Abstract
on the genetic factors contributing to inter-individual variability in muscle fiber size are limited. Recent research has demonstrated that mice lacking the Arkadia (RNF111) N- terminal-like PKA signaling regulator 2N (Ark2n; also known asC18orf25) gene exhibit reduced muscle fiber size, contraction force, and exercise capacity, along with defects in calcium handling within fast- twitch muscle fibers. However, the role of theARK2Ngene in human muscle physiology, and particularly in athletic populations, remains poorly understood. The aim of this study was threefold: (a) to compare ARK2Ngene expression between power and endurance athletes; (b) to analyze the relationship between ARK2Ngene expression and muscle fiber composition; and (c) to investigate the association between the functional variant of theARK2Ngene, muscle fiber size, and sport-related phenotypes. Results: We found thatARK2Ngene expression was significantly higher in power athletes compared to endurance athletes (p= 0.042) and was positively associated with the proportion of oxidative fast-twitch (type IIA) muscle fibers in untrained subjects (p= 0.017, adjusted for age and sex). Additionally, we observed that theARK2Nrs6507691 T allele, which predicts highARK2Ngene expression (p= 3.8×10 −12 ), was associated with a greater cross-sectional area of fast-twitch muscle fibers in strength athletes (p= 0.015) and was over-represented in world-class strength athletes (38.6%; OR = 2.2,p= 0.023) and wrestlers (33.8%; OR = 1.8,p= 0.044) compared to controls (22.0%). Conclusions: In conclusion,ARK2Nappears to be a gene specific to oxidative fast-twitch myofibers, with its functional variant being associated with muscle fiber size and strength-athlete status. Keywords:polymorphism; genotype; gene expression; SNP; athlete status; weightlifting; sport; molecular physiology; muscle hypertrophy; skeletal muscle Metabolites2024,14, 684.
specific to oxidative fast-twitch myofibers, with its functional variant being associated with muscle fiber size and strength-athlete status. Keywords:polymorphism; genotype; gene expression; SNP; athlete status; weightlifting; sport; molecular physiology; muscle hypertrophy; skeletal muscle Metabolites2024,14, 684.
Metabolites2024,14, 684 2 of 13 1. Introduction Strength is a fundamental component of athletic performance, with muscle strength and power being essential in competitive sports requiring high-force outputs, such as weightlifting, sprinting, and jumping. Muscle strength is known to be a highly heritable trait, with heritability estimates for strength-related phenotypes ranging from 30% to 80% [1–3]. Genetic contributions to strength are polygenic, involving numerous genetic variants that collectively influence the phenotype [4–10]. This complex genetic architecture underscores the diversity of biological factors con- tributing to strength performance, including greater muscle fiber size [11], the prevalence of oxidative fast-twitch (type IIA) muscle fibers [12], shifts in muscle metabolism toward glycolysis [13], increased testosterone levels [14], and neural adaptations that enhance force production capabilities [15]. Research on the genetics of strength and related phenotypes has advanced significantly in recent years, especially with the use of genome-wide approaches [4–6,16–18]. This research has identified over 40 genetic variants associated with strength-athlete status and weightlifting performance, including those located near or within theABHD17C, ACE,ACTG1,ACTN3,ADCY3,ADPGK,AGT,ALDH2,ANGPT2,AR,ARPP21,BCDIN3D, CKM,CNTFR,CRTAC1,DHODH,GALNTL6,GBE1,GBF1,GLIS3,HIF1A,IGF1,IL6,ITPR1, KIF1B,LRPPRC,MLN,MMS22L,MTHFR,NPIPB6,PHACTR1,PLEKHB1,PPARA,PPARG, PPARGC1A,R3HDM1,RASGRF1,RMC1,SLC39A8,TFAP2D,ZKSCAN5, andZNF608 genes [7–9,19–39]. Among these, polymorphisms in theACTN3,AR,LRPPRC,MMS22L, PHACTR1, andPPARGgenes are particularly promising, with each variant being shown to play a role in specific physiological pathways that contribute to muscle strength and performance [40,41]. Overall, the study of genetic contributions to strength provides a foundation for understanding