Background and Objective. Based on the results of many studies, the angiotensinconverting enzyme (ACE) and the α-actinin-3 (ACTN3) genes are considered strong candidate genes associated with human physical performance. On the other hand, the data regarding the association of the ACE I/D and ACTN3 R/X polymorphisms with human physical performance in different populations have been conflicting. The objective of our research was to evaluate the significance of these genetic variants on muscle performance phenotype in Lithuanian athletes. Material and Methods. The study involved 193 Lithuanian elite athletes and 250 controls from the general Lithuanian population. Genotyping was performed by polymerase chain reaction and/ or restriction fragment length polymorphism analysis. Anthropometric measurements and muscle strength (grip strength and vertical jump) were measured. Results. It was determined that ACE I/I and I/D genotypes were more frequent in the athlete group compared with the general Lithuanian population. The results of grip strength and vertical jum p were better in the athletes with the ACE I/I and ACTN3 X/X genotype compared with the athletes with ACE D/D and ACTN3 R/R, respectively. Conclusions. The ACE I and ACTN3 X alleles determine speed and power for Lithuanian athletes. In line with other researchers, it can be confirmed that the absence of a functional ACTN3 in fast-twitch muscle fibers is compensated. Lithuanian athletes who are carriers of the ACE I/I and I/D as well as ACTN3 X/X and R/X genotypes have the potential to achieve better results in power-requiring sports; therefore, the analyzed polymorphisms of these genes might be used as the criteria for the sport type selection.

BackgroundThe C34T genetic polymorphism (rs17602729) in the AMPD1 gene, encoding the skeletal muscle-specific isoform of adenosine monophosphate deaminase (AMPD1), is a common polymorphism among Caucasians that can impair exercise capacity. The aim of the present study was twofold: (1) to determine the C34T AMPD1 allele/genotype frequency distributions in Lithuanian athletes (n = 204, stratified into three groups: endurance, sprint/power and mixed) and compare them with the allele/genotype frequency distributions in randomly selected healthy Lithuanian non-athletes (n = 260) and (2) to compare common anthropometric measurements and physical performance phenotypes between the three groups of athletes depending on their AMPD1 genotype.ResultsThe results of our study indicate that the frequency of the AMPD1 TT genotype was 2.4% in the control group, while it was absent in the athlete group. There were significantly more sprint/power-orientated athletes with the CC genotype (86.3%) compared with the endurance-orientated athletes (72.9%), mixed athletes (67.1%), and controls (74.2%). We determined that the AMPD1 C34T polymorphism is not associated with aerobic muscle performance phenotype (VO2max). For CC genotype the short-term explosive muscle power value (based on Vertical Jump test) of athletes from the sprint/power group was significantly higher than that of the endurance group athletes (P < 0.05). The AMPD1 CC genotype is associated with anaerobic performance (Vertical Jump).ConclusionsThe AMPD1 C allele may help athletes to attain elite status in sprint/power-oriented sports, and the T allele is a factor unfavourable for athletics in sprint/power-oriented sports categories. Hence, the AMPD1 C allele can be regarded as a marker associated with the physical performance of sprint and power. Replications studies are required to confirm this association.

Coronary heart disease (CHD) is a complex and heterogeneous cardiovascular disease. There are many genome-wide association studies (GWAS) performed worldwide to extract the causative genetic factors. Moreover, each population may have some exceptional genetic characteristic. Thus, the background of our study is from the previous Lithuanian studies (the LiVicordia Project), which demonstrated the differences of the atherosclerosis process between Lithuanian and Swedish male individuals.In this study we performed GWAS of 32 families of Lithuanian origin in search of significant candidate genetic markers [single nucleotide polymorphisms (SNPs)] of CHD in this population. After careful clinical and biochemical phenotype evaluation, the ∼770K SNPs genotyping (Illumina HumanOmniExpress-12 v1.0 array) and familial GWAS analyses were performed.Twelve SNPs were found to be significantly associated with the CHD phenotype (p value <0.0001; the power >0.65). The odds ratio (OR) values were calculated. Two SNPs (rs17046570 in the RTN4 gene and rs11743737 in the FBXL17 gene) stood out and may prove to be important genetic factors for CHD risk. Our results correspond with the findings in other studies, and these two SNPs may be the susceptibility loci for CHD.

BackgroundEvery next generation sequencing (NGS) platform relies on proprietary and open source computational tools to analyze sequencing data. NGS tools for Illumina platforms are well documented which is not the case with AB SOLiD systems. We applied several computational and variant calling pipelines to analyse targeted exome sequencing data obtained using AB SOLiD 5500 system. Our investigated tools comprised proprietary LifeScope’s pipeline in combination with open source color-space competent mapping programs and a variant caller. We present instrumental details of the pipelines that were used and quantitative comparative analysis of variant lists generated by LifeScope’s pipeline versus open source tools.ResultsSufficient coverage of targeted regions was achieved by all investigated pipelines. High variability was observed in identities of variants across the mapping programs. We observed less than 50 % concordance of variant lists produced by approaches based on different mapping algorithms. We summarized different approaches with regards to coverage (DP) and quality (QUAL) properties of the variants provided by GATK and found that LifeScope’s computational pipeline is superior. Fusion of information on mapping profiles (pileup) at genomic positions of variants in several different alignments proved to be a useful strategy to assess questionable singleton variants.ConclusionsWe quantitatively supported a conclusion that Lifescope’s pipeline is superior for processing sequencing data obtained by AB SOLiD 5500 system. Nevertheless the use of alternative pipelines is encouraged because aggregation of information from other mapping and variant calling approaches helps to resolve questionable calls and increases the confidence of the call. It was noted that a coverage threshold for variant to be considered for further analysis has to be chosen in data-driven way to prevent a loss of important information.