Epigenetic alterations and genetic variations of angiotensin-converting enzyme 2 (ACE2) as a functional receptor for SARS-CoV-2: potential clinical implications

Micro-Epigenetic Markers in Viral Genome: SARS-CoV-2 Infection Impact on Host Cell MicroRNA Landscape

INTRODUCTION

MicroRNAs (miRs) are crucial micro-genetic markers that significantly manipulate gene expression in neoplastic/malignant and non-neoplastic diseases, as viral infections. Different expression patterns of miRs seem to partially influence the response rates to specific chemo-targeted therapeutic regimens and prognosis in cancer patients. Concerning their nature, miRs are short non-coding RNAs including 20-25 nucleotides hosted in intra- or intergenic regions. Their most important function is the positive regulation of post-transcriptional gene silencing levels. Based on this activity, they enhance normal cell functions, including proliferation, apoptosis and tissue differentiation. Their deregulation in cancerous cells due to epigenetic and transcriptional imbalances is correlated with an excessive production of target mRNA.

OBJECTIVE

In the current paper, our aim was to generally describe the role of MiRs in cancer genome and we mainly focused on specific host target-cell miRs that are affected by SARS-CoV-2 in the COVID-19 pandemic.

MATERIAL AND METHOD

A systematic review of the literature was carried out based on the international database PubMed focused on miR nature, origin, structure and function in cancer genome and more recently on the influence of SARS-CoV-2 on affected cells. The following keywords were used: microRNA, SARS-CoV-2, COVID-19, infection, cancer, virus. A pool of 52 important articles were selected for the present review at the basis of exploring the SARS-CoV-2 efficacy in miRs.

RESULTS

A broad set of miRs, including miR-122, miR-16-2-3p, miR-3605-3p, miR-15b-5p, miR-486-3p, miR-486-5p, miR-447b, miR-3672, miR-325, miR-447b and miR-222, has been identified to be deregulated by SARS-CoV-2 infection.

CONCLUSIONS

miRs represent significant micro-epigenetic markers frequently deregulated in SARS-CoV-2 mediated infection (COVID-19). Interactions between miRs and SARS-CoV-2 RNA genome are under investigation. miR overexpression/expression loss in SARS-CoV-2 affected epithelia is correlated with specific genetic and by epigenetic signatures in the corresponding patients.

Decoding the intricacies: a comprehensive analysis of microRNAs in the pathogenesis, diagnosis, prognosis and therapeutic strategies for COVID-19

The pandemic of coronavirus disease-19 (COVID-19), provoked by the appearance of a novel coronavirus named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), required a worldwide healthcare emergency. This has elicited an immediate need for accelerated research into its mechanisms of disease, criteria for diagnosis, methods for forecasting outcomes, and treatment approaches. microRNAs (miRNAs), are diminutive RNA molecules, that are non-coding and participate in gene expression regulation post-transcriptionally, having an important participation in regulating immune processes. miRNAs have granted substantial interest in their impact on viral replication, cell proliferation, and modulation of how the host's immune system responds. This narrative review delves into host miRNAs' multifaceted roles within the COVID-19 context, highlighting their involvement in disease progression, diagnostics, and prognostics aspects, given their stability in biological fluids and varied expression profiles when responding to an infection. Additionally, we discuss complicated interactions between SARS-CoV-2 and host cellular machinery facilitated by host miRNAs revealing how dysregulation of host miRNA expression profiles advances viral replication, immune evasion, and inflammatory responses. Furthermore, it investigates the potential of host miRNAs as therapeutic agents, whether synthetic or naturally occurring, which could be harnessed to either mitigate harmful inflammation or enhance antiviral responses. However, searching more deeply is needed to clarify how host's miRNAs are involved in pathogenesis of COVID-19, its diagnosis processes, prognostic assessments, and treatment approaches for patients.

Expression patterns of lncRNA MALAT-1 in SARS-COV-2 infection and its potential effect on disease severity via miR-200c-3p and SIRT1

Downregulating Angiotensin Converting Enzyme2 (ACE2) expression may be a shared mechanism for RNA viruses.

Aim

Evaluate the expressions of ACE2 effectors: the long non-coding RNA 'MALAT-1', the micro-RNA 'miR-200c-3p' and the histone deacetylase 'SIRT1' in SARS-COV-2 patients and correlate to disease severity. Sera samples from 98 SARS-COV-2 patients and 30 healthy control participants were collected. qRT-PCR was used for MALAT-1 and miR-200c-3p expression. SIRT1 was measured using ELISA.