individual variability in athletic performance and offers pathways for personalized approaches in sports training and rehabilitation. As research continues to map the genetic landscape of strength, identifying specific markers and their physiological roles will enhance our understanding of how genetics shape strength-related traits and inform precision-based interventions to maximize human potential in sports and health contexts [9,10]. Recently, a new and promising candidate gene related to strength performance and skeletal muscle hypertrophy has been identified [42]. Specifically, research has demon- strated that mice lacking theArk2ngene (also known asC18orf25; chromosome 18 open reading frame 25) exhibit a reduced muscle fiber size, contraction force, and exercise ca- pacity, along with defects in calcium handling within fast-twitch muscle fibers [42,43]. TheARK2Ngene encodes a protein known as Arkadia (RNF111) N-terminal-like PKA signaling regulator 2N (ARK2N),
hypertrophy has been identified [42]. Specifically, research has demon- strated that mice lacking theArk2ngene (also known asC18orf25; chromosome 18 open reading frame 25) exhibit a reduced muscle fiber size, contraction force, and exercise ca- pacity, along with defects in calcium handling within fast-twitch muscle fibers [42,43]. TheARK2Ngene encodes a protein known as Arkadia (RNF111) N-terminal-like PKA signaling regulator 2N (ARK2N), which is homologous to ring finger protein 111 (RNF111), an E3 ubiquitin ligase. Unlike RNF111, ARK2N lacks the domain necessary for ubiquitin binding and is therefore considered an adaptor or signaling protein without ubiquitination activity [44]. Furthermore, ARK2N has been shown to undergo phosphorylation by AMP- activated protein kinase (AMPK) in humans following acute exercise, which enhances skeletal muscle contractile function ex vivo [43]. Given that elite weightlifters typically exhibit a high proportion of oxidative fast- twitch (type IIA) muscle fibers [12], we hypothesized that strength-relatedARK2Ngene expression is positively correlated with the proportion of type IIA muscle fibers and that functional variants within theARK2Ngene are associated with elite weightlifting performance and power-athlete status. This study aimed to (a) compareARK2Ngene expression between power and endurance athletes; (b) analyze the relationship between ARK2Ngene expression and muscle fiber composition; and (c) investigate the association between the functional variant of theARK2Ngene, muscle fiber size, and sport-related phenotypes.
Metabolites2024,14, 684 3 of 13 2. Materials and Methods 2.1. Ethical Approval This study was approved by the Ethics Committee of Bingol University (reference 23/20; approval date: 9 November 2023) and the Ethics Committees of the Federal Research and Clinical Center of Physical–Chemical Medicine of the Federal Medical and Biological Agency of Russia (reference 2017/04; approval date: 4 July 2017). Written informed consent was obtained from each participant before the start of this study, which complied with the Declaration of Helsinki and ethical standards for sport and exercise science research. 2.2. Study Participants 2.2.1. The Turkish Cohorts The study included 60 Turkish track and field athletes, consisting of 31 power athletes (11 females and 20 males: 100–400 m runners [n= 9], jumpers [n= 3], and throwers [n= 19]; age 26.6 (3.0) years; sport experience 7.4 (3.6) years) and 29 endurance athletes (10 females and 19 males: 3000 m [n= 12], 5000 m [n= 5], 10,000 m [n= 4], and marathon runners [n= 8]; age 27.5 (4.2) years; sport experience 11.5 (5.1) years). All athletes were affiliated with the Turkish Athletics Federation and were ranked within the top ten nationally in their respective disciplines. The control group included 20 healthy, unrelated Turkish individuals without competitive sports experience. Allele frequencies of theARK2Nrs6507691 polymorphism were verified by comparison with data from 557 healthy participants in the Turkish Genome Project ( 5 August 2024). All athletes and controls were of Caucasian ancestry, and none had tested positive for doping. 