African Americans and European Americans exhibit distinct gene expression patterns across tissues and tumors that are associated with immunologic and infectious functions and environmental exposures (preprint)

The COVID-19 pandemic has affected African American populations disproportionately with respect to prevalence, morbidity, and mortality. Because gene expression profiles represent combined genetic, socioenvironmental, and physiological effects, and could provide therapeutic biomarkers and environmental mitigation strategies, we undertook a large-scale assessment of differential gene expression between African Americans and European Americans. To do this, we mined RNA-Seq datasets from normal and diseased (tumor) conditions whose metadata could be used to evaluate differential patterns. We observed widespread differential expression of genes implicated in COVID-19 and integral to epithelial boundary function, inflammation, infection, and reactive oxygen stress. Notably, expression of the little-studied F8A2 gene is up to 40-fold greater in African Americans. F8A2, like F8A1, encodes HAP40 protein, which mediates early endosome movement. African American gene expression signatures reveal increased number or activity of esophageal glandular cells and lung ACE2-positive basal keratinocytes. These findings have potential to establish prognostic signatures, refine approaches to minimizing risk of severe infection, and improve precision treatment of COVID-19.

Estimating Unreported Deaths Associated with COVID-19 (preprint)

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. Datasets available from the National Center for Health Statistics (NCHS) record weekly numbers of deaths attributed to a set of 'select causes' from 1 September 2019 through 12 August, 2020, including deaths from COVID-19 from 1 February through 12 August, 2020 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 identified a number of changes that exceeded 95% confidence limits on historical mean values, including three states with possible deaths from COVID-19 in December 2019. Comparing the NCHS datasets with data compiled by four public pandemic tracking sites on deaths from COVID-19 suggests that a large number of deaths counted by the public data tracking sites have not yet been reported to the NCHS. Estimates using the percentage of deaths from COVID-19 relative to all Natural Causes as reported to the NCHS and the numbers of COVID-19 deaths counted by the public tracking sites suggests that perhaps 20% of 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.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission (preprint)

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.

ACE2 and TMPRSS2 expression by clinical, HLA, immune, and microbial correlates across 34 human cancers and matched normal tissues: implications for SARS-COV-2 COVID-19 (preprint)

Background: Pandemic 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. Methods: We 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. Results: Matched 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. Conclusions: We 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.