Genetic Polymorphisms and Their Impact on Body Composition and Performance of Brazilians in a 105 Km Mountain Ultramarathon

orphisms affect muscular proteins, aerobic adaptations, and recovery, their in uence on the anthropometric variables and performance in ultramarathon runners is still poorly understood. This study aimed to determine the in uence ofACTN3 R577X,ACE I/D, andCK MM A/G NcoIpolymorphisms on the changes in the anthropometric variables and running time of 105 km mountain runners, in which 22 male Brazilian elite athletes (35.9 6.5 years) were evaluated. Genotyping of theR577X(RR, RX, and XX),ACE I/D(DD, ID, and II), andCK MM A/G Ncol (AA, AG, and GG) polymorphisms was performed using the Polymerase Chain Reaction–Restriction

ofACTN3 R577X,ACE I/D, andCK MM A/G NcoIpolymorphisms on the changes in the anthropometric variables and running time of 105 km mountain runners, in which 22 male Brazilian elite athletes (35.9 6.5 years) were evaluated. Genotyping of theR577X(RR, RX, and XX),ACE I/D(DD, ID, and II), andCK MM A/G Ncol (AA, AG, and GG) polymorphisms was performed using the Polymerase Chain Reaction–Restriction Fragment Length Polymorphism (PCR-RFLP) technique with DNA extracted from saliva. Body composition was determined via bioimpedance. Pre- and post-race weight differences were observed on athletes with the AA genotype (77.1 5.9 kg; 74.6 5.6 kg) compared with those with the AG genotype (74.5 8.0 kg; 68 5.1 kg) (p= 0.02;p= 0.02). The RR genotype showed a correlation between BMI and running time (R = 0.97;p= 0.004). The genotype II showed a correlation with % fat and fat mass concerning running time (R = 0.91;p= 0.003; R = 0.99;p< 0.0001). The AA genotype was associated with post-race weight and lean mass loss, while the RR genotype correlated with BMI, and the genotype II correlated with % body fat and fat mass in relation to times in the 105 km mountain ultramarathon. Keywords:polymorphism; genetic; athletic performance; marathon; running 1. Introduction Mountain ultramarathons are running events that encompass distances greater than the standard marathon length (42.195 km), featuring a signi cant cumulative elevation gain (up to 25,000 m) [1]. These races, despite requiring at least 10 h to complete and posing a strenuous physiological challenge to the human body [2], have witnessed a substantial increase in popularity over the past three decades [3]. This surge in popularity has spurred researchers to delve into the physiological adaptations associated with long- distance events [4]. Regarding predictor evaluation, behavioral, psychological, mechanical, and physiolog- ical factors, such as the maximal oxygen consumption and the lactate threshold, they may be linked to the nal performance of long-distance runners [5–7]. Previous research has Eur. J. Investig. Health Psychol. Educ.2023,13, 1751–1761.

as the maximal oxygen consumption and the lactate threshold, they may be linked to the nal performance of long-distance runners [5–7]. Previous research has Eur. J. Investig. Health Psychol. Educ.2023,13, 1751–1761.

Eur. J. Investig. Health Psychol. Educ.2023,13 1752 examined the association between anthropometric measures and the runners' performance, revealing a correlation between a decrease in body mass index (BMI) [8] and body weight loss [9], with faster running times in ultramarathon athletes. In another line of research, a study conducted by Belli et al. [10] demonstrated that weight loss among ultramarathon runners in 217 km races occurs within the rst 84 km of the race and is then maintained until the race's conclusion. Furthermore, this study concluded that higher accumulations of body fat, concentrated in the lower limbs and abdominal region, may have a negative impact on athletes' performance in this type of event. Lower levels of body fat ( 12%) appear to provide advantages for a faster race [11]. However, despite evidence of a correlation between anthropometry and nal per- formance, it is necessary to emphasize that genes and their polymorphisms are partially responsible for determining the physiological, anthropometric, and psychological char- acteristics needed to achieve athletic performance and elite athlete status [12]. Variables such as height and body mass index are highly heritable and both contribute to identifying talent in different sports [13]. In general, there are few studies that have considered the relationship between genes and their polymorphisms and body composition phenotypes in male or female athletes [14]. Nevertheless, there is substantial evidence that genes and their polymorphisms, such as the Alpha Actinin 3 gene (ACTN3 R577X), Angiotensin Converting Enzyme (ACE I/D), and Creatine Kinase MM Enzyme (CK MM A/G Ncol), in uence muscle performance and metabolism in humans [15,16]. It is important to note that the ACTN3 R577X gene polymorphism is involved in the structure of fast-twitch muscle bers. The presence or absence of the R577X polymorphism can in uence the composition of muscle bers, thereby affecting athletic performance [17]. Individuals with the XX genotype show higher percentages of Type I muscle bers, a condition associated with higher volumetric densities of mitochondria, making them more resistant to muscle fatigue [18]. On the other hand, the ACE I/D polymorphism is associated with ACE activity, which plays a role

