Investigation of Interaction Between the Spike Protein of SARS-CoV-2 and ACE2-Expressing Cells Using an In Vitro Cell Capturing System (preprint)

Background: The Interaction between severe acute respiratory syndrome coronavirus 2 ( SARS-CoV-2 ) spike protein with Angiotensin converting enzyme 2 (ACE2) on the host cells is a crucial step for the viral entry and infection. Therefore, investigating the molecular mechanism underlying the interaction is of great importance for the prevention of the infection of SARS-CoV-2. In this study, we aimed to establish a virus-free in vitro system to study the interaction between the spike protein and host cells of SARS-CoV-2.Results: Our results show that ACE2-overexpressing HEK293T cells are captured by immobilized spike protein, and the cell capturing process can be inhibited by the receptor binding domain of the spike protein or antibodies against S protein. Furthermore, spike protein variant with D614G mutant show a higher cell capturing ability than wild type spike protein. In addition, the captured cells can be eluted as living cells for further investigation.Conclusions: This study provides a new in vitro system for investigating the interaction between SARS-CoV-2 and host cells and purifying ACE2-expressing cells.

Expression of ACE2, TMPRSS2, and CTSL in human airway epithelial cells under physiological and pathological conditions: Implications for SARS-CoV2 infection (preprint)

SARS-CoV-2 enters into human airway epithelial cells via membrane fusion or endocytosis, and this process is dependent on ACE2, TMPRSS2, and cathepsin L. In this study, we examined the expression profiles of the three SARS-CoV-2 entry-related genes in primary human airway epithelial cells isolated from donors with different physiological and pathological backgrounds such as smoking, COPD, asthma, lung cancer, allergic rhinitis, cystic fibrosis, or viral infections. By reanalyzing 54 GEO datasets comprising transcriptomic data of 3428 samples, this study revealed that i) smoking is associated with an increased expression of ACE2 and TMPRSS2 and a decreased expression of cathepsin L; ii) infection of rhinovirus as well as poly(I:C) stimulation leads to high expression of all three SARS-CoV-2 entry-related genes; iii) expression of ACE2 and cathepsin L in nasal epithelial cells are decreased in patients with asthma and allergic rhinitis. In conclusion, this study implicates that infection of respiratory viruses, cigarette smoking and allergic respiratory diseases might affect the susceptibility to and the development of COVID-19.

Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea (preprint)

Objectives: Elderly people had suffered disproportional burden of COVID-19. We hypothesized that males and females in different age groups might have different epidemic trajectories. Methods: Using publicly available data from South Korea, daily new COVID-19 cases were fitted with generalized additive models, assuming Poisson and negative binomial distributions. Epidemic dynamics by age and gender groups were explored with interactions between smoothed time terms and age and gender. Results: A negative binomial distribution fitted the daily case counts best. Interaction between the dynamic patterns of daily new cases and age groups was statistically significant (p<0.001), but not with gender group. People aged 20-39 years led the epidemic processes in the society with two peaks: one major peak around March 1 and a smaller peak around April 7, 2020. The epidemic process among people aged 60 or above was trailing behind that of younger people with smaller magnitude. After March 15, there was a consistent decline of daily new cases among elderly people, despite large fluctuations of case counts among young adults. Conclusions: Although young people drove the COVID-19 epidemic in the whole society with multiple rebounds, elderly people could still be protected from virus infection after the peak of epidemic.

Risk interactions of coronavirus infection across age groups after the peak of COVID-19 epidemic (preprint)

Background: the COVID-19 pandemic has incurred significant disease burden worldwide, particularly on elderly population. This study aims to explore how risks of infection interact across age groups using data from South Korea. Methods: Daily new COVID-19 cases from March 10 to April 30, 2020 were scraped from online open sources. A multivariate vector autoregressive model for time series count data was used to examine the risk interactions across age groups. Case counts from previous days were included as predictors to dynamically examine the change of risk patterns. Results: In South Korea, the risk of coronavirus infection among elderly people was significantly affected by other age groups. An increase of virus infection among people aged 20-39 was associated with a double risk of infection among elderly people. Meanwhile, an increase in virus infection among elderly people was also significantly associated with risks of infection among other age groups. The risks of infection among younger people were relatively unaffected by that of other age groups. Conclusions: Protecting elderly people from coronavirus infection could not only reduce the risk of infection among themselves but also ameliorate the risks of virus infection among other age groups. Such interventions should be effective and for long term.

