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Infection by SARS-CoV-2 leads to diverse symptoms, which can persist for months. While antiviral antibodies are protective, those targeting interferons and other immune factors are associated with adverse COVID-19 outcomes. Instead, we discovered that antibodies against specific chemokines are omnipresent after COVID-19, associated with favorable disease, and predictive of lack of long COVID symptoms at one year post infection. Anti-chemokine antibodies are present also in HIV-1 infection and autoimmune disorders, but they target different chemokines than those in COVID-19. Monoclonal antibodies derived from COVID- 19 convalescents that bind to the chemokine N-loop impair cell migration. Given the role of chemokines in orchestrating immune cell trafficking, naturally arising anti-chemokine antibodies associated with favorable COVID-19 may be beneficial by modulating the inflammatory response and thus bear therapeutic potential. One-Sentence SummaryNaturally arising anti-chemokine antibodies associate with favorable COVID-19 and predict lack of long COVID.
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BackgroundQuantitative CT (QCT) analysis is an invaluable diagnostic tool to assess lung injury and predict prognosis of patients affected by COVID-19 pneumonia. PTX3 was recently described as one of the most reliable serological predictors of clinical deterioration and short-term mortality. The present study was designed to evaluate a correlation between serological biomarkers of inflammation and lung injury measured by QCT. MethodsThis retrospective monocentric study analysed a cohort of patients diagnosed with COVID-19 and admitted because of respiratory failure, or significant radiological involvement on chest CT scan. All patients, males and non-pregnant females older than 18 years, underwent chest CT scan and laboratory testing at admission. Exclusion criteria were defined by concurrent acute pathological processes and ongoing specific treatments which could interfere with immune activity. The cohort was stratified based on severity in mild and severe forms. Compromised lung at QCT was then correlated to serological biomarkers representative of SARS-CoV-2. We further developed a multivariable logistic model to predict CT data and clinical deterioration based on a specific molecular signature. Internal cross-validation led to evaluate discrimination, calibration, and clinical utility of the tool that was provided by a score to simplify its application. Findings592 patients were recruited between March 19th and December 1st, 2020. Applying exclusion criteria which consider confounders, the cohort resulted in 366 individuals characterized by 177 mild and 189 severe forms. In our predictive model, blood levels of PTX3, CRP and LDH were found to correlate with QCT values in mild COVID-19 disease. A signature of these three biomarkers had a high predictive accuracy in detecting compromised lungs as assessed by QCT. The score was elaborated and resulted representative of lung CT damage leading to clinical deterioration and oxygen need in mild disease. InterpretationThe LDH, PTX3, CRP blood signature can serve as a strong correlate of compromised lung in COVID-19, possibly integrating cellular damage, systemic inflammation, myeloid and endothelial cell activation. FundingThis work was supported by a philanthropic donation by Dolce & Gabbana fashion house (to A.M., C.G.) and by a grant from Italian Ministry of Health for COVID-19 (to A.M. and C.G.). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSBesides nasopharyngeal swab and serological test, chest CT scan represents one of the most useful tools to confirm COVID-19 diagnosis; moreover, QCT has been demonstrated to foresee oxygen need as well as deterioration of health status. Several clinical and serological parameters have been studied alone or combined in scores to be applied as prognostic tools of SARS-CoV-2 pneumonia; however, no one has yet reached the everyday practice. Recently, our group has investigated the expression and clinical significance of PTX3 in COVID-19 demonstrating the correlation with short-term mortality independently of confounders. The result was confirmed by other studies in different settings increasing evidence of PTX3 as a strong biomarker of severity; noteworthy, a recent report analysed proteomic data with a machine learning approach identifying age with PTX3 or SARS-CoV-2 RNAemia as the best binary signatures associated to 28-days mortality. Added value of this studyThe present study was designed to investigate associations between markers of damage and the CT extension of SARS-CoV-2 pneumonia in order to provide a biological footprint of radiological results in paucisymptomatic patients. QCT data were considered in a binary form identifying a threshold relevant for clinical deterioration, as already proved by literature. Our findings demonstrate a significant correlation with three peripheral blood proteins (PTX3, LDH and CRP) which result representative of COVID-19 severity. The study presents a predictive model of radiological lung involvement which performs with a high level of accuracy (cvAUC of 0{middle dot}794{+/-}0{middle dot}107; CI 95%: 0{middle dot}74-0{middle dot}87) and a simple score was provided to simplify the interpretation of the three biomarkers. Besides additional finding on PTX3 role in SARS-CoV2 pathology, its prognostic value was confirmed by data on clinical deterioration; indeed, paucisymptomatic subjects showed a 11{middle dot}9% deaths. The model offers the possibility to quickly assess patients resulted positive for SARS-CoV-2 and estimate people at risk of deterioration despite normal clinical and blood gases analysis, with potential to identify those who need better clinical monitoring and interventions. Implications of all the available evidencePredicting the extension, severity, and clinical deterioration in COVID-19 patients its pivotal to allocate enough resources in emergency and to avoid health system burden. Despite the urgent clinical need of biomarkers, SARS-CoV-2 pneumonia still lacks something able to provide an easy measure of its severity. Some multiparametric scores have been proposed for severe COVID-19 and rely on deep assessment of patients status (clinical, serological, and radiological data). Our model represents an unprecedented effort to provide a tool which could predict CT pneumonia extension, oxygen requirement and clinical deterioration in mild COVID-19. Based on the measurement of three proteins on peripheral blood, this score could improve early assessment of asymptomatic patients tested positive by SARS-CoV2 specifically in first level hospitals as well in developing countries.
