Identification of a de novo, Novel Pathogenic Variant in the Splice Region of the SOX10 Gene in an Iranian Azeri Turkish Family with Waardenburg Syndrome.

Background: Waardenburg syndrome (WS) is an inherited heterogeneous auditory pigmentary syndrome, divided into at least four types and characterized by iris heterochromia, white forelock, prominent nasal root, dystopia canthorum, middle eyebrow hypertrichosis, and deafness. Pathogenic variants in the SOX10 gene have been reported to be involved in WS disease. Methods: Whole exome sequencing (WES) was conducted on a 24-year-old male, who originated from Iranian Azeri Turkish ethnic group, with symptoms of deafness and blue eyes from brown-eyed parents. Web-based tools including Mutation Taster, VarSome, SIFT, Human Splicing Finder (HSF), and I-TASSER, were used for bioinformatics analysis. To verify the WES findings, DNAs taken from the blood samples of all family members were subjected to PCR-Sanger sequencing. Results: A novel heterozygous pathogenic variant, NC_000022.11 (NM_006941):c.428+1G>T, located in the second intron of the SOX10 gene and disrupting the splicing site, was identified in the proband. Sanger sequencing was applied on the proband and his parents. The results showed that the variant was a de novo pathogenic variant with an autosomal dominant inheritance pattern. Conclusions: Identification of a novel de novo pathogenic variant, NC_000022.11 (NM_006941):c.428+1G>T, in the second intron of the SOX10 gene with autosomal dominant inheritance pattern.

Association between leukocyte telomere length and COVID-19 severity.

Background: Inter-individual variations in the clinical manifestations of SARS-CoV-2 infection are among the challenging features of COVID-19. The known role of telomeres in cell proliferation and immune competency highlights their possible function in infectious diseases. Variability in telomere length is an invaluable parameter in the heterogeneity of the clinical presentation of diseases. Result: In this study, our aim was to investigate the possible association between leukocyte telomere length (LTL) and COVID-19 severity. LTL was measured in 100 patients with moderate and severe forms of COVID-19 using the quantitative PCR (q-PCR) method. Statistical analysis confirmed a strong inverse correlation between relative LTL and COVID-19 severity. Conclusions: These findings suggest that LTL can be a useful parameter for predicting disease severity in patients, as individuals with short telomeres may have a higher risk of developing severe COVID-19. Supplementary Information: The online version contains supplementary material available at 10.1186/s43042-023-00415-z.

Understanding the role of telomere attrition and epigenetic signatures in COVID-19 severity.

Within the past several decades, the emergence and spread of infectious diseases with pandemic potential have endangered human lives. Coronavirus disease 2019 (COVID-19) outbreak represents an unprecedented threat for all health systems worldwide. The clinical spectrum of COVID-19 is highly heterogeneous, ranging from asymptomatic and mild upper respiratory tract illness to severe interstitial pneumonia with respiratory failure and even death. Highly age-dependent patterns of immune response potentially explain the higher rates of the severe forms of COVID-19 in elderly patients. However, genetic and epigenetic architecture can influence multiple biological processes during the lifespan, therefore as far as our knowledge shows, vulnerability to viral infection concerning telomere length and epigenetic signature is not a new idea. This review aims is to summarize the current understanding of the role of telomere length and epigenetic mechanisms on the severity of COVID-19. The current knowledge highlights the significant association between the shorter telomere length and the higher risk of developing severe COVID-19. Differential DNA methylation patterns and miRNA expression profiles imply that these hallmarks can play a pivotal role in COVID- 19 pathogenesis. Understanding the causes of inter-individual variations in COVID-19 outcomes could provide clues to the development of the personalized therapeutic intervention.

An updated overview and classification of bioinformatics tools for MicroRNA analysis, which one to choose?

The term 'MicroRNA' (miRNA) refers to a class of small endogenous non-coding RNAs (ncRNAs) regenerated from hairpin transcripts. Recent studies reveal miRNAs' regulatory involvement in essential biological processes through translational repression or mRNA degradation. Recently, there is a growing body of literature focusing on the importance of miRNAs and their functions. In this respect, several databases have been developed to manage the dispersed data produced. Therefore, it is necessary to know the parameters and characteristics of each database to benefit their data. Besides, selecting the correct database is of great importance to scientists who do not have enough experience in this field. A comprehensive classification along with an explanation of the information contained in each database leads to facilitating access to these resources. In this regard, we have classified relevant databases into several categories, including miRNA sequencing and annotation, validated/predicted miRNA targets, disease-related miRNA, SNP in miRNA sequence or target site, miRNA-related pathways, or gene ontology, and mRNA-miRNA interactions. Hence, this review introduces available miRNA databases and presents a convenient overview to inform researchers of different backgrounds to find suitable miRNA-related bioinformatics web tools and relevant information rapidly.