Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes (preprint)

Background: The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) can present with a broad range of clinical manifestations, ranging from asymptomatic to severe multiple organ failure. The severity of the disease can vary depending on factors such as age, sex, and ethnicity, as well as pre-existing medical conditions. Despite efforts to identify reliable prognostic factors and biomarkers, the predictive capacity of these markers for clinical outcomes remains poor. Circulating proteins, which reflect the active mechanisms in an individual can be easily measured in clinical practice, and therefore may be useful as biomarkers for COVID-19 disease severity. In this study, we sought to identify protein biomarkers and endotypes for COVID-19 severity and evaluate their reproducibility in an independent cohort. Methods: We investigated a cohort of 153 Greek patients with confirmed SARS-CoV-2 infection in which plasma protein levels were measured using the Olink Explore 1536 panel, which consists of 1472 proteins. We compared protein profiles from severe and moderate COVID-19 patients to identify proteins associated with disease severity. To evaluate the reproducibility of our findings, we compared the protein profiles of 174 patients with comparable COVID-19 severities in a US COVID-19 cohort to identify proteins consistently correlated with COVID-19 severity in both groups. Results: We identified 31 differentially regulated proteins, 20 of which were also significantly different in our initial cohort. Moreover, we performed unsupervised clustering of patients based on 97 proteins with the highest fold changes in order to identify COVID-19 endotypes. Clustering of patients based on differentially regulated proteins revealed the presence of three clinical endotypes. While endotypes 2 and 3 were enriched for severe COVID-19 patients, endotypes 3 represented the most severe form of the disease. Conclusions: These results suggest that identified circulating proteins may be useful for identifying COVID-19 patients with worse outcomes, and this potential utility may extend to other populations. Trial registration: NCT04357366

Anakinra in hospitalized COVID-19 patients guided by baseline soluble urokinase plasminogen receptor plasma levels: a real world, retrospective cohort study (preprint)

Background In patients with COVID-19 and baseline soluble urokinase plasminogen receptor plasma (suPAR) levels [≥] 6ng/mL, early administration of anakinra, a recombinant interleukin-1 receptor antagonist, may prevent disease progression and death. In case of suPAR testing unavailability, the Severe COvid Prediction Estimate (SCOPE) score may be used as an alternative in guiding treatment decisions. Methods We conducted a monocenter, retrospective cohort study, including patients with SARS-CoV2 infection and respiratory failure. Patients treated with anakinra (anakinra group, AG) were compared to two control groups of patients who did not receive anakinra, respectively with [≥] 6 ng/mL (CG1) and < 6 ng/mL (CG2) baseline suPAR levels. Controls were paired by age, sex, date of admission and vaccination status. Primary endpoint of the study was disease progression at day 14 from admission, as defined by patient distribution on a simplified version of the 11-point World Health Organization Clinical Progression Scale (WHO-CPS). Results Between July, 2021 and January, 2022, 153 patients were included, among which 56 were treated with off-label anakinra, 49 retrospectively fulfilled prescriptive criteria for anakinra and were assigned to CG1, and 48 presented with suPAR levels < 6ng/mL and were assigned to CG2. At day 14, when comparing to CG1, patients who received anakinra had significantly reduced odds of progressing towards worse clinical outcome both in ordinal regression analysis (OR 0.25, 95% CI 0.11-0.54, p<0.001) and in multivariable analysis (OR 0.19, 95% CI 0.03-0.82, p=0.037), and these results were confirmed even when controlling for age, sex, BMI and vaccinal status. Sensitivities of baseline suPAR and SCOPE score in predicting progression towards severe disease or death at day 14 were similar (83% vs 100%, p=0.59). Conclusion This real-word, retrospective cohort study confirmed the safety and the efficacy of suPAR-guided, early use of anakinra in hospitalized COVID-19 patients with respiratory failure.

IL-1α Mediates Tissue Specific Inflammation and Severe Respiratory Failure In Covid-19: Clinical And Experimental Evidence (preprint)

