ABSTRACT
Variants of SARS-CoV-2 have been associated with different transmissibilities and disease severities. The present study examines SARS-CoV-2 genetic variants and their relationship to risk for hospitalization, using data from 12,538 patients from a large, multisite observational cohort study. The association of viral genomic variants and hospitalization is examined with clinical covariates, including COVID-19 vaccination status, outpatient monoclonal antibody treatment status, and underlying risk for poor clinical outcome. Modeling approaches include XGBoost with SHapley Additive exPlanations (SHAP) analysis and generalized linear mixed models. The results indicate that several SARS-CoV-2 lineages are associated with increased hospitalization risk, including B.1.1.7, AY.44, and AY.54. As found in prior studies, Omicron is associated with lower hospitalization risk compared to prior WHO variants. In addition, the results suggest that variants at specific amino acid locations, including locations within Spike protein N-terminal domain and in non-structural protein 14, are associated with hospitalization risk.
Subject(s)
COVID-19ABSTRACT
BackgroundThe COVID-19 pandemic has been characterized by ongoing evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with concomitant variation in viral transmissibility and morbidity. Within specific timeframes and geographic areas, multiple SARS-CoV-2 variants have coexisted in the human population, each characterized by distinct biologic and clinical features, such as varying susceptibility to neutralizing monoclonal antibodies (nMAbs), a major frontline treatment. As part of an observational real-world data study of the effectiveness of nMAbs for treatment of COVID-19, SARS-CoV-2 viral samples were obtained from patients under treatment, generating paired clinical and genomics data. This paper describes the processing pipeline and findings from the genomics portion of this combined data set. MethodsSARS-CoV-2 sequences were generated from 14,796 diagnostic samples from four large U.S. health systems between July 2020 and March 2022. Among nMAbs-treated patients, samples were collected on the same day as, or prior to, treatment with nMAbs. Thus, these samples represent a snapshot of SARS-CoV-2 variants circulating in the respective patient groups, as opposed to variants that arose in response to specific treatments. Health systems collected viral samples and performed library creation and sequencing according to local protocols, using tiled ARTIC amplicon primers. FASTQ files were submitted to a study data platform and processed through a common pipeline. This pipeline enabled a unified approach to quality control, assembly, and production of genomics features for downstream analysis. ResultsAlpha and pre-Alpha SARS-CoV-2 lineages were predominant in the data set prior to June 2021. From June 2021 through November 2021, Delta was the dominant variant. Beginning in December 2021, Omicron was dominant. A variety of mutations associated with decreased nMAbs binding to the spike protein in vitro were detected, including lineage-defining mutations and non-lineage-defining mutations such as E340A, G446V, and S494P. Distinct patterns of sequence gaps and ambiguous base calls were associated with distinct variants. ConclusionsThe distribution of SARS-CoV-2 variants, per WHO nomenclature, across epochs in this data set matched concurrent CDC genomic surveillance results across the U.S. Detection of putative nMAbs escape mutations within clinical samples was consistent with FDA decisions to amend EUAs as variants emerged. This genomics data set provides an opportunity to examine associations between SARS-CoV-2 genomic variation and clinical outcomes in the associated EHR data set. The expansion of real-world data sets such as this to study the relationship between viral sequence and treatment outcomes could provide the foundation for future efforts to achieve near-real-time understanding of clinical outcomes related to genomic variation over time, and evidence to update treatment decisions more rapidly and to greater effect during ongoing and future pandemics.
Subject(s)
COVID-19 , Coronavirus InfectionsABSTRACT
Host genetic susceptibility is a key risk factor for severe illness associated with COVID-19. Despite numerous studies of COVID-19 host genetics, our knowledge of COVID-19-associated variants is still limited, and there is no resource comprising all the published variants and categorizing them based on their confidence level. Also, there are currently no computational tools available to predict novel COVID-19 severity variants. Therefore, we collated 820 host genetic variants reported to affect COVID-19 susceptibility by means of a systematic literature search and confidence evaluation, and obtained 196 high-confidence variants. We then developed the first machine learning classifier of severe COVID-19 variants to perform a genome-wide prediction of COVID-19 severity for 82,468,698 missense variants in the human genome. We further evaluated the classifier's predictions using feature importance analyses to investigate the biological properties of COVID-19 susceptibility variants, which identified conservation scores as the most impactful predictive features. The results of enrichment analyses revealed that genes carrying high-confidence COVID-19 susceptibility variants shared pathways, networks, diseases and biological functions, with the immune system and infectious disease being the most significant categories. Additionally, we investigated the pleiotropic effects of COVID-19-associated variants using phenome-wide association studies (PheWAS) in ~40,000 BioMe BioBank genotyped individuals, revealing pre-existing conditions that could serve to increase the risk of severe COVID-19 such as chronic liver disease and thromboembolism. Lastly, we generated a web-based interface for exploring, downloading and submitting genetic variants associated with COVID-19 susceptibility for use in both research and clinical settings (https://itanlab.shinyapps.io/COVID19webpage/). Taken together, our work provides the most comprehensive COVID-19 host genetics knowledgebase to date for the known and predicted genetic determinants of severe COVID-19, a resource that should further contribute to our understanding of the biology underlying COVID-19 susceptibility and facilitate the identification of individuals at high risk for severe COVID-19.