can in uence the composition of muscle bers, thereby affecting athletic performance [17]. Individuals with the XX genotype show higher percentages of Type I muscle bers, a condition associated with higher volumetric densities of mitochondria, making them more resistant to muscle fatigue [18]. On the other hand, the ACE I/D polymorphism is associated with ACE activity, which plays a role in blood pressure regulation and the renin–angiotensin–aldosterone response mechanism [19]. The I allele of the ACE I/D polymorphism is associated with lower ACE levels, resulting in better endothelium-dependent vasodilation [20]. Individuals with the I allele have a 50% higher volumetric density of mitochondria and sarcoplasm, contributing to fatigue resistance [18]. On the other hand, the D allele is associated with higher ACE levels, which can in uence cardiovascular function during exercise and oxidative stress responses [2]. Equally important, the CK MM A/G Ncol polymorphism is related to creatine kinase (CK), an enzyme involved in muscle energy production. Therefore, variations in this polymorphism can in uence CK's ability to regenerate after exercise, potentially affecting energy availability and muscle resilience during prolonged activities. This, in turn, can affect ATP availability for mitochondria and thus in uence aerobic energy production in muscle cells [21]. It is worth emphasizing that the worldwide prevalence of genetic polymorphisms, including theACTN3 R577Xpolymorphism,ACE I/D, andCK MM A/G NcoI, can vary among different athlete groups across various sports disciplines. Particularly for mountain ultramarathon athletes, these polymorphisms might manifest unique genotypic distribu- tions, playing a pivotal role in adaptations and athletic performance. This is exempli ed by studies covering power-oriented athletes [22], climbers [23], marathon runners [24], and ultramarathon runners [25]. However, upon searching the literature for the analyses of the association between body composition and genetics, only three studies have been documented, involving ballet dancers [26], rugby athletes [14], and Chinese rowing athletes [12]. This highlights the need for studies in the literature that explore the body composition of mountain ultramarathon runners, along with the analysis of theACTN3 R577X,ACE I/D, andCK MM A/G Ncol gene polymorphisms. Filling this knowledge gap, this study aims to assess the in uence of

have been documented, involving ballet dancers [26], rugby athletes [14], and Chinese rowing athletes [12]. This highlights the need for studies in the literature that explore the body composition of mountain ultramarathon runners, along with the analysis of theACTN3 R577X,ACE I/D, andCK MM A/G Ncol gene polymorphisms. Filling this knowledge gap, this study aims to assess the in uence of theACTN3 R577X,ACE I/D, andCK MM A/G NcoIpolymorphisms on changes in the

