COVID-19 Genetic and Environmental Risk Factors: A Look at the Evidence

Genotype and Haplotype Analysis With In Silico Prediction of TMPRSS2 Gene in Jordanian Population

BACKGROUND

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly become a global health concern. The entry of the virus into host cells is facilitated by the transmembrane protease serine 2 (TMPRSS2) receptor, and genetic variations in the TMPRSS2 gene may influence disease susceptibility. However, there is a lack of knowledge regarding TMPRSS2 genetic variants and haplotypes in the Jordanian population.

AIMS

This study aimed to characterize the genotype and haplotype variations in the TMPRSS2 binding domain with SARS-CoV-2 among Jordanian volunteers.

METHODS

The binding domain of TMPRSS2 with SARS-CoV-2 (Exons 9 and 10) was amplified using polymerase chain reaction (PCR) for a random sample of 120 healthy unrelated Jordanian volunteers, followed by Sanger DNA sequencing for the PCR products. The effect of the novel genetic variants on the TMPRSS2 protein structure was predicted using in silico methods.

RESULTS

The results showed significant (p < 0.05, chi-square) allele frequencies for known TMPRSS2 variants, with c.888C > T being the most prevalent among Jordanian volunteers. Novel genetic variants, including c.869A > G and c.923T > A, were also identified, with the latter being the most common novel variant. Haplotype analysis showed that the most prevalent TMPRSS2 haplotype is c.911G/1051A/1052T/1010 + 45C/1011 - 38T/1011 - 52C/1011 - 54A. In silico programs predicted that TMPRSS2 c.923T > A and c.1052T > A variants affect transmembrane proteins and catalytic sites.

CONCLUSIONS

This research provides information about the gene structure of the TMPRSS2 binding domain in Jordanians. Some of the identified variants, especially c.923T > A, may influence protein function, warranting further in vitro and in vivo investigations. In addition, further clinical research studies are needed to link the identified TMPRSS2 variants with COVID-19 susceptibility and severity among Jordanians.

The effects of meteorological factors on the COVID-19 omicron variant in Bangladesh

The COVID-19 omicron variant is exceptionally complicated and uncertain due to its rapid transmission and volume of infections. This study examines the impact of climatic factors on daily confirmed cases of COVID-19 omicron variant in Bangladesh. The secondary data of daily confirmed cases from 1 January 2022, to 31 March 2022, of eight distinct geographic divisions have been used for the current study. The multivariate generalized linear negative binomial regression model was applied to determine the effects of climatic factors on omicron transmission. The model revealed that the maximum temperature (Odds: 0.67, p < 0.05), sky clearness (Odds: 0.05, p < 0.05), wind speed (Odds: 0.76, p < 0.05), relative humidity (Odds: 1.02, p < 0.05), and air pressure (Odds: 0.27, p < 0.05) significantly impacted COVID-19 omicron transmission in Bangladesh. The study's findings can assist the concerned authorities and decision-makers take necessary measures to control the spread of omicron cases in Bangladesh.

Analysis of associations between the TLR3 SNPs rs3775291 and rs3775290 and COVID-19 in a cohort of professionals of Belém-PA, Brazil

The objective of this article was to verify associations between the SNPs rs3775291 (Cytosine [C]>Thymine [T]) and rs3775290 (C>T) of TLR3 in professionals from Health Institutions (HI) who worked during the first pandemic wave and COVID-19. A case-control study was carried out with workers from HI in Belém-PA, Brazil, divided into symptomatology groups (Asymptomatic-AS, n=91; and Symptomatic-SI, n=121), and severity groups, classified by Chest CT scan (symptomatic with lung involvement - SCP, n=34; symptomatic without lung involvement - SSP, n=8). Genotyping was performed by Sanger sequencing and statistical analysis was performed using the SPSS program. In the analysis of SNP rs3775291, the homozygous recessive genotype (T/T) was not found and the frequency of the mutant allele (T) was less than 2% in the cohort. For the rs3775290 SNP, the frequency of the mutant allele (T) was greater than 42% in the cohort. No significant associations were found for these SNPs in this cohort (N= 212 individuals). The scientific community and physicians can use these facts to find new methods of managing COVID-19.

