Discriminatory power of a circulating multi-noncoding RNA panel in acute coronary syndrome subtypes: Towards precision detection.

BACKGROUND: Acute Coronary Syndrome (ACS) stands as a significant contributor to cardiovascular mortality, necessitating improved diagnostic tools for early detection and tailored therapeutic interventions. Current diagnostic modalities, exhibit limitations in sensitivity and specificity, urging the quest for novel biomarkers to enhance discrimination of the different stages of ACS including unstable angina, Non-ST-segment Elevation Myocardial Infarction (NSTEMI), and ST-segment Elevation Myocardial Infarction (STEMI). METHODS: This study investigated the potential of a plasma-circulating multi-noncoding RNA (ncRNA) panel, comprising four miRNAs (miR-182-5p, miR-23a-3p, miR-146a-5p, and miR-183-5p) and three lncRNAs (SNHG15, SNHG5, and RMRP), selected based on their intricate involvement in ACS pathogenesis and signaling pathways regulating post-myocardial infarction (MI) processes. The differential expression of these ncRNAs was validated in sera of ACS patients and healthy controls via real-time polymerase chain reaction (RT-PCR). RESULTS: Analysis revealed a marked upregulation of the multi-ncRNAs panel in ACS patients. Notably, miRNA-182-5p and lncRNA-RMRP exhibited exceptional discriminatory power, indicated by the high area under the curve (AUC) values (0.990 and 0.980, respectively). Importantly, this panel displayed superior efficacy in discriminating between STEMI and NSTEMI, outperforming conventional biomarkers like creatine kinase-MB and cardiac troponins. Additionally, the four miRNAs and lncRNA RMRP showcased remarkable proficiency in distinguishing between STEMI and unstable angina. CONCLUSION: The findings underscore the promising potential of the multi-ncRNA panel as a robust tool for early ACS detection, and precise differentiation among ACS subtypes, and as a potential therapeutic target.

Identifying SARS-CoV-2 Lineage Mutation Hallmarks and Correlating Them With Clinical Outcomes in Egypt: A Pilot Study.

The SARS-CoV-2 pandemic has led to over 4.9 million deaths as of October 2021. One of the main challenges of creating vaccines, treatment, or diagnostic tools for the virus is its mutations and emerging variants. A couple of variants were declared as more virulent and infectious than others. Some approaches were used as nomenclature for SARS-CoV-2 variants and lineages. One of the most used is the Pangolin nomenclature. In our study, we enrolled 35 confirmed SARS-CoV-2 patients and sequenced the viral RNA in their samples. We also aimed to highlight the hallmark mutations in the most frequent lineage. We identified a seven-mutation signature for the SARS-CoV-2 C36 lineage, detected in 56 countries and an emerging lineage in Egypt. In addition, we identified one mutation which was highly negatively correlated with the lineage. On the other hand, we found no significant correlation between our clinical outcomes and the C36 lineage. In conclusion, the C36 lineage is an emerging SARS-CoV-2 variant that needs more investigation regarding its clinical outcomes compared to other strains. Our study paves the way for easier diagnosis of variants of concern using mutation signatures.

In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity.

(1) Background: The coronavirus (COVID-19) pandemic is still a major global health problem, despite the development of several vaccines and diagnostic assays. Moreover, the broad symptoms, from none to severe pneumonia, and the various responses to vaccines and the assays, make infection control challenging. Therefore, there is an urgent need to develop non-invasive biomarkers to quickly determine the infection severity. Circulating RNAs have been proven to be potential biomarkers for a variety of diseases, including infectious ones. This study aimed to develop a genetic network related to cytokines, with clinical validation for early infection severity prediction. (2) Methods: Extensive analyses of in silico data have established a novel IL11RA molecular network (IL11RNA mRNA, LncRNAs RP11-773H22.4 and hsa-miR-4257). We used different databases to confirm its validity. The differential expression within the retrieved network was clinically validated using quantitative RT-PCR, along with routine assessment diagnostic markers (CRP, LDH, D-dimmer, procalcitonin, Ferritin), in100 infected subjects (mild and severe cases) and 100 healthy volunteers. (3) Results: IL11RNA mRNA and LncRNA RP11-773H22.4, and the IL11RA protein, were significantly upregulated, and there was concomitant downregulation of hsa-miR-4257, in infected patients, compared to the healthy controls, in concordance with the infection severity. (4) Conclusion: The in-silico data and clinical validation led to the identification of a potential RNA/protein signature network for novel predictive biomarkers, which is in agreement with ferritin and procalcitonin for determination of COVID-19 severity.

