Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome

Carlo Cervia,Patrick Taeschler,Alain Rudiger,Tala Ballouz,Sara Hasler,Lars C Huber,Milo A Puhan,Miro E Raeber,Melina Stüssi-Helbling,Yves Zurbuchen,Onur Boyman,Esther Bächli,Ulrike Held,Dominik Menges,Jakob Nilsson,Sarah Adamo

doi:10.1038/s41467-021-27797-1

Abstract

Following acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a significant proportion of individuals develop prolonged symptoms, a serious condition termed post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) or long COVID. Predictors of PACS are needed. In a prospective multicentric cohort study of 215 individuals, we study COVID-19 patients during primary infection and up to one year later, compared to healthy subjects. We discover an immunoglobulin (Ig) signature, based on total IgM and IgG3 levels, which – combined with age, history of asthma bronchiale, and five symptoms during primary infection – is able to predict the risk of PACS independently of timepoint of blood sampling. We validate the score in an independent cohort of 395 individuals with COVID-19. Our results highlight the benefit of measuring Igs for the early identification of patients at high risk for PACS, which facilitates the study of targeted treatment and pathomechanisms of PACS.

Highlights

Following acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) a significant proportion of individuals develop prolonged symptoms, a serious condition termed post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) or long COVID
We found distinct patterns of total immunoglobulin (Ig) levels in patients with COVID-19 and integrated these in a clinical prediction score, which allowed early identification of both outpatients and hospitalized individuals with COVID-19 that were at high risk for PACS
Symptoms of PACS were about 2–6.5fold more frequent in severe compared to mild COVID-19 cases overall, with the exception of smell or taste disorders (Table 1)

Summary

Introduction

Following acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) a significant proportion of individuals develop prolonged symptoms, a serious condition termed post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) or long COVID. A rapid systemic immune response is mounted against SARS-CoV-2, characterized by increased serum concentrations of chemokines and proinflammatory cytokines, such as interleukin (IL)-6 and tumor necrosis factor (TNF), and the appearance of activated monocytes, followed by SARS-CoV-2-specific immunoglobulin M (IgM), IgA, and IgG antibodies and interferon-γ-producing T cells[2–7] This concerted action of the immune system controls the replication of SARS-CoV-2, and infectious SARS-CoV-2 cannot be isolated from the respiratory tract after 3 weeks[8]. Self-reported data and telehealth are at risk for bias, and risk factors associated with a severe course of primary SARS-CoV-2 infection complicate the detection of underlying risk factors for PACS independent of disease severity To address these issues, we have characterized a prospective cohort of 215 individuals by clinical visits and laboratory analyses up to one year of follow-up. We found distinct patterns of total immunoglobulin (Ig) levels in patients with COVID-19 and integrated these in a clinical prediction score, which allowed early identification of both outpatients and hospitalized individuals with COVID-19 that were at high risk for PACS

Methods

Results

Conclusion