KCNA4 Gene Variant is Auxiliary in Endurance Running Performance Level.

The present is an observational study following a genetic epidemiology model using a case-control design. We tested the hypothesis of an association between the prevalence of the genotypic and allelic frequencies distribution of the potassium voltage-gated channel of the shaker related subfamily member 4 gene (KCNA4) rs1323860 (C/T transition) and endurance performance level in Hispanic male marathon runners (MR). The subjects (n=1876) were adult Hispanic male MR. Fast-MR (cases; n=938) were finishers in the top 3rd percentile. Slow MR (controls; n=938) were finishers in the lowest 3rd percentile of their respective age. Genomic DNA was purified from a whole blood sample. Polymerase chain reaction was used to amplify a KCNA4 SNP which consists of a C/T (rs1323860) transition. The observed genotype frequencies, in both Cases and Controls, met Hardy-Weinberg equilibrium (X2, P≥0.05). Genotype and allele frequencies were statistically different (P<0.01) between cases and controls. Odds ratio revealed that the C allele was 1.33 times more likely prevalent in the cases than in the controls (95% CI; 1.17, 1.51; P<0.001). The magnitude of the statistical power for the present study was 0.86. In conclusion, the findings strongly suggest that KCNA4 gene rs1323860 (C/T transition) is auxiliary in the complex phenotype of endurance running performance level in Hispanic male marathon runners.

The Association of Aquaporin-1 Gene with Marathon Running Performance Level: a Confirmatory Study Conducted in Male Hispanic Marathon Runners.

BACKGROUND: Replication studies are essential for identifying credible associations between alleles and phenotypes. Validation of genotype-phenotype associations in the sports and exercise field is rare. An initial genetic association study suggested that rs1049305 (C > G) in the 3' untranslated region (3'UTR) of the aquaporin-1 (AQP1) gene was associated with marathon running (MR) performance level in Hispanic males. To validate this finding, we conducted a replication analysis in an independent case-control sample of Hispanic male marathon runners (n = 1430; cases n = 713 and controls n = 717). A meta-analysis was utilized to test the extent of the association between the initial results and the present report. It also provided to test the heterogeneity (variation) between the two studies. RESULTS: The replication study showed a statistically significant (p ≤ 0.05) association between rs1049305 (C > G) of the AQP1 gene and MR performance level. Association test results using a fixed effect model for the combined, original study and the present report, yielded an odds ratio = 1.28, 95% confidence interval = 1.13-1.45, p = 0.0001. The extent of the measures of heterogeneity was Tau-squared = 0, H statistic = 1, I2 statistic = 0, and Cochran's Q test (Q = 0.29; p value 0.59), indicated the variation between studies were due to chance and not to differences in heterogeneity between the two studies. Within the limitations of the present replication, contrast of two studies and its effects on meta-analysis, the findings were robust. CONCLUSION: This study successfully replicated the results of Martínez et al. (Med Sportiva 13:251-5, 2009). The meta-analysis provided further epidemiological credibility for the hypothesis of association between the DNA rs1049305 (C > G) variation in the 3'UTR of the AQP1 gene and MR running performance level in Hispanics male marathon runners. It is not precluded that a linked DNA structure in the surrounding molecular neighborhood could be of influence by been part of the overly complex phenotype of MR performance level.

Dietary Protein Intake Patterns and Inadequate Protein Intake in Older Adults from Four Countries.

Recent interest in protein intake per meal is observed in studies that have reported the protein intake patterns in different countries; however, comparisons of these data are lacking. We aimed to compare protein intake patterns and the percentage of inadequate protein intake (IPI) per day and meal in older adults from different countries. We acquired data of protein intake in older adults from four countries (Mexico, United States of America, Germany, and United Kingdom). We compared protein intake (per day and meal), IPI per day and meal, and the number of meals with an adequate protein content among countries. The IPI per day significantly differed among countries for <0.8 and <1.0 (both p < 0.001), but not for <1.2 g/kg/d (p = 0.135). IPI per meal (<30 g/meal) did not differ among countries at breakfast (p = 0.287) and lunch (p = 0.076) but did differ at dinner (p < 0.001). Conversely, IPI per meal (<0.4 g/kg/meal) significantly differed among countries at breakfast, lunch, and dinner (all p < 0.001). The percentage of participants that ate ≥30 g/meal or ≥0.4 g/kg/meal at zero, one, and two or three meals per day significantly differed among countries (all p < 0.05). IPI at breakfast and lunch (<30 g/meal) was a common trait in the analyzed samples and might represent an opportunity for nutritional interventions in older adults in different countries.

Accuracy of Anthropometric Equations to Estimate DXA-Derived Skeletal Muscle Mass in Professional Male Soccer Players.

BACKGROUND: Several anthropometric equations that estimate skeletal muscle mass (SMM) have been published, but their applicability and accuracy among athletes are still uncertain. PURPOSE: To assess the accuracy of different anthropometric equations that estimate SMM in professional male soccer players, as compared to dual-energy X-ray absorptiometry (DXA) as the reference method. METHODS: In this cross-sectional study, we evaluated 179 professional male soccer players aged between 18 and 37 years. Anthropometric measurements (height, body weight, skinfold thicknesses, and girths) and a DXA whole body scan were performed the same day for each participant, and SMM was estimated with nine anthropometric equations (Heymsfield, Martin, Doupe, Kerr, Drinkwater, Lee, De Rose, and two equations published by Kuriyan). To determine differences between SMM estimated with anthropometric equations and SMM evaluated with DXA, a Kruskal-Wallis test was performed using Dunn's test as post hoc. The significance level was set at p < 0.05. We calculated the mean difference and 95% limits of agreement for the analyzed equations (Equation - DXA). RESULTS: Only Heymsfield's and Lee's equations showed no significant differences with DXA. Heymsfield's equation had the smallest mean difference (-0.17 kg), but wider limits of agreement with DXA (-6.61 to 6.94 kg). Lee's equation had a small mean difference (1.10 kg) but narrower limits of agreement with DXA (-1.83 to 4.03 kg). CONCLUSIONS: In this study, the prediction equation published by Lee et al. showed the best agreement with DXA and is able to estimate SMM accurately in professional male soccer players.

Accuracy of Anthropometric Equations for Estimating Body Fat in Professional Male Soccer Players Compared with DXA.

BACKGROUND: There are several published anthropometric equations to estimate body fat percentage (BF%), and this may prompt uncertainty about their application. PURPOSE: To analyze the accuracy of several anthropometric equations (developed in athletic [AT] and nonathletic [NAT] populations) that estimate BF% comparing them with DXA. METHODS: We evaluated 131 professional male soccer players (body mass: 73.2 ± 8.0 kg; height: 177.5 ± 5.8 cm; DXA BF% [median, 25th-75th percentile]: 14.0, 11.9-16.4%) aged 18 to 37 years. All subjects were evaluated with anthropometric measurements and a whole body DXA scan. BF% was estimated through 14 AT and 17 NAT anthropometric equations and compared with the measured DXA BF%. Mean differences and 95% limits of agreement were calculated for those anthropometric equations without significant differences with DXA. RESULTS: Five AT and seven NAT anthropometric equations did not differ significantly with DXA. From these, Oliver's and Civar's (AT) and Ball's and Wilmore's (NAT) equations showed the highest agreement with DXA. Their 95% limits of agreement ranged from -3.9 to 2.3%, -4.8 to 1.8%, -3.4 to 3.1%, and -3.9 to 3.0%, respectively. CONCLUSION: Oliver's, Ball's, Civar's, and Wilmore's equations were the best to estimate BF% accurately compared with DXA in professional male soccer players.