Effect of Cytomegalovirus Reactivation on Inflammatory Status and Mortality of Older COVID-19 Patients

Herpesviridae reactivation such as cytomegalovirus (CMV) has been described in severe COVID-19 (COronaVIrusDisease-2019). This study aimed to understand if CMV reactivation in older COVID-19 patients is associated with increased inflammation and in-hospital mortality. In an observational single-center cohort study, 156 geriatric COVID-19 patients were screened for CMV reactivation by RT-PCR. Participants underwent a comprehensive clinical investigation that included medical history, functional evaluation, laboratory tests and cytokine assays (TNF-α, IFN-α, IL-6, IL-10) at hospital admission. In 19 (12.2%) of 156 COVID-19 patients, CMV reactivation was detected. Multivariate Cox regression models showed that in-hospital mortality significantly increased among CMV positive patients younger than 87 years (HR: 9.94, 95% CI: 1.66–59.50). Other factors associated with in-hospital mortality were C-reactive protein (HR: 1.17, 95% CI: 1.05–1.30), neutrophil count (HR: 1.20, 95% CI: 1.01–1.42) and clinical frailty scale (HR:1.54, 95% CI: 1.04–2.28). In patients older than 87 years, neutrophil count (HR: 1.13, 95% CI: 1.05–1.21) and age (HR: 1.15, 95% CI: 1.01–1.31) were independently associated with in-hospital mortality. CMV reactivation was also correlated with increased IFN-α and TNF-α serum levels, but not with IL-6 and IL-10 serum changes. In conclusion, CMV reactivation was an independent risk factor for in-hospital mortality in COVID-19 patients younger than 87 years old, but not in nonagenarians.

Spatial shifting of COVID-19 clusters and disease association with environmental parameters in India: A time series analysis

BACKGROUND

The viability and virulence of COVID-19 are complex in nature. Although the relationship between environmental parameters and COVID-19 is well studied across the globe, in India, such studies are limited. This research aims to explore long-term exposure to weather conditions and the role of air pollution on the infection spread and mortality due to COVID-19 in India.

METHOD

District-level COVID-19 data from April 26, 2020 to July 10, 2021 was used for the study. Environmental determinants such as land surface temperature, relative humidity (RH), Sulphur dioxide (SO₂), Nitrogen dioxide (NO₂), Ozone (O₃), and Aerosol Optical Depth (AOD) were considered for analysis. The bivariate spatial association was used to explore the spatial relationship between Case Fatality Rate (CFR) and these environmental factors. Further, the Bayesian multivariate linear regression model was applied to observe the association between environmental factors and the CFR of COVID-19.

RESULTS

Spatial shifting of COVID-19 cases from Western to Southern and then Eastern parts of India were well observed. The infection rate was highly concentrated in most of the Western and Southern regions of India, while the CFR shows more concentration in Northern India along with Maharashtra. Four main spatial clusters of infection were recognized during the study period. The time-series analysis indicates significantly more CFR with higher AOD, O₃, and NO₂ in India.

CONCLUSIONS

COVID-19 is highly associated with environmental parameters and air pollution in India. The study provides evidence to warrant consideration of environmental parameters in health models to mediate potential solutions. Cleaner air is a must to mitigate COVID-19.

Analysis of Gene Single Nucleotide Polymorphisms in COVID-19 Disease Highlighting the Susceptibility and the Severity towards the Infection

Many factors may influence the risk of being infected by SARS-CoV-2, the coronavirus responsible for coronavirus disease 2019 (COVID-19). Exposure to the virus cannot explain the variety of an individual's responses to the virus and the high differences of effect that the virus may cause to some. While a person's preexisting condition and their immune defenses have been confirmed to play a major role in the disease progression, there is still much to learn about hosts' genetic makeup towards COVID-19 susceptibility and risk. The host genetic makeup may have direct influence on the grade of predisposition and outcomes of COVID-19. In this study, we aimed to investigate the presence of relevant genetic single nucleotide polymorphisms (SNPs), the peripheral blood level of IL6, vitamin D and arterial blood gas (ABG) markers (pH, oxygen-SpO₂ and carbon dioxide-SpCO₂) on two groups, COVID-19 (n = 41, study), and the healthy (n = 43, control). We analyzed cytokine and interleukin genes in charge of both pro-inflammatory and immune-modulating responses and those genes that are considered involved in the COVID-19 progression and complications. Thus, we selected major genes, such as IL1β, IL1RN (IL-1 β and α receptor) IL6, IL6R (IL-6 receptor), IL10, IFNγ (interferon gamma), TNFα (tumor necrosis factor alpha), ACE2 (angiotensin converting enzyme), SERPINA3 (Alpha-1-Antiproteinase, Antitrypsin member of Serpin 3 family), VDR (vitamin D receptor Tak1, Bsm1 and Fok1), and CRP (c-reactive protein). Though more research is needed, these findings may give a better representation of virus pleiotropic activity and its relation to the immune system.