2.2.2. The Russian Cohorts The gene-expression study included 10 sub-elite power athletes (four powerlifters, four weightlifters, one decathlete, and one taekwondo athlete; mean age 30.1±7.4 years; height 178.2±6.7 cm; body mass 85.6±12.4 kg) and 13 sub-elite endurance athletes (nine long- distance runners, three triathletes, and one cross-country skier; mean age 34.2 (10.0) years; height 182.8 (6.8) cm; body mass 76.0 (9.9) kg), all of European descent (Russians), as pre- viously described [45]. The muscle-fiber-size study included 24 sub-elite strength athletes (17 powerlifters, 7 weightlifters; mean age 30.0 (5.3) years; height 178.9 (6.3) cm; body mass 90.9 (11.3) kg) of European descent. Additionally, a case-control study
one cross-country skier; mean age 34.2 (10.0) years; height 182.8 (6.8) cm; body mass 76.0 (9.9) kg), all of European descent (Russians), as pre- viously described [45]. The muscle-fiber-size study included 24 sub-elite strength athletes (17 powerlifters, 7 weightlifters; mean age 30.0 (5.3) years; height 178.9 (6.3) cm; body mass 90.9 (11.3) kg) of European descent. Additionally, a case-control study involved 90 weightlifters (55 males, mean age 27.7 (5.4) years; 35 females, mean age 26.8 (3.3) years), 125 wrestlers (87 males, mean age 25.7 (4.2) years; 38 females, mean age 29.2 (3.5) years; 38 Greco-Roman wrestlers, 33 freestyle wrestlers, 26 sambo wrestlers, 17 judo wrestlers, and 11 belt wrestlers), and 182 controls (138 males, 44 females; mean age 44.9 (4.2) years). Among the 215 athletes (strength athletes and wrestlers), 56 were world class (Olympic/world/European Champi- onship medalists: 22 weightlifters and 34 wrestlers), while 159 were elite (international level, non-medalists). None of the athletes had tested positive for doping. 2.2.3. The FUSION Cohort The gene-expression study (vastus lateralis) included 291 sedentary individuals of European descent from the FUSION study [46], comprising 166 men (mean age 59.5 (8.1) years; height 176.7 (6.7) cm; body mass 87.3 (15.1) kg) and 125 women (mean age 60.3 (8.1) years; height 162.8 (5.6) cm; body mass 71.8 (9.8) kg). 2.3. Performance Analysis To analyze the performance levels of the Turkish athletes, their personal bests were evaluated using the World Athletics (formerly IAAF) scoring system, as previously de- scribed [17]. 2.4. Genotyping Genotyping of the rs6507691 polymorphism in the Turkish participants was per- formed using either in-house (laboratory-developed) real-time PCR for the athletes or
Metabolites2024,14, 684 4 of 13 SNP array analysis for the other participants, using genomic DNA isolated from pe- ripheral blood. DNA was isolated using the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. Quantification of the iso- lated DNA was carried out with a NanoDrop1000 spectrophotometer (Thermo Scien- tific, Waltham, MA, USA). Real-time PCR was conducted using a TaqMan probe-based strategy. The primer–probe sets (forward primer: 5 ′ GCCCAAAAGTCGTGTCCCTT 3 ′ ; reverse primer: 5 ′ ATTAGCTGGCGTAGTGGTGG 3 ′ ; Probe-1: 5 ′ [FAM] CCTCTGCCTC- CCAGGTTCAAGCG 3 ′ ; Probe-2: 5 ′ [HEX] CCTCTGCCTCCCAGGCTCAAGCG 3 ′ ; Probe-3: 5 ′ [HEX] CCTCTGCCTCCCAGGGTCAAGCG 3 ′ ) were designed using the Primer-BLAST tool (https://www.ncbi.nlm.nih.gov/tools/primer-blast/; accessed on 5 August 2024). The PCR was then performed with the Takyon ROX Probe 2X MasterMix dTTP (Eurogentec, Seraing, Belgium). Each PCR mix consisted of 10µL of the probe mastermix, 1µL of 10µM forward and reverse primers, 0.5µL of 10µM Probe-1 and Probe-2 or Probe-3, and 30 ng of genomic DNA. The reactions were conducted on a BioRad CFX 96 instrument (BioRad Inc., Hercules, CA, USA) with the following thermal profile: 95 ◦ C for 5 min for initial denaturation, followed by 40 cycles of 95 ◦ C for 30 s (denaturation), and 60 ◦ C for 30 s (annealing, extension, and signal acquisition on FAM and HEX channels). Negative controls and samples with known rs6507691 genotypes were included. Genotypes of participants were manually determined based on amplification curves. For the Russian athletes and control subjects, molecular genetic analysis was performed with DNA obtained from leuko- cytes (4 mL of venous blood). DNA extraction and purification were conducted using a commercial kit according to the manufacturer’s instructions (Technoclon, Moscow, Russia). Genotyping of rs6507691 was performed using microarray technology (Illumina, San Diego, CA, USA) with HumanOmni1-Quad and HumanOmniExpress BeadChips (Illumina), as previously described [11]. 