Precision epidemiology could help explain variability in COVID-19 symptoms

Researchers from National Taiwan University have presented a multi-omics view of how mutations in angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) affect infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and progression of coronaviruses disease 2019 (COVID-19).

ACE2 is the human receptor that COVID-19's causative agent - SARS-COV-2 - uses to bind to host cells, and TMPRSS2 is the enzyme that activates the viral spike protein for membrane fusion.

For both the ACE2 and TMPRS22 genes, Eric Chuang and colleagues report on findings from a comparative analysis of the single nucleotide polymorphisms (SNPs) that may contribute to variability in COVID-19 symptoms among sub-populations. They also report on calculations of the prevalence of structural variations amongst populations and a study of expression patterns across all human tissues.

"This work is a good first step to be followed by additional studies and functional assays towards informed treatment decisions and improved control of the infection rate," writes the team.

A pre-print version of the paper is available on the server bioRxiv*, while the article undergoes peer review.

COVID-19 disease course is highly variable

Precision epidemiology using genomic technologies enables a targeted approach towards infectious disease control. It includes genome-based approaches to provide information on molecular diagnosis and treatment regimens at both the population and individual level.

The disease course in cases of COVID-19 is highly variable, ranging from mild or asymptomatic to severe and potentially fatal.

Aside from known risk factors associated with severe disease such as older age and co-existing comorbidity, such variability in symptoms and outcomes may be explained by genetic architecture differences, suggest Chuang and colleagues.

"It is necessary to identify variants of the ACE2 and TMPRSS2 genes that confer higher susceptibility to fatality and symptoms," say the researchers.

However, the team says a susceptibility gene may likely have low penetrance, meaning not all carriers will develop COVID-19. Furthermore, specific environmental factors may affect the degree of transmission and severity of infections.

Therefore, the team has presented multiple lines of supporting evidence from multi-omics data, including information on SNPs, structural variations such as copy number variations (CNVs), and gene expression patterns, to show how such approaches can help identify COVID-19 risk factors.

The SNP analysis

The researchers used an online database they developed called VariED, which provides annotation and expression profiles for variants related to human diseases, to obtain allele frequencies for all SNP variants from both ACE2 and TMPRSS2 for different global sub-populations.

They identified SNPs in both ACE2 and TMPRSS2 that had higher allele frequencies among Africans and East Asian populations than among Europeans and Americans.

Chuang and the team say that Africans exhibited particularly significant variation for most SNPs, which may indicate differential susceptibility towards coronavirus in the respective populations.

Analysis of structural variations

The team used a web-based system they developed called CNVIntegrate to study the candidate genes' CNV frequencies in the control cohort ExAC, which consists of healthy individuals from global sub-populations, and the control cohort TWCNV, which consists of healthy Taiwanese individuals.

The researchers calculated the duplications and deletions frequencies for both ACE2 and TMPRSS2 among the two cohorts.

For ACE2, no duplications or deletions were observed among either population. For TMPRSS2, duplication was observed in 0.06% of samples from TWCNV and in 0.014% of samples from ExAC. TMPRSS2 deletion was also observed in 1.08% of TWCNV samples.

Chuang and colleagues say this suggests that these variations are rare among healthy cohorts and provides evidence that they could be pathogenic.

The gene expression analysis

The team used a database tool they developed called CellExpress to study ACE2 and TMPRSS2 gene expression patterns across all human tissues, stratified by gender and age.

The gene expression data for baseline healthy populations did not show any significant difference in gene expression levels between males and females, with the exception of the pituitary gland. Similarly, no significant difference was observed when gene expression was stratified by age.

However, a search for both genes across all tissues in cancer datasets did reveal high expression levels of both ACE2 and TMPRS22 across all tissues, with no effect of gender and age.

"A good first step" towards identifying high-risk patients

"This study conducts genetic probing with the intention of explaining the variability in symptoms and diverse outcomes of COVID-19. It provides some significant findings (SNP, CNV, and gene expression) from ACE2 and TMPRSS2, as evidence, for a plausible place to start looking into them," said Chuang and colleagues.

"The work is a good first step to be followed by additional studies and functional assays that could potentially evaluate the findings to identify patients who may be at a higher risk of COVID-19-related mortality or infection, towards informed decisions for treatment and cure," concludes the team.

*Important Notice

bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
Sally Robertson

Written by

Sally Robertson

Sally first developed an interest in medical communications when she took on the role of Journal Development Editor for BioMed Central (BMC), after having graduated with a degree in biomedical science from Greenwich University.


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