Hypoxic Inducible Factor 1A is one of the markers that frequently been studied in genomics area whether in medical or sport genomics due to the important functions that it carried. Like in the sports genomics which began in the early of 2000s, HIF1A gene polymorphism had been studied in more than 5 studies since then. They were involving athletes mostly from the European and the Caucasian. Positive results of the studies were analyzed and reported in a lot of of the researches that focusing in current state of the sport genomic knowledge around the world.
2.1 Related studies
Functions of HIF1A gene polymorphism
Based on the list of the evidences, HIF1A gene polymorphisms is one of the markers that contribute to the polygenic profile of an elite athlete. It is probably due to its functions that importantly play role in the physiology of the human performances such as controlling the transcription gene for glucose metabolism and tissue oxygenation. The gene polymorphism of HIF1A will increase its transcriptional activity, hence leading to benefits in human performances. For example, when there are tissues in high Oxygen demand after working in very high intensity, it responded to them by regulating the angiogenesis (proliferation of new blood vessels) , red cells productions (erythropoiesis) and glycolysis (glucose metabolism) as a body acclimation to hypoxia (Lippi, Longo, & Maffulli, 2010).
Its importance in glycolysis as the first sources for energy in anaerobic metabolism are being studied in Russian sprint athletes and it is suggested positive result that HIF1A P582S gene polymorphism distributed in the athletes compared with sedentary controls (Ahmetov, Ii, Hakimullina, Lyubaeva, Vinogradova, & Rogozkin, 2008). Besides, this study by (Ahmetov, Ii et al., 2008) also reported that HIF1A P582S gene polymorphism significantly associated with muscles growth and composition when proportion of a fast twitch muscles fibers in m. vastus lateralis of all-round speed skaters increased. Thus, it suggested that this polymorphism also does have an effect on muscles composition and growth.
Endurance vs strength athletes
In the area of classifying the HIF1A P582S into endurance or strength markers, it was something conflicting as there are studies that showed positive results in both training. Thus, a study by (Ahmetov, Ildus & Fedotovskaya, 2015) showed a few studies conducted by the researchers around the world according to the endurance or strength markers. Few studies reported the positive distributions of the HIF1A gene polymorphism in strength/power athletes and most of them corresponded in European and Caucasian athletic population such as Polish (Ci?szczyk et al., 2011), Russians (Gabbasov et al., 2013) and Ukrainians (Drozdovska, Dosenko, Ahmetov, & Ilyin, 2013). All of these studies suggested significant association between HIF1A P582S gene polymorphism and power/strength athlete physical performances. On the other hand, these studies conflicting with a study that showed a negative association between the gene polymorphism of HIF1A P582S and physical performances of 265 strength/power Israeli athletes (Eynon et al., 2010).
There were also study reported that HIF1A P582S gene polymorphisms may associate with the endurance capacity of the human physical performances. As reported by (Prior et al., 2003), the participant who had rare T allele at 55 years old had increased the VO2 Max through 24weeks of aerobic training to a similar extent of those having wild type allele. This also followed by a study that reported the gene polymorphism might be related to endurance training when the polymorphism had been detected in 316 Caucasian endurance athletes (Döring et al., 2010). On the other hand, (Ahmetov, I. I. et al., 2009) showed a negative association between the gene polymorphism and physical performances of endurance athletes.
Combination of 2 genetic polymorphisms
Based on a study by (Ostrander, Huson, & Ostrander, 2009), performance enhanced polymorphism also work together as a combined polymorphisms to produce synergistic effects on the physical performances. For example in a study by (Williams et al., 2004) , the author reported that combination of Angiotensin Converting Enzyme Inhibitor (ACE I) and Bradykinin Beta 2 Receptor (BDKRB2-9) genetic polymorphisms was significantly associated in endurance elite athlete status while combination of genetic polymorphism of Bradykinin Beta 2 Receptor (BDKRB2) and Nitric Oxide Synthase (NOS3) associated in endurance performance of the participants in Ironman Triathlon (Saunders et al., 2006). These studies corresponded to a study that reported on combination between the genetic polymorphism of HIF1A (Pro/Pro) homozygous and ACTN3 RR allele which enhancing on the sprint performance in 155 sprint athletes (Eynon et al., 2010). Otherwise, to the extent of the knowledge there is no other research on the combination of HIF1A P582S and other genetic markers.
HIF1A gene polymorphisms in medical – related studies.
