Combinatorial influence of environmental temperature, obesity and cholesterol on SARS-CoV-2 infectivity

Abstract

The continuing evolution of SARS-CoV-2 variants not only causes a long-term global health concerns but also encounters the vaccine/drug effectiveness. The degree of virus infectivity and its clinical outcomes often depend on various biological parameters (e.g., age, genetic factors, diabetes, obesity and other ailments) of an individual along with multiple environmental factors (e.g., air temperature, humidity, seasons). Thus, despite the extensive search for and use of several vaccine/drug candidates, the combinative influence of these various extrinsic and intrinsic risk factors involved in the SARS-CoV-2 virus infectivity has yet to be explored. Previous studies have reported that environment temperature is negatively associated with virus infectivity for SARS-CoV-2. This study elaborates on our previous findings, investigating the link between environmental temperature and other metabolic parameters, such as average total cholesterol and obesity, with the increase in COVID-19 cases. Statistical analysis conducted on a per country basis not only supports the existence of a significant negative correlation between environmental temperature and SARS-CoV-2 infections but also found a strong positive correlation between COVID-19 cases and these metabolic parameters. In addition, a multiphase growth curve model (GCM) was built to predict the contribution of these covariates in SARS-CoV-2 infectivity. These findings, for first time, support the idea that there might be a combinatorial impact of environmental temperature, average total cholesterol, and obesity in the inflation of the SARS-CoV-2 infectivity.

Adsorption of pulmonary and exogeneous surfactants on SARS-CoV-2 spike protein

“…These results are consistent with literature data on cholesterol effects on SARS-CoV-2 infectivity. [42] , [43] , [44] , [45] , [46] Our simulations also reveal preference of SDS to RBD and high affinity of all surfactants considered to the recently discovered fatty acid binding site. Analysis of interactions of different surfactant functional groups, represented by hydrophilic head, hydrophobic tail, cationic and anionic beads, with the S1 residues shows that anionic head groups are preferred by the protein compared to cationic ones.…”

“…The strong interaction of cholesterol with S1 domain found in our simulations is consistent with the observations that have been made regarding the cholesterol effects on COVID-19 disease. [42] , [43] , [44] , [45] , [46] An early study [42] reported that CHOL-rich microdomains in the plasma membrane facilitates the Spike-ACE2 interaction. The influence of cholesterol on the SARS-CoV infectivity was found to be solely due to the Spike-CHOL interaction and not due to CHOL interaction with any other coronavirus protein.…”

“…Cholesterol effects on COVID-19 disease have been documented in multiple studies. [39] , [42] , [43] , [44] , [45] , [46] Wei et al [47] have identified several cholesterol binding motifs in the S1 domain of the SARS-CoV-2 spike protein, and observed that cholesterol binding to S1 domain and high density lipoprotein (HDL) components enhances COVID-19 infection. It is also reported that cholesterol strongly binds to the recently discovered fatty acid binding site (FABS) of the SARS-CoV-2 spike protein.…”

Mechanistic view on the influence of fluctuations in outdoor temperature on the worsening of the course of the disease and hospitalizations associated with the SARS-CoV-2 Omicron wave in 2022 in the Tomsk region, Russia

“…It is important to note that since the pandemic started, many authors have analyzed the issue of impact of many factors (weather conditions, air pollution and etc.) on COVID-19 incidence, severity, and mortality, and literature linking to this issue has increased exponentially and now hundreds studies show the different results (see related revies in (Kang et al, 2021; Prévost et al, 2021; Liang & Yuan, 2022; Mandal et al, 2022; McClymont & Hu, 2021; Mejdoubi et al, 2020; Runkle et al, 2020; To et al, 2021; Tripathi et al, 2022; Xie & Zhu, 2020; Carballo et al, 2022; Culqui et al, 2022; Ishmatov, 2022; Kang et al, 2021; Perone, 2022; Taylor et al, 2022)). Most of the studies are statistical and analyze the correlation between various influencing factors.…”

“…It is worth noting that today there are many studies of the correlation of weather factors and air temperature with COVID-19 in many countries and cities. Most of them agree that air temperature affects COVID-19 and authors describe some possible effects of air temperature on COVID-19 disease severity and transmission rates (see related reviews in (Kang et al, 2021; Prévost et al, 2021; Liang & Yuan, 2022; Mandal et al, 2022; McClymont & Hu, 2021; Mejdoubi et al, 2020; Runkle et al, 2020; Tripathi et al, 2022).…”