Racial/ethnic minority and neighborhood disadvantage leads to disproportionate mortality burden and years of potential life lost due to COVID-19 in Chicago, Illinois.

Epidemiological studies have highlighted the disparate impact of coronavirus disease 2019 (COVID-19) on racial and ethnic minority and socioeconomically disadvantaged populations, but data at the neighborhood-level is sparse. The objective of this study was to investigate the disparate impact of COVID-19 on disadvantaged neighborhoods and racial/ethnic minorities in Chicago, Illinois. Using data from the Cook County Medical Examiner, we conducted a neighborhood-level analysis of COVID-19 decedents in Chicago and quantified age-standardized years of potential life lost (YPLL) due to COVID-19 among demographic subgroups and neighborhoods with geospatial clustering of high and low rates of COVID-19 mortality. We show that age-standardized YPLL was markedly higher among the non-Hispanic (NH) Black (559 years per 100,000 population) and the Hispanic (811) compared with NH white decedents (312). We demonstrate that geomapping using residential address data at the individual-level identifies hot-spots of COVID-19 mortality in neighborhoods on the Northeast, West, and South areas of Chicago that reflect a legacy of residential segregation and persistence of inequality in education, income, and access to healthcare. Our results may contribute to ongoing public health and community-engaged efforts to prevent the spread of infection and mitigate the disproportionate loss of life among these communities due to COVID-19 as well as highlight the urgent need to broadly target neighborhood disadvantage as a cause of pervasive racial inequalities in life and health.

Computational Analysis of Targeting SARS-CoV-2, Viral Entry Proteins ACE2 and TMPRSS2, and Interferon Genes by Host MicroRNAs.

Rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), has led to a global pandemic, failures of local health care systems, and global economic recession. MicroRNAs (miRNAs) have recently emerged as important regulators of viral pathogenesis, particularly among RNA viruses, but the impact of host miRNAs on SARS-CoV-2 infectivity remains unknown. In this study, we utilize the combination of powerful bioinformatic prediction algorithms and miRNA profiling to predict endogenous host miRNAs that may play important roles in regulating SARS-CoV-2 infectivity. We provide a collection of high-probability miRNA binding sites within the SARS-CoV-2 genome as well as within mRNA transcripts of critical viral entry proteins ACE2 and TMPRSS2 and their upstream modulators, the interferons (IFN). By utilizing miRNA profiling datasets of SARS-CoV-2-resistant and -susceptible cell lines, we verify the biological plausibility of the predicted miRNA-target RNA interactions. Finally, we utilize miRNA profiling of SARS-CoV-2-infected cells to identify predicted miRNAs that are differentially regulated in infected cells. In particular, we identify predicted miRNA binders to SARS-CoV-2 ORFs (miR-23a (1ab), miR-29a, -29c (1ab, N), miR-151a, -151b (S), miR-4707-3p (S), miR-298 (5'-UTR), miR-7851-3p (5'-UTR), miR-8075 (5'-UTR)), ACE2 3'-UTR (miR-9-5p, miR-218-5p), TMPRSS2 3'-UTR (let-7d-5p, -7e-5p, miR-494-3p, miR-382-3p, miR-181c-5p), and IFN-α 3'-UTR (miR-361-5p, miR-410-3p). Overall, this study provides insight into potential novel regulatory mechanisms of SARS-CoV-2 by host miRNAs and lays the foundation for future investigation of these miRNAs as potential therapeutic targets or biomarkers.