A Spatiotemporal Analytical Outlook of the Exposure to Air Pollution and COVID-19 Mortality in the USA

The world is experiencing a pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), also known as COVID-19. The USA is also suffering from a catastrophic death toll from COVID-19. Several studies are providing preliminary evidence that short- and long-term exposure to air pollution might increase the severity of COVID-19 outcomes, including a higher risk of death. In this study, we develop a spatiotemporal model to estimate the association between exposure to fine particulate matter PM2.5 and mortality accounting for several social and environmental factors. More specifically, we implement a Bayesian zero-inflated negative binomial regression model with random effects that vary in time and space. Our goal is to estimate the association between air pollution and mortality accounting for the spatiotemporal variability that remained unexplained by the measured confounders. We applied our model to four regions of the USA with weekly data available for each county within each region. We analyze the data separately for each region because each region shows a different disease spread pattern. We found a positive association between long-term exposure to PM2.5 and the mortality from the COVID-19 disease for all four regions with three of four being statistically significant. Data and code are available at our GitHub repository. Supplementary materials accompanying this paper appear on-line.

Occupational Risk Factors for SARS-CoV-2 Infection in Hospital Health Care Workers: A Prospective Nested Case-Control Study

Introduction: Health Care Workers (HCWs) are at a particular high risk of SARS-CoV-2 infection due to direct and indirect exposure to COVID-19 patients and Aerosol-Generating Procedures (AGPs). The aim of the study was to assess the risk factors for SARS-CoV-2 infection in HCWs exposed to COVID-19 patients, to evaluate the adherence and effectiveness of Infection Prevention and Control (IPC) measures, to describe the clinical presentation for SARS-CoV-2 infection in HCWs and to determine serological responses in HCWs. Methods: HCWs exposed to COVID-19 patients during the previous 14 days with a confirmed case status were recruited as cases; HCWs exposed to COVID-19 patients during the previous 14 days in the same ward without a suspected/probable/confirmed case status were recruited as controls. Serum samples were collected as soon as possible and after 21–28 days from all participants. Data were collected with a WHO standardized questionnaire as soon as possible and after 21–28 days. Results: All social, occupational and personal variables considered were not associated with an increased risk of SARS-CoV-2 infection. Conclusions: Our study showed a high knowledge of IPC measures and very high PPE use among HCWs.

Interaction between meteorological parameters and COVID-19: an ecological study on 406 authorities of the UK

Understanding the factors affecting COVID-19 transmission is critical in assessing and mitigating the spread of the pandemic. This study investigated the transmissibility and death distribution of COVID-19 and its association with meteorological parameters to study the propagation pattern of COVID-19 in UK regions. We used the reported case and death per capita rate (as of November 13, 2020; before mass vaccination) and long-term meteorological data (temperature, humidity, precipitation, wind speed, and visibility) in 406 UK local authority levels based on publicity available secondary data. We performed correlation and regression analysis between COVID-19 variables and meteorological parameters to find the association between COVID-19 and independent variables. Student's T and Mann-Whitney's tests were used to analyze data. The correlation and regression analyses revealed that temperature, dew point, wind speed, and humidity were the most important factors associated with spread and death of COVID-19 (P <0.05). COVID-19 cases negatively correlated with humidity in areas with high population density, but the inverse in low population density areas. Wind speeds in low visibility areas, which are considered polluted air, may increase the spread of disease (r=0.42, P <0.05) and decrease the spread in high visibility areas (r=-0.16, P <0.05). Among low (T <10°C) and high (T >10°C) temperature areas, the average incidence rates were 2056.86 (95% confidence interval (CI): 1909.49-2204.23) and 1446.76 (95% CI: 1296.71-1596.81). Also, COVID-19 death per capita rates were 81.55 (95% CI: 77.40-85.70) and 69.78 (95% CI: 64.39-75.16) respectively. According to the comprehensive analysis, the spread of disease will be suppressed as the weather warms and humidity and wind speed decrease. Different environmental conditions can increase or decrease spread of the disease due to affecting spread of disease vectors and by altering people's behavior.