Eur. J. Investig. Health Psychol. Educ.2023,13 1753 anthropometric variables and race time in male mountain runners covering 105 km. The main hypothesis of this study posited that theACTN3 R577X,ACE I/D, andCK MM A/G NcoIpolymorphisms would exert an in uence on the body composition variables and running time in mountain runners covering a distance of 105 km. 2. Materials and Methods 2.1. Subjects and Ethical Approval The study was approved by the local Research Ethics Committee (CEP number 2.275.040). All study procedures were conducted in accordance with Resolution 466/12 of the Brazilian National Health Council and carried out during the Ultramaratona dos Perdidos SkyMarathon ® , which took place at Morro dos Perdidos in Tijucas do Sul, Paran¡. The racecourse ranged in altitude from 255 to 1654 m above sea level, including ascents of up to 1330 m and descents of up to 530 m. This study included 22 elite male athletes who competed in a 105 km mountain race, with ages ranging from 35.9 6.5 years. The inclusion criteria established for athletes to participate in the study were as follows: hav- ing a minimum experience of at least two races above 50 km and one race above 80 km between 2015 and 2016; no reports of non-communicable chronic-degenerative diseases; and a cardiorespiratory examination for cardiovascular function assessment, certi ed by a cardiologist. Athletes who did not sign the Informed Consent Form (ICF), did not complete one of the two data collection stages, or expressed a desire to withdraw their consent were excluded from the study. 2.2. Anthropometric Assessment The anthropometric evaluation consisted of measurements of body weight (BW), height, fat percentage (%F), fat mass (FM), and lean mass (LM). BW was measured on a platform-type anthropometric scale (Filizola, S¢o Paulo, Brazil) with a precision of 100 g, and height was determined with a portable stadiometer (Seca, Hamburg, Germany) with a precision of 0.1 cm, considering the arithmetic mean of three consecutive measurements as the nal value. From BW and height, the body mass index (BMI) was determined [27]. The body fat percentage (%F), fat mass (FM), and lean mass (LM)

Brazil) with a precision of 100 g, and height was determined with a portable stadiometer (Seca, Hamburg, Germany) with a precision of 0.1 cm, considering the arithmetic mean of three consecutive measurements as the nal value. From BW and height, the body mass index (BMI) was determined [27]. The body fat percentage (%F), fat mass (FM), and lean mass (LM) were determined using the bioimpedance tetra polar whole-body method (Maltron, Rayleigh, UK) with electrical frequencies of 50 kHz. 2.3. Genotyping For all athlete samples, genomic DNA was extracted from saliva collected through scraping the buccal mucosa and rinsing with a 3% glucose solution, using a standard phenol–chloroform extraction method. All samples were stored in the freezer at 20 C for two days [28]. For genotyping the ACTN3 R577X polymorphism, speci c primers were used (Table). The PCR ampli cation protocol included (a) 95 C for 5 min, (b) 94 C for 30 s, (c) 58 C for 30 s, (d) 72 C for 30 s, (e) repeating steps “b” to “d” 30 times, and(f) 72 C for 5 min. After ampli cation, the PCR product was subjected to digestion with the DdeI restriction enzyme (SIGMA Aldrich, St. Louis, MO, USA) at 37 C for 4 h [29]. Table 1.Primers used and their respective gene accession numbers. Gene Primer Forward Primer Reverse Accession Number ACTN3 5 0 -CTGTTGCCTGTGGTAAGTGGG-3 0 5 0 -TGGTCACAGTATGCAGGAGGG-3 0 89 ACE 5 0 -TGGGACCACAGCGCCCGCCACTAC-3 0 5 0 -CTGGAGACCACTCCCATCCTTTCT-3 0 1636 CKMM 5 0 -GTGCGGTGGACACAGCTGCCG-3 0 5-CAGCTTGGTCAAAGACATTGAGG-3 1158 For genotyping the ACE I/D polymorphism, speci c primers were used (Table). The PCR ampli cation protocol included (a) 95 C for 5 min of initial denaturation and enzyme release, (b) 30 cycles of denaturation at 94 C for 30 s, (c) annealing at 57 C for

