Notably, individuals with Down syndrome are at very high risk of developing severe COVID-19. The HTP is co-organized and funded by the Global Down Syndrome Foundation and is one of the world's largest studies aimed at understanding co-occurring conditions of Down syndrome. The development of the COVIDome dataset was modeled after the Crnic Institute Human Trisome Project (HTP) which was launched in 2016. Importantly, this large dataset is made openly available through the COVIDome Explorer portal, a user-friendly online tool that has been employed by 1500+ users across 60+ countries since its launch in November 2020. Omics technologies analyze the genome, transcriptome, proteome, and metabolome of biological samples. The samples were provided through the CU COVID Biobank led by Thomas Flaig, MD, vice chancellor of research at the CU Anschutz Medical Campus, and subjected to a deep analysis using the latest ' omics technologies as part of a multidisciplinary effort led by Espinosa and Flaig known as the COVIDome Project. The collaborative team led by Joaquin Espinosa, Ph.D., executive director of the Linda Crnic Institute for Down Syndrome and professor at the University of Colorado School of Medicine used blood samples and data from patients hospitalized with COVID-19 through a partnership with UCHealth and Children's Hospital Colorado. However, a prolonged and exacerbated immune response can cause organ damage and even death. If the immune response, including the production of IFNs, is unable to clear the virus, the immune system continues to fight. Interferons (IFNs) are signaling proteins produced by a host cell to activate the antiviral defenses within the body. Credit: DOI: 10.1073/pnas.2116730119Ī recent study published in the Proceedings of the National Academy of Sciences by a team of researchers at the University of Colorado Anschutz Medical Campus significantly advances the understanding of a key aspect of the immune system during COVID-19: the interferon response. Values displayed are NES from GSEA asterisks indicate significant enrichment (10% FDR) columns and rows are grouped by hierarchical clustering.
(H) Heatmap representing enrichment of Hallmark gene sets among Spearman correlations between mRNA levels and plasma levels of IFNs. (G) Scatter plots showing the relationship between ISG mRNA levels and plasma abundance of IFNs in COVID-19 patients. Points are colored by density blue lines represent linear model fit with 95% confidence intervals in gray. (F) Scatter plots showing the relationship between RNA-based IFN-α score and plasma abundance of IFNs in COVID-19 patients. Numbers above brackets are q-values for Mann–Whitney U tests. Data are presented as modified sina plots with boxes indicating median and interquartile range. (E) Sina plots comparing abundance for the indicated IFNs by COVID-19 status. Values are Spearman correlation coefficients (rho) asterisks indicate significant correlations (10% FDR). (D) Ranked heatmap representing correlations between RNA-based IFN-α scores and plasma levels of IFNs. Data are presented as a modified sina plot with box indicating median and interquartile range number above bracket is the q-value for Mann–Whitney U test. (C) RNA-based IFN-α scores by COVID-19 status. Bar color represents NES bar length represents -log10(q-value). (B) Bar plot of top 10 Hallmark gene sets as ranked by absolute normalized enrichment score (NES) from GSEA. Horizontal dashed line indicates a false-discovery rate (FDR) 10% for negative binomial Wald test numbers above plot indicate significant genes. (A) Volcano plot for differential mRNA expression analysis by COVID-19 status, adjusted for age and sex. IFN signaling at the whole-blood transcriptome level correlates with a subset of IFNs.
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