COVID-19 Disease Severity among People with HIV Infection or Solid Organ Transplant in the United States: A Nationally-representative, Multicenter, Observational Cohort Study (preprint)

Background Individuals with immune dysfunction, including people with HIV (PWH) or solid organ transplant recipients (SOT), might have worse outcomes from COVID-19. We compared odds of COVID-19 outcomes between patients with and without immune dysfunction. Methods We evaluated data from the National COVID-19 Cohort Collaborative (N3C), a multicenter retrospective cohort of electronic medical record (EMR) data from across the United States, on. 1,446,913 adult patients with laboratory-confirmed SARS-CoV-2 infection. HIV, SOT, comorbidity, and HIV markers were identified from EMR data prior to SARS-CoV-2 infection. COVID-19 disease severity within 45 days of SARS-CoV-2 infection was classified into 5 categories: asymptomatic/mild disease with outpatient care; mild disease with emergency department (ED) visit; moderate disease requiring hospitalization; severe disease requiring ventilation or extracorporeal membrane oxygenation (ECMO); and death. We used multivariable, multinomial logistic regression models to compare odds of COVID-19 outcomes between patients with and without immune dysfunction. Findings Compared to patients without immune dysfunction, PWH and SOT had a greater likelihood of having ED visits (adjusted odds ratio [aOR]: 1.28, 95% confidence interval [CI] 1.27-1.29; aOR: 2.61, CI: 2.58-2.65, respectively), requiring ventilation or ECMO (aOR: 1.43, CI: 1.43-1.43; aOR: 4.82, CI: 4.78-4.86, respectively), and death (aOR: 1.20, CI: 1.19-1.20; aOR: 3.38, CI: 3.35-3.41, respectively). Associations were independent of sociodemographic and comorbidity burden. Compared to PWH with CD4>500 cells/mm3, PWH with CD4<350 cells/mm3 were independently at 4.4-, 5.4-, and 7.6-times higher odds for hospitalization, requiring ventilation, and death, respectively. Increased COVID-19 severity was associated with higher levels of HIV viremia. Interpretation Individuals with immune dysfunction have greater risk for severe COVID-19 outcomes. More advanced HIV disease (greater immunosuppression and HIV viremia) was associated with higher odds of severe COVID-19 outcomes. Appropriate prevention and treatment strategies should be investigated to reduce the higher morbidity and mortality associated with COVID-19 among PWH and SOT.

Epidemiological associations with genomic variation in SARS-CoV-2 (preprint)

The 2019 novel coronavirus (SARS-CoV-2) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. To diminish the short-term and long-term impacts of coronavirus (CoV), we investigated CoV differences at the nucleotide and protein level and CoV genomic variation associated with epidemiological variation and geography. We divided the CoV genome into 29 constituent regions for this analysis. Our results highlight the variation of CoV variants of lineage and show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation, which makes these two proteins potential targets for treatments. S protein variation is highly correlated with nsp3, nsp6, and 3'−to−5' exonuclease. Country of origin and time since the start of the pandemic were the most influential metadata in these differences. Host sex and age are the lowest in terms of explaining the virus genome variation. We quantified variation explained by regions of the CoV genome across different CoV viruses including, SARS-CoV-2, Middle East respiratory syndrome coronavirus (MERS-CoV), other severe acute respiratory syndrome coronavirus SARS-CoV (SARS-related), and bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses (Bat-SL-CoV). We found that Spike protein and nsp3 explain most of the variation among these viruses; they are also among the genomic regions with the highest number of sites under natural selection. Our results provide a direction to prioritize genes associated with outcome predictors, including health, therapeutic, and vaccine outcomes, and to inform improved DNA tests for predicting disease status.

