RESUMEN
Efforts to mitigate the spread of coronavirus disease 2019 (COVID-19) in the United States require an accurate understanding of how the epidemic is progressing. The National Center for Health Statistics (NCHS) releases weekly numbers of deaths attributed to a set of select causes, including deaths from COVID-19 in the entire United States (US), by state, and cumulatively for individual counties. Comparing US and state level deaths from select causes recorded in 2020 with values from 2014-2019 identifies a number of differences that exceeded 95% confidence limits on historical mean values, including three states with deaths possibly from COVID-19 in December 2019. Comparing county-level NCHS datasets with county-level data on deaths from COVID-19 compiled by four public pandemic tracking sites suggests that a large number of COVID-19 deaths have not yet been reported to the NCHS. Dividing the numbers of COVID-19 deaths counted by the public tracking sites by the percentage of COVID-19 deaths reported to the NCHS suggests that approximately 20% of all US deaths from Natural Causes, as many as 200,000, may not yet have been reported to the NCHS. Evaluating changes in the fractions of deaths attributed to COVID-19 and other specific causes or nonspecific outcomes during the epidemic, relative to 2020 totals or historical mean values, can provide a valuable perspective on the public health consequences of COVID-19. Significance StatementEstimating total deaths from natural causes using the percentage of natural cause deaths from COVID-19 reported to the CDC and the number of COVID-19 deaths counted by public tracking sites suggests that up to 200,000 deaths from natural causes between 22 April and 15 August, 2020, around 20% of the total recorded as of 26 August, have not yet been reported to the CDC.
RESUMEN
The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.
RESUMEN
BackgroundPandemic COVID-19 by SARS-COV-2 infection is facilitated by the ACE2 receptor and protease TMPRSS2. Modestly sized case series have described clinical factors associated with COVID-19, while ACE2 and TMPRSS2 expression analyses have been described in some cell types. Cancer patients may have worse outcomes to COVID-19. MethodsWe performed an integrated study of ACE2 and TMPRSS2 gene expression across and within organ systems, by normal versus tumor, across several existing databases (The Cancer Genome Atlas, Census of Immune Single Cell Expression Atlas, The Human Cell Landscape, and more). We correlated gene expression with clinical factors (including but not limited to age, gender, race, BMI and smoking history), HLA genotype, immune gene expression patterns, cell subsets, and single-cell sequencing as well as commensal microbiome. ResultsMatched normal tissues generally display higher ACE2 and TMPRSS2 expression compared with cancer, with normal and tumor from digestive organs expressing the highest levels. No clinical factors were consistently identified to be significantly associated with gene expression levels though outlier organ systems were observed for some factors. Similarly, no HLA genotypes were consistently associated with gene expression levels. Strong correlations were observed between ACE2 expression levels and multiple immune gene signatures including interferon-stimulated genes and the T cell-inflamed phenotype as well as inverse associations with angiogenesis and transforming growth factor-{beta} signatures. ACE2 positively correlated with macrophage subsets across tumor types. TMPRSS2 was less associated with immune gene expression but was strongly associated with epithelial cell abundance. Single-cell sequencing analysis across nine independent studies demonstrated little to no ACE2 or TMPRSS2 expression in lymphocytes or macrophages. ACE2 and TMPRSS2 gene expression associated with commensal microbiota in matched normal tissues particularly from colorectal cancers, with distinct bacterial populations showing strong associations. ConclusionsWe performed a large-scale integration of ACE2 and TMPRSS2 gene expression across clinical, genetic, and microbiome domains. We identify novel associations with the microbiota and confirm host immunity associations with gene expression. We suggest caution in interpretation regarding genetic associations with ACE2 expression suggested from smaller case series.