MicroRNAs and cytokines as potential predictive biomarkers for COVID-19 disease progression

Exploring non-coding genetic variability in ACE2: Functional annotation and in vitro validation of regulatory variants

The surge in human whole-genome sequencing data has facilitated the study of non-coding region variations, yet understanding their biological significance remains a challenge. We used a computational workflow to assess the regulatory potential of non-coding variants, with a particular focus on the Angiotensin Converting Enzyme 2 (ACE2) gene. This gene is crucial in physiological processes and serves as the entry point for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 19 (COVID-19). In our analysis, using data from the gnomAD population database and functional annotation, we identified 17 significant Single Nucleotide Variants (SNVs) in ACE2, particularly in its enhancers, promoters, and 3' untranslated regions (UTRs). We found preliminary evidence supporting the regulatory impact of some of these variants on ACE2 expression. Our detailed examination of two SNVs, rs147718775 and rs140394675, in the ACE2 promoter revealed that these co-occurring SNVs, when mutated, significantly enhance promoter activity, suggesting a possible increase in specific ACE2 isoform expression. This method proves effective in identifying and interpreting impactful non-coding variants, aiding in further studies and enhancing understanding of molecular bases of monogenic and complex traits.

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82-0.84) and a balanced accuracy of 0.78 (95% CI 0.77-0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40-0.74). Quantitative PCR validated LEF1-AS1's adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management.

Altered expression of serum lncRNA CASC2 and miRNA-21-5p in COVID-19 patients

Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) has a high incidence of spread. On January 30, 2020, the World Health Organization proclaimed a public health emergency of worldwide concern. More than 6.9 million deaths and more than 768 million confirmed cases had been reported worldwide as of June 18, 2023. This study included 51 patients and 50 age- and sex-matched healthy subjects. The present study aimed to identify the expression levels of lncRNA CASC2 and miRNA-21-5p (also known as miRNA-21) in COVID-19 patients and their relation to the clinicopathological characteristics of the disease. The expression levels of noncoding RNAs were measured by RT-PCR technique. Results detected that CASC2 was significantly downregulated while miRNA-21-5p was significantly upregulated in COVID-19 patients compared to healthy subjects. A significant negative correlation was found between CASC2 and miRNA-21-5p. ROC curve analysis used to distinguish COVID-19 patients from controls. MiRNA-21-p serum expression level had a significant positive association with temperature and PO2 (p = 0.04 for each). These findings indicate that CASC2 and miRNA-21-p might be used as potential diagnostic and therapeutic biomarkers in COVID-19.

MicroRNAs in the Regulation of RIG-I-like Receptor Signaling Pathway: Possible Strategy for Viral Infection and Cancer

The retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs) play a crucial role as pattern-recognition receptors within the innate immune system. These receptors, present in various cell and tissue types, serve as essential sensors for viral infections, enhancing the immune system's capacity to combat infections through the induction of type I interferons (IFN-I) and inflammatory cytokines. RLRs are involved in a variety of physiological and pathological processes, including viral infections, autoimmune disorders, and cancer. An increasing body of research has examined the possibility of RLRs or microRNAs as therapeutic targets for antiviral infections and malignancies, despite the fact that few studies have focused on the regulatory function of microRNAs on RLR signaling. Consequently, our main emphasis in this review is on elucidating the role of microRNAs in modulating the signaling pathways of RLRs in the context of cancer and viral infections. The aim is to establish a robust knowledge base that can serve as a basis for future comprehensive investigations into the interplay between microRNAs and RIG-I, while also facilitating the advancement of therapeutic drug development.

Exploring the immunogenic properties of SARS-CoV-2 structural proteins: PAMP:TLR signaling in the mediation of the neuroinflammatory and neurologic sequelae of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) produces an array of neurologic and neuropsychiatric symptoms in the acute and post-acute phase of infection (PASC; post-acute sequelae of SARS-CoV-2 infection). Neuroinflammatory processes are considered key factors in the etiology of these symptoms. Several mechanisms underpinning the development of inflammatory events in the brain have been proposed including SARS-CoV-2 neurotropism and peripheral inflammatory responses (i.e., cytokine storm) to infection, which might produce neuroinflammation via immune-to-brain signaling pathways. In this review, we explore evidence in support of an alternate mechanism whereby structural proteins (e.g., spike and spike S1 subunit) derived from SARS-CoV-2 virions function as pathogen-associated molecular patterns (PAMPs) to elicit proinflammatory immune responses in the periphery and/or brain via classical Toll-Like Receptor (TLR) inflammatory pathways. We propose that SARS-CoV-2 structural proteins might directly produce inflammatory processes in brain independent of and/or in addition to peripheral proinflammatory effects, which might converge to play a causal role in the development of neurologic/neuropsychiatric symptoms in COVID-19.

Cytokine Response Following SARS-CoV-2 Antigen Stimulation in Patients with Predominantly Antibody Deficiencies

Predominantly antibody deficiencies (PADs) are inborn disorders characterized by immune dysregulation and increased susceptibility to infections. Response to vaccination, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may be impaired in these patients, and studies on responsiveness correlates, including cytokine signatures to antigen stimulation, are sparse. In this study, we aimed to describe the spike-specific cytokine response following whole-blood stimulation with SARS-CoV-2 spike peptides in patients with PAD (n = 16 with common variable immunodeficiency and n = 15 with selective IgA deficiency) and its relationship with the occurrence of coronavirus disease 2019 (COVID-19) during up to 10-month follow-up period. Spike-induced antibody and cytokine production was measured using ELISA (anti-spike IgG, IFN-γ) and xMAP technology (interleukin-1β (IL-1β), IL-4, IL-6, IL-10, IL-15, IL-17A, IL-21, TNF-α, TGF-β1). No difference was found in the production of cytokines between patients with PAD and controls. Anti-spike IgG and cytokine levels did not predict contraction of COVID-19. The only cytokine that distinguished between vaccinated and naturally infected unvaccinated PAD patients was IFN-γ (median 0.64 (IQR = 1.08) in vaccinated vs. 0.10 (IQR = 0.28) in unvaccinated). This study describes the spike-specific cytokine response to SARS-CoV-2 antigens, which is not predictive of contracting COVID-19 during the follow-up.