A new insight into sex-specific non-coding RNAs and networks in response to SARS-CoV-2

Revealing miRNAs patterns by employing matrix representations and energy analysis

MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression. Despite their relatively short length (about 21 nucleotides), they can regulate thousands of transcripts within a cell. Due to their low complementarity to targets, studying their activity and binding region preferences (3'UTR, 5'UTR, or CDS) is challenging. In this paper, we analyzed a set of human miRNAs to uncover their general patterns. We began with a sequence logo to verify conservation at specific positions. To discover long-range correlations, we employed chaos game representation (CGR) and genomatrix, methods that enable both graphical and analytical analysis of sequence sets and are well-established in bioinformatics. Our results showed that miRNAs exhibit strongly non-random and characteristic patterns. To incorporate physicochemical properties into the analysis, we applied the electron-ion interaction potential (EIIP) parameter. An important part of our study was to validate the division of miRNAs into two parts-seed and puzzle. The seed region is responsible for target binding, while the puzzle region likely interacts with the RISC complex. We estimated duplex binding energy within the 3'UTR, 5'UTR, and CDS regions using the miRanda tool. Based on the median energy distribution, we divided the miRNAs into two subsets, reflecting different patterns in chaos game representation. Interestingly, one subset displayed significant similarity to conserved and highly confidential miRNAs. Our results confirm the low complementarity of miRNA/mRNA interactions and support the functional division of miRNA structure. Additionally, we present findings related to the localization of transcript target sites, which form the basis for further analyses.

COVID-19 in patients with anemia and haematological malignancies: risk factors, clinical guidelines, and emerging therapeutic approaches

Extensive research in countries with high sociodemographic indices (SDIs) to date has shown that coronavirus disease 2019 (COVID-19) may be directly associated with more severe outcomes among patients living with haematological disorders and malignancies (HDMs). Because individuals with moderate to severe immunodeficiency are likely to undergo persistent infections, shed virus particles for prolonged periods, and lack an inflammatory or abortive phase, this represents an overall risk of morbidity and mortality from COVID-19. In cases suffering from HDMs, further investigation is needed to achieve a better understanding of triviruses and a group of related variants in patients with anemia and HDMs, as well as their treatment through vaccines, drugs, and other methods. Against this background, the present study aimed to delineate the relationship between HDMs and the novel COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Besides, effective treatment options for HDM cases were further explored to address this epidemic and its variants. Therefore, learning about how COVID-19 manifests in these patients, along with exploiting the most appropriate treatments, may lead to the development of treatment and care strategies by clinicians and researchers to help patients recover faster. Video Abstract.

Analyzing the expression pattern of the noncoding RNAs (HOTAIR, PVT-1, XIST, H19, and miRNA-34a) in PBMC samples of patients with COVID-19, according to the disease severity in Iran during 2022-2023: A cross-sectional study

Background and aims

MicroRNAs (miRNAs) and long noncoding RNAs (lncRNAs) are well-known types of noncoding RNAs (ncRNAs), which have been known as the key regulators of gene expression. They can play critical roles in viral infection by regulating the host immune response and interacting with genes in the viral genome. In this regard, ncRNAs can be employed as biomarkers for viral diseases. The current study aimed to evaluate peripheral blood mononuclear cell (PBMC) ncRNAs (lncRNAs-homeobox C antisense intergenic RNA [HOTAIR], -H19, X-inactive-specific transcript [XIST], plasmacytoma variant translocation 1 [PVT-1], and miR-34a) as diagnostic biomarkers to differentiate severe COVID-19 cases from mild ones.

Methods

Candidate ncRNAs were selected according to previous studies and assessed by real-time polymerase chain reaction in the PBMC samples of patients with severe coronavirus disease 2019 (COVID-19) (n = 40), healthy subjects (n = 40), and mild COVID-19 cases (n = 40). Furthermore, the diagnostic value of the selected ncRNAs was assessed by analyzing the receiver-operating characteristic (ROC).

Results

The results demonstrated that the expression pattern of the selected ncRNAs was significantly different between the studied groups. The levels of HOTAIR, XIST, and miR-34a were remarkably overexpressed in the severe COVID-19 group in comparison with the mild COVID-19 group, and in return, the PVT-1 levels were lower than in the mild COVID-19 group. Interestingly, the XIST expression level in men with severe COVID-19 was higher compared to women with mild COVID-19. ROC results suggested that HOTAIR and PVT-1 could serve as useful biomarkers for screening mild COVID-19 from severe COVID-19.

Conclusions

Overall, different expression patterns of the selected ncRNAs and ROC curve results revealed that these factors can contribute to COVID-19 pathogenicity and can be considered diagnostic markers of COVID-19 severe outcomes.

ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics

Background

The aim of this study is to investigate the genetic and epigenetic mechanisms involved in the pathogenesis of age-related cataract (ARC).

Methods

We obtained the transcriptome datafile of th ree ARC samples and three healthy, age-matched samples and used differential expression analyses to identify the differentially expressed genes (DEGs). The differential lncRNA-associated competing endogenous (ceRNA) network, and the protein-protein network (PPI) were constructed using Cytoscape and STRING. Cluster analyses were performed to identify the underlying molecular mechanisms of the hub genes affecting ARC progression. To verify the immune status of the ARC patients, immune-associated analyses were also conducted.

Results

The PPI network identified the FOXO1 gene as the hub gene with the highest score, as calculated by the Maximal Clique Centrality (MCC) algorithm. The ceRNA network identified lncRNAs H19, XIST, TTTY14, and MEG3 and hub genes FOXO1, NOTCH3, CDK6, SPRY2, and CA2 as playing key roles in regulating the pathogenesis of ARC. Additionally, the identified hub genes showed no significant correlation with an immune response but were highly correlated with cell metabolism, including cysteine, methionine, and galactose.

Discussion

The findings of this study may provide clues toward ARC pathogenic mechanisms and may be of significance for future therapeutic research.

Complement activation in COVID-19 and targeted therapeutic options: A scoping review

Increasing evidence suggests that activation of the complement system plays a key role in the pathogenesis and disease severity of Coronavirus disease 2019 (COVID-19). We used a systematic approach to create an overview of complement activation in COVID-19 based on histopathological, preclinical, multiomics, observational and clinical interventional studies. A total of 1801 articles from PubMed, EMBASE and Cochrane was screened of which 157 articles were included in this scoping review. Histopathological, preclinical, multiomics and observational studies showed apparent complement activation through all three complement pathways and a correlation with disease severity and mortality. The complement system was targeted at different levels in COVID-19, of which C5 and C5a inhibition seem most promising. Adequately powered, double blind RCTs are necessary in order to further investigate the effect of targeting the complement system in COVID-19.

Potential Predictive Value of miR-125b-5p, miR-155-5p and Their Target Genes in the Course of COVID-19

Purpose

This study aimed to provide new biomarkers for predicting the disease course of COVID-19 by analyzing the dynamic changes of microRNA (miRNA) and its target gene expression in the serum of COVID-19 patients at different stages.

Methods

Serum samples were collected from all COVID-19 patients at three time points: the acute stage, the turn-negative stage, and the recovery stage. The expression level of miRNA and the target mRNA was measured by Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR). The classification tree model was established to predict the disease course, and the prediction efficiency of independent variables in the model was analyzed using the receiver operating characteristic (ROC) curve.

Results

The expression of miR-125b-5p and miR-155-5p was significantly up-regulated in the acute stage and gradually decreased in the turn-negative and recovery stages. The expression of the target genes CDH5, STAT3, and TRIM32 gradually down-regulated in the acute, turn-negative, and recovery stages. MiR-125b-5p, miR-155-5p, STAT3, and TRIM32 constituted a classification tree model with 100% accuracy of prediction and AUC >0.7 for identification and prediction in all stages.

Conclusion

MiR-125b-5p, miR-155-5p, STAT3, and TRIM32 could be useful biomarkers to predict the time nodes of the acute, turn-negative, and recovery stages of COVID-19.

Insights into Cardiovascular Defects and Cardiac Epigenome in the Context of COVID-19

Although few in number, studies on epigenome of the heart of COVID-19 patients show that epigenetic signatures such as DNA methylation are significantly altered, leading to changes in expression of several genes. It contributes to pathogenic cardiac phenotypes of COVID-19, e.g., low heart rate, myocardial edema, and myofibrillar disarray. DNA methylation studies reveal changes which likely contribute to cardiac disease through unknown mechanisms. The incidence of severe COVID-19 disease, including hospitalization, requiring respiratory support, morbidity, and mortality, is disproportionately higher in individuals with co-morbidities. This poses unprecedented strains on the global healthcare system. While their underlying conditions make patients more susceptible to severe COVID-19 disease, strained healthcare systems, lack of adequate support, or sedentary lifestyles from ongoing lockdowns have proved detrimental to their underlying health conditions, thus pushing them to severe risk of congenital heart disease (CHD) itself. Prophylactic vaccines against COVID-19 have ushered new hope for CHD. A common connection between COVID-19 and CHD is SARS-CoV-2’s host receptor ACE2, because ACE2 regulates and protects organs, including the heart, in various ways. ACE2 is a common therapeutic target against cardiovascular disease and COVID-19 which damages organs. Hence, this review explores the above regarding CHDs, cardiovascular damage, and cardiac epigenetics, in COVID-19 patients.