Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19 (preprint)

Our understanding of protective vs. pathologic immune responses to SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19), is limited by inadequate profiling of patients at the extremes of the disease severity spectrum. Here, we performed multi-omic single-cell immune profiling of 64 COVID-19 patients across the full range of disease severity, from outpatients with mild disease to fatal cases. Our transcriptomic, epigenomic, and proteomic analyses reveal widespread dysfunction of peripheral innate immunity in severe and fatal COVID-19, with the most profound disturbances including a prominent neutrophil hyperactivation signature and monocytes with anti-inflammatory features. We further demonstrate that emergency myelopoiesis is a prominent feature of fatal COVID-19. Collectively, our results reveal disease severity-associated immune phenotypes in COVID-19 and identify pathogenesis-associated pathways that are potential targets for therapeutic intervention.

International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study (preprint)

Objectives: To perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions. Design: Retrospective cohort study. Setting: The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe. Participants: Patients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2. Primary and secondary outcome measures: Patients were categorized as ''ever-severe'' or ''never-severe'' using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction. Results: Of 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites. Conclusions: Laboratory test values at admission can be used to predict severity in patients with COVID-19. There is a need for prediction models that will perform well over the course of the disease in hospitalized patients.

SNPnexus COVID: Facilitating the analysis of COVID-19 host genetics (preprint)

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has presented a crisis for global healthcare systems. Human SARS-CoV-2 infection can result in coronavirus disease 2019 (COVID-19), which has been characterised as an acute respiratory illness, with most patients displaying flu-like symptoms, such as a fever, cough and dyspnoea. However, the range and severity of individual symptoms experienced by patients can vary significantly, indicating a role for host genetics in impacting the susceptibility and severity of COVID-19 disease. Whilst most symptomatic infections are known to manifest in mild to moderate respiratory symptoms, severe pneumonia and complications including cytokine release syndrome, which can lead to multi-organ dysfunction, have also been observed in cases worldwide. Global initiatives to sequence the genomes of patients with COVID-19 have driven an expanding new field of host genomics research, to characterise the genetic determinants of COVID-19 disease. The functional annotation and analysis of incoming genomic data, within a clinically relevant turnaround time, is therefore imperative given the importance and urgency of research efforts to understand the biology of SARS-CoV-2 infection and disease. To address these requirements, we developed SNPnexus COVID. This is a web-based variant annotation tool, powered by the SNPnexus software.

assayM: a web application to monitor mutations in COVID-19 diagnostic assays. (preprint)

Reverse Transcriptase - Polymerase Chain Reaction (RT-PCR) is the gold standard as diagnostic assays for the detection of COVID-19 and the specificity and sensitivity of these assays depend on the complementarity of the RT-PCR primers to the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the virus mutates over time during replication cycles, there is an urgent need to continuously monitor the virus genome for appearances of mutations and mismatches in the PCR primers used in these assays. Here we present assayM, a web application to explore and monitor mutations introduced in the primer and probe sequences published by the World Health Organisation (WHO) or in any custom-designed assay primers for SARS-CoV-2 detection assays in globally available SARS-CoV-2 genome datasets.

Genomic and phylogenetic analyses of SARS-CoV-2 strains isolated in the city of Gwangju, South Korea (preprint)

Since the first identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China in late December 2019, the coronavirus disease 2019 (COVID-19) has spread fast around the world. RNA viruses, including SARS-CoV-2, have higher gene mutations than DNA viruses during virus replication. Variations in SARS-CoV-2 genome could contribute to efficiency of viral spread and severity of COVID-19. In this study, we analyzed the locations of genomic mutations to investigate the genetic diversity among isolates of SARS-CoV-2 in Gwangju. We detected non-synonymous and frameshift mutations in various parts of SARS-CoV-2 genome. The phylogenetic analysis for whole genome showed that SARS-CoV-2 genomes in Gwangju isolates are clustered within clade V and G. Our findings not only provide a glimpse into changes of prevalent virus clades in Gwangju, South Korea, but also support genomic surveillance of SARS-CoV-2 to aid in the development of efficient therapeutic antibodies and vaccines against COVID-19.