BackgroundAcute respiratory distress syndrome (ARDS) in COVID-19 has been associated with dysregulated immune responses leading to catastrophic inflammation. The activation pathways remain to be fully elucidated. We investigated the ability of circulating to induce dysregulated immune responses. Materials & MethodsCalprotectin and high mobility group box 1 (HMGB1) were associated with ARDS in 60 COVID-19 patients. In a second cohort of 40 COVID-19 patients calprotectin at hospital admission was associated with serum levels of soluble urokinase plasminogen activator receptor (suPAR). A COVID-19 animal model was developed by intravenous injection of plasma from healthy volunteers or patients with COVID-19 ARDS into C57/BL6 mice once daily for 3 consecutive days. In separate experiments, mice were treated with a) the IL-1 receptor antagonist Anakinra or vehicle and b) Flo1-2a anti-murine anti-IL-1 monoclonal antibody or the specific anti-human IL-1 antibody XB2001, or isotype controls. Mice were sacrificed on day 4. Cytokines and myeloperoxidase (MPO) in tissues were measured. ResultsCalprotectin, but not HMGB1, was elevated ARDS. Higher suPAR readouts indicated higher calprotectin levels. CHallenge of mice with COVID-19 plasma led to inflammatory reactions in murine lung and intestines as evidenced by increased levels of TNF, IL-6, IFN{gamma} and MPO. Anakinra treatment brought these levels down. Similar decrease was found in mice treated with Flo1-2a but not with XB2001. ConclusionCirculating alarmins, specifically calprotectin, of critically ill COVID-19 patients induces tissue-specific inflammatory responses through an IL-1 mediated mechanism. This could be attenuated through inhibition of IL-1 receptor or specific inhibition of IL-1.

ESCAPE: An Open-Label Trial of Personalized Immunotherapy in Critically Ill COVID-19 Patients (preprint)

ABSTRACT Rationale Macrophage activation syndrome (MAS) and complex immune dysregulation (CID) often underlie acute respiratory distress (ARDS) in COVID-19. Objective To investigate the outcome of personalized immunotherapy in critical COVID-19. Methods In this open-label prospective trial, 102 patients with SOFA (sequential organ failure assessment) score [≥]2 or ARDS by SARS-CoV-2 were screened for MAS (ferritin more than 4420 ng/ml) and CID (ferritin [≤]4420 ng/ml and low expression of HLA-DR on CD14-monocytes). Patients with MAS and CID with increased aminotransferases were assigned to intravenous anakinra; those with CID and normal aminotransferases to tocilizumab. The primary outcome was at least 25% decrease of SOFA score and/or 50% increase of respiratory ratio by day 8; 28-day mortality, change of SOFA score by day 28; serum biomarkers and cytokine production by mononuclear cells were secondary endpoints. Measurements and Main Results The primary study endpoint was met in 58.3% of anakinra-treated patients and in 33.3% of tocilizumab-treated patients (odds ratio 3.11; 95% CIs 1.29-7.73; P: 0.011). No differences were found in mortality and in SOFA score changes. By day 4, ferritin was decreased among anakinra-treated patients; interleukin (IL)-6, soluble urokinase plasminogen activator receptor (suPAR) and the expression of HLA-DR were increased among tocilizumab-treated patients. Anakinra increased capacity of mononuclear cells to produce IL-6. Survivors by day 28 who received anakinra were distributed to scales of the WHO clinical progression of lower severity. Greater incidence of secondary infections was found with tocilizumab treatment. Conclusions Biomarkers may guide favourable anakinra responses in critically ill patients with COVID-19. Trial Registration: ClinicalTrials.gov, NCT04339712 Key-words: anakinra; tocilizumab; acute respiratory distress syndrome; COVID-19; interleukin-6; ferritin; HLA-DR; macrophage activation; monocytes Abstract Word count: 250

Distant Residues Modulate the Conformational Opening in SARS-CoV-2 Spike Protein (preprint)

Infection by SARS-CoV-2 involves the attachment of the receptor binding domain (RBD) of its spike proteins to the ACE2 receptors on the peripheral membrane of host cells. Binding is initiated by a down to up conformational change in the spike protein, an opening which presents the RBD to the receptor. To date, computational and experimental studies for therapeutics have concentrated, for good reason, on the RBD. However, the RBD region is highly prone to mutations, and therefore will possibly arise drug resistance. In contrast, we here focus on the correlations between the RBD and residues distant to it in the spike protein. We thereby provide a deeper understanding of the role of distant residues in the molecular mechanism of infection. Predictions of key mutations in distant allosteric binding sites are provided, with implications for therapeutics. Identifying these emerging mutants can also go a long way towards pre-designing vaccines for future outbreaks. The model we use, based on time-independent component analysis (tICA) and protein graph connectivity network, is able to identify multiple residues that exhibit long-distance coupling with the RBD opening. Mutation on these residues can lead to new strains of coronavirus with different degrees of transmissibility and virulence. The most ubiquitous D614G mutation and the A570D mutation of the highly contageous UK SARS-CoV-2 variant are predicted ab-initio from our model. Conversely, broad spectrum therapeutics like drugs and monoclonal antibodies can be generated targeting these key distant but conserved regions of the spike protein. Significance statementThe novel coronavirus SARS-CoV-2 has created the largest pandemic of recent times, resulting in economic and public health crises. Significant research effort to design drugs against COVID-19 is focused on the receptor binding domain of the spike protein, although this region is prone to mutations that can cause resistance against therapeutics. We applied deep data analysis methods on all-atom molecular dynamics simulations of the spike protein to identify key non-RBD residues that play a crucial role in spike-receptor binding and infection of human cells. These residues can not only be targeted by broad spectrum antibodies and drugs, but can also offer predictive insights into the mutations with the potential to generate new strains that might appear during future epidemics.