SARS-CoV-2 Infection Reduces Human Nasopharyngeal Commensal Microbiome with Inclusion of Pathobionts (preprint)

Background The SARS-CoV-2 primarily enters into the human body through nasopharyngeal tract (NT) and is the etiological agent of COVID-19. The microbiota of the NT may play a role in host immunity against respiratory infectious diseases. However, scant information is available on interactions of SARS-CoV-2 with the nasopharyngeal microbiome. To shed light on the effects and consequences of SARS-CoV-2 infection on microbiome diversity and composition, we conducted a high throughput RNA-Seq metagenomic investigation of 22 NT swab samples (including COVID-19 = 8, Recovered = 7, and Healthy = 7). Results This study for the first time demonstrates the association of microbiome diversity and their concomitant genomic features in the NT of COVID-19 and Recovered patients compared to Healthy humans, and discusses the role of the altered microbiomes in the pathophysiology of the SARS-CoV-2 infections. Our RNA-Seq metagenomic analyses detected 2281 bacterial species (including 1477, 919 and 676 in samples of Healthy human, COVID-19 and Recovered patients, respectively) indicating a distinct microbiome dysbiosis (COVID-19>Recovered>Healthy). The samples from COVID-19 patients and Recovered individuals had inclusion of 67% (including Streptococcus salivarius, S. mitis, Neisseria subflava, Veillonella dispar, Acinetobacter junii, Prevotella melaninogenica etc.) and 77% (including Pseudomonas stutzeri, Staphylococcus capitis, S. epidermidis, P. mendocina, Moraxella osloensis, A. indicus, Escherichia coli etc.) opportunistic pathogenic bacteria, respectively compared to Healthy individuals. Notably, 79% commensal bacteria (e.g., Pseudomonas sp. LPH1, Brevundimonas sp. Bb-A, P. oleovorans, Pseudomonas sp. phDV1, Brevundimonas sp. DS20, Idiomarinaceae bacterium HL-53, Alishewanella sp. 205, Sphingobacterium psychroaquaticum etc.) were found in healthy individuals but not detected in COVID-19 patients and Recovered individuals. Similar dysbiosis was also found in viral and archaeal fraction of the microbiomes. Although, 55 viral and 48 archaeal genera were detected, only 16% viral and 27% archaeal genera were shared across three metagenomes. We also detected altered metabolic pathways and functional genes including resistance to antibiotics and toxic compounds in the pathophysiology of COVID-19.Conclusions The nasopharyngeal microbiome dysbiosis and their genomic features in COVID-19, Recovered and Healthy individuals determined by our RNA-Seq analyses shed light on early interactions of SARS-CoV-2 with the nasopharyngeal resident microbiota that might be helpful for developing microbiome-based diagnostics and therapeutics for this novel pandemic disease.

Evolving Infection Paradox of SARS-CoV-2: Fitness Costs Virulence? (preprint)

Background: SARS-CoV-2 is continuously spreading worldwide at an unprecedented scale and evolved into seven clades according to GISAID where four (G, GH, GR and GV) are globally prevalent in 2020. These major predominant clades of SARS-CoV-2 are continuously increasing COVID-19 cases worldwide; however, after an early rise in 2020, the death-case ratio has been decreasing to a plateau. G clade viruses contain four co-occurring mutations in their genome (C241T+C3037T+C14408T: RdRp.P323L+A23403G:spike.D614G). GR, GH, and GV strains are defined by the presence of these four mutations in addition to the clade-featured mutation in GGG28881-28883AAC:N. RG203-204KR, G25563T:ORF3a.Q57H, and C22227T:spike.A222V+C28932T-N.A220V+G29645T, respectively. The research works are broadly focused on the spike protein mutations that have direct roles in receptor binding, antigenicity, thus viral transmission and replication fitness. However, mutations in other proteins might also have effects on viral pathogenicity and transmissibility. How the clade-featured mutations are linked with viral evolution in this pandemic through gearing their fitness and virulence is the main question of this study. Methodology: We thus proposed a hypothetical model, combining a statistical and structural bioinformatics approach, endeavors to explain this infection paradox by describing the epistatic effects of the clade-featured co-occurring mutations on viral fitness and virulence. Results and Discussion: The G and GR/GV clade strains represent a significant positive and negative association, respectively, with the death-case ratio (incidence rate ratio or IRR = 1.03, p <0.001 and IRR= 0.99/0.97, p < 0.001), whereas GH clade strains showed no association with the Docking analysis showed the higher infectiousness of a spike mutant through more favorable binding of G614 with the elastase-2. RdRp mutation p.P323L significantly increased genome-wide mutations (p<0.0001) since more expandable RdRp (mutant)-NSP8 interaction may accelerate replication. Superior RNA stability and structural variation at NSP3:C241T might impact upon protein or RNA interactions. Another silent 5'UTR:C241T mutation might affect translational efficiency and viral packaging. These G-featured co-occurring mutations might increase the viral load, alter immune responses in host and hence can modulate intra-host genomic plasticity. An additional viroporin ORF3a:p.Q57H mutation, forming GH-clade, prevents ion permeability by cysteine (C81)-histidine (H57) inter-transmembrane-domain interaction mediated tighter constriction of the channel pore and possibly reduces viral release and immune response. GR strains, four G clade mutations and N:p.RG203-204KR, would have stabilized RNA interaction by more flexible and hypo-phosphorylated SR-rich region. GV strains seemingly gained the evolutionary advantage of superspreading event through confounder factors; nevertheless, N:p.A220V might affect RNA binding. Conclusion: These hypotheses need further retrospective and prospective studies to understand detailed molecular and evolutionary events featuring the fitness and virulence of SARS-CoV-2.

