Angiotensin-converting enzyme 2 SNPs as the common genetic loci and optimal early identification genetic markers for COVID-19 (preprint)

Background: Angiotensin-converting enzyme 2 (ACE2) is implicated as a host cell receptor that causes infection in the pathogenesis of Coronavirus disease 2019 (COVID-19), and its genetic polymorphisms in the ACE2 gene may promote cardiovascular disease and systemic inflammatory injury in COVID-19. Hence, genetic background may potentially explain the broad inter-individual variation of disease susceptibility and/or severity. Methods The genetic susceptibility to COVID-19 by examining single-nucleotide polymorphisms (SNPs) of ACE2 was analyzed in 196 patients with COVID-19 and 210 normal controls using TaqMan genotyping assay. Results We demonstrated that ACE2 SNP rs4646142, rs6632677, and rs2074192 were associated with COVID-19 (all P < 0.05), and the differences of ACE2 SNPs rs4646142 and rs6632677 were correlated with COVID-19 related systemic inflammatory injury and cardiovascular risk. Specially, rs4646142 was associated with high-sensitive C-reactive protein (hs-CRP), prealbumin (PAB), apolipoprotein A (APOA), high-density lipoprotein (HDL), and acid glycoprotein (AGP). Rs6632677 was also associated with elevated CRP and haptoglobin (HPT). Conclusions Our results suggest that early identification of these individuals can provide a possible strategy for preventing the spread of the COVID-19, and ACE2 SNPs rs4646142 and rs6632677 may be a common genetic loci and optimal early identification genetic marker for COVID-19 with cardiovascular risks.

COVID-19: Comparison between 8-days and extended 4-weeks outbreak periods through socioeconomic and natural factors (preprint)

Since mid-March 2020, global COVID-19 pandemic has experienced an exponential growth in process from sporadic to sudden outbreaks. This paper selects the 8-day surge data of daily cases, death and recovery rates (March 19-26, 2020) from 18 countries with severe pandemic situation to discuss the impact of 9 factors of both socioeconomic and natural on the pathogen outbreak. Moreover, the paper also elaborates analysis and comparison of relatively slow 4-week (February 1-29, 2020) data of China's surge cases to determine the relationship between social and natural factors and on the spread of pandemic, which provides an effective reference for delaying and controlling the pandemic development.