Early and Rapid Identification of COVID-19 Patients with Neutralizing Type I Interferon Auto-antibodies

Since its first detection in Wuhan, China, in 2019, severe-acute-respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed an unprecedented burden on health care systems worldwide. The clinical spectrum of the associated disease, COVID-19, ranges from asymptomatic infection to severe disease with hypoxemia, acute respiratory distress syndrome (ARDS), multiorgan failure, and death [1]. Approximately 35% of patients remain asymptomatic, 55% develop upper respiratory tract infections, whereas 15% develop severe pneumonia (defined as SpO2 < 90% at room air) and 5% critical pneumonia (defined as acute respiratory distress syndrome (ARDS), requiring mechanical ventilation or extra-corporeal membrane oxygenation (ECMO) [2].

Scores containing clinical and laboratory parameters support risk stratification and resource allocation in clinical practice worldwide [3]. Demographic and clinical risk factors for a severe disease course include advanced age, male sex, and pre-existing comorbidities [4]. Moreover, genetic polymorphisms are associated with progression to severe disease [5]. Cell-intrinsic innate viral sensors and antiviral cytokines, including type I and type III interferons (IFNs), orchestrate the control of SARS-CoV-2 infection [6]. Inherited mutations of genes involved in IFN induction and signaling and circulating auto-antibodies (AABs) that neutralize type I IFNs have been found to predispose infected individuals to severe COVID-19 [7, 8], presumably by contributing to an ineffective immune response with delayed or abolished type I IFN signaling. Neutralizing type I IFN-AABs are present in 6–17% of hospitalized COVID-19 patients with severe pneumonia [7, 9, 10] and 11–19% in critically ill COVID-19 patients [7, 11, 12], greatly exceeding estimated prevalences of around 0.33% [7] in uninfected individuals. Intriguingly, while neutralizing IFN-AABs in patients with autoimmune polyendocrine syndrome type 1 (APS-1) can associate with a severe course of SARS-CoV-2 infection [13‐17], their mere presence does not inevitably lead to severe disease [18]. A recent global multi-cohort study reports prevalence of neutralizing IFN-AABs in 4% of uninfected individuals over 70 years of age, suggesting that IFN-AABs may pre-exist in some individuals that develop a critical course of COVID-19 [19]. Thus, we reasoned that IFN-AABs may serve as biomarkers that could, in conjunction with other clinical parameters, help to predict risk for developing severe COVID-19 and to stratify patients for specific therapies.

Specific therapies may comprise the administration of recombinant IFN-β or therapeutic plasma exchange (TPE). However, the clinical benefit of TPE and other approaches remains to be defined and requires studies involving large numbers of patients. With IFN-AABs present in up to 18% of deceased COVID-19 patients [19] and given the limited therapeutic options for severely affected COVID-19 patients, testing specific therapeutic approaches is of high urgency, yet clinically implementable strategies for rapid and early identification of IFN-AAB-positive patients upfront are missing.

We analyzed 430 serum samples collected within four independent observational clinical studies on COVID-19 for IFN-AAB positivity (Table 1), comprising 237 patients with critical COVID-19 (max. WHO score 6–8). Median age of patients in the CSC (cohorts A–C, 403 patients) was 61 years (IQR 52–71) and 72.2% (291/403) were male. Median Charlson Comorbidity Index (CCI) was 3 (IQR 1–4). Twenty-seven patients with critical disease course (median max. WHO score 7 (IQR 7–8)) who underwent TPE as compassionate use were selected retrospectively from center D (TPEC). Median age of patients in the TPEC was 65 years (IQR 56–72), 74.1% (20/27) were male, and median CCI was 4 (IQR 3–5). All patients from the TPEC required invasive mechanical ventilation (IMV), 77.8% (21/27) renal replacement therapy, one patient was treated with ECMO, and 13 out of 27 (48.2%) patients died despite maximum care. Six hundred sixty-seven serum samples from a healthy cohort (HC) consisting of health-care workers (Table S1) were screened for the presence of neutralizing IFN-AABs to set the cut-off for IFN-AAB positivity.

IFN-AABs strongly associate with adverse clinical outcome of SARS-CoV-2 infection [7, 9‐11, 13, 17, 23].