Results

In sera of COVID-19 patients, gene expression of miR-200c-3p is increased while MALAT-1 is decreased. SIRT1 protein level is decreased (P value < 0.001). Findings are accentuated with increased disease severity. Serum MALAT-1, miR-200c-3p and SIRT1 could be used as diagnostic markers at cut off values of 0.04 (95.9 % sensitivity), 5.59 (94.9 % sensitivity, 99 % specificity), and 7.4 (98 % sensitivity) respectively. A novel MALAT-1-miR-200c-3p-SIRT1 pathway may be involved in the regulation of SARS-COV-2 severity.

Were metabolic and other chronic diseases the driven onset epidemic forces of COVID-19 in Mexico?

The underline hypothesis of this study was that SARS-CoV-2 can infect individuals regardless of health condition, sex, and age in opposition to the classical epidemiological assumption of an identifiable susceptible subpopulation for epidemic development. To address this issue, a population cohort with 24.4 million metadata associated with 226,089 official RT-qPCR positive and 283,450 negative cases, including 27,769 deceased, linked putatively to B.1. and B.1.1. SARS-CoV-2 lineages were analyzed. The analysis baseline was to determine the infection and mortality structure of the diseased cohort at the onset-exponential phase of the first epidemic wave in Mexico under the assumption of limited herd immunity. Individuals with nonchronic diseases (NOCDs) were compared with those exhibiting at least one of 10 chronic diseases (CDs) adjusted by age and sex. Risk factors for infection and mortality were estimated with classification and regression tree (CART) and cluster analysis based on Spearman's matrix of rho-values in RStudio®, complemented with two proposed mortality indices. SARS-CoV-2 infection was independent of health condition (52.8% NOCD vs. 47.2% CDs; p = 0.001-0.009) but influenced by age >46 in one risk analysis scenario (p < 0.001). Sex contributed 9.7% to the overall risk. The independent effect was supported by the health structure of negative cases with a similar tendency but a higher proportion of NOCDs (61.4%, p = 0.007). The infection probability in individuals with one CD was determined by the disease type and age, which was higher in those older individuals (≥56 years) exhibiting diabetes (12.3%, cp = 0.0006), hypertension (10.1%, cp < 0.0001), and obesity (7.8%, cp = 0.001). In contrast, the mortality risk was heavily influenced by CD conditioned by sex and age, accounting for 72.3% of total deaths (p = 0.001-0.008). Significant mortality risk (48%) was comprised of women and men (w, m) aged ≥56 years with diabetes (19% w and 27.9% m, cp < 0.0004), hypertension (11.5% w, cp = 0.0001), and CKD (3.5% w and 5.3% m, cp = 0.0009). Older people with diabetes and hypertension comorbidity increased the risk to 60.5% (p = 0.001). Based on a mortality-weighted index, women were more vulnerable to preexisting metabolic or cardiovascular diseases. These findings support our hypothesis and justify the need for surveillance systems at a communitarian level. This is the first study addressing this fundamental epidemiological question.

Evaluation of altered miRNA expression pattern to predict COVID-19 severity

Outbreak of COVID-19 pandemic in December 2019 affected millions of people globally. After substantial research, several biomarkers for COVID-19 have been validated however no specific and reliable biomarker for the prognosis of patients with COVID-19 infection exists. Present study was designed to identify specific biomarkers to predict COVID-19 severity and tool for formulating treatment. A small cohort of subjects (n = 43) were enrolled and categorized in four study groups; Dead (n = 16), Severe (n = 10) and Moderate (n = 7) patients and healthy controls (n = 10). Small RNA sequencing was done on Illumina platform after isolation of microRNA from peripheral blood. Differential expression (DE) of miRNA (patients groups compared to control) revealed 118 down-regulated and 103 up-regulated known miRNAs with fold change (FC) expression ≥2 folds and p ≤ 0.05. DE miRNAs were then subjected to functional enrichment and network analysis. Bioinformatic analysis resulted in 31 miRNAs (24 Down-regulated; 7 up-regulated) significantly associated with COVID-19 having AUC>0.8 obtained from ROC curve. Seventeen out of 31 DE miRNAs have been linked to COVID-19 in previous studies. Three miRNAs, hsa-miR-147b-5p and hsa-miR-107 (down-regulated) and hsa-miR-1299 (up-regulated) showed significant unique DE in Dead patients. Another set of 4 miRNAs, hsa-miR-224-5p (down-regulated) and hsa-miR-4659b-3p, hsa-miR-495-3p and hsa-miR-335-3p were differentially up-regulated uniquely in Severe patients. Members of three miRNA families, hsa-miR-20, hsa-miR-32 and hsa-miR-548 were significantly down-regulated in all patients group in comparison to healthy controls. Thus a distinct miRNA expression profile was observed in Dead, Severe and Moderate COVID-19 patients. Present study suggests a panel of miRNAs which identified in COVID-19 patients and could be utilized as potential diagnostic biomarkers for predicting COVID-19 severity.