Did elderly people living in small towns or rural areas suffer heavier disease burden during the COVID-19 epidemic? (preprint)

ObjectivesHealth inequalities were often exacerbated during the emerging epidemic. This study examined urban and non-urban inequalities in health services among COVID-19 patients aged 65 or above in US Florida from March 2 to May 27, 2020. MethodsA retrospective time series analysis was conducted using individual patient records. Multivariable Poisson and logistic models were used to calculate adjusted incidence of COVID-19 and the associated rates of emergency department (ED) visits, hospitalizations and deaths. ResultsAs of May 27, 2020, there were 13,659 elderly COVID-19 patients (people aged 65 or above) in Florida and 14.9% of them died. Elderly people living in small metropolitan areas might be less likely to be confirmed with COVID-19 infection than those living in large metropolitan areas. The ED visit and hospitalization rates decreased significantly across metropolitan statuses for both men and women. Those patients living in small metropolitan or rural areas were less likely to be hospitalized than those living in large metropolitan areas (35% and 34% versus 41%). Elderly women aged 75 or above living in rural areas had 113% higher adjusted incidence of COVID-19 than those living in large metropolitan areas, and the rates of hospitalizations were lower compared with those counterparts living in large metropolitan areas (29% versus 46%; OR: 0.37 [0.25-0.54]; p <0.001). ConclusionsFor elderly people living in US Florida, those who living in small metropolitan or rural areas were less likely to receive adequate health care than those who living in large or medium metropolitan areas during the COVID-19 pandemic.

Impact of mitigating interventions and temperature on the instantaneous reproduction number in the COVID-19 epidemic among 30 US metropolitan areas (preprint)

BackgroundAfter more than four months into the coronavirus disease (COVID-19) epidemic, over 347,500 people had died worldwide. The current study aims to evaluate how mitigating interventions affected the epidemic process in the 30 largest metropolitan areas in the US and whether temperature played a role in the epidemic process. MethodsPublicly available data for the time series of COVID-19 cases and deaths and weather were analyzed at the metropolitan level. The time-varying reproductive numbers (Rt) based on retrospective moving average were used to explore the trends. Student t tests were used to compare temperature and peak Rt cross-sectionally. ResultsWe found that virus transmissibility, measured by instantaneous reproduction number (Rt), had declined since the end of March for all areas and almost all of them reached a Rt of 1 or below after April 15, 2020. However, the Rts remained around 1 for most areas since then and some small and short rebounds were presented in some areas, suggesting a persistent epidemic in those areas. The timing of the main decline was concurrent with the implementation of mitigating interventions. Cities with warm temperature also tended to have a lower peak Rt than that of cities with cold temperature. However, large geographic variations existed. ConclusionsAggressive interventions might have mitigated the current epidemic of COVID-19, while temperature might have some weak effects on the virus transmission. We may need to prepare for a possible return of the coronavirus outbreak.

Modeling Return of the Epidemic: Impact of Population Structure, Asymptomatic Infection, Case Importation and Personal Contacts (preprint)

Background: Proactive interventions have halted the pandemic of coronavirus infected disease in some regions. However, without reaching herd immunity, the return of epidemic is possible. We investigate the impact of population structure, case importation, asymptomatic cases, and the number of contacts on a possible second wave of epidemic through mathematical modelling. Methods: we built a modified Susceptible-exposed-Infectious-Removed (SEIR) model with parameters mirroring those of the COVID-19 pandemic and reported simulated characteristics of epidemics for incidence, hospitalizations and deaths under different scenarios. Results: A larger percent of old people leads to higher number of hospitalizations, while a large percent of prior infection will effectively curb the epidemic. The number of imported cases and the speed of importation have small impact on the epidemic progression. However, a higher percent of asymptomatic cases slows the epidemic down and reduces the number of hospitalizations and deaths at the epidemic peak. Finally, reducing the number of contacts among young people alone has moderate effects on themselves, but little effects on the old population. However, reducing the number of contacts among old people alone can mitigate the epidemic significantly in both groups, even though young people remain active within themselves. Conclusion: Reducing the number of contacts among high risk populations alone can mitigate the burden of epidemic in the whole society. Interventions targeting high risk groups may be more effective in containing or mitigating the epidemic.