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The humoral arm of innate immunity includes diverse molecules with antibody-like functions, some of which serve as disease severity biomarkers in COVID-19. The present study was designed to conduct a systematic investigation of the interaction of humoral fluid phase pattern recognition molecules (PRM) with SARS-CoV-2. Out of 10 PRM tested, the long pentraxin PTX3 and Mannose Binding Lectin (MBL) bound the viral Nucleoprotein and Spike, respectively. MBL bound trimeric Spike, including that of variants of concern, in a glycan- dependent way and inhibited SARS-CoV-2 in three in vitro models. Moreover, upon binding to Spike, MBL activated the lectin pathway of complement activation. Genetic polymorphisms at the MBL locus were associated with disease severity. These results suggest that selected humoral fluid phase PRM can play an important role in resistance to, and pathogenesis of, COVID-19, a finding with translational implications.
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PTX3 is an essential component of humoral innate immunity, involved in resistance to selected pathogens and in the regulation of inflammation. PTX3 plasma levels are associated with poor outcome in systemic inflammatory conditions and vascular pathology. The present study was designed to assess expression and significance of PTX3 in COVID-19. By bioinformatics analysis of public databases PTX3 expression was detected in lung respiratory cell lines exposed to SARS-CoV-2. By analysis at single cell level of COVID-19 circulating mononuclear cells, we found that PTX3 was selectively expressed by monocytes among circulating leukocytes. Moreover, in lung bronchoalveolar lavage fluid, single cell analysis revealed selective expression of PTX3 in neutrophils and macrophages, which play a major role in the pathogenesis of the disease. By immunohistochemistry, PTX3 was expressed by lung myelomocytic cells, type 2 pneumocytes and vascular endothelial cells. PTX3 plasma levels were determined by ELISA in 96 consecutive patients with a laboratory-confirmed diagnosis of COVID-19. Higher PTX3 plasma levels were observed in 52 (54.2%) patients admitted in ICU (median 21.0ng/mL, IQT 15.5-46.3 vs 12.4ng/mL IQT 6.1-20.2 in ward patients; p=0.0017) and in 22 (23%) patients died by 28 days (39.8ng/mL, IQT 20.2-75.7 vs 15.7ng/mL, IQT 8.2-21.6 in survivors; p=0.0001). After determining an optimal PTX3 cut-off for the primary outcome, the Kaplan-Meier curve showed an increased mortality in patients with PTX3>22.25ng/mL (Log-rank tests p<0.0001). In Cox regression model, PTX3>22.25ng/mL showed an adjusted Hazard Ratio (aHR) of 7.6 (95%CI2.45-23.76) in predicting mortality. Performing a multivariate logistic regression including all inflammatory markers (PTX3, ferritin, D-Dimer, IL-6, and CRP), PTX3 was the only marker significantly associated with death (aHR 1.13;95%CI1.02-1.24; p=0.021). The results reported here suggest that circulating and lung myelomonocytic cells are a major source of PTX3 and that PTX3 plasma levels can serve as a strong prognostic indicator of short-term mortality in COVID-19.
