The relevance of this study here is that adds evidence to what I have said many times, that you can train as hard as you want, but you will never get even close to the person who has the right genes. The only way to bridge that gap is to manipulate what the lack of right genes can't achieve, that is the use of illegal drugs. Only then you can have a yield and recovery that can do what training can't do. Is that the final solution ? No, because we live in a time and age that we have the people who are already genetically gifted who will also make use of illegal drugs, again widening the gap with those who don't have the right genes and take drugs. So at the end of the day, the problem is unsolvable unless you involve gene manipulation or selection. In many sports though we are now likely close to the limits of human performance that is already a combination of ideal factors in terms of technique, genes, drugs, and environmental conditions.
The full reference of the study is: Thomaes T., et al.: Genetic Predisposition Scores Associate with Muscular Strength, Size, and Trainability. Med. Sci. Sports Exerc. 45, 8: 1451–1459, 2013.
The Abstract of the study is here:
Abstract/Introduction: The number of studies trying to identify genetic sequence variation related to muscular phenotypes has increased enormously. The aim of this study was to identify the role of a genetic predisposition score (GPS) based on earlier identified gene variants for different muscular endophenotypes to explain the individual differences in muscular fitness characteristics and the response to training in patients with coronary artery disease.
Methods: Two hundred and sixty coronary artery disease patients followed a standard ambulatory, 3-month supervised training program for cardiac patients. Maximal knee extension strength (KES) and rectus femoris diameter were measured at baseline and after rehabilitation. Sixty-five single nucleotide polymorphisms (SNP) in 30 genes were selected based on genotype–phenotype association literature. Backward regression analysis revealed subsets of SNP associated with the different phenotypes. GPS were constructed for all sets of SNP by adding up the strength-increasing alleles. General linear models and multiple stepwise regression analysis were used to test the explained variance of the GPS in baseline and strength responses. Receiver operating characteristic curve analyses were performed to discriminate between high- and low-responder status.
Results: GPS were significantly associated with the rectus femoris diameter (P < 0.01) and its response (P < 0.0001), the isometric KES (P < 0.05) and its response (P < 0.01), the isokinetic KES at 60°·s−1 (P < 0.05) and 180°·s−1 (P < 0.001) and their responses to training (P < 0.0001), and the isokinetic KES endurance (P < 0.001) and its change after training (P < 0.0001). The GPS was shown as an independent determinant in baseline and response phenotypes with partial explained variance up to 23%. Receiver operating characteristic analysis showed a significant discriminating accuracy of the models, including the GPS for responses to training, with areas under the curve ranging from 0.62 to 0.85.
Conclusion: GPS for muscular phenotypes showed to be associated with baseline KES, muscle diameter, and the response to training in cardiac rehabilitation patients.