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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.

Background: Type 2 diabetes mellitus is one of the leading causes of morbidity and mortality worldwide and is derived from an accumulation of genetic and epigenetic changes. In this study, we aimed to construct Insilco, a competing endogenous RNA (ceRNA) network linked to the pathogenesis of insulin resistance followed by its experimental validation in patients’, matched control and cell line samples, as well as to evaluate the efficacy of CRISPR/Cas9 as a potential therapeutic strategy to modulate the expression of this deregulated network. By applying bioinformatics tools through a two-step process, we identified and verified a ceRNA network panel of mRNAs, miRNAs and lncRNA related to insulin resistance, Then validated the expression in clinical samples (123 patients and 106 controls) and some of matched cell line samples using real time PCR. Next, two guide RNAs were designed to target the sequence flanking LncRNA/miRNAs interaction by CRISPER/Cas9 in cell culture. Gene editing tool efficacy was assessed by measuring the network downstream proteins GLUT4 and mTOR via immunofluorescence. Results: LncRNA-RP11-773H22.4, together with RET, IGF1R and mTOR mRNAs, showed significant upregulation in T2DM compared with matched controls, while miRNA (i.e., miR-3163 and miR-1) and mRNA (i.e., GLUT4 and AKT2) expression displayed marked downregulation in diabetic samples. CRISPR/Cas9 successfully knocked out LncRNA-RP11-773H22.4, as evidenced by the reversal of the gene expression of the identified network at RNA and protein levels to the normal expression pattern after gene editing. Conclusions: The present study provides the significance of this ceRNA based network and its related target genes panel both in the pathogenesis of insulin resistance and as a therapeutic target for gene editing in T2DM.

IntroductionType 2 diabetes mellitus (T2DM) is a major global health concern. It usually develops gradually and is frequently preceded by undetectable pre-diabetes mellitus (pre-DM) stage. The purpose of this study was to identify a novel set of seven candidate genes associated with the pathogenesis of insulin resistance (IR) and pre-DM, followed by their experimental validation in patients’ serum samples.MethodsWe used the bioinformatics tools and through a two-step process, we first identified and verified two mRNA candidate genes linked to insulin resistance molecular pathogenesis. Second, we identified a non-coding RNAs related to the selected mRNAs and implicated in the insulin resistance molecular pathways followed by pilot study for the RNA panel differential expression in 66 patients with T2DM, 49 individuals with prediabetes and 45 matched controls using real time PCR.ResultsThe levels of expression of TMEM173 and CHUK mRNAs, hsa-miR (-611, -5192, and -1976) miRNAs gradually increased from the healthy control group to the prediabetic group, reaching their maximum levels in the T2DM group (p &lt;10-3), whereas the levels of expression of RP4-605O3.4 and AC074117.2 lncRNAs declined gradually from the healthy control group to the prediabetic group, reaching their lowest levels in the T2DM group (p &lt;10-3). TMEM173, CHUK mRNAs, hsa_miR (-611 &amp; -1976) and RP4-605O3.4 lncRNA were useful in distinguishing insulin resistant from insulin sensitive groups. miR_611 together with RP4-605O3.4 exhibited significant difference in good versus poor glycemic control groups.DiscussionThe presented study provides an insight about this RNA based STING/NOD/IR associated panel that could be used for PreDM-T2DM diagnosis and also as a therapeutic target based on the differences of its expression level in the pre-DM and T2DM stages.

Background: Autophagy and Insulin resistance play a crucial role in pathogenesis of T2DM. Novel accurate strategies for detection of molecular pathogenesis of insulin resistance are distinctly needed. Aim of the work:To retrieve potential mRNA associated with insulin resistance related autophagy from databases followed by validation of this network in patients' clinical samples.Material and Methods: Bioinformatics' Analysis was done to retrieve a gene related to autophagy and IR in T2DM, then biomarker' verification was done through Gene Cards Database. Extraction of total RNA from PMNCs followed by reverse transcription PCR, then quantitative real time PCR for mRNA m-TOR in PMNCs of 123 patients with T2DM and 106 healthy normal volunteers.Results: The mRNA m-TOR had high sensitivity and specificity for discriminating T2DM patients from healthy controls. Conclusion:The mRNA m-TOR can serve as a potential biomarker for T2DM diagnosis and prognosis.