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Background The SARS-CoV-2 virus’s frequent mutations have made disease control with vaccines and antiviral drugs difficult; as a result, there is a need for more effective coronavirus drugs. Therefore, detecting the expression of various diagnostic biomarkers, including ncRNA in SARS-CoV2, implies new therapeutic strategies for the disease. Aim Our study aimed to measure NEAT-1, miR-374b-5p, and IL6 in the serum of COVID-19 patients, demonstrating the correlation between target genes to explore the possible relationship between them. Also, the association between target genes and patients’ clinical findings and radiological severity indices will be explored. Patients and methods The current study included 48 COVID-19-infected individuals and 40 controls. Quantitative real-time PCR (qPCR) was performed to detect lncRNA NEAT-1 and miRNA374b-5p fold change (FC) in the participants’ sera. Enzyme-Linked Immune Sorbent Assay (ELISA) is used to detect IL6. Results Our results showed statistical significance with lower levels of (NEAT-1) [ median (range) = 0.08 (0.001-0.602)], and (miR374b-5p) [ median (range) = 0.14 (.01-7.16)] while higher IL-6 levels [ median (range) = 41.3 (7.2-654) pg/ml] when compared to controls with p-value <0.001. Serum level of NEAT-1 correlates negatively with IL-6 level (r = -.317, P = .008). ROC curve analysis revealed that sensitivity and specificity tests for NEAT-1 and IL-6 levels in the diagnosis of cases illustrated a sensitivity of (100% and 97.9%) and a specificity of (85% and 100%) at cut-off values (0.985 and 12.55), respectively. In comparison, miR374b-5p showed sensitivity and specificity of around 85% in distinguishing COVID-19 patients from controls. No significant association was detected between target genes and radiological severity indices. Conclusions Our study is the first to detect decreased NEAT-1 and miR374b-5p expression in COVID-19 patients’ serum. There was also an increase in IL6 levels. There is a negative correlation between NEAT-1 and IL6 in COVID-19 patients.
Background The SARS-CoV-2 virus’s frequent mutations have made disease control with vaccines and antiviral drugs difficult; as a result, there is a need for more effective coronavirus drugs. Therefore, detecting the expression of various diagnostic biomarkers, including ncRNA in SARS-CoV2, implies new therapeutic strategies for the disease. Aim Our study aimed to measure NEAT-1, miR-374b-5p, and IL6 in the serum of COVID-19 patients, demonstrating the correlation between target genes to explore the possible relationship between them. Also, the association between target genes and patients’ clinical findings and radiological severity indices will be explored. Patients and methods The current study included 48 COVID-19-infected individuals and 40 controls. Quantitative real-time PCR (qPCR) was performed to detect lncRNA NEAT-1 and miRNA374b-5p fold change (FC) in the participants’ sera. Enzyme-Linked Immune Sorbent Assay (ELISA) is used to detect IL6. Results Our results showed statistical significance with lower levels of (NEAT-1) [ median (range) = 0.08 (0.001-0.602)], and (miR374b-5p) [ median (range) = 0.14 (.01-7.16)] while higher IL-6 levels [ median (range) = 41.3 (7.2-654) pg/ml] when compared to controls with p-value <0.001. Serum level of NEAT-1 correlates negatively with IL-6 level (r = -.317, P = .008). ROC curve analysis revealed that sensitivity and specificity tests for NEAT-1 and IL-6 levels in the diagnosis of cases illustrated a sensitivity of (100% and 97.9%) and a specificity of (85% and 100%) at cut-off values (0.985 and 12.55), respectively. In comparison, miR374b-5p showed sensitivity and specificity of around 85% in distinguishing COVID-19 patients from controls. No significant association was detected between target genes and radiological severity indices. Conclusions Our study is the first to detect decreased NEAT-1 and miR374b-5p expression in COVID-19 patients’ serum. There was also an increase in IL6 levels. There is a negative correlation between NEAT-1 and IL6 in COVID-19 patients.
Curated online interaction databases and gene ontology tools have streamlined the analysis of highly complex gene/protein networks. However, understanding of disease pathogenesis has gradually shifted from a protein-based core to complex interactive networks where non-coding RNA (ncRNA) is thought to play an essential role. As current gene ontology is based predominantly on protein-level information, there is a growing need to analyze networks with ncRNA. In this study, we propose a gene ontology workflow integrating ncRNA using the NPInter V5.0 database. To validate the proposed workflow, we analyzed our previously published curated biomarker datasets for hidden disease susceptibility processes and pharmacogenomics. Our results show a novel involvement of melanogenesis in psoriasis response to biological drugs in general. Hyperpigmentation has been previously observed in psoriasis following treatment with currently indicated biological drugs, thus calling attention to melanogenesis research as a response biomarker in psoriasis. Moreover, our proposed workflow highlights the need to critically evaluate computed ncRNA interactions within databases and a demand for gene ontology analysis of large miRNA blocks.
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