Eur. J. Investig. Health Psychol. Educ.2023,13 1754 1 min, (d) an extension at 72 C for 1 min, and (e) a 5 min extension at 72 C [28]. To enhance genotyping speci city, the samples showing the DD genotype were re-evaluated using an insertion-speci c forward primer (Table). The PCR ampli cation protocol included (a) 95 C for 5 min of initial denaturation and enzyme release, (b) 35 cycles of denaturation at 94 C for 30 s, (c) annealing at 56 C for 1 min, (d) an extension at 72 C for 1 min, and (e) after nishing the 35 cycles, there was a 5 min extension at 72 C [28]. For genotyping the CK MM A/G Ncol polymorphism, speci c primers were used (Table). The PCR ampli cation protocol included (a) 1 cycle of denaturation at 95 C for 5 min, (b) 35 cycles of denaturation at 95 C for 30 s, (c) annealing at 66 C for30 s, (d) an extension at 72 C for 1 min, and (e) a 10 min nal elongation cycle at 72 C. Following ampli cation, the PCR product was digested with the Ncol restriction enzyme (New England Biolabs, Beverly, MA, USA) at the speci ed conditions [30]. For genotype analysis, electrophoresis (Kasvi, S¢o Jos²do Pinhais, PR, Brazil) was performed in 3% agarose gel, stained with ethidium bromide, and visualized in a UV transilluminator. 2.4. Statistical Analysis The data were analyzed using descriptive statistics (mean, standard deviation, and percentages) in R software, version 4.0.5. The Shapiro–Wilk test was used and showed that the pre- and post-race anthropometric variables (body weight, BMI, body fat percentage, fat mass, and lean mass) followed a normal distribution. Therefore, the in uence of the ACTN3 R577X,ACE I/D, andCK MM A/G NcoIpolymorphisms and their genotypes on the anthropometric variables at the pre- and post-race moments was veri ed using the Independent Samplest-test. Sample size calculation was performed using statistical power analysis software (GPower, Version 3.1.9.2, Aichach, Germany), adopting a standardized difference of 0.7, with = 0.05 and power = 0.8 to be considered signi cant. Our power analysis suggested

MM A/G NcoIpolymorphisms and their genotypes on the anthropometric variables at the pre- and post-race moments was veri ed using the Independent Samplest-test. Sample size calculation was performed using statistical power analysis software (GPower, Version 3.1.9.2, Aichach, Germany), adopting a standardized difference of 0.7, with = 0.05 and power = 0.8 to be considered signi cant. Our power analysis suggested that nding a signi cant difference in measurement would require a total sample size of 19 subjects. The effect size (ES) magnitude between groups was calculated using Hedges' g with a 95% con dence interval (CI). The correlation of the anthropometric variables (body weight, BMI, %F, FM, and LM) of theACTN3 R577X, ACE I/D, andCK MM A/G NcoIpolymorphisms and their genotypes with running time was evaluated using simple linear regression and categorized as follows: weak correlation (0.20–0.39), moderate correlation (0.40–0.59), strong correlation (0.60–0.79), and very strong correlation (0.80–1.0). For all statistical procedures, a signi cance level ofp 0.05 was adopted. In order to minimize the Type I error, the Bonferroni correction was used, adjusting the signi cance level based on the number of tests conducted. 3. Results Table of theACTN3 R577Xpolymorphism for each anthropometric variable, before and after the race. The results are organized according to the genotype comparisons: RR vs. RX, RX vs. XX, and RR vs. XX. Following the assessment of pre- and post-race mean values for the anthropometric variables with respect to theACTN3 R577Xpolymorphism genotypes, no statistically signi cant differences were observed (p> 0.05). Table I/D andCK MM A/G NcoIpolymorphisms for each anthropometric variable, both before and after the race. The genotypes are categorized as ID vs. II forACE I/Dand AA vs. AG, AA vs. GG, and GG vs. AG forCK MM A/G NcoI. After evaluating the mean values of the pre- and post-race anthropometric variables in relation to the genotypes ofACE I/DandCK MM A/G NcoIpolymorphisms, the statistical analysis revealed that theCK MM A/G NcoI polymorphism (AA vs. AG) showed signi cant differences for weight and MM (p 0.05). This indicates that individuals with the AA genotype exhibited higher weight and lean mass compared to those with

mean values of the pre- and post-race anthropometric variables in relation to the genotypes ofACE I/DandCK MM A/G NcoIpolymorphisms, the statistical analysis revealed that theCK MM A/G NcoI polymorphism (AA vs. AG) showed signi cant differences for weight and MM (p 0.05). This indicates that individuals with the AA genotype exhibited higher weight and lean mass compared to those with the AG genotype before and after the race. The remaining polymorphisms did not show signi cant differences for the statistical variables.

