Detection of epistasis between ACTN3 and SNAP-25 with an insight towards gymnastic aptitude identification

In this study, we performed an analysis of the impact of performance enhancing polymorphisms (PEPs) on gymnastic aptitude while considering epistatic effects. Seven PEPs (rs1815739, rs8192678, rs4253778, rs6265, rs5443, rs1076560, rs362584) were considered in a case (gymnasts)–control (sedentary individuals) setting. The study sample comprised of two athletes’ sets: 27 elite (aged 24.8 ± 2.1 years) and 46 sub-elite (aged 19.7 ± 2.4 years) sportsmen as well as a control group of 245 sedentary individuals (aged 22.5 ± 2.1 years). The DNA was derived from saliva and PEP alleles were determined by PCR, RT-PCR. Following Multifactor Dimensionality Reduction, logistic regression models were built. The synergistic effect for rs1815739 x rs362584 reached 5.43%. The rs1815739 x rs362584 epistatic regression model exhibited a good fit to the data (Chi-squared = 33.758, p ≈ 0) achieving a significant improvement in sportsmen identification over naïve guessing. The area under the receiver operating characteristic curve was 0.715 (Z-score = 38.917, p ≈ 0). In contrast, the additive ACTN3 –SNAP-25 logistic regression model has been verified as non-significant. We demonstrate that a gene involved in the differentiation of muscle architecture–ACTN3 and a gene, which plays an important role in the nervous system–SNAP-25 interact. From the perspective originally established by the Berlin Academy of Science in 1751, the matter of communication between the brain and muscles via nerves adopts molecular manifestations. Further in-vitro investigations are required to explain the molecular details of the rs1815739 –rs362584 interaction.

Furthermore, the Reviewer is free to recalculate our findings since the data input is fully available (Supplementary Material S4).

QUERY:
Have the authors made all data underlying the findings in their manuscript fully available? ANSWER: Data input has been attached as Supplementary Material S4 (.xlsx).

REVIEWER'S COMMENTS TO THE AUTHORS:
COMMENT: As we know that only one allele could not represent a gene. If you want to study the interaction of these 7 genes (ACTN3, PPARGC1A, PPARα, BDNF, AS GNB3, DRD2, SNAP-25), you should include all tag SNPs.

ANSWER:
Indeed, one may find and compile broad list of tag SNP (tSNP) of ACTN3, PPARGC1A, PPARα, BDNF-AS, DRD2, GNB3, SNAP-25 genes [1][2][3][4][5][6][7]. However, in this research, we concentrated on genetic markers that were found to be linked with the elite athlete status [8]. They are regarded as performance enhancing polymorphisms (PEPs) and are believed to play a functional role in athletic performance. It is very well true that apart from the PEPs, which we considered, interactions between other genetic loci could occur. However, expanding the analysis to include all tag SNPs (tSNPs) does not guarantee robustness for stochastic models in the aspect of predicting a predisposition to become a professional gymnast. Of note, till 2016 only twelve genetic markers have shown a positive correlation with the athlete status it at least three or more studies [9] (lines 370-375 (here and below, please compare no marks version after revision)). We wish to point out that a similar PEP-focused analysis has been performed by Tringalia et al. (2014); this analysis included only five SNPs [10].
Furthermore, we agree that any given PEP or SNP is only a part of a specific gene.
However, the interaction between SNPs represents the relationship between entire genes, or de facto their molecular products i.e. the proteins that are encoded by those genes. This line of thinking does not deviate from what is generally accepted in the scientific community. Here, we present a couple of citation records: " … interactions between genetic variants, that is genegene interactions …" [11], "… interactions between genetic variants, that is, gene-gene (whether nuclear or mitochondrial) and gene-environment interactions." [12]. In parallel, the same meaning and terminology have been applied in the main text of our study: "An additional corroboration of our results is the fact that the gene * gene interaction at the rs1815739 and rs362584 loci…" (lines: 350-351) and "This study confirms the interaction between variants in the ACTN3 and SNAP-25 loci." (lines: 48-49).
What is more, it must be acknowledged that when studying complex traits, the potential number of interactions to be tested is enormous [13]. While, the actual size of current marker panels is typically smaller than 1,000,000 SNPs [14] there is a difficulty in setting genome-wide significance level [15]. So, reducing the search space to focus on a particular research question, allows hypotheses to be convincingly tested. For example, assuming two hundred and thirty-nine fitness-related genes [8], the total number of two-way interaction (k = 2) combinations is 56,882. Consequently, type zero hypothesis comprises the expression: Bearing in mind the details stated above, as well as similar research hypotheses tested in [18][19][20], we wish to argue that the suggestion of testing all tag SNPs should not be regarded as a requirement to answer the sort of questions we have asked in this study. COMMENT: Please give the statistical power of this study.

ANSWER:
The results of the power analysis have been provided in the text of the manuscript (line 245 and Figure 2). The true positive fraction (TPF) indicates the power and sensitivity of the discriminatory model [21]. After data processing, TPF totalled 60%, which is significantly better than naïve guessing. Importantly, many other statistics present a broader view of the