Sex-specific genetic effects in physical activity: results from a quantitative genetic analysis
Main descriptive statistics for all PA and SB phenotypes are presented in Table 1. About half of first and second generation subjects did not report VPA. The TPA levels
increase across generations. Reported SB has higher values in the first generation,
as expected, although second and third generation subjects had similar values.
Table 1. Descriptive statistics for age, physical activity levels and sedentary behaviour by
generation and sex
Heritability estimates for the five phenotypes are presented in Table 2. All traits are statistically significant ranging from 0.112 (WT) to 0.456 (WK).
The covariates explained 2Â % to 30Â % of the phenotypic variance.
Table 2. Heritability estimates (h
2
), standard errors (se), p-values and explained variance by covariates
We found GSI effects for VPA (p?=?0.0005) and WT (p?=?0.02), and heterogeneity in
the residual environmental variance for VPA (p?=?0.006), MPA (p?=?0.02) and TPA (p?=?0.001)
(Table 3). Sex-specific heritability estimates are reported in Table 4, showing significantly higher values in males for WT but not for VPA (Fig. 1).
Table 3. P-values for genotype-by-sex interaction effects
Table 4. Sex-specific heritabilities
Fig. 1. Genotype?×?sex interaction effects and sex-specific heritabilities for VPA and WT.
a. VPA. b. WT. Parameter estimates on the vertical axis plotted against sex on the horizontal
axis. Male and female sexes are coded respectively as 1 and 2. Additive genetic and
environmental standard deviations (gsd and esd, respectively) are respectively given
by the solid and dot-dashed lines, and sex-specific heritabilities (h2) are given
by the dotted lines
We report power to detect GSI effects for each trait in Table 5. There was sufficient power to detect GSI due to heterogeneity in the additive genetic
variance for only VPA but not for the other traits. Also, there was sufficient power
to detect GSI due to a genetic correlation coefficient less than 1 for only WT but
not for the other traits. That we found significant GSI due to additive genetic variance
heterogeneity in VPA is not too surprising given that we had sufficient power for
this trait. On the other hand, there are two related issues regarding the power analysis
results for WT that need some explanation. The first issue is that we found significant
GSI due to additive genetic variance heterogeneity for WT but the power to detect
this GSI effect was not sufficient. The second issue is the converse in that we had
maximum power to detect a GSI effect due to a genetic correlation less than 1 and
yet we failed to reject the null hypothesis of ? g(f,m)
?=?1. On these issues, we note the following observations. Low power does not entirely
preclude the rejection of a null hypothesis. Power merely measures the probability
at which rejection of a false null hypothesis may occur. Thus, it is possible (though
perhaps not so probable) to have low power and yet reject a false null hypothesis.
Conversely, maximum power simply means that if a null hypothesis is false, then it
will be rejected every time, but it does not necessarily mean that the null hypothesis
is in fact false. It is well known that complex morphological and physiological traits
may often exhibit marked sexual dimorphism, especially traits associated with body
fat distribution and physiological weight regulation 36]–38]. Marked sex-specific variation is also evident in behavioral characteristics such
as PA and SB, and may have a significant genetic component or may be modulated by
genetic determinants through sex-specific effects 16]. To assess these sex-specific effects on several PA and SB phenotypes, we employed
models of GSI effects and of sex-specific heritabilities. We tested for GSI effects
and heterogeneity in the residual environmental variance. Then, to be able to compare
our results with reports in the literature, which are usually framed in terms of sex-specific
heritabilities, we tested for sex-specific heritabilities in our data.
Table 5. Statistical power analysis for the trait-specific parameters
Table 6. Sex-specific heritabilities of different physical activity phenotypes in twin studies
In the present study, low to moderate genetic contributions to PA and SB phenotypes
were found, ranging from 11Â % to 46Â %. These results are in accord with previous quantitative
genetic studies on nuclear or extended families, which have suggested considerable
genetic influence in these traits, notwithstanding the methodological differences
to measure PA and SB traits and the diversity in statistical procedures 39]. It should be noted, however, that studies in monozygotic and dizygotic twins have
reported greater intraclass correlations for PA levels suggesting moderate to high
genetic influences, from 13Â % to 98Â % 39].
We found evidence of significant GSI for VPA and WT. In particular, VPA and WT exhibited
GSI via significant heterogeneity in the additive genetic variance across genders.
For VPA and WT, the additive genetic variance was higher in males than in females.
Further, evidence of significant heterogeneity in the residual environmental variance
for WT, but not for VPA was shown. Our analysis shows that the male-specific heritabilities
for VPA and WT and the female-specific heritability for VPA were significantly different
from zero. As can be expected from the GSI results, the male- and female-specific
heritabilities for WT were significantly different from each other, which is consistent
with Brazilian families’ sedentarism trait shown by Horimoto et al. 16], although their models were parameterized differently, considered no covariates,
and had a distinct definition of sedentarism. Surprisingly, however, we found that
the male- and female-specific heritabilities for VPA were not significantly different
from each other. The explanation for this apparent discrepancy between the GSI and
sex-specific results for VPA is actually quite simple. For VPA, the difference across
the sexes in the residual environmental variance was of similar magnitude and direction
as the difference across genders in the additive genetic variance, and thus the sex-specific
heritabilities—recall that heritability is the proportion of the additive genetic
variance to the total phenotypic variance—were quite similar for both males and females.
For WT, the additive genetic variance was significantly different across sexes but
not the residual environmental variance. Consequently, the sex-specific heritability
for WT was significantly lower in females compared to males, which is in opposition
to the Brazilian data from Horomito et al. 16], in which the heritability was 22Â % for females and 5Â % for males. It is important
to stress that in their study, if a family member did not take part in sports, they
were classified as having a sedentarism phenotype. Furthermore, in their analysis
no heterogeneity in variance by gender was found when they adjusted their models to
age, sex and age-by-sex interaction covariates. Variance heterogeneity was only found
when no covariates were included in the models.
