MAIN BODY: A total of 42 studies were included in the analysis, with a total number of 41,054 individuals (of which 10,442 were in the athlete group and 30,612 in the control group). For each study included in the analysis, the agreement of genotype frequencies with Hardy-Weinberg equilibrium was tested, as well as the presence of an excess or deficit of heterozygotes. Prediction intervals for the overall effect size (OR-odds ratio) was estimated. Both in the subgroups of athletes and controls, a significant difference FIS from zero was found, suggesting inbreeding or outbreeding, as well as a very wide 95% CI for FIS. A meta-analysis was conducted for dominant, codominant, and recessive inheritance models. The obtained ORs and their 95% CIs were in the range of almost negligible values or have very wide CIs. The evaluation for the recessive model showed 95% PI for the OR lies between 0.74 to 1.92. Statistically, it does not differ from zero, which means that in some 95% of studies comparable to those in the analysis, the true effect size will fall in this interval.
CONCLUSION: Despite numerous attempts to identify genetic variants associated with success in elite sports, progress in this direction remains insignificant. Thus, no sports or sports roles were found for which the C > T variant of the ACTN3 gene would be a reliable prognostic marker for assessing an individual predisposition to achieve high sports performance. The results of the present meta-analysis support the conclusion that neutral gene polymorphism-from evolutionary or adaptive point of view-is not a trait that can be selected or used as a predictive tool in sports.
METHODS: A two-sample bidirectional MR analysis was conducted using data from individuals of European ancestry, utilizing genome-wide association studies (GWAS) statistics. The study selected instrumental single nucleotide polymorphisms (SNPs) significantly associated with circulating cytokines and applied multiple MR methods, including inverse variance weighted (IVW), Weighted Median, MR-Egger, Weighted Mode, Simple Mode, and MR-PRESSO. The traits analyzed were appendicular lean mass (ALM) and grip strength. Heterogeneity, robustness, and consistency of results were assessed using Cochran's Q statistic, MR-Egger regression, and "leave-one-out" sensitivity analyses.
RESULTS: The IVM-MR analysis showed a casual association between genetically predicted circulating levels of interleukin-16 and both ALM and grip strength (ALM: OR = 0.990, 95% CI: 0.980-1.000, p = .049; grip strength: OR = 0.971, 95% CI: 0.948-0.995, p = .020). Additionally, interferon-gamma-induced protein 10 (IP-10), interleukin-1-beta (IL-1β), and hepatocyte growth factor (HGF) were correlated with ALM and vascular endothelial growth factor (VEGF), interleukin-12 (IL-12), and interleukin-5 (IL-5) with grip strength. Comparable results were confirmed via the MR-Egger, Weighted Median, Weighted Mode, and Simple Mode methods. Sensitivity analysis showed no horizontal pleiotropy to bias the causal estimates.
CONCLUSION: The results suggest a significant causal effect of inflammatory cytokines on sarcopenia, offering new avenues for therapeutic target development. However, the study's focus on a European ancestry cohort limits its generalizability to other populations. Future research should aim to include diverse ethnic groups to validate and broaden these findings, thereby enhancing our understanding of sarcopenia's mechanisms in a global context.
METHODS: The BDNF target sequence was detected on a capture probe attached on aluminum microcomb electrodes on the silicon wafer surface. A capture-target-reporter sandwich-type assay was performed to enhance the detection of the BDNF target.
RESULTS: The limit of detection was noticed to be 100 aM. Input of a reporter sequence at concentrations >10 aM improved the detection of the target sequence by enhancing changes in the generated currents. Control experiments with noncomplementary and single- and triple-mismatches of target and reporter sequences did not elicit changes in current levels, indicating the selective detection of the BDNF gene sequence.
CONCLUSION: The above detection strategy will be useful for the detection and quantification of BDNF, thereby aiding in the provision of suitable treatments for BDNF-related disorders.