A small group of genetic variants found in extremely sick COVID patients may help explain big differences in how people get sick
Research to better understand the wide range of responses to infection with the COVID-19 virus – from symptomless to critically ill – has uncovered in some of the sickest patients a handful of rare structural genetic variants involved. in bodily processes, like inflammation, that the virus needs to succeed.
“The virus has to attach to our cells, it has to get inside our cells, and it has to multiply inside our cells. It also has to attract inflammation,” says Dr. Ravindra Kolhe, director from the Georgia Esoteric and Molecular Laboratory at the Medical College of Georgia at Augusta University. “We have identified genes with structural changes in very ill individuals that are part of these four essential processes.”
In apparently the first study of its kind, investigators used optical genome mapping to obtain an in-depth three-dimensional assessment of the genome of 52 critically ill patients with COVID-19.
In nine of the sickest patients, they identified seven rare structural variants affecting a total of 31 genes involved in key pathways mediating the response between a person, or host, and a virus. These include innate immunity, our first-line immune defense against invaders like viruses; the inflammatory response, a key response to infection which, if done wrong, can also destroy the lungs of some of the sickest patients; and the ability of a virus to replicate and spread. As an example, a variant they identified can lead to overexpression of keratin genes. Keratins are proteins that are the structural components of things like our hair and nails, but have also been identified as essential for the transmission of influenza viruses and the COVID-19 virus between cells and are known to be regulated rising in the airways during an infection.
“It’s a hyperactivation of normal systems,” says Kolhe, corresponding author of the study, published by the international collaborative COVID-19 Host Genome Research consortium in the journal iScience.
“Millions of people are infected, and fortunately only a very small percentage become symptomatic, and a very small percentage of symptomatic people need oxygen and a small percentage of those people are hospitalized and die,” Kolhe said. “But even a small percentage is millions of people and that’s too many.”
“Our data show that large (structural variants) identified using optical genome mapping could further explain interindividual clinical variability in response to COVID-19,” the researchers write.
Large structural variants account for much of the genetic diversity among us, including changes that are just unique to the individual and those that can increase their risk for problems like cancer. Optical genome mapping is an emerging technology that can detect these larger variants with multiple changes, such as deletion or insertion of genetic material and/or when a section of chromosome is reversed.
The researchers say that while more work is needed, their findings on the potential role of structural variants in host-virus interaction point to the need to search for genetic variations, ideally with a simple-to-use blood test. Once identified, the goal would be to initiate proactive measures for these people, such as providing vaccination and reinforcement and potentially more aggressive treatment early on, such as monoclonal antibody therapy, to help these people better combat the COVID, says Kolhe.
Clinical studies have identified factors such as older age, being male, hypertension, diabetes, and other chronic diseases as risk factors associated with the degree of illness from COVID-19. The nine sickest patients in this study shared common comorbid conditions, 32 of the patients required mechanical ventilation to support their breathing, and a total of 13 of the 52 patients died in intensive care.
But in their studies, which also included people who were negative for the COVID-19 virus and those who were positive but asymptomatic, there were again outliers, including people with comorbidities who remained asymptomatic when infected with SARS-CoV-2 and those who were perfectly healthy but became extremely sick when infected, another indicator of the role of genetics in determining the degree of response, Kolhe says.
Kolhe notes that the large structural variants they found in the sickest patients were not caused by the virus rather used by the virus and may not increase susceptibility to other, even similar, conditions.
Overall, the individuals in this study had about 40 rare structural variants, which other studies have found to be about average.
The COVID-19 Host Genome Research consortium currently includes 34 institutions, including Duke and Columbia universities, the National Cancer Institute and the New York Genome Center, exploring different aspects of the impact of structural variants on divergent individual responses to infection. by the COVID -19 virus.
The group began to emerge after more common gene sequencing studies, which essentially lay out DNA in a straight line to look for problematic, smaller variations in the usual order of its four base pairs – adenine, thymine, guanine and cytosine – out of thousands of patients provided little information to help explain – and ideally predict – the wide variations in how people will get sick. According to the Human Gene Mutation Database, more than 30% of known pathogenic variants are larger than sequencing single base pair changes can identify.
Even the amount of virus in an individual is not directly correlated to how sick the individual becomes, Kolhe says. “We had individuals with very high viral loads who didn’t even know they were positive,” he says. “It’s something in the host genome that’s different.”
Some studies have shown that blood type could be a predictor of risk, especially type A, and there have also been specific genetic findings that predispose to immune deficiencies that can make people more susceptible.
Kolhe, who is also associate director of genomics at the Georgia Cancer Center, used optical genome mapping to search for patient-specific carcinogenic variations.