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Multiomic Immunophenotyping of COVID-19 Patients Reveals Early Infection Trajectories.

Title: Multiomic Immunophenotyping of COVID-19 Patients Reveals Early Infection Trajectories.
Authors: Su Y; Chen D; Lausted C; Yuan D; Choi J; Dai C; Voillet V; Scherler K; Troisch P; Duvvuri VR; Baloni P; Qin G; Smith B; Kornilov S; Rostomily C; Xu A; Li J; Dong S; Rothchild A; Zhou J; Murray K; Edmark R; Hong S; Jones L; Zhou Y; Roper R; Mackay S; O'Mahony DS; Dale CR; Wallick JA; Algren HA; Michael ZA; Magis A; Wei W; Price ND; Huang S; Subramanian N; Wang K; Hadlock J; Hood L; Aderem A; Bluestone JA; Lanier LL; Greenberg P; Gottardo R; Davis MM; Goldman JD; Heath JR
Source: BioRxiv : the preprint server for biology [bioRxiv] 2020 Jul 31. Date of Electronic Publication: 2020 Jul 31.
Publication Type: Preprint; Journal Article
Language: English
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Abstract: Host immune responses play central roles in controlling SARS-CoV2 infection, yet remain incompletely characterized and understood. Here, we present a comprehensive immune response map spanning 454 proteins and 847 metabolites in plasma integrated with single-cell multi-omic assays of PBMCs in which whole transcriptome, 192 surface proteins, and T and B cell receptor sequence were co-analyzed within the context of clinical measures from 50 COVID19 patient samples. Our study reveals novel cellular subpopulations, such as proliferative exhausted CD8 + and CD4 + T cells, and cytotoxic CD4 + T cells, that may be features of severe COVID-19 infection. We condensed over 1 million immune features into a single immune response axis that independently aligns with many clinical features and is also strongly associated with disease severity. Our study represents an important resource towards understanding the heterogeneous immune responses of COVID-19 patients and may provide key information for informing therapeutic development.
Grant Information: R01 AI032972 United States AI NIAID NIH HHS; U19 AI100627 United States AI NIAID NIH HHS
Entry Date(s): Date Created: 20200809 Latest Revision: 20201124
Update Code: 20260130
PubMed Central ID: PMC7402042
DOI: 10.1101/2020.07.27.224063
PMID: 32766585
Database: MEDLINE

Preprint; Journal Article