Megakaryocytes are a Novel SARS-CoV-2 Infection Target and Risk Factor for Mortality and Multi-Organ Failure

Discovery of a biomarker for patients at high risk of progression to severe Coronavirus Disease 2019 (COVID-19) is critical for clinical management, particularly in areas of the world where widespread vaccine distribution and herd immunity have yet to be achieved. Herein, we characterize peripheral blood from 218 COVID-19 patients with flow cytometry and provide evidence that megakaryocytes are a target for infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). We demonstrate a positive correlation between infected megakaryocytes expressing the protein calprotectin (also called S100A8/A9), a known marker of COVID-19 severity. Additionally, we show that infected, calprotectin expressing megakaryocytes are correlated with COVID-19 severity and are a prognostic indicator of 30-day clinical outcomes including respiratory failure, thrombotic events, acute kidney injury (AKI), ICU admission, and mechanical ventilation. These findings represent a novel SARS-CoV-2 infection target with significant clinical implications as a biomarker for clinical outcomes associated with severe COVID-19.

Stay-at-Home Orders, African American Population, Poverty and State-level Covid-19 Infections: Are there associations?

ImportanceTo cope with the continuing COVID-19 pandemic, state and local health officials need information on the effectiveness of policies aimed at curbing contagion, as well as area-specific socio-demographic characteristics that can portend vulnerability to the disease. ObjectiveTo investigate whether state-imposed stay-at-home orders, African American population in the state, state poverty and other state socio-demographic characteristics, were associated with the state-level incidence of COVID-19 infection. Design, Setting, ParticipantsState-level, aggregated, publicly available data on positive COVID-19 cases and tests were used. The period considered was March 1st-May 4th. All U.S. states except Washington were included. Outcomes of interest were daily cumulative and daily incremental COVID-19 infection rates. Outcomes were log-transformed. Log-linear regression models with a quadratic time-trend and random intercepts for states were estimated. Covariates included log-transformed test-rates, a binary indicator for stay-at-home, percentage of African American, poverty, percentage elderly, state population and prevalence of selected comorbidities. Binary fixed effects for date each state first started reporting test data were included. ResultsStay-at-home orders were associated with decreases in cumulative ({beta}:-1.23; T-stat: - 6.84) and daily ({beta}:-0.46; T-stat: -2.56) infection-rates. Predictive analyses indicated that expected cumulative infection rates would be 3 times higher and expected daily incremental rates about 60% higher in absence of stay-at-home orders. Higher African American population was associated with higher cumulative ({beta}: 0.08; T-stat: 4.01) and daily ({beta}: 0.06; T-stat: 3.50) rates. State poverty rates had mixed results and were not robust to model specifications. There was strong evidence of a quadratic daily trend for cumulative and daily rates. Results were largely robust to alternate specifications. ConclusionsWe find evidence that stay-at-home orders, which were widely supported by public-health experts, helped to substantially curb COVID-19 infection-rates. As we move to a phased re-opening, continued precautions advised by public-health experts should be adhered to. Also, a larger African American population is strongly associated with incidence of COVID-19 infection. Policies and resources to help mitigate African American vulnerability to COVID-19 is an urgent public health and social justice issue, especially since the ongoing mass protests against police brutality may further exacerbate COVID-19 contagion in this community. Key PointsO_ST_ABSQuestionC_ST_ABSDid the stay-at-home orders, African American population and other socio demographic factors across states have any associations with COVID-19 infection rates across states? FindingsMultivariate log-linear regression models using daily state level data from March-May found evidence that when stay-at-home orders were implemented, they helped reduce state COVID-19 cumulative and daily infection rates substantially. Further, we found that states with larger African-American population had higher COVID-19 infection rates. MeaningResults suggest that state-level stay-at-home orders helped reduce COVID-19 infection rates substantially, and also that African American populations may be especially vulnerable to COVID-19 infection.