ABHD4-Regulating RNA Panel: Novel Biomarkers in Acute Coronary Syndrome Diagnosis.

BACKGROUND: Acute coronary syndrome (ACS) is a major cause of death all over the world. STEMI represents a type of myocardial infarction with acute ST elevation. We aimed to assess the predictive power of potential RNA panel expression in acute coronary syndrome. METHOD: We used in silico data analysis to retrieve RNAs related to glycerophospholipid metabolism dysregulation and specific to ACS that results in the selection of Alpha/Beta hydrolase fold domain4 (ABHD4) mRNA and its epigenetic regulators (Foxf1 adjacent noncoding developmental regulatory RNA (FENDRR) lncRNA, miRNA-221, and miRNA-197). We assessed the expression of the serum RNA panel in 68 patients with ACS, 21 patients with chest pain due to non-cardiac causes, and 21 healthy volunteers by quantitative real-time polymerase chain reaction. RESULTS: The study data showed significant down regulation in the expression of the serum levels of FENDRR lncRNA and miRNA-221-3p by 120-fold and 22-fold in Unstable angina (UA) in comparison with healthy volunteers, and by 8.6-fold and 2-fold in ST segment elevation myocardial infarction (STEMI) patients versus UA; concomitant upregulation in the expression of ABHD4 mRNA and miRNA-197-5p by 444-fold and 10-fold in UA compared with healthy volunteers, and by 1.54-fold and 4.5-fold in STEMI versus unstable angina. Performance characteristics analysis showed that the ABHD4-regulating RNA panel were potential biomarkers for prediction of ACS. Moreover, there was a significant association between the 2 miRNAs and ABHD4 mRNA and the regulating FENDRR lncRNA. CONCLUSION: Collectively, ABHD4 mRNA regulating RNA panel based on putative interactions seems to be novel non-invasive biomarkers that could detect ACS early and stratify severity of the condition that could improve health outcome.

Association between Interferon-Lambda-3 rs12979860, TLL1 rs17047200 and DDR1 rs4618569 Variant Polymorphisms with the Course and Outcome of SARS-CoV-2 Patients.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection provides a critical host-immunological challenge. AIM: We explore the effect of host-genetic variation in interferon-lambda-3 rs12979860, Tolloid Like-1 (TLL1) rs17047200 and Discoidin domain receptor 1(DDR1) rs4618569 on host response to respiratory viral infections and disease severity that may probe the mechanistic approach of allelic variation in virus-induced inflammatory responses. METHODS: 141 COVID-19 positive patients and 100 healthy controls were tested for interferon-lambda-3 rs12979860, TLL1 rs17047200 and DDR1 rs4618569 polymorphism by TaqMan probe-based genotyping. Different genotypes were assessed regarding the COVID-19 severity and prognosis. RESULTS: There were statistically significant differences between the studied cases and control group with regard to the presence of comorbidities, total leucocytic count, lymphocytic count, CRP, serum LDH, ferritin and D-dimer (p < 0.01). The CC genotype of rs12979860 cytokine, the AA genotype of TLL1 rs17047200 and the AA genotype of the rs4618569 variant of DDR1 showed a higher incidence of COVID-19 compared to the others. There were significant differences between the rs4618569 variant of DDR and the outcome of the disease, with the highest mortality in AG genotype 29 (60.4%) in comparison to 16 (33.3%) and 3 (6.2%) in the AA and GG genotypes, respectively (p = 0.007*), suggesting that the A allele is associated with a poor outcome in the disease. CONCLUSION: Among people who carry C and A alleles of SNPs IFN-λ rs12979860 and TLL1 rs17047200, respectively, the AG genotype of the DDR1 rs4618569 variant is correlated with a COVID-19 poor outcome. In those patients, the use of anti-IFN-λ 3, TLL1 and DDR1 therapy may be promising for personalized translational clinical practice.