A 6-mRNA host response whole-blood classifier trained using patients with non-COVID-19 viral infections accurately predicts severity of COVID-19 (preprint)

BackgroundWhile major progress has been made to establish diagnostic tools for the identification of SARS-CoV-2 infection, determining the severity of COVID-19 remains an unmet medical need. There is a limited availability of hospital resources in this or any pandemic, and appropriately gauging severity would allow for some patients to safely recover in home quarantine, while ensuring that sicker patients get needed care. MethodsWe here developed a blood-based generalizable host-gene-expression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N=705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune mRNAs. ResultsWe selected 6 host mRNAs and trained a logistic regression classifier with a training cross-validation AUROC of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1,417 samples across 21 independent retrospective validation cohorts the locked 6-mRNA classifier had an AUROC of 0.91 for discriminating patients with severe vs. non-severe infection. Next, in an independent cohort of prospectively enrolled patients with confirmed COVID-19 (N=97) in Athens, Greece, the 6-mRNA locked classifier had an AUROC of 0.89 for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed an isothermal qRT-LAMP (loop-mediated isothermal gene expression) assay for the 6-mRNA panel to facilitate implementation as a rapid assay. ConclusionsWith further study, the classifier could assist in the risk assessment of patients with confirmed SARS-CoV-2 infection and COVID-19 to determine severity and level of care, thereby improving patient management and healthcare burden.

Extended in vitro inactivation of SARS-CoV-2 by titanium dioxide surface coating (preprint)

SARS-CoV-2 transmission occurs via airborne droplets and surface contamination. We show tiles coated with TiO2 120 days previously can inactivate SARS-CoV-2 under ambient indoor lighting with 87% reduction in titres at 1h and complete loss by 5h exposure. TiO2 coatings could be an important tool in containing SARS-CoV-2.

Engineered receptor binding domain immunogens elicit pan-coronavirus neutralizing antibodies (preprint)

Effective countermeasures are needed against emerging coronaviruses of pandemic potential, similar to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Designing immunogens that elicit broadly neutralizing antibodies to conserved viral epitopes on the major surface glycoprotein, spike, such as the receptor binding domain (RBD) is one potential approach. Here, we report the generation of homotrimeric RBD immunogens from different sarbecoviruses using a stabilized, immune-silent trimerization tag. We find that that a cocktail of homotrimeric sarbecovirus RBDs can elicit a neutralizing response to all components even in context of prior SARS-CoV-2 imprinting. Importantly, the cross-neutralizing antibody responses are focused towards conserved RBD epitopes outside of the ACE-2 receptor-binding motif. This may be an effective strategy for eliciting broadly neutralizing responses leading to a pan-sarbecovirus vaccine.

Circular RNA profiling reveals abundant and diverse circRNAs of SARS-CoV-2, SARS-CoV and MERS-CoV origin (preprint)

Circular RNAs (circRNAs) encoded by DNA genomes have been identified across host and pathogen species as parts of the transcriptome. Accumulating evidences indicate that circRNAs play critical roles in autoimmune diseases and viral pathogenesis. Here we report that RNA viruses of the Betacoronavirus genus of Coronaviridae, SARS-CoV-2, SARS-CoV and MERS-CoV, encode a novel type of circRNAs. Through de novo circRNA analyses of publicly available coronavirus-infection related deep RNA-Sequencing data, we identified 351, 224 and 2,764 circRNAs derived from SARS-CoV-2, SARS-CoV and MERS-CoV, respectively, and characterized two major back-splice events shared by these viruses. Coronavirus-derived circRNAs are more abundant and longer compared to host genome-derived circRNAs. Using a systematic strategy to amplify and identify back-splice junction sequences, we experimentally identified over 100 viral circRNAs from SARS-CoV-2 infected Vero E6 cells. This collection of circRNAs provided the first line of evidence for the abundance and diversity of coronavirus-derived circRNAs and suggested possible mechanisms driving circRNA biogenesis from RNA genomes. Our findings highlight circRNAs as an important component of the coronavirus transcriptome. SummaryWe report for the first time that abundant and diverse circRNAs are generated by SARS-CoV-2, SARS-CoV and MERS-CoV and represent a novel type of circRNAs that differ from circRNAs encoded by DNA genomes.

