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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
Since heritability is a population estimate of the relative contribution of genetic differences to a given trait, it does not provide useful information for a given individual. For instance, consider the data depicted in Figure 3.3. Using family data, heritability can be estimated by comparing the regression level of a trait between both parents (midparent value) and their offspring (11). The figure illustrates the distribution of individual scores for two levels of heritability, namely 0.2 and 0.8. Note that even under the conditions of high (80%) heritability, there are very large inter-individual differences in the relation between the midparent value for the trait and the values of their offspring. This is an illustration that heritability is an average population value and is not applicable to a given individual.
Genetics of Obesity: Etiologic Heterogeneity and Temporal Trends
Published in Claude Bouchard, The Genetics of Obesity, 2020
Ingrid B. Borecki, Michael A. Province, Claude Bouchard, D. C. Rao
Genetic studies of the BMI have produced some conflicting results, although it is generally agreed that there is a significant degree of familial resemblance, with low to moderate correlations among first-degree relatives. However, to what degree the resemblance is due to shared genes remains a point of contention. Some family and adoption studies suggest low polygenic effects relative to familial environmental effects,10–13 and in one adoption study8 the midparent-natural child correlation did not differ significantly from the foster midparent-adopted child correlation, providing no evidence to support a role for genetic factors at all. In contrast, accumulating evidence from recent studies of adoptive families and twins reared together and apart suggests that genetic factors are more important than environmental ones.14,21 For example, data from the Danish adoption study suggest that there is a clear absence of effects of the familial environment, and all familial resemblance is attributed to genetic effects yielding a polygenic heritability of about 34%.17,22,23 Aside from genetic effects, examination of the evidence regarding environmental influences also has raised the suggestion that only environmental experiences that are not shared among family members appear to be important.23–25
Genetic Abnormalities of the Na-K-Cl Cotransport in Experimental and Primary Hypertension
Published in Antonio Coca, Ricardo P. Garay, Ionic Transport in Hypertension: New Perspectives, 2019
Patrizia Ferrari, Giuseppe Bianchi
In a second study,83 we also considered the interfamilial correlation of different RBC transport systems and Nai between spouses and between midparent (mean of the two parents) and offspring values in 47 families with at least one hypertensive parent and 39 families with both normotensive parents. This kind of study allows the dissection of the genetic from the environmental component of the variance of a phenotypic trait. Nai and Na-K-Cl pump were found highly and significantly correlated between spouses, suggesting a strong influence of environment on these parameters. Conversely, Na-K-Cl cotransport was found to correlate between mid-parents and offspring only in hypertensive families (r = 0.42 hypertensives, r = 0.09 normotensives) and not between spouses of the two family groups, indicating that only in the hypertensive subset of population does this phenotypic trait have greater genetic polymorphism. According to the bimodal distribution in EH, an arbitrary cutoff for the high and low cotransport activity was put at 530 μmol/l RBC/h-1, and a simple segregation analysis was performed on the total of the families to verify the hypothesis that Na-K-Cl cotransport is transmitted as a recessive character for the high phenotype. The results were compatible with such a hypothesis, suggesting that cotransport can be partly determined by a recessive major gene coding for the “high” phenotype, and this gene effect is present only in hypertensive families, because the “high” phenotype is absent in normotensives with a negative family history.83
Predicting the timing of the peak of the pubertal growth spurt in elite male youth soccer players: evaluation of methods
Published in Annals of Human Biology, 2020
James Parr, Keith Winwood, Emma Hodson-Tole, Frederik J. A. Deconinck, Les Parry, James P. Hill, Robert M. Malina, Sean P. Cumming
The adult height of each player at the observation closest to 13.0 years (see above) was predicted with age-specific equations for males of European ancestry in the Fels Longitudinal Study (Khamis and Roche 1994). The equations require CA, height and weight of the youngster and mid-parent height (average of the heights of the player’s biological mother and father). Heights of the biological parents were self-reported and, as in other studies using the protocol, self-reported heights were adjusted for overestimation using sex specific equations (Epstein et al. 1995). The median error bound between actual and predicted young adult height using the Khamis-Roche equations was 2.2 ± 0.6 cm in males between 4.0 and 17.5 years of age; the estimated median error in males at 13.0 years was 2.5 cm (Khamis and Roche 1994). The height of each player at 13.0 years was expressed (1) as a percentage of his predicted adult height and also (2) as a percentage of his young adult attained height at 18.0 years of age.
Developmental fitness curves: assessing sprint acceleration relative to age and maturity status in elite junior tennis players
Published in Annals of Human Biology, 2020
Gillian K. Myburgh, Sean P. Cumming, Manuel Coelho-e-Silva, Robert M. Malina
Data for the NAGTC sample included reported heights of each player’s biological parents, which were adjusted for overestimation. Age, height, and weight of the player and midparent height were used to predict his/her adult height using equations developed for children and youth in the Fels Longitudinal Study (Khamis and Roche 1994). Current height was then expressed as a percentage of predicted adult height attained at the time of observation, which is an indicator of maturity status (Roche et al. 1983). Percentage of predicted adult height attained at time of observation for each player was then compared to age- and sex-specific growth reference data for the UK (Freeman et al. 1995; Gillison et al. 2017) to derive an index of maturity status, labelled biological age (BA), for each participant. Sex-specific reference values for percentage of adult stature were calculated at approximately 0.1 yearly intervals relative to the UK reference data. Percentages at each age interval were based upon mean attained height attained at each age relative to mean stature at/above 18 years (Gillison et al. 2017). Accordingly, a boy with a CA of 12.5 years attained 88% of his predicted adult height at the time of observation; his percentage of predicted adult height was equivalent to the mean percentage of adult height attained by a UK boy of 13.2 years, which was accepted as his BA.
Bio-banding in academy football: player’s perceptions of a maturity matched tournament
Published in Annals of Human Biology, 2019
Ben Bradley, David Johnson, Megan Hill, Darragh McGee, Adam Kana-ah, Callum Sharpin, Peter Sharp, Adam Kelly, Sean P. Cumming, Robert M. Malina
The maturity status of all players was estimated the week prior to the tournament. Heights and weights of each player were measured by trained staff. Heights of the biological parents of each player were self-reported and subsequently adjusted for over-estimation (Epstein et al. 1995). The chronological age, height and weight of the player and mid-parent (mean of the heights of both parents) were used to predict adult height using equations developed on youth in south-central Ohio in the US (Khamis and Roche 1995). The median error for predicted adult height in boys between 4 and 17 years of age was 2.2 cm.