<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Unterman A</submitter><funding>BLRD VA</funding><funding>NCATS NIH HHS</funding><funding>NIA NIH HHS</funding><funding>NIAID NIH HHS</funding><funding>NHLBI NIH HHS</funding><funding>NLM NIH HHS</funding><funding>Department of Defense</funding><funding>NIGMS NIH HHS</funding><funding>Department of Internal Medicine at Yale School of Medicine</funding><pagination>440</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8782894</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>13(1)</volume><pubmed_abstract>Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100A&lt;sup>hi&lt;/sup>/HLA-DR&lt;sup>lo&lt;/sup> classical monocytes and activated LAG-3&lt;sup>hi&lt;/sup> T cells are hallmarks of progressive disease and highlights the abnormal MHC-II/LAG-3 interaction on myeloid and T cells, respectively. We also find skewed T cell receptor repertories in expanded effector CD8&lt;sup>+&lt;/sup> clones, unmutated IGHG&lt;sup>+&lt;/sup> B cell clones, and mutated B cell clones with stable somatic hypermutation frequency over time. In conclusion, our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19.</pubmed_abstract><journal>Nature communications</journal><pubmed_title>Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19.</pubmed_title><pmcid>PMC8782894</pmcid><funding_grant_id>F30 HL143906</funding_grant_id><funding_grant_id>R21 LM012884</funding_grant_id><funding_grant_id>U01 HL145567</funding_grant_id><funding_grant_id>T32 GM136651</funding_grant_id><funding_grant_id>UL1 TR001863</funding_grant_id><funding_grant_id>PR181442</funding_grant_id><funding_grant_id>R01 HL126094</funding_grant_id><funding_grant_id>R01 AI104739</funding_grant_id><funding_grant_id>T15 LM007056</funding_grant_id><funding_grant_id>K24 AG042489</funding_grant_id><funding_grant_id>R35 GM143072</funding_grant_id><funding_grant_id>R01 AI121207</funding_grant_id><funding_grant_id>I01 BX004661</funding_grant_id><funding_grant_id>P01 AI039671</funding_grant_id><funding_grant_id>P01 AI073748</funding_grant_id><funding_grant_id>U19 AI089992</funding_grant_id><funding_grant_id>R01 HL141852</funding_grant_id><pubmed_authors>Peng X</pubmed_authors><pubmed_authors>Mohanty S</pubmed_authors><pubmed_authors>Wang G</pubmed_authors><pubmed_authors>DeIuliis G</pubmed_authors><pubmed_authors>Cosme C</pubmed_authors><pubmed_authors>Yale IMPACT Research Team</pubmed_authors><pubmed_authors>Vogels CBF</pubmed_authors><pubmed_authors>Grubaugh ND</pubmed_authors><pubmed_authors>Minasyan M</pubmed_authors><pubmed_authors>Ko AI</pubmed_authors><pubmed_authors>Ruff WE</pubmed_authors><pubmed_authors>Nelson A</pubmed_authors><pubmed_authors>Deng W</pubmed_authors><pubmed_authors>Wang Z</pubmed_authors><pubmed_authors>Kaminski N</pubmed_authors><pubmed_authors>Raredon MSB</pubmed_authors><pubmed_authors>Farhadian SF</pubmed_authors><pubmed_authors>Chen M</pubmed_authors><pubmed_authors>Schupp JC</pubmed_authors><pubmed_authors>Zhao AY</pubmed_authors><pubmed_authors>Li N</pubmed_authors><pubmed_authors>Sharma L</pubmed_authors><pubmed_authors>Montgomery RR</pubmed_authors><pubmed_authors>van Dijk D</pubmed_authors><pubmed_authors>Bermejo S</pubmed_authors><pubmed_authors>Hoehn KB</pubmed_authors><pubmed_authors>Dela Cruz CS</pubmed_authors><pubmed_authors>Gasque V</pubmed_authors><pubmed_authors>Niklason LE</pubmed_authors><pubmed_authors>Fournier J</pubmed_authors><pubmed_authors>Hafler DA</pubmed_authors><pubmed_authors>Liu Y</pubmed_authors><pubmed_authors>Ravindra NG</pubmed_authors><pubmed_authors>Iwasaki A</pubmed_authors><pubmed_authors>Asashima H</pubmed_authors><pubmed_authors>Casanovas-Massana A</pubmed_authors><pubmed_authors>Kleinstein SH</pubmed_authors><pubmed_authors>Shaw AC</pubmed_authors><pubmed_authors>Sumida TS</pubmed_authors><pubmed_authors>Zhao H</pubmed_authors><pubmed_authors>Wong P</pubmed_authors><pubmed_authors>Melillo A</pubmed_authors><pubmed_authors>Raddassi K</pubmed_authors><pubmed_authors>Unterman A</pubmed_authors><pubmed_authors>Yan X</pubmed_authors><pubmed_authors>Nouri N</pubmed_authors><pubmed_authors>Rainone M</pubmed_authors><pubmed_authors>Castaldi C</pubmed_authors><pubmed_authors>Stein Y</pubmed_authors><pubmed_authors>Cohen I</pubmed_authors><pubmed_authors>Shepard D</pubmed_authors><pubmed_authors>Meng H</pubmed_authors><pubmed_authors>Wyllie AL</pubmed_authors></additional><is_claimable>false</is_claimable><name>Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19.</name><description>Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100A&lt;sup>hi&lt;/sup>/HLA-DR&lt;sup>lo&lt;/sup> classical monocytes and activated LAG-3&lt;sup>hi&lt;/sup> T cells are hallmarks of progressive disease and highlights the abnormal MHC-II/LAG-3 interaction on myeloid and T cells, respectively. We also find skewed T cell receptor repertories in expanded effector CD8&lt;sup>+&lt;/sup> clones, unmutated IGHG&lt;sup>+&lt;/sup> B cell clones, and mutated B cell clones with stable somatic hypermutation frequency over time. In conclusion, our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19.</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Jan</publication><modification>2025-04-25T17:13:01.851Z</modification><creation>2025-04-06T04:03:04.574Z</creation></dates><accession>S-EPMC8782894</accession><cross_references><pubmed>35064122</pubmed><doi>10.1038/s41467-021-27716-4</doi></cross_references></HashMap>