Identification of methylation signatures and rules for predicting the severity of SARS-CoV-2 infection with machine learning methods

Patients infected with SARS-CoV-2 at various severities have different clinical manifestations and treatments. Mild or moderate patients usually recover with conventional medical treatment, but severe patients require prompt professional treatment. Thus, stratifying infected patients for targeted treatment is meaningful. A computational workflow was designed in this study to identify key blood methylation features and rules that can distinguish the severity of SARS-CoV-2 infection. First, the methylation features in the expression profile were deeply analyzed by a Monte Carlo feature selection method. A feature list was generated. Next, this ranked feature list was fed into the incremental feature selection method to determine the optimal features for different classification algorithms, thereby further building optimal classifiers. These selected key features were analyzed by functional enrichment to detect their biofunctional information. Furthermore, a set of rules were set up by a white-box algorithm, decision tree, to uncover different methylation patterns on various severity of SARS-CoV-2 infection. Some genes (PARP9, MX1, IRF7), corresponding to essential methylation sites, and rules were validated by published academic literature. Overall, this study contributes to revealing potential expression features and provides a reference for patient stratification. The physicians can prioritize and allocate health and medical resources for COVID-19 patients based on their predicted severe clinical outcomes.

The Potential Role of Growth Differentiation Factor 15 in COVID-19: A Corollary Subjective Effect or Not?

Coronavirus disease 2019 (COVID-19) is primarily caused by various forms of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants. COVID-19 is characterized by hyperinflammation, oxidative stress, multi-organ injury (MOI)-like acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Different biomarkers are used in the assessment of COVID-19 severity including D-dimer, ferritin, lactate dehydrogenase (LDH), and hypoxia-inducible factor (HIF). Interestingly, growth differentiation factor 15 (GDF15) has recently become a potential biomarker correlated with the COVID-19 severity. Thus, this critical review aimed to determine the critical association between GDF15 and COVID-19. The perfect function of GDF15 remains not well-recognized; nevertheless, it plays a vital role in controlling cell growth, apoptosis and inflammatory activation. Furthermore, GDF15 may act as anti-inflammatory and pro-inflammatory signaling in diverse cardiovascular complications. Furthermore, the release of GDF15 is activated by various growth factors and cytokines including macrophage colony-stimulating factor (M-CSF), angiotensin II (AngII) and p53. Therefore, higher expression of GDF15 in COVID-19 might a compensatory mechanism to stabilize and counteract dysregulated inflammatory reactions. In conclusion, GDF15 is an anti-inflammatory cytokine that could be associated with the COVID-19 severity. Increased GDF15 could be a compensatory mechanism against hyperinflammation and exaggerated immune response in the COVID-19. Experimental, preclinical and large-scale clinical studies are warranted in this regard.

Regulation of m6A Methylation as a New Therapeutic Option against COVID-19

The rapid spread of SARS-CoV-2 and the resulting pandemic has led to a spasmodic search for approaches able to limit the diffusion of the disease. The epigenetic machinery has aroused considerable interest in the last decades, and much evidence has demonstrated that this type of modification could regulate the early stages of viral infection. Recently it was reported that N6-methyladenosine (m6A) influences SARS-CoV-2 replication, although its role remains to be further investigated. The knockdown of enzymes involved in the m6A pathway could represent an optimal strategy to deepen the epigenetic mechanism. In the present study, we blocked the catalytic activity of the fat mass and obesity-associated protein (FTO) by using the selective inhibitor rhein. We observed a strong broad-spectrum reduction of infectivity caused by various coronaviruses, including SARS-CoV-2. This effect could be due to the modulation of m6A levels and could allow identification of this modification as a new therapeutic target to treat SARS-CoV-2 infection.