SARS-CoV-2-associated gastrointestinal and liver diseases: what is known and what is needed to explore

BACKGROUND

The pandemic of COVID19 which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first described in China as an unexplained pneumonia transmitted by respiratory droplets. Gastrointestinal (GI) and liver injury associated with SARS-CoV-2 infection were reported as an early or sole disease manifestation, mainly outside China. The exact mechanism and incidence of GI and liver involvement are not well elucidated.

MAIN BODY

We conducted a PubMed search for all articles written in the English language about SARS-CoV-2 affecting the GI and liver. Following data extraction, 590 articles were selected. In addition to respiratory droplets, SARS-CoV-2 may reach the GI system through the fecal-oral route, saliva, and swallowing of nasopharyngeal fluids, while breastmilk and blood transmission were not implicated. Moreover, GI infection may act as a septic focus for viral persistence and transmission to the liver, appendix, and brain. In addition to the direct viral cytopathic effect, the mechanism of injury is multifactorial and is related to genetic and demographic variations. The most frequently reported GI symptoms are diarrhea, nausea, vomiting, abdominal pain, and bleeding. However, liver infection is generally discovered during laboratory testing or a post-mortem. Radiological imaging is the gold standard in diagnosing COVID-19 patients and contributes to understanding the mechanism of extra-thoracic involvement. Medications should be prescribed with caution, especially in chronic GI and liver patients.

CONCLUSION

GI manifestations are common in COVID-19 patients. Special care should be paid for high-risk patients, older males, and those with background liver disease.

COVID-19 Mental Health Disparities

Communities of color in the United States have been disproportionately impacted by the COVID-19 pandemic. Studies exploring the mental health implications of these disparities have only just begun to emerge. The purpose of this study is to better understand mental health concerns and test whether social determinants of health and COVID-19-related experiences influence these concerns. In April 2020, we launched a community-based survey for adults across the United States. A total of 341 respondents completed the survey, which included questions about demographics, depression, social isolation, work environment, and preexisting mental health conditions. We generated matched controls by adding county data from the Robert Wood Johnson Foundation to our survey. Chi square, Pearson product-moment correlation, point biserial correlation, and logistic regression were estimated. Our analysis revealed that respondents who identified as Latinx, Latin@, or Hispanic were 10 times more likely to meet the threshold score for depression. Similarly, individuals with prior mental health conditions and those who expressed feelings of social isolation due to COVID-19 were 3 times more likely to meet the threshold score for depression. These results confirm our hypothesis that communities of color will likely experience disproportionate mental health impacts of COVID-19-specifically, the mental health sequela that emerge from exposure, cumulative burden, and social isolation. We discuss the implications for expanding access and quality of health and mental health services to address current inequities.

Evidence of a dysregulated vitamin D endocrine system in SARS-CoV-2 infected patient's lung cells

Although a defective vitamin D endocrine system has been widely suspected to be associated in SARS-CoV-2 pathobiology, the status of the vitamin D endocrine system and vitamin D-modulated genes in lung cells of patients infected with SARS-CoV-2 remains unknown. To understand the significance of the vitamin D endocrine system in SARS-CoV-2 pathobiology, computational approaches were applied to transcriptomic datasets from bronchoalveolar lavage fluid (BALF) cells of such patients or healthy individuals. Levels of vitamin D receptor, retinoid X receptor, and CYP27A1 in BALF cells of patients infected with SARS-CoV-2 were found to be reduced. Additionally, 107 differentially expressed, predominantly downregulated genes, as potentially modulated by vitamin D endocrine system, were identified in transcriptomic datasets from patient's cells. Further analysis of differentially expressed genes provided eight novel genes with a conserved motif with vitamin D-responsive elements, implying the role of both direct and indirect mechanisms of gene expression by the dysregulated vitamin D endocrine system in SARS-CoV-2-infected cells. Protein-protein interaction network of differentially expressed vitamin D-modulated genes were enriched in the immune system, NF-κB/cytokine signaling, and cell cycle regulation as top predicted pathways that might be affected in the cells of such patients. In brief, the results presented here povide computational evidence to implicate a dysregulated vitamin D endocrine system in the pathobiology of SARS-CoV-2 infection.