Eur. J. Investig. Health Psychol. Educ.2023,13 1755 Table 2. Mean and standard deviation pre- and post-race of anthropometric variables related to the genotypes of polymorphism ACTN3R557X to the study sample (n= 22). Polymorphism Genotype Comparison ACTN3 R577X RX (n= 12) vs. RR (n= 5) Variables Pre p-value Hedges' g 95% CI Post p-value Hedges' g 95% CI Weight (Kg) 72.0 6.1–70.7 6.8 0.71 0.2 0.80–1.19 70.5 5.4–69.5 6.9 0.73 0.16 0.83–1.15 BMI (Kg/m 2 ) 24.5 1.8–22.8 2.6 0.18 0.79 0.24–1.81 23.9 1.5–22.4 2.7 0.17 0.75 0.27–1.77 %F 11.2 2.7–9.9 2.0 0.28 0.49 0.52–1.49 9.6 1.8–8.8 1.9 0.42 0.42 0.58–1.42 FM (Kg) 8.1 1.7–6.9 1.2 0.2 0.84 1.87–0.19 6.8 1.5–6.0 1.2 0.34 0.53 0.47–1.54 LM (Kg) 64.0 5.6–63.8 6.9 0.93 0.05 0.94–1.04 63.7 4.6–63.4 7.0 0.9 0.05 0.94–1.04 RX (n= 12) vs. XX (n= 5) Variables Pre p-value Hedges' g 95% CI Post p-value Hedges' g 95% CI Weight (Kg) 72.0 6.1–75.5 7.8 0.33 0.5 1.51–0.50 70.5 5.4–72.6 7.6 0.53 0.33 1.33–0.67 BMI (Kg/m 2 ) 24.5 1.8–25.5 2.7 0.38 0.46 1.46–0.55 23.9 1.5–23.9 1.1 0.94 0 0.99–0.99 %F 11.2 2.7–11.1 2.5 0.95 0.04 0.95–1.03 9.6 1.8–8.8 1.1 0.38 0.46 0.54–1.46 FM (Kg) 8.1 1.7–8.7 2.4 0.57 0.3 1.29–0.70 6.8 1.5–6.4 2.2 0.58 0.22 0.77–1.21 LM (Kg) 64.0 5.6–68.8 8.0 0.18 0.72 1.74–0.30 63.7 4.6–66.2 7.0 0.4 0.44 1.45–0.56 RR (n= 5) vs. XX (n= 5) Variables Pre p-value Hedges' g 95% CI Post p-value Hedges' g 95% CI Weight (Kg) 70.7 6.8–75.5 7.8 0.33 0.59 0.56–1.74 69.5 6.9–72.6 7.6 0.53 0.39 0.75–1.52 BMI (Kg/m 2 ) 22.8 7.2–25.5 2.7 0.16 0.32 0.80–1.45 22.4 2.7–23.9 1.1 0.41 0.66 0.50–1.81 %F 9.9 2.0–11.1 2.5 0.4 0.48 0.66–1.62 8.8 1.9–8.8 1.1 0.85 0 1.12–1.12 FM (Kg) 6.9 1.2–8.7 2.4 0.19 0.86 0.32–2.04 6.0 1.2–6.4 2.2 0.75 0.2 0.92–1.33 LM (Kg) 63.8 6.9–68.8 8.0 0.32 0.6 0.55–1.76 63.4 7.0–66.2 7.0 0.46 0.36 1.49–0.77 p 0.05. BMI = body mass index; %F = body fat percentage; FM = fat mass; LM = lean mass. Table 3. Mean and standard deviation pre- and post-race of anthropometric variables related to the genotypes of polymorphismACE I/DeCK MM

The study assesses genetic influences on body composition and performance in Brazilian ultramarathon runners.