2.5. Gene-Expression Analysis Transcriptomic analysis was performed as previously described [18,45]. Briefly, to minimize confounding factors related to muscle recovery and prior activity, participants (n= 23) were instructed to refrain from training for at least 24 h before the
rs6507691 was performed using microarray technology (Illumina, San Diego, CA, USA) with HumanOmni1-Quad and HumanOmniExpress BeadChips (Illumina), as previously described [11]. 2.5. Gene-Expression Analysis Transcriptomic analysis was performed as previously described [18,45]. Briefly, to minimize confounding factors related to muscle recovery and prior activity, participants (n= 23) were instructed to refrain from training for at least 24 h before the biopsy. This rest period was implemented to ensure the gene-expression profiles reflected a baseline, resting state, without the acute effects of exercise. RNA was isolated from muscle tissue using the RNeasy Mini Fibrous Tissue Kit (Qiagen, Hilden, Germany). RNA concentration was measured using the Qubit spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). RNA quality was assessed using the BioAnalyzer electrophoresis system and BioAnalyzer RNA Nano assay (Agilent Technologies, Santa Clara, CA, USA). The RNA integrity number (RIN) was calculated for each RNA sample. Only RNA samples with RIN > 7 were included in the study. Samples were stored at−80 ◦ C until sequencing libraries were prepared. Total RNA samples were treated with DNAse I using the Turbo DNA-free Kit (Thermo Fisher Scientific) according to the kit guidelines. Libraries for RNA sequencing were prepared using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina with the NEBNext rRNA Depletion Module (New England Biolabs, Ipswich, MA, USA). RNA libraries were sequenced on the HiSeq system (Illumina) for 250 cycles. Gene-level expression abundances were calculated using the tximport Bioconductor package [47], with ARK2Ngene expression presented in transcripts per kilobase million (TPM). Transcriptome analyses of muscle samples from the FUSION cohorts were described by Taylor et al. [46]. 2.6. Evaluation of Muscle Fiber Composition The muscle fiber composition of the vastus lateralis in strength athletes was assessed using immunohistochemistry, as previously described [11]. Briefly, samples from the left vastus lateralis were collected using the modified Bergström needle technique. Prior to analysis, samples were frozen in liquid nitrogen and stored at−80 ◦ C. Serial cross-sections (7µm) were obtained from frozen samples using an ultratom (Leica Microsystems, Wetzlar, Germany). Sections were thaw-mounted on Polysine glass slides, maintained at room
[11]. Briefly, samples from the left vastus lateralis were collected using the modified Bergström needle technique. Prior to analysis, samples were frozen in liquid nitrogen and stored at−80 ◦ C. Serial cross-sections (7µm) were obtained from frozen samples using an ultratom (Leica Microsystems, Wetzlar, Germany). Sections were thaw-mounted on Polysine glass slides, maintained at room
Metabolites2024,14, 684 5 of 13 temperature (RT) for 15 min, and incubated in PBS (3×5 min). The sections were then incubated at RT in primary antibodies against slow or fast isoforms of the myosin heavy chains (M8421, 1:5000; M4276; 1:600, respectively; Sigma–Aldrich, St. Louis, MO, USA) for 1 h and incubated in PBS (3×5 min). Next, the sections were incubated at RT in secondary antibodies conjugated with FITC (F0257; 1:100; Sigma–Aldrich) for 1 h. The antibodies were removed, and the sections washed in PBS (3×5 min), placed in mounting media and covered with a cover slip. Images were captured by fluorescent microscope (Eclipse Ti-U, Nikon, Tokyo, Japan). Fibers stained in serial sections with antibodies against slow and fast isoforms were considered to be hybrid fibers. Muscle fiber composition in the vastus lateralis of the FUSION cohort was estimated based on the expression ofMYH1,MYH2, andMYH7genes, as previously described [46]. 