Association of RTEL1 gene polymorphisms with stroke risk in a Chinese Han population

A comprehensive in silico investigation into the pathogenic SNPs in the RTEL1 gene and their biological consequences

The Regulator of Telomere Helicase 1 (RTEL1) gene encodes a critical DNA helicase intricately involved in the maintenance of telomeric structures and the preservation of genomic stability. Germline mutations in the RTEL1 gene have been clinically associated with Hoyeraal-Hreidarsson syndrome, a more severe version of Dyskeratosis Congenita. Although various research has sought to link RTEL1 mutations to specific disorders, no comprehensive investigation has yet been conducted on missense mutations. In this study, we attempted to investigate the functionally and structurally deleterious coding and non-coding SNPs of the RTEL1 gene using an in silico approach. Initially, out of 1392 nsSNPs, 43 nsSNPs were filtered out through ten web-based bioinformatics tools. With subsequent analysis using nine in silico tools, these 43 nsSNPs were further shortened to 11 most deleterious nsSNPs. Furthermore, analyses of mutated protein structures, evolutionary conservancy, surface accessibility, domains & PTM sites, cancer susceptibility, and interatomic interaction revealed the detrimental effect of these 11 nsSNPs on RTEL1 protein. An in-depth investigation through molecular docking with the DNA binding sequence demonstrated a striking change in the interaction pattern for F15L, M25V, and G706R mutant proteins, suggesting the more severe consequences of these mutations on protein structure and functionality. Among the non-coding variants, two had the highest likelihood of being regulatory variants, whereas one variant was predicted to affect the target region of a miRNA. Thus, this study lays the groundwork for extensive analysis of RTEL1 gene variants in the future, along with the advancement of precision medicine and other treatment modalities.

A phenotype driven integrative framework uncovers molecular mechanisms of a rare hereditary thrombophilia

Antithrombin resistance is a rare subtype of hereditary thrombophilia caused by prothrombin gene variants, leading to thrombotic disorders. Recently, the Prothrombin Belgrade variant has been reported as a specific variant that leads to antithrombin resistance in two Serbian families with thrombosis. However, due to clinical data scarcity and the inapplicability of traditional genome-wide association studies (GWAS), a broader perspective on molecular and phenotypic mechanisms associated with the Prothrombin Belgrade variant is yet to be uncovered. Here, we propose an integrative framework to address the lack of genomic samples and support the genomic signal from the full genome sequences of five heterozygous subjects by integrating it with subjects' phenotypes and the genes' molecular interactions. Our goal is to identify candidate thrombophilia-related genes for which our subjects possess germline variants by focusing on the resulting gene clusters of our integrative framework. We applied a Non-negative Matrix Tri-Factorization-based method to simultaneously integrate different data sources, taking into account the observed phenotypes. In other words, our data-integration framework reveals gene clusters involved with this rare disease by fusing different datasets. Our results are in concordance with the current literature about antithrombin resistance. We also found candidate disease-related genes that need to be further investigated. CD320, RTEL1, UCP2, APOA5 and PROZ participate in healthy-specific or disease-specific subnetworks involving thrombophilia-annotated genes and are related to general thrombophilia mechanisms according to the literature. Moreover, the ADRA2A and TBXA2R subnetworks analysis suggested that their variants may have a protective effect due to their connection with decreased platelet activation. The results show that our method can give insights into antithrombin resistance even if a small amount of genetic data is available. Our framework is also customizable, meaning that it applies to any other rare disease.

Genetic analysis of the relation of telomere length-related gene (RTEL1) and coronary heart disease risk

BACKGROUND

Regulator of telomere elongation helicase 1 (RTEL1), a telomere length-related gene, is closely linked to cancer and age-related diseases. The aim of this study was to investigate the association between genetic polymorphisms in the RTEL1 gene and coronary heart disease (CHD) risk.

METHODS

In this case-control study, which includes samples from 596 CHD patients and 603 healthy controls, five SNPs in RTEL1 were selected. The genotypes were studied using the Agena MassARRAY platform, and the statistical analyses were performed using the chi-square and Fisher's exact tests, genetic model analysis, and haplotype analysis.

RESULTS

In the allele model, using the chi-square test, we found that the patients with the "G" allele of rs6010620 and the "C" allele of rs4809324 in the RTEL1 gene showed a decreased risk of CHD once the results were adjusted for age and gender. In the genetic model, logistic regression analyses revealed that the rs6010620 polymorphism conferred a decreased risk of CHD in the codominant model (OR = 0.52, 95% CI: 0.31-0.88, p = 0.007 for the "G/G" genotype) and the recessive model (OR = 0.49, 95% CI: 0.30-0.80, p = 0.004 for the "G/G" genotype). In addition, the haplotype "G_rs6010620 T_rs6010621 T_rs4809324 " of RTEL1 was associated with a 0.03-fold decreased risk of CHD once the results were adjusted for age and gender (OR = 0.03, 95% CI: 0.01-0.12, p < 0.001).

CONCLUSION

Our findings have demonstrated that the genetic variants of RTEL1 may have a protective role against CHD risk.

Relative Telomere Length and Stroke Risk in a Chinese Han Population

This study aimed to further understand the role of relative telomere length (RTL) in susceptibility to stroke and investigate the association regulator of telomere elongation helicase 1 (RETL1) gene polymorphisms and RTL. RTL was measured using the real-time quantitative polymerase chain reaction (qPCR) from 300 stroke patients and 299 healthy controls. Genotyping was performed using the Sequenom MassARRAY platform. The results indicated that stroke patients had significantly shorter median RTL than controls (P < 0.001). Compared with the longer RTL (≥ 0.766), the shorter RTL (< 0.766) was significantly increased the risk of stroke (odds ratio [OR] = 8.44, 95% confidence interval [CI] 5.42-13.14, P < 0.001). The RTL was categorized into tertiles, we found that the shorter RTL (0.515-1.366) (OR = 16.27, 95% CI 7.72-34.29, P < 0.001) and lowest RTL (< 0.515) (OR = 30.63, 95% CI 14.27-65.75, P < 0.001) were significantly increased stroke risk compared with the highest RTL (> 1.366). Stratified analysis showed that the shorter RTL was also significantly increased the risk of stroke compared with the longer RTL in male, age < 60 years and ≥ 60 years, except the female participants. In addition, individuals with the genotypes AA (rs2297441) and GG (rs6089953) have shorter telomeres than the genotypes GG (P = 0.031) and AA (P = 0.032), respectively. Our results suggested that shorter RTL was associated with an increased risk of stroke. The association was found between the genotypes AA (rs2297441) and GG (rs6089953) and shorter RTL in case group. Further studies in larger sample size and biological functional assays are warranted to validate our findings.