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

BackgroundIn 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. MethodsWe 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). ResultsBetween 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). ConclusionThis 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

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

RationaleMacrophage activation syndrome (MAS) and complex immune dysregulation (CID) often underlie acute respiratory distress (ARDS) in COVID-19. ObjectiveTo investigate the outcome of personalized immunotherapy in critical COVID-19. MethodsIn 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 ResultsThe 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. ConclusionsBiomarkers may guide favourable anakinra responses in critically ill patients with COVID-19. Trial RegistrationClinicalTrials.gov, NCT04339712

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

BackgroundDetermining the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. MethodsWe developed the 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 response messenger RNAs. ResultsWe selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1,417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.91 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N=97) and retrospectively (N=100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. ConclusionsWith further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.

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

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.

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

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.

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

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.

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

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.

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

BackgroundInfection 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. MethodsIn 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. FindingsA 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. InterpretationWe 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. FundingVidi grant (F.L.v.d.V.) and Spinoza grant (M.G.N.) from the Netherlands Organization for Scientific Research, and ERC Advanced Grant (#833247 to M.G.N.).