Binding of SARS-CoV-2 spike protein to ACE2 is disabled by thiol-based drugs; evidence from in vitro SARS-CoV-2 infection studies. (preprint)

Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the SARS-CoV-2 spike protein is an envelope glycoprotein that binds angiotensin converting enzyme 2 as an entry receptor. The capacity of enveloped viruses to infect host cells depends on a precise thiol/disulfide balance in their surface glycoprotein complexes. To determine if cystines in the SARS-CoV-2 spike protein maintain a native binding interface that can be disrupted by drugs that cleave cystines, we tested if thiol-based drugs have efficacy in receptor binding and cell infection assays. We found that thiol-based drugs, cysteamine and WR-1065 (the active metabolite of amifostine) in particular, decrease binding of SARS-CoV-2 spike protein to its receptor, decrease the entry efficiency of SARS-CoV-2 spike pseudotyped virus, and inhibit SARS-CoV-2 live virus infection. Our findings uncover a vulnerability of SARS-CoV-2 to thiol-based drugs and provide rationale to test thiol-based drugs, especially cysteamine and amifostine, as novel treatments for COVID-19. One Sentence SummaryThiol-based drugs decrease binding of SARS-CoV-2 spike protein to its receptor and inhibit SARS-CoV-2 cell entry.

In vitro efficacy of Artemisinin-based treatments against SARS-CoV-2 (preprint)

Effective and affordable treatments for patients suffering from coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are needed. We report in vitro efficacy of Artemisia annua extracts as well as artemisinin, artesunate, and artemether against SARS-CoV-2. The latter two are approved active pharmaceutical ingredients of anti-malarial drugs. Proof-of-concept for prophylactic efficacy of the extracts was obtained using a plaque-reduction assay in VeroE6 cells. Subsequent concentration-response studies using a high-throughput antiviral assay, based on immunostaining of SARS-CoV-2 spike glycoprotein, revealed that pretreatment and treatment with extracts, artemisinin, and artesunate inhibited SARS-CoV-2 infection of VeroE6 cells. In treatment assays, artesunate (50% effective concentration (EC50): 7 g/mL) was more potent than the tested plant extracts (128-260 g/mL) or artemisinin (151 g/mL) and artemether (>179 g/mL), while generally EC50 in pretreatment assays were slightly higher. The selectivity index (SI), calculated based on treatment and cell viability assays, was highest for artemisinin (54), and roughly equal for the extracts (5-10), artesunate (6) and artemether (<7). Similar results were obtained in human hepatoma Huh7.5 cells. Peak plasma concentrations of artesunate exceeding EC50 values can be achieved. Clinical studies are required to further evaluate the utility of these compounds as COVID-19 treatment.

Reference ontology and database annotation of the COVID-19 Open Research Dataset (CORD-19) (preprint)

The COVID-19 Open Research Dataset (CORD-19) was released in March 2020 to allow the machine learning and wider research community to develop techniques to answer scientific questions on COVID-19. The data set consists of a large collection of scientific literature, including over 100,000 full text papers. Annotating training data to normalise variability in biological entities can improve the performance of downstream analysis and interpretation. To facilitate and enhance the use of the CORD-19 data in these applications, in late March 2020 we performed a comprehensive annotation process using named entity recognition tool, TERMite, along with a number of large reference ontologies and vocabularies including domains of genes, proteins, drugs and virus strains. The additional annotation has identified and tagged over 45 million entities within the corpus made up of 62,746 unique biomedical entities. The latest updated version of the annotated data, as well as older versions, is made openly available under GPL-2.0 License for the community to use at: https://github.com/SciBiteLabs/CORD19 .