2.7. Statistical Analyses Statistical analyses were performed using SPSS software version 29.0. Allelic and genotypic frequencies were assessed for the Hardy–Weinberg equilibrium (HWE) and evaluated using the chi-square (χ 2) or Fisher’s exact test. Sample size and power calcula- tions were performed using G*Power (v3.1) with the chi-squared test for proportions to ensure sufficient power to detect a difference in allelic frequencies between athletes and controls. Associations with alleles or genotypes were determined using SNPStats software v1 [48] with co-dominant, dominant, recessive, and over-dominant models. The SNPStats results were further validated using one-way ANCOVA with sex and sports experience as categorical covariates. A normality test was used to assess the linearity of the data. Mean differences between groups were analyzed using Student’s unpairedt-test. Relationships between gene expression and muscle-related traits were assessed using regression analysis adjusted for covariates (age and sex). Scatter plots were generated based on Pearson corre- lation coefficients. A Pearson correlation was used to calculate the correlation coefficient (r) and the coefficient of determination (R 2 ). All data are presented as mean (SD), with p-values < 0.05 considered statistically significant. 3. Results 3.1. Gene-Expression Studies ARK2Ngene expression was significantly higher (5.7 (1.0) vs. 5.0 (0.5) TPM,p= 0.042) in
plots were generated based on Pearson corre- lation coefficients. A Pearson correlation was used to calculate the correlation coefficient (r) and the coefficient of determination (R 2 ). All data are presented as mean (SD), with p-values < 0.05 considered statistically significant. 3. Results 3.1. Gene-Expression Studies ARK2Ngene expression was significantly higher (5.7 (1.0) vs. 5.0 (0.5) TPM,p= 0.042) in the vasus lateralis muscle of power athletes (n= 10) compared to endurance athletes (n= 13) (FigureMetabolites 2024, 14, x FOR PEER REVIEW 6 of 14 Figure 1. Comparison of Arkadia (RNF111) N-terminal-like PKA signaling regulator 2N (ARK2N) gene expression between power and endurance athletes. In the FUSION cohort (n = 291), males and females had significantly different pro- portions of type IIA muscle fibers (33.0% vs. 39.2%, p < 0.0001); therefore, we adjusted our results for sex and age. Accordingly, ARK2N gene expression was positively associated with the proportion of oxidative fast-twitch (type IIA) muscle fibers in untrained subjects (p = 0.017, adjusted for age and sex; females: p = 0.029, r = 0.2, R 2 = 4%; males: p = 0.124, r = 0.12, R 2 = 1.4%) (Figure 2). This association remained significant (p = 0.019) after adjusting for body mass index and smoking status as additional covariates. No significant relation- ship was observed between ARK2N gene expression and the proportion of glycolytic fast- twitch (type IIX) muscle fibers (p = 0.654) or slow-twitch (type I) muscle fibers (p = 0.242). Figure 2. Relationship between Arkadia (RNF111) N-terminal-like PKA signaling regulator 2N (ARK2N) gene expression and the proportion of type IIA muscle fibers in the FUSION cohort (p = 0.017; adjusted for age and sex). 3.2. Case-Control and Genotype–Phenotype Studies According to the GTEx portal (https://gtexportal.org/; accessed on 9 November 2024), the ARK2N gene includes several functional variants. Among these, the ARK2N rs6507691 C/T polymorphism is one of the most significant, with the T allele associated with higher ARK2N gene expression (p = 3.8 × 10 −12 ). We therefore analyzed this polymorphism in the athlete cohorts and control groups. Figure 1.Comparison of Arkadia (RNF111) N-terminal-like PKA signaling
Description
This study investigates the association of the ARK2N gene variant with muscle fiber size and strength in athletes.