Subject(s)
Thromboembolism , End Stage Liver Disease , Communicable Diseases , COVID-19 , DiseaseABSTRACT
Background: COVID-19 has had a significant impact on the wellbeing of healthcare workers, with quantitative studies identifying increased stress, anxiety, depression, insomnia, and PTSD in a wide range of settings. Limited qualitative data so far has offered in-depth details concerning what underlies these challenges, but none provide comprehensive comparison across different healthcare systems. Objective: To explore qualitative findings relating to healthcare worker distress from two different countries to understand the nuanced similarities and differences with respect to the sources and impact of distress relating to COVID-19. Method: A comparative interpretive thematic analysis was carried out between two qualitative data sets examining healthcare workers’ experiences of distress during the COVID-19 pandemic. Data from Canada and the UK were collected in parallel and analyzed in an iterative, collaborative process. Results: A number of sources of distress cut across both study settings including concerns about safety and patient care, challenges at home or in one’s personal life, communication issues, work environment, media and public perception, and government responses to the pandemic. These sit on a spectrum from individual to institutional sources and were mutually reinforcing. Our analysis also suggested that common mechanisms such as exacerbations in uncertainty, hypervigilance, and moral injury underpinned these sources, which contributed to how they were experienced as distressing. Conclusion: This is the first international collaboration utilising qualitative data to examine this pressing issue. Despite differences in the political, social, health service, and pandemic-related context, the sources and mechanisms of distress experienced by healthcare workers in Canada and the UK were remarkably similar. HIGHLIGHTS This international comparative qualitative study explores how mechanisms that lead to distress are shared across different geographies and cultures, even as the local context shapes the sources of distress themselves.
ABSTRACT
Background: Patients with immunodeficiency-associated antibody disorders are at a higher risk of prolonged/persistent coronavirus disease 2019 (COVID-19) infection, having no viable treatment options. Methods: This is a retrospective analysis of patients with primary and/or secondary immunodeficiency-associated antibody disorders who received casirivimab and imdevimab (REGEN-COV(R)) under emergency compassionate use. The objectives were to describe safety and response to REGEN-COV, with a focus on the subset of patients who had disease duration [≥]21 days prior to treatment. Quantitative (change in oxygenation status and/or viral load) and/or qualitative (physician-reported clinical status) patient outcomes data are reported. Results: Data is available from 64 patients who received REGEN-COV. Improvement in [≥]1 outcome measure was observed in 90.6% of the overall patient group. Thirty-seven of these had COVID-19 duration [≥]21 days prior to treatment, with a mean time from RT-PCR diagnosis to REGEN-COV administration of 60.5 days. Of the 29 patients with disease duration [≥]21 days prior to treatment who had available outcome data, 96.6% showed improvement in [≥]1 outcome measure evaluated following use of REGEN-COV. In the 14 patients who had post-treatment RT-PCR results available, 11 (78.6%) reported a negative RT-PCR following treatment with REGEN-COV, with 5 patients (45.5%) reporting a negative RT-PCR within 5 days of treatment and 8 (72.7%) reporting a negative RT-PCR within 21 days of treatment. Conclusions: In this retrospective analysis of immunodeficient patients who were granted REGEN-COV under the compassionate use program, REGEN-COV treatment was associated with rapid viral clearance and clinical improvement in the evaluable patients with long-standing COVID-19.
Subject(s)
COVID-19 , Immunologic Deficiency SyndromesABSTRACT
BACKGROUNDSarilumab (anti-interleukin-6 receptor- monoclonal antibody) may attenuate the inflammatory response in Covid-19. METHODSWe performed an adaptive, phase 2/3, randomized, double-blind, placebo-controlled trial of intravenous sarilumab 200 mg or 400 mg in adults hospitalized with Covid-19. The phase 3 primary analysis population (cohort 1) was patients with critical Covid-19 receiving mechanical ventilation (MV) randomized to sarilumab 400 mg or placebo. The primary end point for phase 3 was the proportion of patients with [≥]1-point improvement in clinical status from baseline to day 22. RESULTSFour-hundred fifty-seven (457) and 1365 patients were randomized and treated in phases 2 and 3, respectively. Among phase 3 critical patients receiving MV (n=289; 34.3% on corticosteroids), the proportion with [≥]1-point improvement in clinical status (alive not receiving MV) at day 22 was 43.2% in sarilumab 400 mg and 35.5% in placebo (risk difference [RD] +7.5%; 95% confidence interval [CI], -7.4 to 21.3; P=0.3261), representing a relative risk improvement of 21.7%. Day 29 all-cause mortality was 36.4% in sarilumab 400 mg versus 41.9% in placebo (RD -5.5%; 95% CI, -20.2 to 8.7; relative risk reduction 13.3%). In post hoc analyses pooling phase 2 and 3 critical patients receiving MV, the hazard ratio (HR) for death in sarilumab 400 mg compared with placebo was 0.76 (95% CI, 0.51 to 1.13) overall, improving to 0.49 (95% CI, 0.25 to 0.94) in patients receiving corticosteroids at baseline. CONCLUSIONIn hospitalized patients with Covid-19 receiving MV, numerical benefits with sarilumab did not achieve statistical significance, but benefit may be greater in patients receiving corticosteroids. A larger study is required to confirm this observed numerical benefit. (ClinicalTrials.gov number, NCT04315298)