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Genetics and exercise: an introduction
Published in Adam P. Sharples, James P. Morton, Henning Wackerhage, Molecular Exercise Physiology, 2022
Claude Bouchard, Henning Wackerhage
As an example, let’s use data of a twin study on the methylation level (i.e. the addition of CH3/methyl groups) in a specific stretch of DNA (9). A higher correlation of 0.88 was found among pairs of monozygous twins when compared to a correlation of 0.48 in dizygous twins. Using the correlations from Figure 3.2 and the Falconer formula yields the following heritability estimate:
Perceived Stress and Sleep Quality in Midlife and Later: Controlling for Genetic and Environmental Influences
Published in Behavioral Sleep Medicine, 2020
Yueqin Hu, Marieke Visser, Sierra Kaiser
Using the twin data, an ACE model was established for each variable. Figure 3 shows an example of ACE model for perceived stress. The ACE model specification for other variables is the same but with different coefficients (a, c and e). These coefficients are shown in Table 3. Besides the ACE model, we can also use Falconer’s formula (Falconer, 1960) which examines the differences between
Quantile-specific heritability of serum growth factor concentrations
Published in Growth Factors, 2021
The estimates of VEGF heritability from Falconer’s formula probably inadequately represent the complexity VEGF genetics as suggested by a heritability greater than 1 at the VEGF 90th percentile. Moreover, full-sibling regression slopes from HGF, angiopoietin-2, sTie-2, and sFlt-1 probably include shared environmental effects in addition to genetic concordance (e.g. 20.1% of VEGF variance has been attributed to unknown common familial factors (Pantsulaia et al. 2004)). We also note that only a limited number of published gene–environment interactions are available for assessing their consistency with quantile-dependent expressivity, and those that are seldom include the data required to test its applicability, namely unadjusted growth factor concentrations by condition and genotype. For example, Yi et al. (2016) reported significant effects of the VEGF rs833070 (P < 0.01) and VEGF rs3025030 (P < 0.01) polymorphisms in rheumatoid arthritis patients whose VEGF concentrations were significantly higher than matched controls (P < 0.0001) without presenting the effects of these polymorphisms in controls. Similarly, Almawi et al. (2016) reported significant effects of the VEGF rs2010963 (P = 0.05) and VEGF rs3025030 (P = 0.007) polymorphisms in polycystic ovary syndrome patients whose VEGF concentrations were significantly higher than matched controls (P = 0.007) without presenting the effects of these polymorphisms in the controls.