Multi-cohort analysis of host immune response identifies conserved protective and detrimental modules associated with severity irrespective of virus (preprint)

SARS-CoV-2 pandemic, the fourth pandemic of the decade, has underscored gaps in global pandemic preparedness and the need for generalizable tests to avert overwhelming healthcare systems worldwide, irrespective of a virus. We integrated 4,780 blood transcriptome profiles from patients infected with one of 16 viruses across 34 independent cohorts from 18 countries, and 71 scRNA-seq profiles of 264,224 immune cells across three independent cohorts. We found a myeloid cell-dominated conserved host response associated with severity. It showed increased hematopoiesis, myelopoiesis, and myeloid-derived suppressor cells with increased severity. We identified four gene modules that delineate distinct trajectories associated with mild and severe outcomes, and show the interferon response was decoupled from protective host response during severe viral infection. These modules distinguished non-severe from severe viral infection with clinically useful accuracy. Together, our findings provide insights into immune response dynamics during viral infection, and identify factors that may influence patient outcomes.

Integration of heparin-binding protein and interleukin-6 in the early prediction of respiratory failure and mortality in pneumonia by SARS-CoV-2 (COVID-19) (preprint)

Purpose Recent publications on the probable role of heparin-binding protein (HBP) as a biomarker in sepsis prompted us to investigate its diagnostic and prognostic performance in severe COVID-19Methods HBP and IL-6 were measured by immunoassays at admission and on day 7 in 178 patients with pneumonia by SARS-CoV-2. Patients were classified into non-sepsis and sepsis as per the Sepsis-3 definitions and were followed-up for the development of severe respiratory failure (SRF) and for outcome. Results were confirmed by multivariate analyses.Results HBP was significantly higher in patients classified as having sepsis and was negatively associated with the oxygenation ratio and positively associated with creatinine and lactate. Logistic regression analysis evidenced admission HBP more than 18 ng/ml and IL-6 more than 30 pg/ml as independent risk factors for the development of SRP. Their integration prognosticated SRF with respective sensitivity, specificity, positive predictive value and negative predictive 59.1%, 96.3%, 83.9% and 87.8%. Cox regression analysis evidenced admission HBP more than 35 ng/ml and IL-6 more than 30 pg/ml as independent risk factors for 28-day mortality. Their integration prognosticated 28-day mortality with respective sensitivity, specificity, positive predictive value and negative predictive 69.2%, 92.7%, 42.9% and 97.5%. HBP remained unchanged over-time course. Conclusion A prediction score of the disposition of patients with COVID-19 is proposed taking into consideration admission levels of IL-6 and HBP. Using different cut-offs the score may predict the likelihood for SRF and for 28-day outcome. 

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients (preprint)

The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases calls for a better characterization and understanding of the changes in the immune system. Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 11 COVID-19 patients. Comparison of COVID-19 blood transcriptomes with those of a collection of over 2,800 samples derived from 11 different viral infections, inflammatory diseases and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host.

A novel optical biosensor for the early diagnosis of sepsis and severe COVID-19: the PROUD study (preprint)

Background The accuracy of a new optical biosensor (OB) point-of-care device for the detection of severe infections is studied.Methods The OB emits different wavelengths and outputs information associated with heart rate, pulse oximetry, levels of nitric oxide and kidney function. At the derivation phase, recordings were done every two hours for three consecutive days after hospital admission in 142 patients at high-risk for sepsis by placing the OB on the forefinger. At the validation phase, single recordings were done in 54 patients with symptoms of viral infection; 38 were diagnosed with COVID-19.Results At the derivation phase, the cutoff value of positive likelihood of 18 provided 100% specificity and 100% positive predictive value for the diagnosis of sepsis. These were 87.5% and 91.7% respectively at the validation phase. OB diagnosed severe COVID-19 with 83.3% sensitivity and 87.5% negative predictive value.Conclusions The studied OB seems valuable for the discrimination of infection severity.

Swarm Learning as a privacy-preserving machine learning approach for disease classification (preprint)

Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis and COVID-19 is an important goal of precision medicine. We recently illustrated that leukemia patients are identified by machine learning (ML) based on their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, blockchain-based peer-to-peer networking and coordination as well as privacy protection without the need for a central coordinator thereby going beyond federated learning. Using more than 14,000 blood transcriptomes derived from over 100 individual studies with non-uniform distribution of cases and controls and significant study biases, we illustrate the feasibility of SL to develop disease classifiers based on distributed data for COVID-19, tuberculosis or leukemias that outperform those developed at individual sites. Still, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

Transcriptomic Similarities and Differences in Host Response between SARS-CoV-2 and Other Viral Infections (preprint)

