Host genetic variants associated with COVID-19 reconsidered in a Slovak cohort.

We present the results of an association study involving hospitalized coronavirus disease 2019 (COVID-19) patients with a clinical background during the 3rd pandemic wave of COVID-19 in Slovakia. Seventeen single nucleotide variants (SNVs) in the eleven most relevant genes, according to the COVID-19 Host Genetics Initiative, were investigated. Our study confirms the validity of the influence of LZTFL1 and 2'-5'-oligoadenylate synthetase (OAS)1/OAS3 genetic variants on the severity of COVID-19. For two LZTFL1 SNVs in complete linkage disequilibrium, rs17713054 and rs73064425, the odds ratios of baseline allelic associations and logistic regressions (LR) adjusted for age and sex ranged in the four tested designs from 2.04 to 2.41 and from 2.05 to 3.98, respectively. The OAS1/OAS3 haplotype 'gttg' carrying a functional allele G of splice-acceptor variant rs10774671 manifested its protective function in the Delta pandemic wave. Significant baseline allelic associations of two DPP9 variants in all tested designs and two IFNAR2 variants in the Omicron pandemic wave were not confirmed by adjusted LR. Nevertheless, adjusted LR showed significant associations of NOTCH4 rs3131294 and TYK2 rs2304256 variants with severity of COVID-19. Hospitalized patients' reported comorbidities were not correlated with genetic variants, except for obesity, smoking (IFNAR2), and hypertension (NOTCH4). The results of our study suggest that host genetic variations have an impact on the severity and duration of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Considering the differences in allelic associations between pandemic waves, they support the hypothesis that every new SARS-CoV-2 variant may modify the host immune response by reconfiguring involved pathways.

High Expression of ERK-related RASGRF2 predicts Poor prognosis in patients with Stomach Adenocarcinoma and correlates with M2 macrophage.

Background: The role of RASGRF2 has been verified in the development of various cancers. However, its roles in stomach adenocarcinoma (STAD) are still under investigation. Methods: RASGRF2 transcript-level data and the associated clinical information from patients with STAD were extracted from The Cancer Genome Atlas (TCGA). Diagnostic and prognostic values of RASGRF2 were analyzed using receiver-operator characteristics (ROC) analysis, correlation analysis, and survival analysis in conjunction with a prognostic model. In addition, gene expression profiles, differentially-expressed genes for co-varying expression, and a differential expressed genes (DEG) protein-protein interaction network for influential nodes were also analyzed. To identify the molecular role of RASGRF2 in STAD, gene ontology (GO) term, Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway, and gene set enrichment analysis (GSEA)-mediated functional module enrichment analyses were conducted. The relationship between RASGRF2 and gene signature-based predicted immune cell infiltration patterns were also investigated. To validate the bioinformatic findings, RASGRF2 protein expression was investigated in vitro using western blot and immunohistochemistry. Furthermore, relationships among RASGRF2 protein expression, clinicopathologic characteristics, and patient survival were analyzed. Results: Bioinformatic analysis revealed a significantly higher RASGRF2 transcript level in STAD tissue, which was positively associated with the T stage, histological type, histological grade, and TP53 status. Moreover, the RASGRF2 transcript level indicated poor overall survival in STAD patients (hazard ratio = 1.47, P = 0.023). Multivariate Cox regression analysis showed that primary therapy outcome, age, and RASGRF2 transcript level were independent prognostic factors for survival, and the C-index of a nomogram was 0.695. Additionally, 159 genes were differentially expressed according to RASGRF2 transcript levels; 15 exhibited co-varying expression, and 13 were identified as influential nodes. The DEG-list was significantly enriched for several GO terms, biological pathways, and functional modules, including MAPK, RAS, ERK, and immunoregulatory pathways. RASGRF2 transcript levels were significantly positively correlated with infiltration levels of Tem, Macrophages, pDCs, and NK cells. Validation analysis showed similar results for the RASGRF2 protein expression level in both in vitro analyses. Conclusion: Bioinformatic predictions combined with in vitro validation suggest that RASGRF2 plays diagnostic and prognostic roles and serves as a negative protective molecular factor in STAD patients.