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The incidence of cystic fibrosis (CF) and the spectrum of cystic fibrosis transmembrane conductance regulator (CFTR) gene variants differ among geographic regions. Differences in CF carrier distribution are also reported among Italian regions. We described the spectrum of the CFTR variants observed in a large group of subjects belonging from central-southern Italy. We also provide a predictive evaluation of the novel variants identified. CFTR screening was performed in a south-central Italian cohort of 770 subjects. We adopted a next-generation sequencing (NGS) approach using the Devyser CFTR NGS kit on the Illumina MiSeq System coupled with Amplicon Suite data analysis. Bioinformatics evaluation of the impact of novel variants was described. Overall, the presence of at least one alternative allele in the CFTR gene was recorded for 23% of the subjects, with a carrier frequency of CF pathogenic variants of 1:12. The largest sub-group corresponded to the heterozygous carriers of a variant with a conflicting interpretation of pathogenicity. The common CFTR p.(Phe508del) pathogenic variants were identified in 37% of mutated subjects. Bioinformatics prediction supported a potential damaging effect for the three novel CFTR variants identified: p.(Leu1187Phe), p.(Pro22Thr), and c.744-3C > G . NGS applied to CF screening had the benefit of: effectively identifying asymptomatic carriers. It lies in a wide overview of CFTR variants and gives a comprehensive picture of the carrier prevalence. The identification of a high number of unclassified variants may represent a challenge whilst at the same time being of interest and relevance for clinicians.

Next-generation sequencing (NGS) is nowadays commonly used for clinical purposes, and represents an efficient approach for the molecular diagnosis of familial hypercholesterolemia (FH). Although the dominant form of the disease is mostly due to the low-density lipoprotein receptor (LDLR) small-scale pathogenic variants, the copy number variations (CNVs) represent the underlying molecular defects in approximately 10% of FH cases. Here, we reported a novel large deletion in the LDLR gene involving exons 4-18, identified by the bioinformatic analysis of NGS data in an Italian family. A long PCR strategy was employed for the breakpoint region analysis where an insertion of six nucleotides (TTCACT) was found. Two Alu sequences, identified within intron 3 and exon 18, could underlie the identified rearrangement by a nonallelic homologous recombination (NAHR) mechanism. NGS proved to be an effective tool suitable for the identification of CNVs, together with small-scale alterations in the FH-related genes. For this purpose, the use and implementation of this cost-effective, efficient molecular approach meets the clinical need for personalized diagnosis in FH cases.

Several genes are involved in sport performance, especially in injuries incidence. The aim of this study was to investigate the association of ACE , ACTN3 , COL1A1 , and MCT1 genotypes and injuries in rugby players in order to find a genotype/phenotype correlation and provide useful information improving athletic performance. One-hundred male professional and semiprofessional rugby players were selected. Analysis was performed genotyping the genes ACE , ACTN3 , COL1A1 , and MCT1 as candidate gene of interest involved in athletic performance. A control group of non-athletic Italian male participants was analyzed to compare the results. We found statistical significance of MCT1 rs1049434 AA for total injuries (χ 2 = 0.115; p = 0.003) and bone injuries (χ 2 = 0.603; p = 0.007) in the rugby athlete population. No statistical significance was found between injury incidence and ACE , ACTN3 , COL1A1 genotypes. The MCT1 AA genotype is associated with the incidence of total and bone injuries in the rugby player population. Although environmental factors such as lifestyle, diet, training, and stress can influence athletic performance, our data demonstrated the importance of genetic study in sport aimed at developing personalized training and achieving the best possible athletic excellence.

Athletic performance is influenced by many factors such as the environment, diet, training and endurance or speed in physical effort and by genetic predisposition. Just a few studies have analyzed the impact of genotypes on physical performance in rugby. The aim of this study was to verify the modulation of genetic influence on rugby-specific physical performance. Twenty-seven elite rugby union players were involved in the study during the in-season phase. Molecular genotyping was performed for: angiotensin-converting enzyme ( ACE rs4646994), alfa-actinin-3 ( ACTN3 rs1815739) and monocarboxylate transporter 1 ( MCT1 rs1049434) and their variants. Lean mass index (from skinfolds), lower-limb explosive power (countermovement jump), agility (505), speed (20 m), maximal aerobic power (Yo-yo intermittent recovery test level 1) and repeated sprint ability (12 × 20 m) were evaluated. In our rugby union players ACE and ACTN3 variants did not show any influence on athletic performance. MCT1 analysis showed that TT-variant players had the highest peak vertical power ( p = 0.037) while the ones with the AA genotype were the fastest in both agility and sprint tests ( p = 0.006 and p = 0.012, respectively). Considering the T-dominant model, the AA genotype remains the fastest in both tests (agility: p = 0.013, speed: p = 0.017). Only the MCT1 rs1049434 A allele seems to be advantageous for elite rugby union players, particularly when power and speed are required.