The COVID-19 pandemic has resulted in a global humanitarian crisis. Despite ongoing research, transmission risks and many disease characteristics remain unclear. Most patients have displayed elevated levels of certain inflammatory markers, which we sought to investigate further in relation to disease severity. The aim of this study was to examine the correlation between inflammatory markers and the severity of COVID-19 among patients. We conducted a cross-sectional study from April to September 2020, involving 143 COVID-19 PCR-positive patients from Ziauddin Hospital. Electronic patient records provided data on demographics, clinical status, and laboratory results. The majority of PCR-positive patients were elderly males with comorbidities such as diabetes and hypertension. Almost all patients exhibited increased levels of various inflammatory markers, with procalcitonin (97.2%) being the most common. Statistically significant differences were observed in the levels of TLC (p=0.005), CRP (p=0.001), LDH (p=0.001), Ferritin (p=0.001), D-dimer (p=0.001), and procalcitonin (p=0.028), in relation to COVID-19 severity. The data suggest a significant association between levels of inflammatory markers and COVID-19 severity. All markers, except procalcitonin, demonstrated a significant correlation with disease severity. These results could enhance our understanding of COVID-19 pathogenesis and help predict and manage severe cases.

Science is digging for the varied presentation of COVID-19 patients exposed to the same risk factors, and medical conditions may be influenced by the presence of polymorphic genetic variants. This study investigated the link between ACE2 gene polymorphisms and the severity of SARS-CoV-2. This cross-sectional study recruited COVID-19 PCR-positive patients by consecutive sampling from Ziauddin Hospital from April to September 2020. DNA was extracted from whole blood, followed by gene amplification and Sanger’s sequencing. Most of the patients, 77: 53.8%, were serious. Males were higher (80; 55.9%) with age more than 50 years (106: 74.1%). We found 22 ACE2 SNPs. rs2285666 SNP was most prevalent with 49.2% CC, 45.2% TT, 4.8% CT heterozygosity, and 0.8% AA genotypes. Variants with multiple genotypes were also insignificantly associated with the severity of COVID-19 in the analysis of the dominant model. Only rs2285666 had a significant statistical link with gender (p-value 0.034, OR; 1.438, CI; 1.028–2.011) while rs768883316 with age groups (p-value 0.026, OR; 1.953, CI; 1.085–3.514). Haplotypes ATC of three polymorphisms (rs560997634, rs201159862, and rs751170930) commonly found in 120 (69.77%) and TTTGTAGTTAGTA haplotype consisting of 13 polymorphisms (rs756737634, rs146991645, rs1601703288, rs1927830489, rs1927831624, rs764947941, rs752242172, rs73195521, rs781378335, rs756597390, rs780478736, rs148006212, rs768583671) in 112 (90.32%) had statistically significant association with the severity having p = value 0.029 and 0.001 respectively. Males of old age and diabetics are found to have more severe COVID-19 infection in the current study. We also found that common ACE2 polymorphism rs2285666 influences the susceptibility of acquiring the severe SARS-CoV-2 infection.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common types of cancer in the world and a reason behind different oncogenes activation and tumor suppressor genes inactivation. Hyper-methylation of tumor suppressor genes including RASSF1a, GSTP1, p16, and APC cause gene silencing as well as tumor cell invasion. STAT 1 gene is a part of signaling cascade of JAK/STAT and any dysregulation in signaling has been implicated in tumor formation. OBJECTIVE: The current investigation focus on the methylation role of STAT1 gene as a non-invasive biomarker in the progression and diagnosis of hepatocellular carcinoma. METHODS: STAT1 gene methylation status in 46 HCV induced hepatocellular carcinoma patients and 40 non-HCC controls were examined by methylation specific PCR. STAT1 gene expression was examined by real time PCR and further validated by various bioinformatics tools. RESULTS: STAT1 methylation in HCV-induced HCC (67.4%) was significantly higher compared to the non-HCC controls (p< 0.01). However, mRNA expression of STAT1 gene in methylated groups was significantly lower compared to unmethylated groups (p< 0.05). Furthermore, insilco analysis of STAT1 validated our results and shown expression of STAT1 mRNA was lower in liver cancer with the median 24.3 (p= 0.085). CONCLUSION: After using peripheral blood samples we observed that STAT1 silencing caused by aberrant methylation could be used as potential non-invasive biomarker for the diagnosis of HCV induced hepatocellular carcinoma. We conclude that blood as a sample source could be used instead of biopsy for early detection of HCC.