Genetic variation of interleukin-1 receptor type 1 is associated with severity of COVID-19 disease.
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ABSTRACT:
SUBMITTER: Wang R
PROVIDER: S-EPMC8690223 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The potential protective or pathogenic role of the adaptive immune response to SARS-CoV-2 infection has been vigorously debated. While COVID-19 patients consistently generate a T cell response to SARS-CoV-2 antigens, evidence of significant immune dysregulation in these patients continues to accumulate. In this study, next generation sequencing of the T cell receptor Beta chain (TRB) repertoire was conducted in hospitalized COVID-19 patients to determine if immunogenetic differences of the TRB repertoire contribute to the severity of the disease course. Clustering of highly similar TRB CDR3 amino acid sequences across COVID-19 patients yielded 785 shared TRB sequences. The TRB sequences were then filtered for known associations with common diseases such as EBV and CMV. The remaining sequences were cross-referenced to a publicly accessible dataset that mapped COVID-19 specific TCRs to the SARS-CoV-2 genome. We identified 140 SARS-CoV-2 specific TRB sequences belonging to 119 clusters in our COVID-19 patients. Next, we investigated 92 SARS-CoV-2 specific clusters binding only one peptide target in relation to disease course. Distinct skewing of SARS-CoV-2 specific TRB sequences towards the nonstructural proteins (NSPs) of ORF1a/b of the SARS-CoV-2 genome was observed in clusters with critical disease course when compared to COVID-19 clusters with a severe disease course. These data imply that T-lymphocyte reactivity towards peptides from nonstructural proteins of SARS-CoV-2 may not constitute an effective adaptive immune response and thus may negatively affect disease severity.
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Project description:In this article, we report first data on the urinary test COVID31 that enables prediction of critical progression and death outcomes in COVID-19 patients. COVID31 is composed of 31 endogenous peptides mainly derived from various collagen chains that enable differentiation of moderate and severe disease courses from those that progress to a critical state or death. The test is based on non-invasive urine analysis and expected to have a major impact on the management of COVID-19 outpatients by guiding patient’s stratification towards timely and targeted intervention to improve disease outcome.
2020-09-28 | PXD020444 | Pride
Project description:PurposePatients with type 2 diabetes (T2D) have demonstrated a higher risk for developing more severe cases of COVID-19, but the complex genetic mechanism between them is still unknown. The aim of the present study was to untangle this relationship using genetically based approaches.MethodsBy leveraging large-scale genome-wide association study (GWAS) summary statistics of T2D and COVID-19 severity, linkage disequilibrium score regression and Mendelian randomization (MR) analyses were utilized to quantify the genetic correlations and causal relationships between the two traits. Gene-based association and enrichment analysis were further applied to identify putative functional pathways shared between T2D and COVID-19 severity.ResultsSignificant, moderate genetic correlations were detected between T2D and COVID-19 hospitalization (rg = 0.156, SE = 0.057, p = 0.005) or severe disease (rg = 0.155, SE = 0.057, p = 0.006). MR analysis did not support evidence for a causal effect of T2D on COVID-19 hospitalization (OR 1.030, 95% CI 0.979, 1.084, p = 0.259) or severe disease (OR 0.999, 95% CI 0.934, 1.069, p = 0.982). Genes having pgene < 0.05 for both T2D and COVID-19 severe were significantly enriched for biological pathways, such as response to type I interferon, glutathione derivative metabolic process and glutathione derivative biosynthetic process.ConclusionsOur findings further confirm the comorbidity of T2D and COVID-19 severity, but a non-causal impact of T2D on severe COVID-19. Shared genetically modulated molecular mechanisms underlying the co-occurrence of the two disorders are crucial for identifying therapeutic targets.
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