Diversity and genomic determinants of the microbiomes associated with COVID-19 and non-COVID respiratory diseases (preprint)

The novel coronavirus disease 2019 (COVID-19) is a rapidly emerging and highly transmissible disease caused by the Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2). Understanding the microbiomes associated with the upper respiratory tract infection (URTI), chronic obstructive pulmonary disease (COPD) and COVID-19 diseases has clinical interest. We hypothesized that the diversity of microbiome compositions and their genomic features are associated with different pathological conditions of these human respiratory tract diseases (COVID-19 and non-COVID; URTI and COPD). To test this hypothesis, we analyzed 21 whole metagenome sequences (WMS) including eleven COVID-19 (BD = 6 and China = 5), six COPD (UK = 6) and four URTI (USA = 4) samples to unravel the diversity of microbiomes, their genomic features and relevant metabolic functions. The WMS data mapped to 534 bacterial, 60 archaeal and 61 viral genomes with distinct variation in the microbiome composition across the samples (COVID-19>COPD>URTI). Notably, 94.57%, 80.0% and 24.59% bacterial, archaeal and viral genera shared between the COVID-19 and non-COVID samples, respectively, however, the COVID-19 related samples had sole association with 16 viral genera other than SARS-CoV-2. Strain-level virome profiling revealed 660 and 729 strains in COVID-19 and non-COVID sequence data, respectively and of them 34.50% strains shared between the conditions. Functional annotation of metagenomics sequences of thevCOVID-19 and non-COVID groups identified the association of several biochemical pathways related to basic metabolism (amino acid and energy), ABC transporters, membrane transport, replication and repair, clustering-based subsystems, virulence, disease and defense, adhesion, regulation of virulence, programmed cell death, and primary immunodeficiency. We also detected 30 functional gene groups/classes associated with resistance to antibiotics and toxic compounds (RATC) in both COVID-19 and non-COVID microbiomes. Furthermore, a predominant higher abundance of cobalt-zinc-cadmium resistance (CZCR) and multidrug resistance to efflux pumps (MREP) genes were detected in COVID-19 metagenome. The profiles of microbiome diversity and associated microbial genomic features found in both COVID-19 and non-COVID (COPD and URTI) samples might be helpful for developing the microbiome-based diagnostics and therapeutics for COVID-19 and non-COVID respiratory diseases. However, future studies might be carried out to explore the microbiome dynamics and the cross-talk between host and microbiomes employing larger volume of samples from different ethnic groups and geoclimatic conditions.

An engineered decoy receptor for SARS-CoV-2 broadly binds protein S sequence variants (preprint)

The spike S of SARS-CoV-2 recognizes ACE2 on the host cell membrane to initiate entry. Soluble decoy receptors, in which the ACE2 ectodomain is engineered to block S with high affinity, potently neutralize infection and, due to close similarity with the natural receptor, hold out the promise of being broadly active against virus variants without opportunity for escape. Here, we directly test this hypothesis. We find an engineered decoy receptor, sACE22.v2.4, tightly binds S of SARS-associated viruses from humans and bats, despite the ACE2-binding surface being a region of high diversity. Saturation mutagenesis of the receptor-binding domain followed by in vitro selection, with wild type ACE2 and the engineered decoy competing for binding sites, failed to find S mutants that discriminate in favor of the wild type receptor. We conclude that resistance to engineered decoys will be rare and that decoys may be active against future outbreaks of SARS-associated betacoronaviruses.

