We investigated the association of genetic variation in SLC16A1 with leisure-time physical activity in a population-based sample with appreciable score-lowering effect estimates, but 95% CIs were wide. Results were more consistent for males than for females, and the SNP rs1049434 presented the most consistent results.
To the best of the authors’ knowledge, this is the first investigation of an association between genetic variation in SLC16A1 and physical activity in the general population. Furthermore, this is the first candidate-gene assessment of the associations of SLC16A1 SNPs other than rs1049434 with physical activity. To date, there are only four reports of associations between rs1049434 and physical activity. The first reported an association between the SNP and lactate accumulation and maximum lactate concentration in 10 men aged 20–26 under controlled high-intensity circuit training (3). Later, a study in 15 men and 14 women observed an association between rs1049434 and blood lactate accumulation during different training series in males but not in females (4). Two recent studies provided further evidence on this topic: one observed a higher prevalence of the A allele in endurance-oriented athletes than in non-athletic individuals, while mean blood lactate levels were higher in male rowers carrying the T-allele than in AA ones (8); the other provided evidence that sprint/power athletes (n = 100) were more likely than endurance athletes (n = 112) and matched controls (n = 621) to present the T allele (24).
Our findings agree with previously published studies regarding the general notion that SLC16A1 SNPs influence physical activity. Although effect estimates were larger for the rs3849174 SNP, the rs1049434 variant (which was associated with different aspects of physical activity in the aforementioned studies) presented very consistent effect estimates in males. However, the literature supports that rs1049434-T allele is associated with reduced predisposition to be physically active, but we observed the opposite. Additionally, an association was observed in females but not in males, which also is contrary to available evidence (4). However, women have consistently been reported to be less active (regarding overall and leisure-time physical activity) than men (1) and some data suggest women are less motivated to exercise (21, 29). If SLC16A1 SNPs influence exercise levels – a component of leisure-time physical activity – lower participation in structured exercise in women may explain the sex differences observed. Nevertheless, the inconsistencies with the literature evidence the need of future population-based studies in different genetic backgrounds to evaluate the association of these SNPs with leisure-time physical activity and whether this association is different between sexes.
One of the important limitations of our study is the use of self-reported physical activity. In this regard, we have focused on leisure-time physical activity for two reasons. First, it is well-known that occupational and housework domains are overestimated by IPAQ in Latin America (11). Second, the roles of genetic determinants are likely to be more pronounced in leisure-time than in transport-related physical activity, especially in low/middle income populations, where transport-related physical activity is likely determined by socioeconomic factors rather than individual choice (10). Moreover, given Mendel’s 1st and 2nd laws (26, 27), it is unlikely that germline genetic variants (including SNPs) are associated with potential sources of systematic error in physical activity reports. Another potential source of bias in our study is the fact that our sample is multi-ethnic. However, ancestry-informative principal components obtained from genome-wide genotyping data were available and are known to provide a robust protection against population stratification (23). It is also reassuring that the results for the overall sample were similar comparing crude and adjusted analysis.
Although two SNPs (especially rs1049434) presented consistent results in males at different ages, our study is likely underpowered. Some causes of this limitation include measurement error of questionnaire measurers of physical activity (12), the multi-factorial nature of this behavior (1) and the low effect sizes frequently observed for common genetic variants. In the future (when the effects of life-long physical activity patterns will be more apparent in our cohort) it will also be possible to test the association of these SNPs with physical activity-related traits as an additional replication strategy, evaluating the effects of these SNPs on physical activity at different ages. However, the wide confidence intervals we observed do not allow excluding the possibility that our findings are due to chance. Although the associations we reported have biological plausibility, replication in other populations is warranted.
Considering that physical inactivity is a major risk factor for non-communicable diseases, identifying its correlates and determinants may have important public health impacts by providing evidence for effective interventions. In contrast to other factors such as socioeconomic characteristics, the current knowledge regarding the effects of genetic factors on physical activity levels is still modest. Although germline genetic factors are not subject to interventions, their study is important to understand causes of physical inactivity as well as variation in physical activity levels among populations and population sub-groups. Our findings indicate that rs1049434 and rs3849174 SNPs are possibly associated with leisure-time physical activity in males in the general population, but this notion needs to be tested in additional population-based studies.