Introduction: In this study, coagulation and fibrinolysis parameters and their association with disease severity were investigated in coronavirus disease (COVID-19) patients. Materials and Methods: COVID-19 patients (n = 446) admitted to our institute between 21 February 2021 and 17 March 2022, were recruited. Clinical data and staging were collected from all patients. Blood samples were collected and analyzed for several parameters of fibrinolysis and coagulation, including alpha-2-antiplasmin(α2AP) and plasminogen, thrombin activatable fibrinolysis inhibitor (TAFI), tissue plasminogen activator (tPA), plasminogen activator inhibitor-1 (PAI-1), D-dimer, and fibrinogen levels. Results: The TAFI, fibrinogen, and tPA levels were significantly higher in participants who died compared to that of patients who recovered (p < 0.001). However, PAI-1, tPA, and TAFI were significantly higher in patients admitted to the ICU than those of the healthy controls (p < 0.001 for PAI-1 and tPA; p = 0.0331 for TAFI). Our results showed that stage C and D COVID-19 patients had significantly higher levels of PAI-1 (p = 0.003). Furthermore, stage D COVID-19 patients had significantly higher tPA and TAFI values (p = 0.003). Conclusions: Hypofibrinolysis was the most prevalent condition among patients with severe COVID-19. In this study, several coagulation markers were elevated, making them suitable prognostic markers for hypofibrinolysis.

Background: COVID-19 is associated with coagulopathy and increased mortality. The ABO blood group system has been implicated in modulating susceptibility to SARS-CoV-2 infection and disease severity, but its relationship with viral RNAemia, spike gene mutations, and thrombosis remains underexplored. Methods: We analyzed 446 hospitalized COVID-19 patients between 2021 and 2022. SARS-CoV-2 RNAemia was assessed via RT-qPCR on whole blood, and spike gene mutations were identified through whole-genome sequencing in RNAemia-positive samples. ABO blood groups were determined by agglutination testing, and thrombotic events were evaluated using coagulation markers. Statistical analyses included chi-square tests and Kruskal–Wallis tests, with significance set at p < 0.05. Results: RNAemia was detected in 26.9% of patients, with no significant association with ABO blood group (p = 0.175). Omicron was the predominant variant, especially in blood group A (62.5%). The N501Y mutation was the most prevalent in group O (53.2%), and K417N was most prevalent in group B (36.9%), though neither reached statistical significance. Thrombotic events were significantly more common in blood group A (OR = 2.08, 95% CI = 1.3–3.4, p = 0.002), particularly among RNAemia-positive patients. Conclusions: ABO blood group phenotypes, particularly group A, may influence thrombotic risk in the context of SARS-CoV-2 RNAemia. While no direct association was found between blood group and RNAemia or spike mutations, the observed trends suggest potential host–pathogen interactions. Integrating ABO typing and RNAemia screening may enhance risk stratification and guide targeted thromboprophylaxis in COVID-19 patients.

Background: CDKN2A (p16^INK4a^) is integral to the regulation of the RB–E2F cell-cycle checkpoint and is widely acknowledged as a surrogate marker for high-risk human papillomavirus (HPV)-related cervical neoplasia. Nevertheless, its diagnostic and prognostic significance in uterine corpus endometrial carcinoma (UCEC), a predominantly HPV-independent malignancy, remains inadequately characterized. This study utilized an integrated multi-omics approach to examine CDKN2A dysregulation in cervical squamous cell carcinoma (CESC) and UCEC. Methods: Pan-cancer and tumor–normal differential expression analyses were performed using TIMER2.0 and GEPIA2 (TCGA/GTEx). Clinicopathological correlations were assessed with UALCAN. Protein expression patterns were analyzed using immunohistochemistry data from the Human Protein Atlas (HPA). Prognostic significance and immune-infiltration associations were evaluated using TCGA survival data and TIMER modules. Independent transcriptomic validation and diagnostic classification performance were assessed using GEO datasets GSE9750 (CESC) and GSE63678 (UCEC), including ROC-AUC analysis with cross-validation. Results: Integrated analyses revealed elevated CDKN2A expression in both CESC and UCEC across multiple transcriptomic cohorts, with pronounced tumor-specific protein expression on immunohistochemistry. TCGA-only tumor–normal RNA comparisons were non-significant, likely due to limited normal sample representation. In independent GEO cohorts, CDKN2A exhibited excellent tumor–normal discrimination in CESC (AUC = 0.982) and moderate discrimination in UCEC (AUC = 0.761). Survival analysis indicated tumor-specific patterns, with limited prognostic stratification in CESC and context-dependent associations in UCEC. Immune-infiltration analysis suggested tumor-type-specific interactions between CDKN2A expression and immune cell subsets. Conclusions: CDKN2A exhibits strong diagnostic performance in HPV-associated cervical cancer and moderate, cohort-dependent discriminatory ability in endometrial carcinoma. These findings reinforce its established diagnostic role in CESC and propose adjunctive utility in UCEC, underscoring the importance of tumor-contextual interpretation of CDKN2A expression in gynecologic malignancies.