Most studies on the relationship between PA levels and WT-like measures have found
that the two variables tend to show either a weak relationship or no relationship
at all 40]–44]. Further, at least two studies have shown that PA levels and WT-like variables have
independent effects on cardiovascular disease risk factors, which seems to suggest
that there is a weak or even no relationship between the two variables 45], 46]. We should point out, however, that a few studies have found an inverse relationship
between PA levels and WT-like measures 47]–49]. Nonetheless, evidence from the majority of studies conversant on this issue supports
the hypothesis that PA levels and WT-like measures are only weakly associated at best.
Our results introduce an interesting twist to this weak relationship between PA levels
and WT-like measures. We showed that the residual environmental variance decreased
from males to females for VPA but not for WT. A plausible two-fold explanation of
these different patterns is given as follows. It may be that for whatever set of sociocultural
reasons there are more opportunities for PA for males than for females (e.g. leisure
time practice of team sports) and/or a greater emphasis placed on males relative to
that placed on females to be physically active. Additionally, to explain the effectively
similar levels of residual environmental variance in males and females for WT it may
be that there is enough of a variety of TV shows to equally attract the attention
of both sexes and/or that there are TV shows both sexes tend to watch. In the VPA
case, the sex-specific heritabilities were rendered statistically indistinguishable
by virtue of the residual environmental variance, even in the face of significant
heterogeneity in the sex-specific additive genetic variance. These results serve as
a sobering reminder that heritabilities are also significantly influenced by the residual
environmental variance.
A number of twin studies have reported sex-specific heritabilities of several PA traits,
including leisure time PA (LTPA), sports participation (SP), and SP index (SPI) (Table
6). As can be gathered from Table 6, the 95 % CIs on the heritability estimates overlap, which implies that the sex-specific
heritabilities are not different. However, as we showed for VPA it is quite possible
that there is significant GSI even in the face of effectively equal sex-specific heritabilities.
Moreover, although we did not find evidence of the across-sex genetic correlation
being different from one, it is in theory possible for the across-sex genetic correlation
to be different than one in these studies. Thus, it may still be possible that, even
though most of the studies in Table 6 report sex-specific heritabilities that are not significantly different from each
other, there are still significant GSI effects influencing these traits. Conversely,
our results logically imply that even if sex-specific heritabilities are significantly
different, as in the study by Aaltonen et al. 50] in Table 6, it may not be due to heterogeneity in the additive genetic variance but instead
to heterogeneity in the residual environmental variance. That is, it is possible that
the sex-specific heritabilities are rendered statistically dissimilar by virtue of
heterogeneity in the residual environmental variance, even in the face of an additive
genetic variance that is stable across the sexes. These considerations show that in
order to be able to make robust statistical inferences about sex-specific genetic
determinants it is not enough to estimate sex-specific heritabilities, but rather
a formal GSI model must be employed.
The GSI model showed the presence of sex-specific effects in two phenotypes, namely
VPA and WT. In light of the power analysis results, these findings are somewhat surprising
in that our sample had low power overall to detect GSI effects. Comparing the present
results with previous studies is difficult because we could only find one report from
a similar extended family design 16], which, as previously mentioned, used a different set of PA phenotypes.. Studies
with nuclear or extended families 19]–21] typically just report mean values of different PA levels and tend to conclude that
males are more active than females. However, GSI results are available from twin data
analysis 50]–52] and suggest the presence of a stronger genetic component in males than in females
in some PA phenotypes. This dissimilarity between sexes may not be accurately explained
by different sets of genes acting in males and females, which is consistent with our
inability to reject the hypothesis that genetic correlation across the sexes is unity.
However, it suggests a stronger genetic influence mainly in males. Besides a genetic
predisposition towards being physically active or sedentary, genetic variation in
PA levels may also be influenced by differences in body size and shape, motor performance,
and psychological-drive to be physically active 51], 52].
Molecular genetic studies on PA levels and SB are scant, with little to offer in regard
to sex-specific effects. The only association study reporting on this issue was by
Simonen et al. 53] who found a consistent association between DNA sequence variation in the dopamine
D2 receptor gene (DRD2) with PA levels only in females. To explain this finding they
suggested that, because maternal-offspring correlations were consistently higher than
paternal-offspring correlations, maternal genotype may have had a stronger impact
on offspring’s PA levels relative to the effect of paternal genotype. Alternatively,
they suggested that the effect of DRD2 in males could have been diluted by a stronger
influence of environmental factors relative to that influencing females.
The results and conclusions of the present study may be affected by two main limiting
factors. The first refers to the PA assessment through a self-administered questionnaire
for individuals over 15 years-old. However, the International Physical Activity Questionnaire’s
short form has acceptable measurement properties to access PA levels with validation
in several countries 8], 24]. The second limitation has to do with inadequately accounting for household effects.
In the case of the Brazilian family data previously mentioned, no significant household
effects were found in any PA phenotype. Controlling for the shared environmental effects
has been a difficult task. These involve several non-measurable living aspects within
families and data regarding their magnitude are still inconsistent 17], 18], 21].
Although there are limitations, this study presents strengths to be highlighted. The
participation of a large sample size and age range as well as relationship among different
kinship degrees allow structuring expected covariates to a polygenic model 54]. The adequacy of our sample size in regard to the polygenic model notwithstanding,
our power analysis results revealed that overall our study had low power to detect
GSI effects. We can increase our power in this respect by increasing our sample size
for future investigations and by using more sensitive PA and SB measures.