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Distinguishing features of long COVID identified through immune profiling

Author

Listed:
  • Jon Klein

    (Yale School of Medicine)

  • Jamie Wood

    (Icahn School of Medicine at Mount Sinai)

  • Jillian R. Jaycox

    (Yale School of Medicine)

  • Rahul M. Dhodapkar

    (Yale School of Medicine
    USC Keck School of Medicine)

  • Peiwen Lu

    (Yale School of Medicine)

  • Jeff R. Gehlhausen

    (Yale School of Medicine
    Yale School of Medicine)

  • Alexandra Tabachnikova

    (Yale School of Medicine)

  • Kerrie Greene

    (Yale School of Medicine)

  • Laura Tabacof

    (Icahn School of Medicine at Mount Sinai)

  • Amyn A. Malik

    (Yale School of Public Health)

  • Valter Silva Monteiro

    (Yale School of Medicine)

  • Julio Silva

    (Yale School of Medicine)

  • Kathy Kamath

    (SerImmune)

  • Minlu Zhang

    (SerImmune)

  • Abhilash Dhal

    (SerImmune)

  • Isabel M. Ott

    (Yale School of Medicine)

  • Gabrielee Valle

    (Yale School of Medicine)

  • Mario Peña-Hernández

    (Yale School of Medicine
    Yale School of Medicine)

  • Tianyang Mao

    (Yale School of Medicine)

  • Bornali Bhattacharjee

    (Yale School of Medicine)

  • Takehiro Takahashi

    (Yale School of Medicine)

  • Carolina Lucas

    (Yale School of Medicine
    Yale School of Medicine)

  • Eric Song

    (Yale School of Medicine)

  • Dayna McCarthy

    (Icahn School of Medicine at Mount Sinai)

  • Erica Breyman

    (Icahn School of Medicine at Mount Sinai)

  • Jenna Tosto-Mancuso

    (Icahn School of Medicine at Mount Sinai)

  • Yile Dai

    (Yale School of Medicine)

  • Emily Perotti

    (Yale School of Medicine)

  • Koray Akduman

    (Yale School of Medicine)

  • Tiffany J. Tzeng

    (Yale School of Medicine)

  • Lan Xu

    (Yale School of Medicine)

  • Anna C. Geraghty

    (Stanford University)

  • Michelle Monje

    (Stanford University
    Howard Hughes Medical Institute)

  • Inci Yildirim

    (Yale School of Public Health
    Yale School of Medicine
    Yale New Haven Hospital
    Yale School of Public Health)

  • John Shon

    (SerImmune)

  • Ruslan Medzhitov

    (Yale School of Medicine
    Yale School of Medicine
    Howard Hughes Medical Institute)

  • Denyse Lutchmansingh

    (Yale School of Medicine)

  • Jennifer D. Possick

    (Yale School of Medicine)

  • Naftali Kaminski

    (Yale School of Medicine)

  • Saad B. Omer

    (Yale School of Public Health
    Yale School of Medicine
    Yale School of Public Health
    Yale School of Medicine)

  • Harlan M. Krumholz

    (Yale School of Medicine
    Yale New Haven Hospital
    Yale School of Medicine
    Yale School of Public Health)

  • Leying Guan

    (Yale School of Medicine
    Yale School of Public Health)

  • Charles S. Cruz

    (Yale School of Medicine
    Yale School of Medicine)

  • David Dijk

    (Yale School of Medicine
    Yale University
    Yale School of Medicine)

  • Aaron M. Ring

    (Yale School of Medicine
    Yale School of Medicine)

  • David Putrino

    (Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai)

  • Akiko Iwasaki

    (Yale School of Medicine
    Yale School of Medicine
    Howard Hughes Medical Institute)

Abstract

Post-acute infection syndromes may develop after acute viral disease1. Infection with SARS-CoV-2 can result in the development of a post-acute infection syndrome known as long COVID. Individuals with long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions2–4. However, the biological processes that are associated with the development and persistence of these symptoms are unclear. Here 275 individuals with or without long COVID were enrolled in a cross-sectional study that included multidimensional immune phenotyping and unbiased machine learning methods to identify biological features associated with long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to the matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with long COVID. Furthermore, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with long COVID, particularly Epstein–Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with long COVID. Integration of immune phenotyping data into unbiased machine learning models identified the key features that are most strongly associated with long COVID status. Collectively, these findings may help to guide future studies into the pathobiology of long COVID and help with developing relevant biomarkers.

Suggested Citation

  • Jon Klein & Jamie Wood & Jillian R. Jaycox & Rahul M. Dhodapkar & Peiwen Lu & Jeff R. Gehlhausen & Alexandra Tabachnikova & Kerrie Greene & Laura Tabacof & Amyn A. Malik & Valter Silva Monteiro & Juli, 2023. "Distinguishing features of long COVID identified through immune profiling," Nature, Nature, vol. 623(7985), pages 139-148, November.
  • Handle: RePEc:nat:nature:v:623:y:2023:i:7985:d:10.1038_s41586-023-06651-y
    DOI: 10.1038/s41586-023-06651-y
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