In several studies, detection and quantification of IFN-AABs in sera from COVID-19 patients relies on ELISA and multiplex particle-based assay. While these assays are amenable to high-throughput and are highly sensitive, they result in a small proportion of false-positive results [22, 24], highlighting the ongoing need to reanalyze positive-tested patient material in functional assays demonstrating the neutralization activity. However, such assays are sophisticated and time-consuming. They include luciferase-based interferon-stimulated response element (ISRE) promoter reporter assays [10, 11], flow cytometry-based analyses of STAT phosphorylation [7, 11, 18], and virus infection-based assays [18, 23]. The latter allows probing the activity of the IFN-AABs in the context of infection-inhibitory concentrations of IFN-α and IFN-ω. Here, we applied and cross-validated previously established assays comprising an ELISA for sensitive identification, a specificity-validating competition assay, and a functional neutralization assay [18] using a large collection of serum samples obtained from three cross-sectional cohorts.

Surprisingly, sera from two patients were found to neutralize exogenous IFN-ω despite negative ELISA results. Presence of neutralization activity in the absence of detectable IFN-AABs has been reported [19]. Explanations for this phenomenon could include technical aspects of the detection method, including the possibility that IFN-AABs may be concealed by the binding of the cytokine to the plate or biotinylation of the cytokine [25].

Here, we calibrated our ELISA cut-off based on the 97.5th percentile in a cohort of uninfected individuals. Although this strategy may be inexact, the absence of prevalence IFN-AABs in a cohort of younger and predominantly female healthcare workers supports an age-dependent increase of IFN-AAB prevalence in uninfected individuals [19]. Furthermore, the prevalence of 3.2% (13/403) of patients with neutralizing AABs against IFN-α and/or IFN-ω in our cross-sectional patient cohort (median max. WHO score 6) and 18.5% (5/27) in critically affected patients (median max. WHO-Score 7) is in line with reported prevalences of 6–17% in severely [7, 9, 10, 12, 19] and 11–19% in critically ill [7, 11, 12, 19] individuals with COVID-19. Moreover, IFN-AAB positivity is associated with a worse clinical outcome and a decreased survival probability of hospitalized patients in our cohorts, confirming previous reports [7, 9‐11, 13, 17, 19, 23]. Interestingly, a single study to date [26] suggested that survival was not adversely affected by the presence of type I IFN-AABs, while confirming the widely accepted association with an increased risk of admission to the intensive care unit.

We failed to identify a clear association of IFN-AABs with previously described demographic parameters in our cross-sectional cohort, including male sex or advanced age [7, 13], probably due to the relatively limited sample size of our cohorts. However, the presence of neutralizing IFN-AABs was associated with fever and need for supplementary oxygen within 72 h post hospital admission, as well as with elevated soluble and cellular markers of acute-phase reaction including elevated levels of CRP, procalcitonin, LDH and ferritin, and elevated total neutrophil and leukocyte counts within the first 3 days of admission in our CSC. Higher CRP values constitute a biomarker for a severe disease course, are included in a widely-used clinical risk score for mortality of COVID-19 [3], and associate with neutralizing IFN-AABs along with lower lymphocyte counts in severely affected patients [10]. As hospital admission and thus clinical deterioration occurred at a median of 5 days post-symptom onset in the CSC, fever and need for supplemental oxygen therapy up to 72 h post hospital admission may serve as suitable and simple clinical criteria to identify patients at risk for a severe disease course.

Our ability to detect IFN-AABs as early as 4 days post-symptom onset in sera from most patients that present with IFN-AABs at the peak of their disease suggest that they were present prior to the infection, or alternatively, but less likely, were induced very early post infection. Our data are in agreement with recently demonstrated presence of IFN-AABs at the day of hospital admission [23] and in 4% of uninfected individuals > 70 years old [19], underlining the idea that they can serve as biomarkers for predisposition for a severe course of SARS-CoV-2 infection. Future studies are required to elucidate the biological mechanisms that lead to elicitation of IFN-AABs in an age-dependent manner.