COVID-19 Biomarkers in research: Extension of the OncoMX cancer biomarker data model to capture biomarker data from other diseases. (preprint)

Scientists, medical researchers, and health care workers have mobilized worldwide in response to the outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; SCoV2). Preliminary data have captured a wide range of host responses, symptoms, and lingering problems post-recovery within the human population. These variable clinical manifestations suggest differences in influential factors, such as innate and adaptive host immunity, existing or underlying health conditions, co-morbidities, genetics, and other factors. As COVID-19-related data continue to accumulate from disparate groups, the heterogeneous nature of these datasets poses challenges for efficient extrapolation of meaningful observations, hindering translation of information into clinical applications. Attempts to utilize, analyze, or combine biomarker datasets from multiple sources have shown to be inefficient and complicated, without a unifying resource. As such, there is an urgent need within the research community for the rapid development of an integrated and harmonized COVID-19 Biomarker Knowledgebase. By leveraging data collection and integration methods, backed by a robust data model developed to capture cancer biomarker data we have rapidly crowdsourced the collection and harmonization of COVID-19 biomarkers. Our resource currently has 138 unique biomarkers. We found multiple instances of the same biomarker substance being suggested as multiple biomarker types during our extensive cross-validation and manual curation. As a result, our Knowledgebase currently has 265 biomarker type combinations. Every biomarker entry is made comprehensive by bringing in together ancillary data from multiple sources such as biomarker accessions (canonical UniProtKB accession, PubChem Compound ID, Cell Ontology ID, Protein Ontology ID, NCI Thesaurus Code, and Disease Ontology ID), BEST biomarker category, and specimen type (Uberon Anatomy Ontology) unified with ontology standards. Our preliminary observations show distinct trends in the collated biomarkers. Most biomarkers are related to the immune system (SAA,TNF-{propto}, and IP-10) or coagulopathies (D-dimer, antithrombin, and VWF) and a few have already been established as cancer biomarkers (ACE2, IL-6, IL-4 and IL-2). These trends align with proposed hypotheses of clinical manifestations compounding the complexity of COVID-19 pathobiology. We explore these trends as we put forth a COVID-19 biomarker resource that will help researchers and diagnosticians alike. All biomarker data are freely available from https://data.oncomx.org/covid19.

Genome Wide Analysis of Severe Acute Respiratory Syndrome Coronavirus-2 Implicates World-Wide Circulatory Virus Strains Heterogeneity (preprint)

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a novel evolutionarily divergent RNA virus etiological agent of COVID-19, is responsible for present devastating pandemic respiratory illness. To explore the genomic signatures, we comprehensively analyzed 2,492 complete and/or near-complete genome sequences of SARS-CoV-2 strains reported from across the globe to the GISAID database up to 30 March 2020. Genome-wide annotations revealed 1,407 nucleotide-level mutations at different positions throughout the entire genome of SARS-CoV-2. Moreover, nucleotide deletion analysis found nine deletions throughout the genome, including in polyprotein (n=6), ORF10 (n=1) and 3´-UTR (n=2). Evidence from the systematic gene-level mutational and protein profile analyses revealed a large number of amino acid (aa) substitutions (n=722), making the viral proteins heterogeneous. Notably, residues of receptor-binding domain (RBD) having crucial interactions with angiotensin-converting enzyme 2 (ACE2), and cross-reacting neutralizing antibody were found to be conserved among the analyzed SARS-CoV-2 strains, except for replacement of Lysine with Arginine at 378 position of the cryptic epitope of a Shanghai isolate, hCoV-19/Shanghai/SH0007/2020 (EPI_ISL_416320). Our method of genome annotation is a promising tool for monitoring and tracking the epidemic, the associated genetic variants, and their implications for the development of effective control and prophylaxis strategy.