Defective type I interferon immunity is associated with increasing COVID-19 severity (preprint)

Host immunity to infection with SARS-CoV-2 is highly variable, dictating diverse clinical outcomes ranging from asymptomatic to severe disease and death. We previously reported that reduced blood type I interferon (IFN-I) in severe COVID-19 patients preceded clinical worsening. These results were supported by studies which identified genetic mutations in loci of the TLR3- or TLR7-dependent IFN-I pathways, or autoantibodies neutralizing IFNα or IFNω, as major risk factors for development of severe and critical COVID-19 pneumonia. Here, we analyzed a range of IFN-I associated responses in patient cohorts with different severities of COVID-19, showing that baseline plasma IFNα measures differed significantly according to the immunoassay used, as well as timing of sampling, the IFNα subtype measured, and the presence of autoantibodies. We then compared immune responses induced by ex vivo stimulation between non-hospitalized moderate cases (n=27) and hospitalized (n=17) adult patients that required oxygen supplementation. This showed a consistently reduced induction of IFN-I proteins in hospitalized COVID-19 patients upon stimulation, that was not associated with detectable neutralizing autoantibodies against IFNα or IFNω. We confirmed the poor induction of IFN-I in an independent patient cohort (n=33), and showed it was more pronounced with severe disease. Intracellular proteomic analysis showed that while monocyte numbers were increased in hospitalized COVID-19 patients, they did not secrete IFN-I in response to stimulation. This was further confirmed by ex vivo whole blood stimulation with IFN-I which induced a transcriptomic response associated with inflammation in hospitalized COVID-19 patients, that was not seen in controls or non-hospitalized moderate cases. These results may explain the dichotomy of the poor clinical response to IFN-I based treatments in late stage COVID-19, despite the critical importance of IFN-I in early acute infection. An improved understanding of such variable responses to treatment may help to identify potential alternative therapeutic strategies.

Severe COVID-19 is characterised by inflammation and immature myeloid cells early in disease progression (preprint)

SARS-CoV-2 infection causes a wide spectrum of disease severity. Immune changes associated with severe disease include pro-inflammatory cytokine production and expansion of immature myeloid populations. The relative importance of the immunological changes in driving progression to severe disease remain poorly understood. We aimed to identify and rank clinical and immunological features associated with progression to severe COVID-19. We sought to use tests available in an on-site diagnostic hospital laboratory to identify an immunological signature for severe disease development which could be detected prior to peak severity thereby allowing initiation of therapeutic interventions. We used univariate and multivariate analysis, including unbiased machine learning, to investigate the relationships between clinical and demographic characteristics, inflammatory markers, and leukocyte immunophenotypes with progression to severe disease in 108 patients and to rank these in importance. A combination of four features (elevated levels of interleukin-6 and C-reactive protein, coupled with reduced monocyte HLA-DR expression and reduced neutrophil CD10 expression), were strongly predictive of severe disease with an average prediction score of 0.925. HighlightsO_LISevere COVID-19 can be predicted by a combination of emergency myelopoiesis (CD10-neutrophils and HLA DR-monocytes) and inflammation (raised IL-6 and CRP) C_LIO_LIThese changes can be identified from tests carried out prior to peak illness severity in a diagnostic laboratory C_LIO_LIThis predictive model was derived from a cohort of patients with a wide range of ages, frailty and COVID-19 severity C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=191 HEIGHT=200 SRC="FIGDIR/small/21262953v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@16c6947org.highwire.dtl.DTLVardef@73ba2corg.highwire.dtl.DTLVardef@1c3dd82org.highwire.dtl.DTLVardef@3a48f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Serological reconstruction of COVID-19 epidemics through analysis of antibody kinetics to SARS-CoV-2 proteins (preprint)