Given that IFN-AABs are risk factors for a worse clinical outcome in hospitalized patients with COVID-19, future rapid identification of IFN-AAB-positive patients after hospital admission seems key for the potential implementation and success of specific interventions such as antivirals and/or monoclonal antibodies and/or TPE. Mass screening of all hospitalized COVID-19 patients may be the ideal goal. However, in the context of limited resources, combination of clinical parameters and targeted diagnostic testing may serve to facilitate early, sensitive, and specific identification of IFN-AAB-positive patients. In the CSC cohort, the patient number needed to screen (NNS) without preselection in order to identify one patient with neutralizing IFN-AAB was 31.0 (403/13). We hypothesized that applying clinical pre-selection criteria which co-present with the neutralizing IFN-AAB positivity diminishes the NNS. Due to the limited number of IFN-AAB-positive patients (13), multiple testing correction was not feasible. Using univariate analyses, we established that temperature (> 38.5 °C or self-reported fever) before or upon hospital admission and the need for supplemental oxygen within the first 72 h after admission correlated best with presence of IFN-AAB positivity in the screening assay in all hospitalized COVID-19 patients (fever: p = 0.0079; supplemental oxygen p = 0.0528). In order to prevent early exclusion of IFN-AAB-positive patients by mere pre-selection on statistically significant parameters, we included fever and the need for supplemental oxygen which nominally associated with IFN-AAB positivity. Importantly for clinical implementation, both parameters are easily measurable and clinically reasonable and reduce the NNS to 15.6 (172/11). Selection of patients exceeding the cut-off for ELISA positivity (in our cohort 97.5th percentile of the HC) for further testing by competition assay would adjust the NNS in the competition assay to 1.4 (15/11). Therefore, in order to increase sensitivity, we propose to consider the need for supplemental oxygen within 72 h after admission and fever as pre-selection criteria for patients that undergo ELISA screening (Fig. 7).

Sera from all patients exceeding the LSC value of 35,639 (13/13) in the screening ELISA assay demonstrated neutralizing activity against IFN-α (Fig. 2c). We therefore propose to conduct the IFN neutralization assay only in case of an LSC value lower than 35,639, whereas patients with sera exceeding this value can be considered positive for neutralizing IFN-AABs without further testing (Fig. 7). Taken together, we identified clinical parameters that co-present with IFN-AAB positivity at hospital admission, which may serve as preselection in a yet-to-be-verified diagnostic algorithm. Due to the low number of IFN-AAB-positive patients in our study, the usefulness of these parameters and their statistical robustness require assessment and verification in prospective clinical studies.

Treatment with antiviral compounds and monoclonal antibodies is recommended in the early phase of SARS-CoV-2 infection for patients at high risk for progression to severe disease and may therefore also serve as therapeutic options for IFN-AAB-positive COVID-19 patients in addition to removal of autoantibodies by TPE and substitution of type I IFN by IFN-β administration. TPE in the context of COVID-19 has been analyzed in individual case reports and case–control studies, including IFN-AAB-positive and negative patients [17, 21, 23, 27] and might efficiently remove soluble circulating FcγReceptor-activating immune complexes [28]. TPE effectively decreased circulating IFN-AAB, but not SARS-CoV-2 antibody concentrations in four IFN-AAB-positive, severely ill patients [23] and in a child with APS-1 suffering from severe COVID-19 [17]. In our study, TPE was offered to patients in one center. Here, it reduced circulating IFN-AABs with patient-specific efficiency and appeared to increase the chances of in-hospital survival. Although clinical characteristics in both groups were similar, we cannot rule out confounding factors due to different clinical settings between centers contributing to different survival rates, such as the differences regarding administration of remdesivir described above. However, our data underline the rationale to initiate large-scale, adequately powered clinical trials in order to corroborate the potential benefit of TPE in a general cohort of adult, critically ill COVID-19 patients. Interestingly, SARS-CoV-2-IgG and IgA quantities were less affected by TPE for unknown reasons, which may include their rapid replenishment by highly abundant plasmablasts or an extravascular-to-intravascular rebound since immunoglobulins have a substantial extravascular distribution.

Given the low prevalence of detectable IFN-β-AABs (up to 1.3% in patients with critical COVID-19 [19]), IFN-β administration may substitute for neutralized IFN-α and -ω. While IFN-β therapy failed to result in a detectable clinical benefit in the SOLIDARITY trial [29], specifically IFN-AAB-positive patients may benefit from IFN-β therapy, a patient group that might have been under-represented in this study. Furthermore, the benefit of IFN-β administered by different routes should be systematically explored in this patient group.