HIF1A is believed to be the master of regulator of the various genes implicated in glucose metabolism, cell survivors and angiogenesis (Tanimoto et al., 2003). In a cancer-related study by (Tanimoto et al., 2003) in head and neck squamous cell carcinoma (HNSCC), it is reported that the patients with the rare T allele exhibited increment of the microvessels (angiogenesis) as an adaptive responses to hypoxia and possibly influenced the tumor growths. It is also been studied widely in diseases related studies to see the distribution of the gene polymorphism and the pathogenesis of the disease. Related to that, there were some positive results that showed the HIF1A gene polymorphism associated with diseases such as Type 2 Diabetes (Nagy et al., 2009; Yamada et al., 2005), Diabetic Foot Ulcers (Pichu, Sathiyamoorthy, Krishnamoorthy, Umapathy, & Viswanathan, 2015) and renal cell carcinoma (Ollerenshaw, Page, Hammonds, & Demaine, 2004).
After all, a study to deepen the knowledge on this genetic polymorphism of HIF1A P582S should be considered as no study had been conducted in Asian population especially in Malaysian population. Furthermore, this current study will determine the type of physical performances that this genetic polymorphism do enhance whether it is endurance or strength markers based on physical test that will be administered among the athletes.
The purpose of this study is to investigate the genotypic frequencies polymorphism of HIF1A P582S in Malaysian adolescent athletes and its association in enhancing their physical performances.
3.1 Research Design
A Non-Experimental Causal Comparative Design will be used to test the hypothesis in this research. This is because it attempts to determine the cause of differences that already exist between groups of individuals (athletes and sedentary) and the research seeks to identify associations among variables. Besides, since the genetic variation could not be manipulated as it is inborn nature, there is no choice of conducting it by experimental research.
3.2 Sample and Sampling Techniques
The study will be conducted on experienced athletes and the sample will be specifically recruited among adolescent athletes. Using a purposive sampling method, 80 male adolescent active athletes (footballers) from National Sport School were selected based on their certain experience and characteristics. They were young athletes with the age ranging from 13 to 14 years old, representing schools in sports competitions and had minimum 3 years of football experiences.
Otherwise, for control groups, 80 sedentary controls were prepared from young student that were healthy, performing 2 or fewer days in a week of recreational activities less than 30 min for the past 3 months prior to data collection (Pate, O’neill, & Lobelo, 2008).
Permission by the Human Research Ethics Committee in University Teknologi MARA will be applied before doing all the procedures.
3.3 Procedure and instrumentation
3.3.1 Anthropometric measurement
Firstly, subject’s body height was measured by portable stadiometer (Seca 213,Seca Corporation, USA).Then, subject’s body weight, body mass index and body fat were measured by Omron KARADA Scan Body Composition & Scale (HBF-362, Omron Corporation, Japan) .
3.3.2 Physical test
Physical test will then administer to the athletes to determine their endurance and strength performances.
1. Beep test (Progressive Aerobic Cardiovascular Endurance Run)
Participants ran from one marker to another marker set 20 m apart, while keeping pace with a prerecorded cadence. The cadence is set to music and increased every minute. Participants were instructed to keep up with the cadence for as long as possible. The test was terminated when a participant failed to reach the appropriate marker in the allocated time twice or could no longer maintain the pace. The number of laps completed was recorded (Welk & Meredith, 2010).
2. Isometric handgrip strength test
The test will be performed on a hand dynamometer (Takei A5401, Takei Scientific Instrument Co. Ltd., Japan). The dynamometer is calibrated. The participant will hold the dynamometer with the arm hanging straight. When all set, the atlete squeezed the dynamometer maximally for 5 seconds. The athletes perform for 3 times and the average score recorded (Welk & Meredith, 2010).
3.3.3 Genotyping Procedure
DNA sample taken from buccal swab of the subject using Sterile Swab Applicator (Classic Swabs by Copan Flock Technologies, Bresica, Italy). Then, isolation of genomic DNA from the swab by GeneAll ExgeneTM Cell SV Kit (GeneAll Biotechnology Co. Ltd., Seoul, South Korea).
Polymerase Chain Reaction (PCR) was subsequently done using PCR the product were genotyped by restriction fragment length polymorphism (RFLP). Then, the product was amplified with primers were as follows: forward 5′ –GACTTTGAGTTTCACTTGTTT -3′ and reverse 5′ ACTTGCGCTTTCAGGGCTTGCGGAACTGCTT -3′ generating a fragment of 197 bp (base pair).
The polymerase chain reaction products were digested with NmuCI (ThermoFisher Scientific) for 12 hours at 37ºC and were separated by 8% polyacrylamide gel electrophoresis, stained with ethidium bromide, and visualized in ultraviolet light.
3.4 Data Analysis
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