| Grant number: | 12/22516-6 |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| Start date: | March 01, 2013 |
| End date: | January 31, 2017 |
| Field of knowledge: | Health Sciences - Physical Education |
| Principal Investigator: | Antonio Herbert Lancha Junior |
| Grantee: | João Paulo Limongi França Guilherme |
| Host Institution: | Escola de Educação Física e Esporte (EEFE). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
Abstract The human genome project revealed that the human genetic code is 99.9% identical between each individual, so there is a variation of 0.1% which can explain differences between individuals. While all humans possess the same genes, have been identified structural variations (polymorphisms) in genes that show associations with phenotypes related to physical performance. Since the sports performance is a polygenic phenomenon, i.e. influenced by several genes, the association of a single polymorphism is insufficient to characterize an athlete. Therefore, there is currently an effort to identify the distribution of various polymorphisms (polygenic profile) existing in elite athletes. Initial studies have already outlined a preliminary polygenic profile of European athletes, which does not imply that other populations will exhibit the same profile. The objective of this project is therefore to draw for the first time a polygenic profile of Brazilian athletes. Eight genes were selected to trace the profile of endurance athletes: ACE, AGT, ACTN3, AMPD1, CNTF, GABPB1, MSTN and PPARGC1A. Likewise, eight genes are used to identify the profile of strength and power athletes: ACE, AGT, ACTN3, ACTVR1B, CNTF, IGF1, MSTN and NOS3. A cohort of non-athletes (controls) will also have their genotype determined for the same genes. All genotypes will be determined by real time PCR. The total genotyping score (TGS), proposed in 2008, will be calculated for each individual. The score was based on the alleles structural existing for each of the genes described above. The distribution and frequency of polymorphisms will be analyzed using contingency tables. The TGS will be expressed as mean ± standard deviation and the results will be compared between groups of athletes and non-athletes through the Kruskal-Wallis test. | |
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