cogburn; David B Allison; Nengjun Yi; Samuel E Aggrey Journal: BMC Genomics Date: 2010-02-11 Impact factor: 3.969
Authors: Gia M Bradley; Scott M Blackman; Christopher P Watson; Vishal K Doshi; Garry R Cutting Journal: Am J Clin Nutr Date: 2012-11-07 Impact factor: 7.045