Epidemiological associations with genomic variation in SARS-CoV-2

Abstract

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.

Metabolite, Protein, And Tissue Dysfunction Associated With COVID-19 Disease Severity

“…We have shown that the SARS-CoV-2 genomic variation is independent of host characteristics (e.g., age and gender) 1 , and here as a next step, we investigated the factors that influence COVID-19 disease severity using an integrated approach involving analyses of metabolite and protein profiles, epidemiological data, and clinical data, previously published 2 . The measurements included a complete blood cell count panel, a comprehensive metabolic test panel, and quantification of 941 metabolites and 894 proteins from serum samples.…”

Hospital Antimicrobial Stewardship: Non-Bacterial Saliva Microbiome Emerges as a Biomarker of COVID-19 Severity

“…Patients' saliva was sampled upon admission in most cases, but as the hospital resources were strained with a heavy influx of COVID-19 patients during that time, some patients were recruited 3 or more days after admission, when they had started treatment. While many COVID-19 studies have focused on epidemiological associations of SARS-CoV-2 8 and dynamics of microbiome during infection, CLAIRE (CLuster AI pREdiction of disease progression) is the only study to investigate the COVID-19 saliva microbiome in hospitalized patients with a focus on sepsis and broad-spectrum antibiotics. The SARS-CoV-2 virus was characterized through Illumina's Respiratory Viral Oligo Panel (RVOP) sequencing 9 .…”