Rapid and early identification of COVID-19 patients with circulating IFN-AABs at hospital admission is key to provide them with yet-to-be-established specific therapies before they clinically deteriorate. A high-throughput-amenable assay pipeline, composed of an ELISA-based assay for IFN-AABs in serum and a consecutive ELISA-based validation assay, can substitute methodologically complex gold-standard assays that quantify functional neutralization of IFNs. Future, large-scale prospective observational studies are required to verify if this pipeline may be stratified to a preselected group of patients based on clinical parameters that appeared to associate with IFN-AAB positivity, including presentation with fever and need for supplemental oxygen therapy within 72 h after admission. Identification of at-risk patients will enable clinicians to directly allocate them to larger clinical trials which are urgently required to determine clinical effectiveness of targeted therapies in this particularly vulnerable patient group.

Set up study platform: Stefan Hippenstiel⁴, Martin Witzenrath⁴, Elisa T. Helbig⁴, Lena J. Lippert⁴, Pinkus Tober-Lau⁴, David Hillus⁴, Sarah Steinbrecher⁴, Sascha S. Haenel⁴, Alexandra Horn⁴, Willi M⁴. Koch, Nadine Olk⁴, Rosa C. Schuhmacher⁴, Katrin K. Stoyanova⁴, Lisa Ruby⁴, Claudia Zensen⁴, Mirja Mittermaier⁴, Fridolin Steinbeis⁴, Tilman Lingscheid⁴, Bettina Temmesfeld-Wollbrück⁴, Thomas Zoller⁴, Holger Müller-Redetzky⁴, Alexander Uhrig⁴, Daniel Grund⁴, Christoph Ruwwe-Glösenkamp⁴, Miriam S. Stegemann⁴, Katrin M. Heim⁴, Bastian Opitz⁴, Kai-Uwe Eckardt²⁶, Martin Möckel²⁷, Felix Balzer²⁸, Claudia Spies²⁸, Steffen Weber-Carstens²⁸, Frank Tacke²⁹, Chantip Dang-Heine², Michael Hummel³⁰, Georg Schwanitz³¹, Uwe D. Behrens³¹, Maria Rönnefarth², Sein Schmidt², Alexander Krannich², Saskia Zvorc², Jenny Kollek² and Christof von Kalle².

Inclusion of patients and clinical data curation: Linda Jürgens⁴, Malte Kleinschmidt⁴, Sophy Denker³², Moritz Pfeiffer⁴, Belén Millet Pascual-Leone⁴, Luisa Mrziglod⁴, Felix Machleidt⁴, Sebastian Albus⁴, Felix Bremer⁴, Tim Andermann⁴, Carmen Garcia⁴, Philipp Knape⁴, Philipp M. Krause⁴, Liron Lechtenberg⁴, Yaosi Li⁴, Panagiotis Pergantis⁴, Till Jacobi⁴, Teresa Ritter²⁶, Berna Yedikat⁴, Lennart Pfannkuch⁴, Ute Kellermann⁴, Susanne Fieberg⁴, Laure Bosquillon de Jarcy¹, Anne Wetzel⁴, Markus C. Brack⁴, Moritz Müller-Plathe⁴, Jan M. Kruse²⁶, Daniel Zickler²⁶, Andreas Edel²⁸, Britta Stier²⁶, Roland Körner²⁶, Nils B. Müller²⁶, Philipp Enghard²⁶, Lucie Kretzler², Lil A. Meyer-Arndt³³, Linna Li², and Isabelle Wirsching².

Biobanking and -sampling: Denise Treue³⁰, Dana Briesemeister³⁰, Jenny Schlesinger³⁰, Birgit Sawitzki²⁵, Lara Bardtke⁴, Kai Pohl⁴, Philipp Georg⁴, Daniel Wendisch⁴, Anna L. Hiller⁴, Sophie Brumhard⁴, Marie Luisa Schmidt¹, Leonie Meiners¹, and Patricia Tscheak¹.

²⁶Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Nephrology and Internal Intensive Care Medicine, Berlin, Germany.

²⁷Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Division of Emergency Medicine and Department of Cardiology, Berlin, Germany.

²⁸Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Anesthesiology and Intensive Care Medicine, Berlin, Germany.

²⁹Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Hepatology and Gastroenterology, Berlin, Germany.

³⁰Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Central Biobank Charité (ZeBanC), Institute of Pathology, Berlin, Germany.

³¹Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Clinical Study Center, Berlin, Germany.

³²Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Hematology, Oncology and Tumor Immunology, Berlin, Germany.

³³Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Berlin, Germany.