Pregnant women are at an increased risk of severe influenza complications, necessitating vaccination as a preventive measure. Despite World Health Organization (WHO) recommendations for influenza vaccination during pregnancy, vaccination rates remain suboptimal in many regions. This study aims to identify key differentially expressed genes (DEGs) and biological pathways modulated by influenza vaccination in pregnant women pre- and post-vaccination, contributing to improved vaccine strategies. Microarray data from gene expression omnibus GEO dataset GSE166545 was analyzed to identify DEGs in blood samples from pregnant women at three time points: pre-vaccination (Day 0) and post-vaccination (Days 0 and 1) (Days 1 and 7). DEGs were filtered using an adjusted p-value < 0.05 and |log2 fold change| ≥ 1. Protein/protein interaction (PPI) networks, hub gene identification, and pathway enrichment analyses were conducted using STRING, Cytoscape, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome databases. Hub gene validation was performed using the Human Protein Atlas (HPA) and GTEx Portal. The GSE166545 dataset analysis revealed 60 up-regulated and 12,854 down-regulated genes (Day 1 vs. 7), 55 up-regulated and 12,933 down-regulated genes (Day 0 vs. 1), and two up-regulated with no down-regulated genes (Day 0 vs. 7). Key pathways included interferon alpha/beta (IFN-γ\ β) signaling and toll-like receptor signaling (TLR). Hub genes such as GBP1, CXCL10, RSAD2, and IFI44 demonstrated robust up-regulation, correlating with enhanced immune responses. The initial observation of JCHAIN’s notable up-regulation occurred on the seventh day following vaccination. Validation confirmed these genes’ roles in antiviral defense mechanisms and vaccine responses. The findings reveal distinct immune response dynamics in pregnant women following influenza vaccination, highlighting potential biomarkers for vaccine efficacy. This study underscores the importance of tailored vaccine strategies to improve maternal and neonatal outcomes.

The progression of tuberculosis (TB) from a latent infection to an active disease involves intricate modifications in host immune, inflammatory, oxidative, and metabolic pathways. Ferroptosis represents a distinct form of regulated cell death that requires iron and is associated with excessive lipid peroxidation and has been associated with tissue damage in TB; however, its connection with host transcriptional changes during active TB is not fully understood. This study sought to identify and externally validate immune–inflammatory hub genes among differentially expressed genes (DEGs) in active TB that overlap with a ferroptosis-associated gene set derived from FerrDb, employing an integrated transcriptomic and systems-biology methodology. Differential expression analysis of GSE37250 revealed 1015 DEGs in active TB compared to latent TB, comprising 585 upregulated and 430 downregulated genes, and 93 DEGs in active TB compared to healthy controls, including 65 upregulated and 28 downregulated genes. Intersection analysis identified 94 DEGs common to the active TB versus latent TB comparison and the ferroptosis-associated gene set, and eight DEGs common to the active tuberculosis versus healthy-control comparison and the same gene set, with no genes shared across all three sets. Functional enrichment of the 94 intersection genes underscored immune response, defense response, stress response, Toll-like receptor signaling, NOD-like receptor signaling, IL-17 signaling, TNF signaling, glutathione metabolism, neutrophil degranulation, cytokine signaling, and antimicrobial metal sequestration. Protein–protein interaction analysis followed by cytoHubba prioritization identified 10 hub genes: IL1B, TLR4, CXCL10, MMP9, CYBB, MPO, CD36, LCN2, S100A8, and LTF. Subsequent to outcome-independent probe selection, external validation in GSE28623 demonstrated significant positive differential expression of LCN2, S100A8, and LTF, while GSE62525 showed significant positive differential expression of IL1B, TLR4, MMP9, MPO, LCN2, and LTF. LCN2 and LTF were significantly upregulated in both validation datasets, indicating the strongest cross-dataset reproducibility. These results identify an immune–inflammatory transcriptional network intersecting with ferroptosis-associated genes in active TB. Notably, the transcriptomic findings do not confirm ferroptotic cell death but suggest candidate genes and biological processes for future experimental exploration.

Background/Objectives: Genetic variation in human leukocyte antigen (HLA) genes may contribute to inter-individual differences in infectious-disease susceptibility and clinical outcomes. This study aimed to determine the genotype frequency of HLA Class I and Class II loci in patients with COVID-19 in Saudi Arabia and to examine their associations with survival and clinical severity. Methods: A prospective observational study was conducted at King Faisal Specialist Hospital and Research Centre (KFSH&RC), Riyadh, Saudi Arabia, from January 2022 to December 2023. Genomic DNA was extracted, and polymerase chain reaction-sequence specific oligonucleotide (PCR-SSO) testing was performed to screen HLA genetic variation. Patients were grouped by survival status (recovered or deceased) and clinical severity: Stage A (asymptomatic), Stage B (mild), Stage C (moderate), and Stage D (severe). Results: In total, 123 patients with COVID-19 were included; 102 (82.9%) recovered and 21 (17.1%) died. ICU admission was more frequent among deceased patients than among recovered patients (95.2% versus 51.0%, p = 0.0001). At the locus level, HLA-DPB1 represented the largest proportion of HLA calls (21%). In call-position-specific allele-group analyses, B*15 in Allele 1 (14.3% versus 1.0%, p = 0.016), C*06 in Allele 2 (42.9% versus 18.6%, p = 0.023), DRB1*10 in Allele 1 (19.0% versus 4.9%, p = 0.045), and DQB1*05 in Allele 1 (33.3% versus 11.8%, p = 0.021) were significantly more frequent among deceased patients, whereas DQB1*03 in Allele 1 was significantly more frequent among recovered patients (45.1% versus 14.3%, p = 0.013). Severity analyses showed call-position-specific differences involving C*15, C*06, B*14, B*39, B*53, and DQB1*03. Vaccination status did not differ significantly by survival status or across the four clinical severity stages. Conclusions: Selected HLA Class I and Class II allele groups may be associated with COVID-19 survival and clinical severity patterns in this Saudi cohort. These findings should be interpreted cautiously given the cohort size and call-position-specific nature of the analyses.