P-8 Is the AMPD1 polymorphism associated with aerobic performance?

Abstract

We studied frequencies of AMPD1 C34T, UCP2 Ala55Val, ACE I/D, BDKRB2 + 9/−9 and NOS3 Glu298Asp variants in a group of triathletes who were participants of Czechman Triathlon Race 2013 in the Czech Republic. Buccal swap samples were taken from 118 competitors but from only 101 of them we gained complete data including the final race time. Our results showed that only frequency AMPD1 CT genotype was significantly overrepresented in a group of athletes who finished the race in 300 min compared to athletes did not (36.1% vs. 12.3%; P = 0.007) while AMPD1 TT genotype was missing in our group of subjects. This test also fails to reject the null hypothesis that the population is in Hardy-Weinberg equilibrium (χ2 = 1,3499; df = 1; p = 0.25). Adenosine monophosphate deaminase (AMPD) is one of the most important regulators of muscle energy metabolism during exercise. AMPD displaces the equilibrium of the myokinase reaction toward ATP production (2 ADP ↔ ATP +AMP) by converting AMP to inosine monophosphate (IMP). An activity of this enzyme, encoded by AMPD1 gene, can be affected by the C34T genetic polymorphism. These results are quite surprising in the light of previously published studies where 34T allele is considered to be relatively unfavourable for sports performance in general. On the other hand, our results are consistent with the recently published study Lifanov et al. (2014) showing higher frequencies of 34T allele in soccer players compared to sedentary controls. Thus 34T allele could potentially be useful for long-term endurance activities. Acknowledgment This research has been supported by the project of Ministry of Education Youth and Sport, Czech Republic [PRVOUK n. 38]. References Lifanov D, Khadyeva MN, Rahmatullina L, Demenev S V, Ibragimov, RR. Effect of creatine supplementation on physical performance are related to the AMPD1 and PPARG genes polymorphisms in football players. Rossiiskii Fiziologicheskii Zhurnal Imeni I. M. Sechenova, 2014 Jun;100(6):767–776. Sole X, Guino E, Valls J, Iniesta R, Moreno, V. SNPStats: a web tool for the analysis of association studies. Bioinformatics, 2006 Aug;22(15):1928–1929.