Assessing the quality of nontraditional N95 filtering face-piece respirators available during the COVID-19 pandemic (preprint)

Background: During the current COVID-19 pandemic, supply chains for Personal Protective Equipment (PPE) have been severely disrupted and many products, particularly surgical N95 filtering facepiece respirators (FFRs; "masks") are in short supply. As a consequence, an Emergency Use Authorization (EUA) from the FDA has allowed importation of N95-type masks manufactured to international standards; these include KN95 masks from China and FFP2 masks from the European Union. Methods: We conducted a survey of mask in the inventory of major academic medical centers in Boston, MA to determine provenance and manufacturer. We then assembled a simple apparatus for performing a necessary (but not sufficient) test of filtration performance and tested masks from the inventory; an accompanying website shows how to build and use the testing apparatus. Results: Our survey showed that, seven months after the start of the COVID-19 pandemic, over 100 different makes and models of N95-type masks are in the inventory of local hospitals as opposed to 2-5 models under normal circumstances. A substantial number of unfamiliar masks are from unknown manufacturers. Many did not perform to accepted standards and are likely to be counterfeit. Due to the absence of publicly available information on mask suppliers in the FDA EUA and confusing or inconsistent labeling of KN95 masks, it is difficult to distinguish legitimate and counterfeit products. Conclusions: Many of the FFR masks available for procurement during the COVID-19 pandemic do not provide levels of fit and filtration similar to those of N95 masks and are not acceptable for use in healthcare settings. Based on these results, and in consultation with occupational health officers, we make six recommendations for end users to assist in acquiring legitimate products. In particular, institutions should always assess masks from non-traditional supply chains by checking their markings and manufacturer information against data provided by NIOSH and the latest FDA EUA Appendix A. In the absence of verifiable information on the legitimacy of mask source, institutions should consider measuring mask fit and filtration directly. We also make suggestions for U.S and Chinese regulatory agencies with regard to labeling and public disclosure aimed at increase pandemic resilience.

Analysis of SteraMist ionized hydrogen peroxide technology as a method for sterilizing N95 respirators and other personal protective equipment (preprint)

ObjectiveThe COVID-19 pandemic has led to widespread shortages of personal protective equipment (PPE) for healthcare workers, including filtering facepiece respirators (FFRs) such as N95 masks. These masks are normally intended for single use, but their sterilization and subsequent reuse could substantially mitigate a world-wide shortage. DesignQuality assurance. SettingA sealed environment chamber installed in the animal facility of an academic medical center. InterventionsOne to five sterilization cycles using ionized hydrogen peroxide (iHP), generated by SteraMist(R) equipment (TOMI; Frederick, MD). Main outcome measuresPersonal protective equipment, including five N95 mask models from three manufacturers, were evaluated for efficacy of sterilization following iHP treatment (measured with bacterial spores in standard biological indicator assemblies). Additionally, N95 masks were assessed for their ability to efficiently filter particles down to 0.3{micro}m and for their ability to form an airtight seal using a quantitative fit test. Filtration efficiency was measured using ambient particulate matter at a university lab and an aerosolized NaCl challenge at a National Institute for Occupational Safety and Health (NIOSH) pre-certification laboratory. ResultsThe data demonstrate that N95 masks sterilized using SteraMist iHP technology retain function up to five cycles, the maximum number tested to date. Some but not all PPE could also be sterilized using an iHP environmental chamber, but pre-treatment with a handheld iHP generator was required for semi-enclosed surfaces such as respirator hoses. ConclusionsA typical iHP environment chamber with a volume of ~80 m3 can treat ~7000 masks per day, as well as other items of PPE, making this an effective approach for a busy medical center.