FURIN, IFNL4, and TLR2 gene polymorphisms in relation to COVID-19 severity: a case-control study in Egyptian patients.

BACKGROUND AND AIM: A wide range of clinical manifestations and outcomes, including liver injury, have been reported in COVID-19 patients. We investigated the association of three substantial gene polymorphisms (FURIN, IFNL4, and TLR2) with COVID-19 disease susceptibility and severity to help predict prognosis. METHODS: 150 adult COVID-19-assured cases were categorized as follows: 78 patients with a non-severe presentation, 39 patients with severe disease, and 33 critically ill patients. In addition, 74 healthy controls were included. Clinical and laboratory evaluations were carried out, including complete and differential blood counts, D-dimer, lactate dehydrogenase (LDH), C-reactive protein (CRP), procalcitonin, ferritin, interleukin-6 (Il-6), and liver and kidney functions. FURIN (rs6226), IFNL4 (rs12979860), and TLR2 (rs3804099) genotyping allelic discrimination assays were conducted using real-time PCR. RESULTS: The FURIN, IFNL4, and TLR2 genotypes and their alleles differed significantly between COVID-19 patients and controls, as well as between patients with severe or critical illness and those with a non-severe presentation. According to a multivariable regression analysis, FURIN (C/T + T/T) and TLR2 (T/C + C/C) mutants were associated with COVID-19 susceptibility, with odds ratios of 3.293 and 2.839, respectively. FURIN C/C and IFNL4 T/T mutants were significantly linked to severe and critical illnesses. Multivariate regression analysis showed that FURIN (G/C + C/C) genotypes and IFNL4 T/T homozygosity were independent risk factors associated with increased mortality. CONCLUSION: FURIN, IFNL4, and TLR2 gene variants are associated with the risk of COVID-19 occurrence as well as increased severity and poor outcomes in Egyptian patients.

Metabolic profiling during COVID-19 infection in humans: Identification of potential biomarkers for occurrence, severity and outcomes using machine learning.

BACKGROUND: After its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations differ in severity, ranging from mild symptoms to severe disease. Although perturbation of metabolism has been reported as a part of the host response to COVID-19 infection, scarce data exist that describe stage-specific changes in host metabolites during the infection and how this could stratify patients based on severity. METHODS: Given this knowledge gap, we performed targeted metabolomics profiling and then used machine learning models and biostatistics to characterize the alteration patterns of 50 metabolites and 17 blood parameters measured in a cohort of 295 human subjects. They were categorized into healthy controls, non-severe, severe and critical groups with their outcomes. Subject's demographic and clinical data were also used in the analyses to provide more robust predictive models. RESULTS: The non-severe and severe COVID-19 patients experienced the strongest changes in metabolite repertoire, whereas less intense changes occur during the critical phase. Panels of 15, 14, 2 and 2 key metabolites were identified as predictors for non-severe, severe, critical and dead patients, respectively. Specifically, arginine and malonyl methylmalonyl succinylcarnitine were significant biomarkers for the onset of COVID-19 infection and tauroursodeoxycholic acid were potential biomarkers for disease progression. Measuring blood parameters enhanced the predictive power of metabolic signatures during critical illness. CONCLUSIONS: Metabolomic signatures are distinctive for each stage of COVID-19 infection. This has great translation potential as it opens new therapeutic and diagnostic prospective based on key metabolites.

Evaluation of ABCA1 gene polymorphism as a prognostic index of fibrosis progression in NAFLD patients.

INTRODUCTION: It had been evident that non-alcoholic fatty liver disease (NAFLD) is the new era epidemic. Despite emergence of many drugs on the pipeline that considered candidates to cure NAFLD/NASH, the critical need for defining the cohort liable to fibrosis progression is yet unmet. AIM: Evaluate ABCA1 (rs1800977) genotyping as a noninvasive predictor of liver fibrosis severity. MATERIALS AND METHODS: This study included 118 liver biopsy-proven NAFLD-patients. According to Metavir-fibrosis-staging, cases were divided to early fibrosis (74 cases), and 44 cases with significant fibrosis (>F2), added to 49 healthy control subjects. All patients were subjected to liver function tests, lipids profile, triglyceride TG index, and hepatic steatosis index (HSI) and real-time PCR ABCA1 SNP (rs1800977). RESULTS: Significant differences in transaminases (p > .05), albumin (p < .009), cholesterol (p0.03), low density lipoproteins (LDL) (0.006), triglycerides (p < .001), HSI (p < .001), FIB4 (p < .001) and APRI (p < .001) were reported in those with significant than early fibrosis and control groups. CC was the most prevalent in significant (36.4%) than early fibrosis (13.5%) and control groups (8.2%), with prevalence of C allele in significant fibrosis (p ≤ .003). Univariate analysis revealed that DM (p ≤ .001), TG index (p ≤ .022), cholesterol (p ≤ .03), HSI (p ≤ .006), LDL (p ≤ .02), HDL (p ≤ .01), APRI (p ≤ .02) and CC genotype (p ≤ .005) were the main factors affecting fibrosis progression in NAFLD. However multivariate analysis proved only the role of HSI (p ≤ .005), LDL (p ≤ .02), HDL (p ≤ .003) and CC genotype (p ≤ .03) in predicting fibrosis severity. CONCLUSION: Dyslipidemias, hepatic steatosis index and ABCA1 (rs1800977) gene polymorphism CC genotype; were the only independent predictors of advanced fibrosis in NAFLD-patients.

Value of IFNL3 genetic polymorphism in the prediction of HCV treatment response to direct-acting antiviral drugs versus interferon therapy.

Background: Despite the outstanding results of direct-acting antiviral therapies (DAAs) of Hepatitis C infection (HCV), non-responders had to be more defined. Aim: assess the outcome of DAAs in linkage with Interferon lambda 3 (IFNL3) in HCV patients. Methods: This case-control-study was conducted on 495 chronic-HCV (genotype-4a), previously treated Egyptians by either DAAs (responders 195, 120 relapsers) or interferon/ribavirin (IFN/RBV) (140 responders, 60 relapsers), and 98 healthy controls. IFNL3 distribution, clinical and laboratory data were assessed. Results: CT was the most predominant genotype in Egyptians (51%). All genotypes were sensitive to DAAs mainly CT genotype (60%), even TT genotype (resistant to IFN/RBV 40%) had 29.2% sensitivity. CT genotype was predominant in sofosbuvir/Daclatasvir responders (67.6%) (OR = 0.66), while non-CT prevailed in relapsers (56.7%). TT genotype may respond to SOF/Ledi better than other regimens (66.7%). In IFN/RBV relapsers; CT genotype was commoner (50%) than others, while CC genotype predominated in responders (54.3%). The c allele was the commonest in responders to IFN/RBV (71.4%), while the T allele was resistant to treatment (65% in relapsers). Addition of RBV to SOF/DCV reported higher resistance with CT genotype (42.2%-50%) and TT genotype (17.8%-27.8%). Conclusion: This study recommended IFNL3 genotyping to be a prerequisite before stratifying treatment for HCV-4a Egyptians.