Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID

Abstract

While immunologic correlates of COVID-19 have been widely reported, their associations with post-acute sequelae of COVID-19 (PASC) remain less clear. Due to the wide array of PASC presentations, understanding if specific disease features associate with discrete immune processes and therapeutic opportunities is important. Here we profile patients in the recovery phase of COVID-19 via proteomics screening and machine learning to find signatures of ongoing antiviral B cell development, immune-mediated fibrosis, and markers of cell death in PASC patients but not in controls with uncomplicated recovery. Plasma and immune cell profiling further allow the stratification of PASC into inflammatory and non-inflammatory types. Inflammatory PASC, identifiable through a refined set of 12 blood markers, displays evidence of ongoing neutrophil activity, B cell memory alterations, and building autoreactivity more than a year post COVID-19. Our work thus helps refine PASC categorization to aid in both therapeutic targeting and epidemiological investigation of PASC.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 14, 2023
Source ID
10.1038/s41467-023-40012-7

Entities

People

  • Adviteeya N. Dixit
  • Alexander D. Truong
  • Arezou Khosroshahi
  • Candice Y. Kaminski
  • Caterina E. Faliti
  • Fabliha A Anam
  • Frances Lee
  • IƱaki Sanz
  • Jason S. Knight
  • Jenny E Han
  • Kelly Rose Cooper
  • Kevin S. Bonham
  • Mark E. Rudolph
  • Martin C. Ruunstrom
  • Matthew C Woodruff
  • Natalie S Haddad
  • Richard P Ramonell
  • Scott A. Jenks
  • Sherwin Navaz
  • Srilakshmi Yalavarthi
  • Ted Natoli
  • Tiffany Walker
  • Viktoria Betin
  • Yu Zuo
  • Yusho Ishii

Organizations

  • Gates Foundation
  • National Cancer Institute
  • National Institute of Allergy and Infectious Diseases
  • United States Department of Defense
  • United States Department of Health and Human Services

Tags

Fields of Study

  • Biology
  • Medicine

Readers

  • Computer Engineering
  • Immunology and Pathology
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Biotechnology
  • Biotechnology - Cancer Biotech