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a complex antibody response that varies by orders of magnitude between individuals and over time. Waning antibody levels lead to reduced sensitivity of serological diagnostic tests over time. This undermines the utility of serological surveillance as the SARS-CoV-2 pandemic progresses into its second year. Here we develop a multiplex serological test for measuring antibodies of three isotypes (IgG, IgM, IgA) to five SARS-CoV-2 antigens (Spike (S), receptor binding domain (RBD), Nucleocapsid (N), Spike subunit 2, Membrane-Envelope fusion) and the Spike proteins of four seasonal coronaviruses. We measure antibody responses in several cohorts of French and Irish hospitalized patients and healthcare workers followed for up to eleven months after symptom onset. The data are analysed with a mathematical model of antibody kinetics to quantify the duration of antibody responses accounting for inter-individual variation. One year after symptoms, we estimate that 36% (95% range: 11%, 94%) of anti-S IgG remains, 31% (9%, 89%) anti-RBD IgG remains, and 7% (1%, 31%) anti-N IgG remains. Antibodies of the IgM isotype waned more rapidly, with 9% (2%, 32%) anti-RBD IgM remaining after one year. Antibodies of the IgA isotype also waned rapidly, with 10% (3%, 38%) anti-RBD IgA remaining after one year. Quantitative measurements of antibody responses were used to train machine learning algorithms for classification of previous infection and estimation of time since infection. The resulting diagnostic test classified previous infections with 99% specificity and 98% (95% confidence interval: 94%, 99%) sensitivity, with no evidence for declining sensitivity over the time scale considered. The diagnostic test also provided accurate classification of time since infection into intervals of 0 - 3 months, 3 - 6 months, and 6 - 12 months. Finally, we present a computational method for serological reconstruction of past SARS-CoV-2 transmission using the data from this test when applied to samples from a single cross-sectional sero-prevalence survey.

Longitudinal analysis of COVID-19 patients shows age-associated T cell changes independent of ongoing ill-health (preprint)

The trajectory of immunological and inflammatory changes following acute COVID-19 infection are unclear. We investigate immunological changes in convalescent COVID-19 and interrogate their potential relationships with persistent symptoms, termed long COVID . We performed paired immunophenotyping at initial SARS-CoV-2 infection and convalescence (n=40, median 68 days) and validated findings in 71 further patients at median 101 days convalescence. Results were compared to 40 pre-pandemic controls. Fatigue and exercise tolerance were assessed and investigated their relationship with convalescent results. We demonstrate persistent expansion of intermediate monocytes, effector CD8+, activated CD4+ and CD8+ T cells, and reduced naïve CD4+ and CD8+ T cells at 68 days, with activated CD8+ T cells remaining increased at 101 days. Patients >60 years also demonstrate reduced naïve CD4+ and CD8+ T cells and expanded activated CD4+ T cells at 101 days. Ill-health, fatigue, and reduced exercise tolerance were common but were not associated with immunological changes. Graphical Abstract

Persistent fatigue following SARS-CoV-2 infection is common and independent of severity of initial infection (preprint)

Fatigue is a common symptom in those presenting with symptomatic COVID-19 infection. However, it is unknown if COVID-19 results in persistent fatigue in those recovered from acute infection. We examined the prevalence of fatigue in individuals recovered from the acute phase of COVID-19 illness using the Chalder Fatigue Score (CFQ-11). We further examined potential predictors of fatigue following COVID-19 infection, evaluating indicators of COVID-19 severity, markers of peripheral immune activation and circulating pro-inflammatory cytokines. Of 128 participants (49.5 {+/-} 15 years; 54% female), more than half reported persistent fatigue (52.3%; 45/128) at 10 weeks (median) after initial COVID-19 symptoms. There was no association between COVID-19 severity (need for inpatient admission, supplemental oxygen or critical care) and fatigue following COVID-19. Additionally, there was no association between routine laboratory markers of inflammation and cell turnover (leukocyte, neutrophil or lymphocyte counts, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, C-reactive protein) or pro-inflammatory molecules (IL-6 or sCD25) and fatigue post COVID-19. Female gender and those with a pre-existing diagnosis of depression/anxiety were over-represented in those with fatigue. Our findings demonstrate a significant burden of post-viral fatigue in individuals with previous SARS-CoV-2 infection after the acute phase of COVID-19 illness. This study highlights the importance of assessing those recovering from COVID-19 for symptoms of severe fatigue, irrespective of severity of initial illness, and may identify a group worthy of further study and early intervention.