COVID-19 is a pandemic that shares certain clinical characteristics with other acute viral infections. Here, we studied the whole-blood transcriptomic host response to SARS-CoV-2 and compared it with other viral infections to understand similarities and differences in host response. Using RNAseq we profiled peripheral blood from 24 healthy controls and 62 prospectively enrolled patients with community-acquired lower respiratory tract infection by SARS-Cov-2 within the first 24 hours of hospital admission. We also compiled and curated 23 independent studies that profiled 1,855 blood samples from patients with one of six viruses (influenza, RSV, HRV, ebola, Dengue, and SARS-CoV-1). We show gene expression changes in peripheral blood in patients with COVID-19 versus healthy controls are highly correlated with changes in response to other viral infections (r=0.74, p<0.001). However, two genes, ACO1 and ATL3, show significantly opposite changes between conditions. Pathway analysis in patients with COVID-19 or other viral infections versus healthy controls identified similar pathways including neutrophil activation, innate immune response, immune response to viral infection, and cytokine production for over-expressed genes. Conversely, for under-expressed genes, pathways indicated repression of lymphocyte differentiation and T cell activation. When comparing transcriptome profiles of patients with COVID-19 directly with those with other viral infections, we found 114 and 302 genes were over- or under-expressed, respectively, during COVID-19. Pathways analysis did not identify any significant pathways in these genes, suggesting novel responses to further study. Statistical deconvolution using immunoStates found that M1 macrophages, plasmacytoid dendritic cells, CD14+ monocytes, CD4+ T cells, and total B cells showed change consistently in the same direction across all viral infections including COVID-19. Those that increased in COVID-19 but decreased in non-COVID-19 viral infections were CD56bright NK cells, M2 macrophages, and total NK cells. The concordant and discordant responses mapped out here provide a window to explore the pathophysiology of COVID-19 versus other viral infections and show clear differences in signaling pathways and cellularity as part of the host response to SARS-CoV-2.

A systems approach to inflammation identifies therapeutic targets in SARS-CoV-2 infection (preprint)

Background Infection with SARS-CoV-2 manifests itself as a mild respiratory tract infection in the majority of individuals, which progresses to a severe pneumonia and acute respiratory distress syndrome (ARDS) in 10-15% of patients. Inflammation plays a crucial role in the pathogenesis of ARDS, with immune dysregulation in severe COVID-19 leading to a hyperinflammatory response. A comprehensive understanding of the inflammatory process in COVID-19 is lacking. Methods In this prospective, multicenter observational study, patients with PCR-proven or clinically presumed COVID-19 admitted to the intensive care unit (ICU) or clinical wards were included. Demographic and clinical data were obtained and plasma was serially collected. Concentrations of IL-6, TNF-, complement components C3a, C3c and the terminal complement complex (TCC) were determined in plasma by ELISA. Additionally, 269 circulating biomarkers were assessed using targeted proteomics. Results were compared between ICU and non ICU patients. Findings A total of 119 (38 ICU and 91 non ICU) patients were included. IL-6 plasma concentrations were elevated in COVID-19 (ICU vs. non ICU, median 174.5 pg/ml [IQR 94.5-376.3 vs. 40.0 pg/ml [16.5-81.0]), whereas TNF- concentrations were relatively low and not different between ICU and non ICU patients (median 24.0 pg/ml [IQR 16.5-33.5] and 21.5 pg/ml [IQR 16.0-33.5], respectively). C3a and terminal complement complex (TCC) concentrations were significantly higher in ICU vs. non ICU patients (median 556.0 ng/ml [IQR 333.3-712.5]) vs. 266.5 ng/ml [IQR 191.5-384.0 for C3a and 4506 mAU/ml [IQR 3661-6595 vs. 3582 mAU/ml [IQR 2947-4300] for TCC) on the first day of blood sampling. Targeted proteomics demonstrated that IL-6 (logFC 2.2), several chemokines and hepatocyte growth factor (logFC 1.4) were significantly upregulated in ICU vs. non ICU patients. In contrast, stem cell factor was significantly downregulated (logFC -1.3) in ICU vs. non ICU patients, as were DPP4 (logFC -0.4) and protein C inhibitor (log FC -1.0), the latter two factors also being involved in the regulation of the kinin-kallikrein pathway. Unsupervised clustering pointed towards a homogeneous pathogenetic mechanism in the majority of patients infected with SARS-CoV-2, with patient clustering mainly based on disease severity. Interpretation We identified important pathways involved in dysregulation of inflammation in patients with severe COVID-19, including the IL-6, complement system and kinin-kallikrein pathways. Our findings may aid the development of new approaches to host-directed therapy.