Since the start of the coronavirus pandemic, scientists and clinicians have struggled to understand why some people with the infection become seriously ill or die while others have few, if any, symptoms. Age, body mass index and pre-existing health problems account for some of the disparities, but genetics is known to play a significant role.
Now, researchers from Stanford Medicine and the University of Sheffield in the U.K. have identified more than 1,000 genes linked to the development of severe COVID-19 cases that required breathing support or were fatal. The team was also able to identify specific types of cells in which those genes act up. It's one of few studies to link coronavirus-associated genes to specific biological functions.
The researchers used a machine learning tool named RefMap, which can find patterns in vast amounts of data, to help identify the genetic basis for complex and poorly understood diseases.
We mapped the genetic architecture of coronavirus infections and found that these 1,000 genes account for 77% of the drivers of severe COVID-19."
Michael Snyder, PhD, professor and chair of genetics
A paper describing the research published online June 14 in Cell Systems. Snyder, the Stanford W. Ascherman, MD, FACS, Professor in Genetics, and professor of medicine Philip Tsao, PhD, are co-senior authors. Genetics instructor Sai Zhang, PhD, and neuroscientist Jonathan Cooper-Knock, PhD, a Stanford visiting scholar and lecturer at the University of Sheffield, share lead authorship.
Fishing for answers
The researchers used two large data sets to unpack the genetics behind severe COVID-19. The first data set contained genomic information from healthy human lung tissue. The data helped identify gene expression in 19 different types of lung cells, including epithelial cells that line the respiratory tract and are the first defense against infection. (Gene expression is the process by which certain genes are switched on to make RNA and proteins.)
Other data came from the COVID-19 Host Genetics Initiative, one of the largest genome-wide studies of critically ill coronavirus patients. The researchers looked for genetic clues in the data — DNA mutations, called single nucleotide polymorphisms — that might indicate if someone is at a higher risk for severe COVID-19. They tracked whether some mutations occurred more or less often in COVID-19 patients with severe disease.
Posted in: Genomics | Disease/Infection News
Tags: Body Mass Index, Breathing, Cell, Coronavirus, covid-19, DNA, Gene, Gene Expression, Genes, Genetic, Genetics, Genome, Genomic, Machine Learning, Medicine, Nucleotide, Pandemic, Research, Respiratory, RNA, Single Nucleotide Polymorphisms
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