Corpus overview


MeSH Disease

HGNC Genes

SARS-CoV-2 proteins

ProteinS (1)


SARS-CoV-2 Proteins
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    Suboptimal SARS-CoV-2-specific CD8 HGNC+ T-cell response associated with the prominent HLA-A HGNC*02:01 phenotype

    Authors: Jennifer R Habel; Thi H O Nguyen; Carolien E van de Sandt; Jennifer A Juno; Priyanka Chaurasia; Kathleen Wragg; Marios Koutsakos; Luca Hensen; Brendon Chua; Wuji Zhang; Hyon Xhi Tan; Katie L Flanagan; Denise Doolan; Joseph Torresi; Weisan Chen; Linda Wakim; Allen Cheng; Jan Petersen; Jamie Rossjohn; Adam K Wheatley; Stephen Kent; Louise Rowntree; Katherine Kedzierska

    doi:10.1101/2020.08.17.20176370 Date: 2020-08-19 Source: medRxiv

    An improved understanding of human T-cell-mediated immunity in COVID-19 MESHD is important if we are to optimize therapeutic and vaccine strategies. Experience with influenza shows that infection primes CD8 HGNC+ T-cell memory to shared peptides presented by common HLA types like HLA-A2. Following re-infection, cross-reactive CD8 HGNC+ T-cells enhance recovery and diminish clinical severity. Stimulating peripheral blood mononuclear cells from COVID-19 MESHD convalescent patients with overlapping peptides from SARS-CoV-2 Spike PROTEIN SARS-CoV-2 Spike MESHD, Nucleocapsid and Membrane proteins led to the clonal expansion of SARS-CoV-2-specific CD8 HGNC+ and CD4 HGNC+ T-cells in vitro, with CD4 HGNC+ sets being typically robust. For CD8 HGNC+ T-cells taken directly ex vivo, we identified two HLA-A HGNC*02:01-restricted SARS-CoV-2 epitopes, A2/S269-277 and A2/Orf1ab3183-3191. Using peptide-HLA tetramer enrichment, direct ex vivo assessment of the A2/S269+ CD8 HGNC+ and A2/Orf1ab3183+ CD8 HGNC+ populations indicated that the more prominent A2/S269+ CD8 HGNC+ set was detected at comparable frequency (1.3x10-5) in acute and convalescent HLA-A HGNC*02:01+ patients. But, while the numbers were higher than those found in uninfected HLA-A HGNC*02:01+ donors (2.5x10-6), they were low when compared with frequencies for influenza-specific (A2/M158) and EBV-specific (A2/BMLF1280) (1.38x10-4) populations. Phenotypic analysis ex vivo of A2/S269+ CD8 HGNC+ T-cells from COVID-19 MESHD convalescents showed that A2/S269+ CD8 HGNC+ T-cells were predominantly negative for the CD38 HGNC, HLA-DR, PD-1 HGNC and CD71 HGNC activation markers, although the majority of total CD8 HGNC+ T-cells were granzyme and/or perforin-positive. Furthermore, the bias towards naive, stem cell memory and central memory A2/S269+ CD8 HGNC+ T-cells rather than effector memory populations suggests that SARS-CoV2 infection MESHD may be compromising CD8 HGNC+ T-cell activation. Priming with an appropriate vaccine may thus have great value for optimizing protective CD8 HGNC+ T-cell immunity in COVID-19 MESHD.

    ACE2 HGNC interaction networks in COVID-19 MESHD: a physiological framework for prediction of outcome in patients with cardiovascular risk factors

    Authors: Zofia Wicik; Ceren Eyileten; Daniel Jakubik; Rodrigo Pavao; Jolanta M Siller-Matula; Marek Postula

    doi:10.1101/2020.05.13.094714 Date: 2020-05-14 Source: bioRxiv

    BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection MESHD ( coronavirus disease 2019 MESHD; COVID-19 MESHD) is associated with adverse outcome in patients with cardiovascular disease MESHD ( CVD MESHD). AimTo characterize the interaction between SARS-CoV-2 and Angiotensin Converting Enzyme 2 HGNC ( ACE2 HGNC) functional networks with focus on CVD. MethodsUsing bioinformatic tools, network medicine approaches and publicly available datasets, we investigated ACE2 HGNC tissue expression and described ACE2 HGNC interaction network which could be affected by SARS-CoV-2 infection MESHD. We identified top ACE2 HGNC interactors, including miRNAs which are shared regulators between the ACE2 HGNC, virus-infection related proteins and heart interaction networks, using lung and nervous system networks as a reference. We also identified main SARS-CoV-2 risk groups and performed drug predictions for them. ResultsWe found the same range of ACE2 HGNC expression confidence in respiratory and cardiovascular systems (averaging 4.48 and 4.64, respectively). Analysing the complete ACE2 HGNC interaction network, we identified 11 genes ( ACE2 HGNC, DPP4 HGNC, ANPEP HGNC, CCL2 HGNC, TFRC HGNC, MEP1A HGNC, ADAM17 HGNC, FABP2 HGNC, NPC1 HGNC, CLEC4M HGNC, TMPRSS2 HGNC) associated with virus-infection related processes. Previously described genes associated with cardiovascular risk factors DPP4 HGNC, CCL2 HGNC and ANPEP HGNC were extensively connected with top regulators of ACE2 HGNC network, including ACE HGNC, INS and KNG1 HGNC. Enrichment analysis revealed several disease phenotypes associated with interaction networks of ACE2 HGNC, heart tissue, and virus-infection related protein, with the strongest associations with the following diseases (in decreasing rank order): obesity, hypertensive disease, non-insulin dependent diabetes mellitus, congestive heart failure, and coronary artery disease. We described for the first time microRNAs- miR HGNC (miR-302c-5p, miR-1305 HGNC, miR-587 HGNC, miR-26b HGNC-5p, and mir-27a-3p), which were common regulators of the three networks: ACE2 HGNC, heart tissue and virus-infection related proteins. ConclusionOur study provides novel information regarding the complexity of signaling pathways affected by SARS-CoV-2 and proposes predictive tools as miR HGNC towards personalized diagnosis and therapy in COVID-19 MESHD. Additionally, our study provides a list of miRNAs with biomarker potential in prediction of adverse outcome in patients with COVID-19 MESHD and CVD. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/094714v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@11e52b0org.highwire.dtl.DTLVardef@1c6d9ceorg.highwire.dtl.DTLVardef@57be3org.highwire.dtl.DTLVardef@8889c_HPS_FORMAT_FIGEXP M_FIG C_FIG

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MeSH Disease
HGNC Genes
SARS-CoV-2 Proteins

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